Dr.Yu is an ecosystem modeller who has worked in The Netherlands, USA and Canada.He was awarded a Sir Frederick McMaster Fellowship in 2005 and worked at CSIRO Land and Water in Canberra. Prior to his position at UTS, as a professor of Ecological Modelling and Spatial Analyses in The Plant Functional Biology and Climate Change Cluster (C3), he served as a lead professor in the Chinese Academy of Sciences.
His research concerns the simulation and parameterization of biophysical and physiological regulation of mass and energy exchange over the interfaces between plant, soil and atmosphere which provides a basis for the research on impacts of climate change and land surface processes.His current research projects focus on building a spatial analysis platform which integrates regional information of climate, soil, land use and remote sensing using models and GIS. Although the work is challenging in data assimilation of multi-sources and their match with models output, it has great potential in the application of resources management.
Professor Yu leads the Ecological Modelling Research Group.
Adjunct Professor, China Agricultural University
Adjunct Professor, Nanjing University of Information Science and Technology
Can supervise: YES
- Physiological ecology modelling
- Terrestrial ecosystem modelling
- Crop production and water management
- Land surface processes
- Ecological hydrology
- Flux measurement
- Biomass partitioning
Chen, S, Jiang, T, Ma, H, He, C, Xu, F, Malone, RW, Feng, H, Yu, Q, Siddique, KHM, Dong, Q & He, J 2020, 'Dynamic within-season irrigation scheduling for maize production in Northwest China: A Method Based on Weather Data Fusion and yield prediction by DSSAT', Agricultural and Forest Meteorology, vol. 285-286.View/Download from: Publisher's site
© 2020 Elsevier B.V. Current water consumptions are unsustainable in many regions, which requiring more efficient agricultural water management strategies. This study incorporated the DSSAT-CERES-Maize model with a new algorithm for dynamic within-season irrigation scheduling for maize (Zea mays L.) based on trends in daily forecasted yields. Field experiments were undertaken at four arid and semiarid sites in Northwest China, including Changwu (2010 and 2011, rainfed), Yangling (2014 and 2015, irrigated), Jingyang (2015, irrigated), and Shiyanghe (2015, irrigated). Historical 50-year (1968–2017) weather data were available for each site. In daily yield forecasts, weather data before forecast dates were observed from local weather stations, while the unknown data between forecast and harvest dates were supplemented by local 50-year continuous weather series in the same periods. Then 50 maize yields could be obtained on each forecast day, and the median values were calculated as the prediction on that day. As the growing season advanced, historical weather data were gradually replaced by actual weather data. Further, the dynamics of daily forecasted yields were used to schedule irrigation based on a new algorithm. The new algorithm schedule irrigations by considering the feedbacks of maize grain yield to interactions of actual weather, environment, and management. The results showed that forecasted maize yield had considerable uncertainty before tasseling but rapidly converged to the actual yield about one month before harvest. The mean absolute relative errors (MAREs) of daily forecasted yields were 11.7% and 7.3% at Changwu in 2010 and 2011, respectively. Simulated irrigation use efficiency (IUE) for almost all sites and years were improved. The new irrigation scheduling algorithm will help to improve irrigation scheduling in arid and semiarid areas where precipitation is the main limited factor to maize yield.
Cheng, H, Zhu, X, Sun, R, Niu, Y, Yu, Q, Shen, Y & Li, S 2020, 'Effects of different mulching and fertilization on phosphorus transformation in upland farmland', Journal of Environmental Management, vol. 253.View/Download from: Publisher's site
© 2019 Elsevier Ltd In the present study, the impact of different soil surface mulching, fertilization on phosphorus mineralization and bio-availability of spring maize at various growth stages and soil layers (0–20 and 20–40 cm soil layer) were evaluated. The results indicated that the contents of total P and Olsen-Phosphorus (Olsen-P) in the soils of 0–20 cm soil layer were significantly higher than those in the 20–40 cm soil layer at different stages. The addition of organic fertilizer significantly increased the soil total P and Olsen-P content in the 0–20 cm soil layer. The different surface mulching, no mulching (NM), gravel mulching (GM) and film mulching (FM) were significantly affected by the content of Olsen-P in both soil layers during the critical growth period of spring maize. The Ca10–P contents in both soil layers were the maximum in terms of the inorganic phosphorus content in soils with different surface mulching and different fertilization. Surface mulching significantly affected the transformation of inorganic phosphorus in different soil layers of dry-land farmland, and accelerated the increase of Ca2–P content (first phosphorus source) in 0–20 cm soil layer by GM and FM. In addition, phosphorus combined with inorganic nitrogen fertilizer increased Ca8–P (second Olsen-P source) to a certain extent, and reduced the relative content of Ca2–P (first phosphorus source). Compared with phosphate (P), nitrogen and phosphorus (NP) treatments, manure and nitrogen and phosphorus (MNP) treatments increased the contents of Ca2–P (first phosphorus source) and Ca8–P (second effective phosphorus source), while it reduced the insoluble phosphorus source (O–P) content.
Cleverly, J, Vote, C, Isaac, P, Ewenz, C, Harahap, M, Beringer, J, Campbell, DI, Daly, E, Eamus, D, He, L, Hunt, J, Grace, P, Hutley, LB, Laubach, J, McCaskill, M, Rowlings, D, Rutledge Jonker, S, Schipper, LA, Schroder, I, Teodosio, B, Yu, Q, Ward, PR, Walker, JP, Webb, JA & Grover, SPP 2020, 'Carbon, water and energy fluxes in agricultural systems of Australia and New Zealand', Agricultural and Forest Meteorology, vol. 287, pp. 107934-107934.View/Download from: Publisher's site
A comprehensive understanding of the effects of agricultural management on climate–crop interactions has yet to emerge. Using a novel wavelet–statistics conjunction approach, we analysed the synchronisation amongst fluxes (net ecosystem exchange NEE, evapotranspiration and sensible heat flux) and seven environmental factors (e.g., air temperature, soil water content) on 19 farm sites across Australia and New Zealand. Irrigation and fertilisation practices improved positive coupling between net ecosystem productivity (NEP = −NEE) and evapotranspiration, as hypothesised. Highly intense management tended to protect against heat stress, especially for irrigated crops in dry climates. By contrast, stress avoidance in the vegetation of tropical and hot desert climates was identified by reverse coupling between NEP and sensible heat flux (i.e., increases in NEP were synchronised with decreases in sensible heat flux). Some environmental factors were found to be under management control, whereas others were fixed as constraints at a given location. Irrigated crops in dry climates (e.g., maize, almonds) showed high predictability of fluxes given only knowledge of fluctuations in climate (R2 > 0.78), and fluxes were nearly as predictable across strongly energy- or water-limited environments (0.60 < R2 < 0.89). However, wavelet regression of environmental conditions on fluxes showed much smaller predictability in response to precipitation pulses (0.15 < R2 < 0.55), where mowing or grazing affected crop phenology (0.28 < R2 < 0.59), and where water and energy limitations were balanced (0.7 < net radiation ∕ precipitation < 1.3; 0.27 < R2 < 0.36). By incorporating a temporal component to regression, wavelet–statistics conjunction provides an important step forward for understanding direct ecosystem responses to environmental change, for modelling that understanding, and for quantifying nonstationary, nonlinear processes such as precipitation pulses, which have previous...
Feng, P, Wang, B, Liu, DL, Waters, C, Xiao, D, Shi, L & Yu, Q 2020, 'Dynamic wheat yield forecasts are improved by a hybrid approach using a biophysical model and machine learning technique', Agricultural and Forest Meteorology, vol. 285-286.View/Download from: Publisher's site
© 2020 Elsevier B.V. Early and reliable seasonal crop yield forecasts are crucial for both farmers and decision-makers. Commonly-used methods for seasonal yield forecasting are based on process-based crop models or statistical regression-based models. Both have limitations, particularly in regard to accounting for growth stage-specific climate extremes (such as drought, heat, and frost). In this study, we firstly developed a hybrid yield forecasting approach by blending of multiple growth stage-specific indicators, i.e. APSIM (a process-based crop model)-simulated biomass, and climate extremes, NDVI (Normalized Difference Vegetation Index), and SPEI (Standardized Precipitation and Evapotranspiration Index) before forecasting dates, using a regression model (random forest or multiple linear regression). Plot-scale wheat yield (2008–2017) in the southeastern Australian wheat belt was dynamically forecasted at the end of several targeted growth stages as the growing season progressed to harvest. Results showed that the forecasting accuracy increased significantly for both systems as forecast time approached harvest time. The forecasting system based on random forest outperformed the forecasting system based on multiple linear regression at each forecasting event. Satisfactory yield forecasts occurred at one month (~35 days) prior to harvest (r = 0.85, LCCC = 0.81, MAPE = 17.6%, RMSE = 0.70 t ha−1, and ROC score = 0.90), and at two months before harvest (r = 0.62, LCCC = 0.53, MAPE = 27.1%, RMSE = 1.01 t ha−1, and ROC score = 0.88). In addition, drought events throughout the growing season were identified as the main factor causing yield losses in the wheat belt during the past decade. With the increasing availability of farming-related data, we expect that the yield forecasting system proposed in our study may be widely extended to other comparable cropping regions to produce sufficiently accurate wheat yield forecasts for stakeholders to develop strategic decisions...
Feng, P, Wang, B, Luo, JJ, Liu, DL, Waters, C, Ji, F, Ruan, H, Xiao, D, Shi, L & Yu, Q 2020, 'Using large-scale climate drivers to forecast meteorological drought condition in growing season across the Australian wheatbelt', Science of the Total Environment, vol. 724.View/Download from: Publisher's site
© 2020 Elsevier B.V. Recurring drought has caused large crop yield losses in Australia during past decades. Long-term drought forecasting is of great importance for the development of risk management strategies. Recently, large-scale climate drivers (e.g. El Niño-Southern Oscillation) have been demonstrated as useful in the application of drought forecasting. Machine learning-based models that use climate drivers as input are commonly adopted to provide drought forecasts as these models are easy to develop and require less information compared to physical-based models. However, few machine learning-based models have been developed to forecast drought conditions during growing season across all Australian cropping areas. In this study, we developed a growing season (Apr.-Nov.) meteorological drought forecasting model for each climate gauging location across the Australian wheatbelt based on multiple lagged (past) large-scale climate indices and the Random Forest (RF) algorithm. The Standardized Precipitation Index (SPI) was used as the response variable to measure the degree of meteorological drought. Results showed that the RF model could provide satisfactory drought forecasts in the eastern areas of the wheatbelt with Pearson's correlation coefficient r > 0.5 and normalized Root Mean Square Error (nRMSE) < 23%. Forecasted drought maps matched well with observed drought maps for three representative periods. We identified NINO3.4 sea surface temperature and Multivariate ENSO Index as the most influential indices dominating growing season drought conditions across the wheatbelt. In addition, lagged impacts of large-scale climate drivers on growing season drought conditions were long-lasting and the indices in previous year could also potentially affect drought conditions during current year. As large-scale climate indices are readily available and can be rapidly used to feed data driven models, we believe the proposed meteorological drought forecasting models can ...
He, L, Jin, N & Yu, Q 2020, 'Impacts of climate change and crop management practices on soybean phenology changes in China.', The Science of the total environment, pp. 135638-135638.View/Download from: Publisher's site
Crop phenology is determined by both climatic factors and agronomic management practices such as sowing date and cultivar characteristics. Exploring the interactive effects of climate change and crop management practices on crop phenology can be used to devise adaptation strategies to mitigate climate change. The objectives of this study were to: 1) examined trends in soybean (Glycine max L.) phenological development in China from 1981 to 2010; 2) isolate and quantify impacts of climate change and crop management on changes in soybean phenology; 3) determine the relative contribution of climate change and crop management to observed changes in soybean phenology; and 4) determine the relative contribution of temperature, precipitation, and sunshine hours to changes in soybean phenology. Changes in soybean phenology were observed across the major soybean producing area of eastern China during 1981-2010. Observed dates of sowing, emergence, anthesis, and maturity were delayed by an average of 1.78, 0.83, 0.19, and 0.62 days decade-1, respectively. Additionally, the lengths of the vegetative growth period and the soybean growing season were shortened by an average of 0.62 and 1.16 days decade-1, respectively. Conversely, the reproductive period was lengthened by an average of 0.43 days decade-1. Crop management practices had greater influence on sowing, emergence, and maturity dates than climate change. The direction of the changes to phenology trends created by management and climate change were opposite to each other. The relative influence of climate change on dates of anthesis, lengths of the vegetative and reproductive growth periods and growing season was larger than the influence of crop management practices. Mean temperature was the dominant climatic factor influencing most soybean phenological stages and phases. Delayed sowing dates and use of longer-duration cultivars are management adaptations that farmers have used to adapt to climate change occurring in ...
Jin, N, He, J, Fang, Q, Chen, C, Ren, Q, He, L, Yao, N, Song, L & Yu, Q 2020, 'The Responses of Maize Yield and Water Use to Growth Stage-Based Irrigation on the Loess Plateau in China', INTERNATIONAL JOURNAL OF PLANT PRODUCTION.View/Download from: Publisher's site
Li, J, Li, Z, Brandis, KJ, Bu, J, Sun, Z, Yu, Q & Ramp, D 2020, 'Tracing geochemical pollutants in stream water and soil from mining activity in an alpine catchment', Chemosphere, vol. 242, pp. 125167-125167.View/Download from: Publisher's site
Ma, X, Huete, A, Moore, CE, Cleverly, J, Hutley, LB, Beringer, J, Leng, S, Xie, Z, Yu, Q & Eamus, D 2020, 'Spatiotemporal partitioning of savanna plant functional type productivity along NATT', REMOTE SENSING OF ENVIRONMENT, vol. 246.View/Download from: Publisher's site
Shen, J, Huete, A, Ma, X, Ngoc, NT, Joiner, J, Beringer, J, Eamus, D & Yu, Q 2020, 'Spatial pattern and seasonal dynamics of the photosynthesis activity across Australian rainfed croplands', ECOLOGICAL INDICATORS, vol. 108.View/Download from: Publisher's site
Shi, L, Feng, P, Wang, B, Li Liu, D, Cleverly, J, Fang, Q & Yu, Q 2020, 'Projecting potential evapotranspiration change and quantifying its uncertainty under future climate scenarios: A case study in southeastern Australia', Journal of Hydrology, vol. 584, pp. 124756-124756.View/Download from: Publisher's site
Projecting the likely change of potential evapotranspiration (ETp) under future climate scenarios is crucial for quantifying the impacts of climate change on the hydrologic cycle and aridity conditions. However, there are different sources of uncertainty in projecting future ETp that may arise from global climate models (GCMs), emission scenarios, and multiple ETp models used. In this study, we developed three random forest-based (RF-based) ETp models with solar radiation and air temperature at eight climatic stations in southeastern Australia. With Penman model as the benchmark, their performance was firstly compared with four empirical models (Jensen-Haise, Makkink, Abtew, and Hargreaves), which requires the same meteorological inputs. In general, the RF-based ETp models showed better performance in ETp estimates across all stations, with coefficients of determination (R2) ranging from 0.68 to 0.92, root mean square errors (RMSE) ranging from 0.58 mm day−1 to 1.46 mm day−1, and relative mean bias errors (rMBE) ranging from −16.10% to 9.73%. The RF-based and empirical models were then used to project future ETp for the eight stations based on statistically downscaled daily climatic data from 34 GCMs under two different representative concentration pathways (RCP4.5 and RCP8.5). All models indicated that ETp was likely to increase at the eight stations. The ensemble increases of mean ETp across eight stations ranged from 33 mm year−1 (2.1%, 2040s) to 129 mm year−1 (9.2%, 2090s) and from 43 mm year−1 (2.8%, 2040s) to 248 mm year−1 (17.6%, 2090s) under RCP4.5 and under RCP8.5, respectively. In addition, we also quantified uncertainties in ETp projections originating from ETp models, GCMs, RCPs, and their combined effects using the analysis of variance (ANOVA) method. Results showed that RCP-related uncertainty contributed the most to projected ETp uncertainty (around 40% for most stations) while GCM-related and ETp model-related uncertainties accounted for roughly e...
Sima, MW, Fang, QX, Qi, Z & Yu, Q 2020, 'Direct assimilation of measured soil water content in Root Zone Water Quality Model calibration for deficit-irrigated maize', Agronomy Journal.View/Download from: Publisher's site
© 2019 The Authors. Agronomy Journal © 2019 American Society of Agronomy Correct soil water simulation is critical for water balance and plant growth in agricultural systems. Crop production simulation errors have often been attributed to a lack of accuracy in soil water content (SWC) estimates. However, only a few studies have quantified the effects of SWC estimate errors on crop production and evapotranspiration (ET), especially under different irrigation treatments. The objective of this study was to investigate the impacts of direct assimilation of measured SWC during model calibration for deficit irrigated maize (Zea mays L.) on simulated ET, leaf area index (LAI), biomass, and yield. The CERES-Maize model within the Root Zone Water Quality Model (RZWQM) was calibrated using the automatic parameter estimation (PEST) software. Simulation results showed that, using PEST-optimized crop parameters, RZWQM was able to adequately predict crop yield (relative root mean squared error, rRMSE, of 4.8%) and biomass (rRMSE of 7.1%) in response to irrigation levels, in spite of the bias in SWC and ET simulation. However, with the same crop parameters but replacing simulated SWC with measured data, simulations of crop yield and biomass became worse, with higher rRMSE values (14.5% for yield and 21.5% for biomass). This unexpected model performance with SWC assimilation was mainly associated with the water addition and removal from the soil, which was improved only by recalibration of both soil and crop parameters. This study suggested compensating effects between soil and crop parameters during model calibration. Caution should be applied when using measured SWC as model inputs, especially under water stress conditions.
Song, Y, Wang, J, Yu, Q & Huang, J 2020, 'Using MODIS LAI data to monitor spatio-temporal changes of winter wheat phenology in response to climate warming', Remote Sensing, vol. 12, no. 5.View/Download from: Publisher's site
© 2020 by the authors. Understanding spatio-temporal changes in winter wheat (Triticum aestivum L) phenology and its response to temperature will be vital for adapting to climate change in the coming years. For this purpose, the heading date (HD), maturity date (MD), and length of the reproductive growth period (LRGP) were detected from the remotely sensed leaf area index (LAI) data by a threshold-based method during the harvest year 2003 to 2018 across the North China Plain. The results show that there was high spatial heterogeneity of winter wheat phenology in pixel scale across the whole area, which could not be detected in previous site-based studies. The results also verified that climate warming could explain part of the change in the HD. However, for the LRGP, the potential impact of non-climate effects should be further investigated. This study presents the spatio-temporal changes both in winter wheat phenology and corresponding mean temperature and then analyzes their relationships in pixel scale. Additionally, this study further discusses the potential impact of non-climate effects on the LRGP.
Wang, B, Feng, P, Waters, C, Cleverly, J, Liu, DL & Yu, Q 2020, 'Quantifying the impacts of pre-occurred ENSO signals on wheat yield variation using machine learning in Australia', Agricultural and Forest Meteorology, vol. 291.View/Download from: Publisher's site
© 2020 Elsevier B.V. Australia is one of the top wheat exporting countries in the world and the reliable prediction of wheat production plays a key role in ensuring regional and global food security. However, wheat yield in Australia is highly exposed to the impacts of climate variability, especially seasonal rainfall, as wheat is mostly grown in the drylands. Previous studies showed that El Niño Southern Oscillation (ENSO) has a strong influence on Australia's climate and found the ENSO-related phenomena have prognostic features for future climatic conditions. Therefore, we examined the predictability of state-scale variation in Australian wheat yields based on ENSO-related large-scale climate precursors using machine learning techniques. Here, we firstly established a set of random forest (RF, a machine learning method) models based on pre-occurred climate indices to forecast spring rainfall for the four major wheat producing states of Australia, the forecasted rainfall was then combined with selected precedent climate drivers to predict yield variations using another set of RF models for each state. We explored the most influential variables in determining spring rainfall and yield variation. We found that the first set of RF models accounted for 43-59% of the change in spring rainfall across the four states. By incorporating forecasted spring rainfall with selected ENSO climate indices, the RF model accounted for 33-66% of the variation in yield which was greater than the 22-50% of yield variations explained by ENSO-related indices alone. The results suggest that wheat yield variation at a state level could be reliably forecasted at lead-times of three months prior to the commencement of harvest. We also found that forecasted spring rainfall and precedent Southern Oscillation Index (SOI) in July were the most important factors in estimation of crop yield in the winter dominant rainfall states. ENSO climate indices are easy to obtain and can be rapidly used to...
Wu, D, Wang, P, Jiang, C, Yang, J, Huo, Z, Shi, K, Yang, Y & Yu, Q 2020, 'Use of a plastic temperature response function reduces simulation error of crop maturity date by half', AGRICULTURAL AND FOREST METEOROLOGY, vol. 280.View/Download from: Publisher's site
Yang, X, Zhang, X, Lv, D, Yin, S, Zhang, M, Zhu, Q, Yu, Q & Liu, B 2020, 'Remote sensing estimation of the soil erosion cover-management factor for China's Loess Plateau', Land Degradation and Development.View/Download from: Publisher's site
© 2020 John Wiley & Sons, Ltd. The cover-management factor (C-factor) is used in the revised universal soil loss equation to represent the effect of vegetation cover and its management practices on hillslope erosion. Remote sensing has been widely used to estimate vegetation cover and the C-factor, but most previous studies only used the photosynthetic vegetation (PV) or green vegetation indices (VI, e.g., normalized difference VI) for estimating the C-factor and the important non-PV (NPV) component was often ignored. In this study, we developed a new technique to estimate monthly time-series C-factor using the fractional vegetation cover (FVC) including both PV and NPV, and weighted by monthly rainfall erosivity ratio. The monthly FVC was derived from the moderate resolution imaging spectroradiometer and LANDSAT data with field validation. We conducted the case-study over China's Loess Plateau and analysed the spatiotemporal variations of FVC and the C-factor and their impacts on erosion over the Plateau. Our study reveals a significant increase in total vegetation cover (TC) from 56 to 76.8%, with a mean of 71.2%, resulting in about 20% decrease in the C-factor and erosion risk during the 17-year period. Our method has an advantage in estimating the C-factor from TC at a monthly scale providing a basis for continuously and consistently monitoring of vegetation cover, erosion risk and climate impacts.
Yao, N, Li, Y, Xu, F, Liu, J, Chen, S, Ma, H, Wai Chau, H, Liu, DL, Li, M, Feng, H, Yu, Q & He, J 2020, 'Permanent wilting point plays an important role in simulating winter wheat growth under water deficit conditions', Agricultural Water Management, vol. 229.View/Download from: Publisher's site
© 2019 Elsevier B.V. Soil parameters related to soil water holding capacity could play an important role in simulating winter wheat growth under severe soil water stress, which could heavily influence the simulated soil water contents, and then biomass and final yield. In this study, a field experiment of winter wheat (Triticum aestivum L.) was conducted in two consecutive growing seasons (2012–2014) under rainfall shelter in arid areas of China, with the purpose to identify to what extent the soil parameters could influence the simulated output variables in the DSSAT-CERES-Wheat model under water stress conditions. The permanent wilting point (PWP), which were initially indirectly measured based on soil sampling, were manually tuned through a trial-and-error method based on field observations of soil water content and aboveground biomass. The results showed that the maximum advancing of maturity date was about five days under water stress conditions. The stages of returning green and grain-filling were critical periods for agricultural water management of winter wheat in arid areas. The relative mean absolute error (RMAE) of simulated and observed variables were almost all less than 20% when water stress occurred at the heading and grain-filling stages. However, there were relatively large simulation errors when water stress occurred at the wintering and returning green stages. In addition, the CERES-Wheat model did not correctly simulate the discrepancies in phenology dates of winter wheat. The overall averaged root mean square error of all treatments for total water storage in 0−100 cm soil layer and winter wheat biomass decreased to 0.3 mm and 750 kg ha−1 after manually tuning the initially indirectly measured value of PWP. In general, the CERES-Wheat model showed some limitations to simulate winter growth under complicated arid conditions. Meanwhile, the measurement uncertainty in soil parameter PWP could introduce large simulation errors in simulating crop ...
Ye, ZP, Ling, Y, Yu, Q, Duan, HL, Kang, HJ, Huang, GM, Duan, SH, Chen, XM, Liu, YG & Zhou, SX 2020, 'Quantifying Light Response of Leaf-Scale Water-Use Efficiency and Its Interrelationships With Photosynthesis and Stomatal Conductance in C3 and C4 Species', Frontiers in Plant Science, vol. 11.View/Download from: Publisher's site
© Copyright © 2020 Ye, Ling, Yu, Duan, Kang, Huang, Duan, Chen, Liu and Zhou. Light intensity (I) is the most dynamic and significant environmental variable affecting photosynthesis (An), stomatal conductance (gs), transpiration (Tr), and water-use efficiency (WUE). Currently, studies characterizing leaf-scale WUE–I responses are rare and key questions have not been answered. In particular, (1) What shape does the response function take? (2) Are there maximum intrinsic (WUEi; WUEi–max) and instantaneous WUE (WUEinst; WUEinst–max) at the corresponding saturation irradiances (Ii–sat and Iinst–sat)? This study developed WUEi–I and WUEinst–I models sharing the same non-asymptotic function with previously published An–I and gs–I models. Observation-modeling intercomparison was conducted for field-grown plants of soybean (C3) and grain amaranth (C4) to assess the robustness of our models versus the non-rectangular hyperbola models (NH models). Both types of models can reproduce WUE–I curves well over light-limited range. However, at light-saturated range, NH models overestimated WUEi–max and WUEinst–max and cannot return Ii–sat and Iinst–sat due to its asymptotic function. Moreover, NH models cannot describe the down-regulation of WUE induced by high light, on which our models described well. The results showed that WUEi and WUEinst increased rapidly within low range of I, driven by uncoupled photosynthesis and stomatal responsiveness. Initial response rapidity of WUEi was higher than WUEinst because the greatest increase of An and Tr occurred at low gs. C4 species showed higher WUEi–max and WUEinst–max than C3 species—at similar Ii–sat and Iinst–sat. Our intercomparison highlighted larger discrepancy between WUEi–I and WUEinst–I responses in C3 than C4 species, quantitatively characterizing an important advantage of C4 photosynthetic pathway—higher An gain but lower Tr cost per unit of gs change. Our models can accurately return the wealth of key quantities defining s...
Yu, Q, Wu, D, Huo, Z, Wang, P, Song, Y, Huarong, Z & Yang, Y 2020, 'Plastic temperature response function accurately simulates crop flowering or heading date', Agronomy Journal.
Although crop phenology is responsive and adaptable to cultural and climatic conditions, many phenology models are too sensitive to variable climatic conditions. This paper developed a plastic temperature response function by assuming that development rate was linearly related to temperature, and that the linearity was linearly responsive to day of year (DOYv) of the starting date of the vegetative growth period (VGP). Phenology observations and weather data were acquired for winter wheat (Triticum aestivum L.), rice (Oryza sativa L.), maize (Zea mays L.), and soybean (Glycine max L. Merrill) at twelve locations over 15 to 26 years. Additional data were observed for maize grown in an interval planting experiment. For 78.6% of the sites, the crop development rate during the VGP was positively affected by DOYv. Partial correlation analysis (controlling for temperature) indicated that DOYv was independent of temperature. When averaged over all crops and sites, the root mean square error (RMSE) for a plastic phenology model based on both response and adaptation mechanisms was lower (RMSE = 2.81 d) than models (RMSE = 3.39) based only on response mechanism (p < 0.01). Furthermore, simulations produced by the plastic model showed less bias to DOYv, temperature, and year. The plastic function provided a simple and effective method for achieving better phenology simulation accuracy. According to the plastic function, growing season under warming conditions will not be reduced by as much as simulated by models based only on response mechanism, so yield loss due to warming is likely to be overestimated.
- A plastic phenology model was applied to simulate crop vegetative phase
- Wheat, rice, maize, and soybean phenology observations under long‐term natural cultivation and an interval planting experiment were used
- Plastic model assumes development rate is linearly related to temperature, and that the linear relationship is affected by day of year of the starting date of ...
Zhang, H, Wang, B, Liu, DL, Zhang, M, Leslie, LM & Yu, Q 2020, 'Using an improved SWAT model to simulate hydrological responses to land use change: A case study of a catchment in tropical Australia', JOURNAL OF HYDROLOGY, vol. 585.View/Download from: Publisher's site
Zhang, M, Wang, B, Cleverly, J, Liu, DL, Feng, P, Zhang, H, Huete, A, Yang, X & Yu, Q 2020, 'Creating New Near-Surface Air Temperature Datasets to Understand Elevation-Dependent Warming in the Tibetan Plateau', REMOTE SENSING, vol. 12, no. 11.View/Download from: Publisher's site
Zhang, M, Wang, B, Liu, DL, Liu, J, Zhang, H, Feng, P, Kong, D, Cleverly, J, Yang, X & Yu, Q 2020, 'Incorporating dynamic factors for improving a GIS-based solar radiation model', Transactions in GIS.View/Download from: Publisher's site
© 2020 John Wiley & Sons Ltd Solar radiation has been a major input to agricultural, hydrological, and ecological modeling. However, solar radiation is usually influenced by three groups of dynamic factors: sun–earth position, terrain, and atmospheric effects. Therefore, an integrated approach to accurately consider the impacts of those dynamic factors on solar radiation is essential to estimate solar radiation over rugged terrain. In this study, a spatial and temporal gap-filling algorithm was proposed to obtain a seamless daily MODIS albedo dataset. A 1 km-resolution digital elevation model was used to model the impact of local topography and shading by surrounding terrain on solar radiation. A sunshine-based model was adopted to simulate radiation under the influence of clouds. A GIS-based solar radiation model that incorporates albedo, shading by surrounding terrain, and variations in cloudiness was used to address the spatial variability of these factors in mountainous terrain. Compared with other independent solar radiation products, our model generated a more reliable solar radiation product over rugged terrain, with an R2 of 0.88 and an RMSE of 2.55 MJ m−2 day−1. The improved solar radiation products and open source app can be used further in practice or scientific research.
Zhang, Q, Jia, X, Wei, X, Shao, M, Li, T & Yu, Q 2020, 'Total soil organic carbon increases but becomes more labile after afforestation in China's Loess Plateau', Forest Ecology and Management, vol. 461.View/Download from: Publisher's site
© 2020 Elsevier B.V. Afforestation of cropland is recommended as an effective approach to enhance soil organic carbon (SOC) sequestration and labile organic C fractions. However, the stabilization of SOC and its labile organic C fractions on the Loess Plateau is largely unknown. Our objective was to quantify total SOC concentration and labile organic C fractions in the 0–20 cm soil depth for four land use types on the Loess Plateau, including cropland and three afforested areas (composed of R. pseudoacacia forests, P. tabuliformis forests, and R. pseudoacacia + P. tabuliformis mixed forests). Total SOC concentration, particulate organic C (POC), dissolved organic C (DOC), microbial biomass C (MBC), and potassium permanganate-oxidizable C (KMnO4-C) were measured. Carbon management index (CMI) was also calculated. Afforestation showed a significant positive effect on total SOC and labile organic C fractions, compared with cropland. Afforestation with R. pseudoacacia, P. tabuliformis, and R. pseudoacacia + P. tabuliformis significantly increased POC by 57.4%, 22.2%, and 44.4% in the 0–5 cm soil layer; and similar increases were observed in the 5–10 cm and 10–20 cm layers. Similar trends to those observed for POC in response to afforestation were also seen for DOC, MBC, and KMnO4-C. Afforestation with R. pseudoacacia resulted in the highest total SOC concentrations and labile organic C fractions among the three afforestation treatments. These findings suggested that although afforestation can significantly promote total SOC accumulation, especially with R. pseudoacacia, SOC may become more labile following afforestation in the future.
Zhao, CS, Yang, Y, Yang, ST, Xiang, H, Ge, YR, Zhang, ZS, Zhao, Y & Yu, Q 2020, 'Effects of spatial variation in water quality and hydrological factors on environmental flows', Science of the Total Environment, vol. 728.View/Download from: Publisher's site
© 2020 Elsevier B.V. Environmental flow is the quantity, timing, and quality of water flows required to sustain freshwater and estuarine ecosystems and the human livelihoods and well-being that depend on these ecosystems. Environmental flows (e-flows) are crucial parameters for ecosystem restoration. Understanding the effects of spatial variation in the hydrological and water quality factors on e-flows aids the determination of recovery prior areas and helps to improve the success rate of ecosystem restoration projects. However, few studies have investigated the effects, which severely hinder the restoration of aquatic ecosystems and the sustainable use of water resources in inland waters. This paper therefore presents a framework for studying such effects. Spatial autocorrelation, a geostatistical method, is used to analyze the spatial variation in the hydrological and water quality factors and to further analyze the effects of various factors on the spatial heterogeneity of e-flows. Four different methods including the Tennant method, wetted perimeter method, AEHRA, and integrated water quality method are integrated to comprehensively evaluate e-flows. The former three methods consider the demands of biota on the streamflow, whereas the latter considers the demands on both the streamflow and the water quality. The results show that the Tennant and wetted perimeter methods, which focus on the statistics of only streamflow, result in similar spatial distribution of e-flows; the AEHRA and integrated water quality method, which consider the effects of water quality and other hydrological factors such as flow velocity and water depth on fish, also result in a similar spatial variation. Consideration of both demands on the hydrological factors and the water quality environmental factors makes the integrated water quality method more practical, particularly in developing regions with excessive pollutant discharge into rivers. In addition, spatial variation in the hydr...
Zhu, Q, Yang, X, Ji, F, Liu, DL & Yu, Q 2020, 'Extreme rainfall, rainfall erosivity, and hillslope erosion in Australian Alpine region and their future changes', International Journal of Climatology, vol. 40, no. 2, pp. 1213-1227.View/Download from: Publisher's site
© 2019 Royal Meteorological Society The Australian Alpine region is highly vulnerable to extreme climate events such as heavy rainfall and snow falls, these events subsequently impact rainfall erosivity and hillslope erosion in the region. In this study, the relationship between extreme rainfall indices (ERIs) and rainfall erosivity was examined across the Alpine region in New South Wales (NSW) and Australian Capital Territory (ACT) and the surrounding areas including Murray and Murrumbidgee and South East and Tablelands (SET). Rainfall erosivity, hillslope erosion, and their changes were estimated in the future periods using the revised universal soil loss equation and the NSW/ACT Regional Climate Modeling (NARCliM) projections. Results from the study demonstrate a good relationship between ERIs (especially Rx5Day) and rainfall erosivity. The rainfall erosivity and hillslope erosion are projected to increase about 2 and 8% for the near future (2020–2039), further increase to 8 and 18% for the far future (2060–2079) in the Alpine region assuming the groundcover is maintained at the current condition. The change in rainfall erosivity and erosion risk is highly uneven in space and in season with the highest erosion risk in summer with an increase about 33% in the next 50 years. The highest erosion risk area is predicted within SET (maximum rate 19.95 Mg ha−1 year−1), but on average, the ACT has the highest erosion rate, which is above 1.36 Mg ha−1 year−1 in all periods. The snowmelt in spring in the Alpine region is estimated to increase the rainfall erosivity by 13% in the baseline period, up to 24% in the near future, but far less (about 1%) in the far future due to predicted temperature rise and less snow available in the Alpine region in the next 50 years.
Bai, J, Shi, H, Yu, Q, Xie, Z, Li, L, Luo, G, Jin, N & Li, J 2019, 'Satellite-observed vegetation stability in response to changes in climate and total water storage in Central Asia.', The Science of the total environment, vol. 659, pp. 862-871.View/Download from: Publisher's site
Ecosystems in arid and semi-arid regions are vulnerable to climatic and anthropogenic disturbances. However, our understanding of vegetation stability (including resistance and resilience, which are the abilities of ecosystems to resist perturbations and return to pre-disturbance structure or function, respectively) in response to environmental changes in dryland ecosystems remains insufficient, particularly in the absence of large-scale observations of water availability. Here we introduced GRACE monthly total water storage anomaly (TWSA) data into an autoregressive model with remote sensed EVI, air temperature and precipitation to investigate the short-term vegetation stability and its influencing factors in Central Asia (CA) during 2003-2015. The results showed that the grid-level vegetation resilience in CA increased logarithmically as mean annual precipitation (R2 = 0.33, P < 0.05) but decreased linearly with increasing mean annual temperature (R2 = 0.41, P < 0.05). Vegetation resilience was not correlated with TWSA, due to the decoupling of TWSA with precipitation both spatially and temporally in the majority of CA. At the biome level, vegetation resilience also increased as a logarithmical function of aridity index (R2 = 0.80, P < 0.05). Vegetation resistance to TWSA showed minor difference across biomes, while vegetation resistance to precipitation functioned as a parabolic curve along the aridity gradient (R2 = 0.59, P < 0.05). Our results suggest that accounting for the effects of total water column instead of precipitation only is critical in understanding vegetation-water relationships in drylands. The steep decrease in vegetation resilience in areas with high temperature and low water availability implies a high risk of collapse for these water-limited ecosystems if there are severe droughts. Furthermore, reduction in total water storage, induced by, e.g., large-scale extraction of surface runoff or shallow-layer groundwater for irrigation, can resul...
Fang, Q, Ma, L, Harmel, RD, Yu, Q, Sima, MW, Bartling, PNS, Malone, RW, Nolan, BT & Doherty, J 2019, 'Uncertainty of CERES-maize calibration under different irrigation strategies using pest optimization algorithm', Agronomy, vol. 9, no. 5.View/Download from: Publisher's site
© 2019 by the authors. An important but rarely studied aspect of crop modeling is the uncertainty associated with model calibration and its effect on model prediction. Biomass and grain yield data from a four-year maize experiment (2008–2011) with six irrigation treatments were divided into subsets by either treatments (Calibration-by-Treatment) or years (Calibration-by-Year). These subsets were then used to calibrate crop cultivar parameters in CERES (Crop Environment Resource Synthesis)-Maize implemented within RZWQM2 (Root Zone Water Quality Model 2) using the automatic Parameter ESTimation (PEST) algorithm to explore model calibration uncertainties. After calibration for each subset, PEST also generated 300 cultivar parameter sets by assuming a normal distribution of each parameter within their reported values in the literature, using the Latin hypercube sampling (LHS) method. The parameter sets that produced similar goodness of fit (11–164 depending on subset used for calibration) were then used to predict all the treatments and years of the entire dataset. Our results showed that the selection of calibration datasets greatly affected the calibrated crop parameters and their uncertainty, as well as prediction uncertainty of grain yield and biomass. The high variability in model prediction of grain yield and biomass among the six (Calibration-by-Treatment) or the four (Calibration-by-Year) scenarios indicated that parameter uncertainty should be considered in calibrating CERES-Maize with grain yield and biomass data from different irrigation treatments, and model predictions should be provided with confidence intervals.
Feng, P, Liu, DL, Wang, B, Waters, C, Zhang, M & Yu, Q 2019, 'Projected changes in drought across the wheat belt of southeastern Australia using a downscaled climate ensemble', International Journal of Climatology, vol. 39, no. 2, pp. 1041-1053.View/Download from: Publisher's site
© 2018 Royal Meteorological Society Drought is viewed as a naturally recurring phenomenon in many Australian agricultural systems. Identifying regional changes in frequency and severity of drought induced by climate change is required to develop regionally specific adaptation strategies. In this study, we provided a first look at the impacts of climate change on 21st century drought characteristics over the New South Wales wheat belt of southeastern Australia. These impacts were assessed from an ensemble of 28 statistical downscaled global climate models under representative concentration pathway (RCP8.5). A modified relative standardized precipitation and evapotranspiration index (rSPEI) at the seasonal scale (3 months) was used to analyse temporal and spatial changes in drought. Results indicated that there was a tendency towards more frequent and severe winter–spring droughts over the study area. Moreover, winter–spring drought prone areas were expected to expand from west to east. Until the end of the 21st century, more than half the wheat belt would be vulnerable to winter–spring drought. The combined effects of reduced precipitation and increased temperature during future winter and spring seasons were the main reasons causing these changes of drought. In addition, summer and autumn droughts would have both slight temporal and spatial changes across the study region. This study also revealed that traditionally dry areas would likely experience an increased frequency of drought compared to wetter areas when subjected to a same increase in temperature or decrease in precipitation. Furthermore, the western part of the wheat belt might be unsuitable for winter crops in the future, or at least exposed to an increased risk of variable yield and would require a gradual transformation which might include summer crops or pastures. Investments in cropping land should be focused on the east part of the wheat belt to achieve more consistent financial returns.
Feng, P, Wang, B, Liu, DL & Yu, Q 2019, 'Machine learning-based integration of remotely-sensed drought factors can improve the estimation of agricultural drought in South-Eastern Australia', Agricultural Systems, vol. 173, pp. 303-316.View/Download from: Publisher's site
© 2019 Agricultural drought is a natural hazard arising from insufficient crop water supply. Many drought indices have been developed to characterize agricultural drought, relying on either ground-based climate data or various remotely-sensed drought proxies. Ground-based drought indices are more accurate but limited in coverage, while remote sensing drought indices cover large areas but have poor precision. Application of advanced data fusion approaches based on remotely-sensed data to estimate ground-based drought indices may help fill this gap. The overall objective of this study was to determine whether various remotely-sensed drought factors could be effectively used for monitoring agricultural drought in south-eastern Australia. In this study, thirty remotely-sensed drought factors from the Tropical Rainfall Measuring Mission (TRMM) and the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors were used to reproduce a ground-based drought index, SPEI (Standardized Precipitation Evapotranspiration Index) during 2001–2017 for the New South Wales wheat belt in south-eastern Australia. Three advanced machine learning methods, i.e. bias-corrected random forest, support vector machine, and multi-layer perceptron neural network, were adopted as the regression models in this procedure. A station-based historical climate dataset and observed wheat yields were used as reference data to evaluate the performance of the model-predicted SPEI in reflecting agricultural drought. Results show that the bias-corrected random forest model outperformed the other two models for SPEI prediction, as quantified by the lowest root mean square error (RMSE) and the highest R 2 values (<0.28 and ~0.9, respectively). Drought distribution maps produced by the bias-corrected random forest model were then compared with the station-based drought maps, showing strong visual and statistical agreement. Furthermore, the model-predicted SPEI values were more highly correlated ...
Feng, P, Wang, B, Liu, DL, Waters, C & Yu, Q 2019, 'Incorporating machine learning with biophysical model can improve the evaluation of climate extremes impacts on wheat yield in south-eastern Australia', Agricultural and forest meteorology., vol. 275, pp. 100-113.View/Download from: Publisher's site
Accurately assessing the impacts of extreme climate events (ECEs) on crop yield can help develop effective agronomic practices to deal with climate change impacts. Process-based crop models are useful tools to evaluate climate change impacts on crop productivity but are usually limited in modelling the effects of ECEs due to over-simplification or vague description of certain process and uncertainties in parameterization. In this study, we firstly developed a hybrid model by incorporating the APSIM model outputs and growth stage-specific ECEs indicators (i.e. frost, drought and heat stress) into the Random Forest (RF) model, with the multiple linear regression (MLR) model as a benchmark. The results showed that the APSIM + RF hybrid model could explain 81% of the observed yield variations in the New South Wales wheat belt of south-eastern Australia, which had a 33% improvement in modelling accuracy compared to the APSIM model alone and 19% improvement compared to the APSIM + MLR hybrid model. Drought events during the grain-filling and vegetative stages and heat events immediately prior to anthesis were identified as the three most serious ECEs causing yield losses. We then compared the APSIM + RF hybrid model with the APSIM model to estimate the effects of future climate change on wheat yield. It was interesting to find that future yield projected from single APSIM model might have a 1–10% overestimation compared to the APSIM + RF hybrid model. The APSIM + RF hybrid model indicated that we were underestimating the effects of climate change and future yield might be lower than predicted using single APSIM informed modelling due to lack of adequately accounting for ECEs-induced yield losses. Increasing heat events around anthesis and grain-filling periods were identified to be major factors causing yield losses in the future. Therefore, we conclude that including the effects of ECEs on crop yield is necessary to accurately assess climate change impacts. We expect ...
Geng, Q, Ren, Q, Nolan, RH, Wu, P & Yu, Q 2019, 'Assessing China's agricultural water use efficiency in a green-blue water perspective: A study based on data envelopment analysis', Ecological Indicators, vol. 96, pp. 329-335.View/Download from: Publisher's site
© 2018 Uneven water resources and growing food demand due to an increasing population bring challenges to China. One important mechanism to address these challenges is to enhance water use efficiency (WUE). This requires information on current efficiencies in water use for agricultural production. In this study, we provide a benchmarking tool to assess relative agricultural WUE in 31 provinces in China during 2003-2013. Data Envelopment Analysis (DEA) was used with both green-blue water and blue-only scenarios. Results show that China's agricultural WUE has improved evidently after 2008. Overall technical efficiency (TE) and the pure technical efficiency (PTE) in China based on the green-blue scenario are relatively high, with the average potential increase less than 10% (8% and 4%, respectively). However, there is a larger potential for blue water use efficiency (14% and 7% respectively). The PTE in Northern China (NC) is higher than that in Southern China (SC) while the TE in NC is lower under green-blue scenario. Moreover, the TE and PTE in NC are lower than that in SC under blue-only scenario. These results indicate that green water management techniques in NC are superior to SC but the scale efficiency (SE) in NC is lower. There are four provinces where the efficiency values are on the frontier in four cases, i.e. two scenarios (green-blue and blue-only) and two assumptions in DEA, but fourteen provinces where the efficiency values are not on the frontier in any case and most of them were located in SC. Our results also suggest that improving SE can substantially contribute to national WUE, but exploring the solutions to enhance blue water use efficiency in China is also a key task in the future works. The research results have important implications for China and different provinces to improve agricultural WUE by water policies and management.
Geng, Q, Ren, Q, Yan, H, Li, L, Zhao, X, Mu, X, Wu, P & Yu, Q 2019, 'Target areas for harmonizing the Grain for Green Programme in Chinas Loess Plateau', LAND DEGRADATION & DEVELOPMENT, vol. 31, no. 3, pp. 325-333.View/Download from: Publisher's site
Gu, C, Mu, X, Gao, P, Zhao, G, Sun, W & Yu, Q 2019, 'Rainfall erosivity and sediment load over the Poyang Lake Basin under variable climate and human activities since the 1960s', Theoretical and Applied Climatology, vol. 136, no. 1-2, pp. 15-30.View/Download from: Publisher's site
© 2018 Springer-Verlag GmbH Austria, part of Springer Nature Accelerated soil erosion exerts adverse effects on water and soil resources. Rainfall erosivity reflects soil erosion potential driven by rainfall, which is essential for soil erosive risk assessment. This study investigated the spatiotemporal variation of rainfall erosivity and its impacts on sediment load over the largest freshwater lake basin of China (the Poyang Lake Basin, abbreviate to PYLB). The spatiotemporal variations of rainfall erosivity from 1961 to 2014 based on 57 meteorological stations were detected using the Mann–Kendall test, linear regression, and kriging interpolation method. The sequential t test analysis of regime shift (STARS) was employed to identify the abrupt changes of sediment load, and the modified double mass curve was used to assess the impacts of rainfall erosivity variability on sediment load. It was found that there was significant increase (P < 0.05) in rainfall erosivity in winter due to the significant increase in January over the last 54 years, whereas no trend in year and other seasons. Annual sediment load into the Poyang Lake (PYL) decreased significantly (P < 0.01) between 1961 and 2014, and the change-points were identified in both 1985 and 2003. It was found that take annual rainfall erosivity as the explanatory variables of the double mass curves is more reasonable than annual rainfall and erosive rainfall. The estimation via the modified double mass curve demonstrated that compared with the period before change-point (1961–1984), the changes of rainfall erosivity increased 8.0 and 2.1% of sediment load during 1985–2002 and 2003–2014, respectively. Human activities decreased 50.2 and 69.7% of sediment load during the last two periods, which indicated effects of human activities on sediment load change was much larger than that of rainfall erosivity variability in the PYLB.
Guo, L, Changhui Peng, Chengcheng Gang, Eike Luedeling, Ji Chen, Jianchu Xu, Jimin Cheng, Jinghong Wang, Lu Liu, Mingjun Li & Qiang Yu 2019, 'Distribution margins as natural laboratories to infer species' flowering responses to climate warming and implications for frost risk', Agricultural and Forest Meteorology, vol. 268, pp. 299-307.View/Download from: Publisher's site
The timing of flowering phenology in most temperate trees results from the interplay of winter chilling and spring heat. As global warming progresses, reduced chilling may gain increasing importance in regulating flowering dates, and eventually offset flowering advances in response to warmer springs. Later onset of flowering events may arise, with negative effects on plant fitness. However, delayed flowering in trees may also reduce the risk from late frosts. Different temperature conditions at both margins of the apple growing areas of Shaanxi in China provide a natural laboratory to examine the responses of trees' flowering phenology and late frost risk to climate warming. We identified the chilling and heat accumulation periods for apples by Partial Least Squares regression of first flowering dates against daily chilling and heat accumulation rates during 2001–2016. We then analyzed the impacts of temperatures during these periods on flowering timing, and evaluated the frost risk for each site. Results indicated increasing importance of chilling temperatures from north to south, with greatest effects determined for the warmest site, where delayed blossom has been observed during the past 16 years. Since late frosts mostly occurred before tree flowering, only minor frost damage was detected for our study areas, with future delays in flowering likely to reduce the frost risk even further. The redistribution of apple trees to nearby locations with cold winters, either northward or uphill, could be a promising strategy to reduce the risk of insufficient chilling and ensure that production remains viable in a warming future.
Guo, LP, Mu, XM, Hu, JM, Gao, P, Zhang, YF, Liao, KT, Bai, H, Chen, XL, Song, YJ, Jin, N & Yu, Q 2019, 'Assessing impacts of climate change and human activities on streamflow and sediment discharge in the Ganjiang River basin (1964-2013)', Water (Switzerland), vol. 11, no. 8.View/Download from: Publisher's site
© 2019 by the authors. National large-scale soil and water conservation controls on the Gangjiang River basin have been documented, but the effect of governance on regional watershed hydrology and how the main driving factors act have not been systematically studied yet. To do this, this study evaluated changing trends and detected transition years for both streamflow and sediment discharge using long-term historical records at seven hydrological stations in the Ganjiang River basin over the past 50 years. The double mass curve (DMC) method was used to quantify the effects of both climate change and human activities on hydrological regime shifts. The results showed that the distributions of precipitation, streamflow, and sediment discharge within a year are extremely uneven and mainly concentrated in the flood season of Jiangxi Province. None of the stations showed significant trends over time for either annual precipitation or streamflow, while the annual sediment discharge at most stations decreased significantly over time. The estimation of sediment discharge via DMC indicated that after the transition years, there were rapid reductions in sediment discharge at all hydrological stations, and the average decline degree of midstream and downstream were much larger than that of upstream. Human activities, especially the increase of vegetation cover and construction of large and medium-sized reservoirs, provided a significantly greater contribution to the reduction of sediment discharge than did precipitation changes. As a case study of river evolution under global change environment, this study could provide scientific basis for the control of soil erosion and the management of water resources in Ganjiang River, as well as for the related research of Poyang Lake and the Yangtze River basin of China.
He, L, Qian, Z, Jin, N, Yu, Q & Hou, Y 2019, 'Drought Early Warning of Winter Wheat Based on Soil Water Dynamic Model Coupled with Grid Weather Forecast Data', Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, vol. 50, no. 9, pp. 170-176.View/Download from: Publisher's site
© 2019, Chinese Society of Agricultural Machinery. All right reserved. Drought is one of the most serious natural disasters and a threat of food security. It is extremely important to have accurate and timely early warning of drought for prevention and reduction of agricultural disasters. Current method of drought early warning was characterized by weak mechanism, low spatial resolution and lack of crop growth information. A daily crop growth and soil moisture dynamics simulation system using a soil water dynamic model in northern winter wheat zone was constructed. Based on this soil moisture simulation system, a drought early warning system for winter wheat was constructed. Daily drought early warning products from April to May in 2018 were generated by using this warning system. The results showed that forecast accuracy of soil relative moisture in next 10 days was high since its coefficient of determination was 0.63~0.91 and its root mean squared error was 5.6%~18.2%. The closer soil moisture forecast was in time, the more accurate was. Forecast accuracy of drought grades for severe and extreme drought was higher than those of mild and moderate grade. This drought warning system satisfied the needs of drought early warning in national agro-meteorological service department in China. The research result would provide scientific basis for prevention and reduction of agricultural disasters and national drought early warning services.
Tang, J, Wang, J, Fang, Q, Dayananda, B, Yu, Q, Zhao, P, Yin, H & Pan, X 2019, 'Identifying agronomic options for better potato production and conserving water resources in the agro-pastoral ecotone in North China', Agricultural and forest meteorology., vol. 272-273, pp. 91-101.View/Download from: Publisher's site
Potato is a main food crop in the agro-pastoral ecotone (APE) of North China, but its yield is low and highly variable. Agronomic managements, such as irrigation, fertilization and intensive cropping systems, has been used for increasing potato yield but resulted in negative environmental sequences (e.g., soil dryness and groundwater table decline) in such arid and semi-arid regions. This study aims to quantify the agronomic options for better potato production and groundwater conservations based on field experiments together with APSIM-Potato model. The long-term simulated crop yield, economic income and environmental impact (surface soil water content and groundwater table) were analyzed for the different cropping systems of potato (continuous planting, CP; alternating planting and fallowing, APF; long-term continuous fallowing, LF) and irrigation scheduling (rainfed and one-four irrigations). The calibrated APSIM-Potato performed well in simulating the responses of soil water dynamics, leaf area index (LAI), biomass, evapotranspiration (ET) and yield of potato to different irrigation treatments. Long-term (1981–2010) simulated potato yield could be increased by 43.4–90.2% from rainfed yield if irrigation was applied from 60 to 240 mm and the yield gap between the potential and rainfed yields could be narrowed by 41.5–85.9%. Across the APE, CP with four irrigations (240 mm) produced the maximum income of 18,445 Yuan·ha−1 while WUE was the highest for both CP and APF with two irrigations (120 mm). However, such irrigation amounts would decrease the groundwater table by 4.1–42 m across the APE during this period. Rainfed CP could enhance the groundwater table by 0–3 m but decrease available soil water content in 1 m depth by 15.5 mm per decade from 1981 to 2010. Rainfed APF and LF increase available soil water content in 1 m depth by 2–79 mm and 100–143 mm respectively. The study suggested that CP would decrease the soil moisture significantly and increase the ri...
Wang, B, An, S, Fang, Y, Liu, Y, Ma, R, Yu, Q & Zhao, X 2019, 'Using soil aggregate stability and erodibility to evaluate the sustainability of large-scale afforestation of Robinia pseudoacacia and Caragana korshinskii in the Loess Plateau', Forest ecology and management, vol. 450.View/Download from: Publisher's site
Revegetation in fragile ecosystems is an efficient means to increase aggregate stability and thus reduce soil erosion. However, the influence of large-scale afforestation on soil aggregate stability and erodibility in the Loess Plateau is not well understood. To assess the sustainability and suitability of widespread, long-term planting of plantations in terms of soil aggregate stability (mean weighted diameter (MWD) and geometric mean diameter (GMD)) and erodibility (K), we performed a large-scale investigation of soil aggregate stability and soil erodibility of Robinia pseudoacacia (RP) and Caragana korshinskii (CK) plantations on the Loess Plateau. The results showed that the soil macroaggregate fraction (>0.25 mm) content under RP and CK plantations had a decreasing trend with increasing latitude. Moreover, soil aggregate stability and soil organic carbon (SOC) and total nitrogen (TN) contents in RP and CK plantations decreased with increasing latitude. RP and CK plantations did not always result in improvement of soil aggregate stability and the accumulation of SOC and TN, which depended on the latitude and precipitation conditions. Specifically, RP planting in the south warm temperate forest subzone (STFZ) and north warm temperate forest subzone (NTFZ) could enhance the macroaggregate content (>5 mm), soil aggregate stability and soil nutrients, while CK planting for the improvement of the soil macroaggregate content, soil aggregate stability and soil nutrients in the temperate forest steppe subzone (TFSZ) was more effective than was RP planting. Correlation analysis showed that the latitude, longitude and mean annual precipitation (MAP) were significantly correlated with soil MWD, GMD, K values, SOC and TN across the RP and CK plantations, and soil MWD, GMD, and K values were significantly correlated with SOC and TN in RP and CK plantations. The changing trends of SOC and TN with latitude and longitude were consistent with that of soil aggregate stability ...
Wang, B, Feng, P, Chen, C, Liu, DL, Waters, C & Yu, Q 2019, 'Designing wheat ideotypes to cope with future changing climate in South-Eastern Australia', Agricultural Systems, vol. 170, pp. 9-18.View/Download from: Publisher's site
© 2018 Elsevier Ltd Global food demand is increasing with the rapid growth of the world's population and improvement in living standards. To meet this demand, crop yields need to increase but climate change presents a potential threat. Genetic and agronomic strategies are helping agriculture adapt to climate change, but introducing new genetic traits into crops is time-consuming and costly. Process-based biophysical modelling is a powerful tool for targeting and accelerating development of new synthetic cultivars, and we have used it to identify the traits of rain-fed wheat ideotypes and suitable sowing dates needed to adapt to future climate change in south-eastern Australia. Our simulations involved two Global Climate Models (GCMs) with the driest conditions under a high emission scenario of Representative Concentration Pathway (RCP) 8.5. We compared simulated yields under future climate with those under historical climate with and without changes in cultivar and sowing date. Our results show that wheat yield for the reference cultivar would decrease on average by 23% and 38% in 2061–2100 under RCP8.5 at two contrasting sites (wet and dry, respectively). Ideotypes with an early flowering date, longer grain filling period, larger radiation use efficiency, larger maximum grain size and faster potential grain filling rate, sown on the optimum sowing date proved to be effective at the wet site in reversing these declines, leading to an average yield increase of 20–24% for both GCMs. However, improving cultivars and altering sowing times would have little impact for a drier GCM at the dry site. Although there is some uncertainty in simulations related to the genetic coefficients used in the crop model, climate projections and emission scenarios, we demonstrate that it is possible to enhance wheat production under a future climate if a cultivar with a longer grain filling period and larger yield component parameter was adopted in eastern Australian wheat-growing area...
Wu, D, Wang, P, Jiang, C, Yang, J, Huo, Z & Yu, Q 2019, 'Correction to: Measured Phenology Response of Unchanged Crop Varieties to Long-Term Historical Climate Change (International Journal of Plant Production, (2019), 13, 1, (47-58), 10.1007/s42106-018-0033-z)', International Journal of Plant Production, vol. 13, no. 1, pp. 91-91.View/Download from: Publisher's site
© 2019, Springer Nature Switzerland AG. The original version of this article unfortunately contained mistakes. Table 1 was incorrect. The corrected table is given below.
Wu, D, Wang, P, Jiang, C, Yang, J, Huo, Z & Yu, Q 2019, 'Measured Phenology Response of Unchanged Crop Varieties to Long-Term Historical Climate Change', International Journal of Plant Production, vol. 13, no. 1, pp. 47-58.View/Download from: Publisher's site
© 2018, Springer Nature Switzerland AG. Understanding how crop phenology responds to historical climate change is a prerequisite for evaluating crop phenology and future yield responses. Most phenology response investigations are based on the phenology observed under circumstances of varieties changing over time, which then necessitates disentangling the role of climate change from the effect of changing varieties using various models. However, results from such studies are limited by the uncertainties caused by model mechanisms and assumptions and parameter calibration and validation. In this study, phenology observations were made for varieties of winter wheat (Triticum aestivum L.), rice (Oryza sativa L.), and spring maize (Zea mays L.) at 11 agro-meteorological observation sites in north China. The varieties observed for each species did not change over a period of at least 15 years. The observations were used to investigate the measured phenology response to climate. Dates of major wheat phenology stages tended to occur earlier due to warming, but the trend in rice and spring maize was not clear. Growth duration was shortened during the vegetative period of winter wheat, but was prolonged during vegetative period of rice and in the reproductive period of winter wheat and rice. Growing degree days (GDD) were generally increased for both vegetative and reproductive periods for all crops except during the vegetative period for winter wheat. We found that most trends in date of phenology stages, duration of growth phases, and GDD were similar to previous reports in which the varieties observed did not remain constant. This indicates that previous reports are likely to have overestimated the effect of cultivar shifting on crop phenology and underestimated the role of climate. Based on our results, growth duration under future warmer conditions may be longer than previously simulated, and hence yield may also be higher than previously estimated.
Yang, X, Li, J, Yu, Q, Ma, Y, Tong, X, Feng, Y & Tong, Y 2019, 'Impacts of diffuse radiation fraction on light use efficiency and gross primary production of winter wheat in the North China Plain', Agricultural and forest meteorology., vol. 275, pp. 233-242.View/Download from: Publisher's site
The increase of diffuse radiation fraction (kd) has been reported to significantly impact light use efficiency (LUE) and carbon uptake in terrestrial ecosystems. The impact of kd on LUE should be considered in crop models to accurately evaluate the effect of radiation changes on crop production. However, the magnitude of the kd effect is difficult to quantify because of the complicated interacting relationships among all of the meteorological parameters, as well as the changing effects for various ecosystem types and research sites. Eight site-years of flux data and two years of diffuse radiation data from two field ecosystems in the North China Plain were used to (1) compare the performance of five kd models, (2) explore the impacts of environmental factors on LUE and gross primary production (GPP) of winter wheat (Triticum aestivum L.), and (3) quantify the relationships between kd and both LUE and GPP of winter wheat. Comparison results showed that the kd model developed by Boland et al. performed the best of the five models evaluated. This model was chosen to calculate kd in this research. Path analysis show that kd was the main factor affecting LUE of winter wheat, explaining up to 55% of the variability in LUE. The relationship between kd and LUE was significantly linear (slope of about 0.326 g C mol−1). GPP initially increased and then decreased with increasing kd. A moderate radiation condition (kd = 0.53) was favorable for increasing GPP. The effect of kd on LUE should be added in the LUE module of APSIM-Nwheat to improve simulation accuracy. The results of this study highlight the importance of kd in correctly modeling LUE for winter wheat with a crop model and provide quantitative relationships between these two parameters. These relationships will be helpful in improving crop model simulation accuracy under changed climate conditions.
Zhang, H, Wang, B, Liu, DL, Zhang, M, Feng, P, Cheng, L, Yu, Q & Eamus, D 2019, 'Impacts of future climate change on water resource availability of eastern Australia: A case study of the Manning River basin', Journal of Hydrology, vol. 573, pp. 49-59.View/Download from: Publisher's site
© 2019 Elsevier B.V. Hydrological responses of catchments to climate change require detailed examination to ensure sustainable management of both water resources and natural ecosystems. This study evaluated the impacts of climate change on water resource availability of a catchment in eastern Australia (i.e. the Manning River catchment) and analyzed climate-hydrology relationships. For this evaluation, the Xinanjiang (XAJ) model was used and validated to simulate monthly rainfall-runoff relationships of the catchment. Statistically downscaled climate data based on 28 global climate models (GCMs) under RCP8.5 scenarios were used to assess the impacts of climate changes on the Manning River catchment. Our results showed that the XAJ model was able to reproduce observed monthly rainfall-runoff relationships with an R 2 ≥ 0.94 and a Nash-Sutcliffe Efficiency ≥0.92. The median estimates from the ensemble of downscaled GCM projections showed a slight decrease in annual rainfall and runoff for the period 2021–2060 and an increase for the period 2061–2100. Annual actual evapotranspiration was projected to increase slightly, while annual soil moisture content was predicted to decrease in the future. Our results also demonstrated that future changes in seasonal and annual runoff, actual evapotranspiration and soil moisture are largely dominated by changes in rainfall, with a smaller influence arising from changes in temperature. An increase in the values of high runoffs and a decrease in the values of low runoffs predicted from the ensemble of the 28 GCMs suggest increased variability of water resources at monthly and seasonal time-scales in the future. A trend of decreasing values in winter runoff and soil moisture content in the future is likely to aggravate possible future reductions in water availability in eastern Australia. These results contribute to the development of adaptive strategies and future policy options for the sustainable management of water resources i...
Zhao, CS, Yang, Y, Yang, ST, Xiang, H, Wang, F, Chen, X, Zhang, HM & Yu, Q 2019, 'Impact of spatial variations in water quality and hydrological factors on the food-web structure in urban aquatic environments.', Water research, vol. 153, pp. 121-133.View/Download from: Publisher's site
Global aquatic ecosystems are essential to human existence and have deteriorated seriously in recent years. Understanding the influence mechanism of habitat variation on the structure of the food-web allows the effective recovery of the health of degraded ecosystems. Whereas most previous studies focused on the selection of driving habitat factors, the impact of habitat variation on the food-web structure was rarely studied, resulting in the low success rate of ecosystem restoration projects globally. This paper presents a framework for exploring the effects of spatial variations in water quality and hydrological habitat factors on the food-web structure in city waters. Indices for the evaluation of the food-web structure are first determined by integrating model-parameter extraction via literature refinement. The key water quality and hydrological factors are then determined by coupling canonical correspondence analysis with partial least squares regression. Their spatial variation is investigated using spatial autocorrelation. Finally, fuzzy clustering is applied to analyze the influence of the spatial variations in water quality and hydrological factors on the food-web structure. The results obtained in Ji'nan, the pilot city of water ecological civilization in China, show that the Shannon diversity index, connectance index, omnivory index, and the ratio of total primary production to the total respiration are important indicators of food-web structural change. They show that the driving factors affecting the aquatic food-web structure in Ji'nan are hydrological factors (e.g., river width, water depth, and stream flow), physical aspects of water quality (e.g., air temperature, water temperature, electrical conductivity, and transparency), and chemical aspects (e.g., potassium, dissolved oxygen, calcium, and total hardness). They also show that the stability of the food-web is more prone to spatial variations in water quality than in hydrological factors. Highe...
Zhao, F, Wang, R, Zhang, K, Lei, J & Yu, Q 2019, 'Predicting spring wheat yields based on water use-yield production function in a semi-arid climate', SPANISH JOURNAL OF AGRICULTURAL RESEARCH, vol. 17, no. 2.View/Download from: Publisher's site
Zhu, Q, Yang, X, Yu, B, Tulau, M, McInnes-Clarke, S, Nolan, RH, Du, Z & Yu, Q 2019, 'Estimation of event-based rainfall erosivity from radar after wildfire', Land Degradation and Development, vol. 30, no. 1, pp. 33-48.View/Download from: Publisher's site
© 2018 John Wiley & Sons, Ltd. Rainfall erosivity impacts all stages of hillslope erosion processes and is an important factor (the 'R factor') in the Revised Universal Soil Loss Equation. It is estimated as the average annual value of the sum of all erosive events (EI30) over a period of many years. For each storm event, the EI30 value is the product of storm energy, E in MJ ha−1, and peak 30-min rainfall intensity (I30, mm hr−1). Previous studies often focused on estimation of the R factor for prediction of mean annual or long-term soil losses. However, many applications require EI30 values at much higher temporal resolution, such as postfire soil erosion monitoring, which requires a time step at storm events or on a daily basis. In this study, we explored the use of radar rainfall data to estimate the storm event-based EI30 after a severe wildfire in Warrumbungle National Park in eastern Australia. The radar-derived rainfall data were calibrated against 12 tipping bucket rain gauges across an area of 239 km2 and subsequently used to produce a time series of rainfall erosivity maps at daily intervals since the wildfire in January 2013. The radar-derived daily rainfall showed good agreement with the gauge measurements (R2 > 0.70, Ec = 0.66). This study reveals great variation in EI30 values ranging from near zero to 826.76 MJ·mm·ha−1·hr−1 for a single storm event. We conclude that weather radar rainfall data can be used to derive timely EI30 and erosion information for fire incident management and erosion control. The methodology developed in this study is generic and thus readily applicable to other areas where weather radar data are available.
Feng, P, Wang, B, Liu, DL, Xing, H, Ji, F, Macadam, I, Ruan, H & Yu, Q 2018, 'Impacts of rainfall extremes on wheat yield in semi-arid cropping systems in eastern Australia', Climatic Change, vol. 147, no. 3-4, pp. 555-569.View/Download from: Publisher's site
© 2018, Springer Science+Business Media B.V., part of Springer Nature. Investigating the relationships between climate extremes and crop yield can help us understand how unfavourable climatic conditions affect crop production. In this study, two statistical models, multiple linear regression and random forest, were used to identify rainfall extremes indices affecting wheat yield in three different regions of the New South Wales wheat belt. The results show that the random forest model explained 41–67% of the year-to-year yield variation, whereas the multiple linear regression model explained 34–58%. In the two models, 3-month timescale standardized precipitation index of Jun.–Aug. (SPIJJA), Sep.–Nov. (SPISON), and consecutive dry days (CDDs) were identified as the three most important indices which can explain yield variability for most of the wheat belt. Our results indicated that the inter-annual variability of rainfall in winter and spring was largely responsible for wheat yield variation, and pre-growing season rainfall played a secondary role. Frequent shortages of rainfall posed a greater threat to crop growth than excessive rainfall in eastern Australia. We concluded that the comparison between multiple linear regression and machine learning algorithm proposed in the present study would be useful to provide robust prediction of yields and new insights of the effects of various rainfall extremes, when suitable climate and yield datasets are available.
Gan, R, Zhang, Y, Shi, H, Yang, Y, Eamus, D, Cheng, L, Chiew, FHS & Yu, Q 2018, 'Use of satellite leaf area index estimating evapotranspiration and gross assimilation for Australian ecosystems', ECOHYDROLOGY, vol. 11, no. 5.View/Download from: Publisher's site
Guo, L-P, Yu, Q, Gao, P, Nie, X-F, Liao, K-T, Chen, X-L, Hu, J-M & Mu, X-M 2018, 'Trend and Change-Point Analysis of Streamflow and Sediment Discharge of the Gongshui River in China during the Last 60 Years', WATER, vol. 10, no. 9.View/Download from: Publisher's site
He, L, Cleverly, J, Wang, B, Jin, N, Mi, C, Liu, DL & Yu, Q 2018, 'Multi-model ensemble projections of future extreme heat stress on rice across southern China', Theoretical and Applied Climatology, vol. 133, no. 3-4, pp. 1107-1118.View/Download from: Publisher's site
Extreme heat events have become more frequent and intense with climate warming, and these heatwaves are a threat to rice production in southern China. Projected changes in heat stress in rice provide an assessment of the potential impact on crop production and can direct measures for adaptation to climate change. In this study, we calculated heat stress indices using statistical scaling techniques, which can efficiently downscale output from general circulation models (GCMs). Data across the rice belt in southern China were obtained from 28 GCMs in the Coupled Model Intercomparison Project phase 5 (CMIP5) with two emissions scenarios (RCP4.5 for current emissions and RCP8.5 for increasing emissions). Multi-model ensemble projections over the historical period (1960–2010) reproduced the trend of observations in heat stress indices (root-mean-square error RMSE = 6.5 days) better than multi-model arithmetic mean (RMSE 8.9 days) and any individual GCM (RMSE 11.4 days). The frequency of heat stress events was projected to increase by 2061–2100 in both scenarios (up to 185 and 319% for RCP4.5 and RCP8.5, respectively), especially in the middle and lower reaches of the Yangtze River. This increasing risk of exposure to heat stress above 30 °C during flowering and grain filling is predicted to impact rice production. The results of our study suggest the importance of specific adaption or mitigation strategies, such as selection of heat-tolerant cultivars and adjustment of planting date in a warmer future world.
He, L, Hou, Y, Yu, Q & Jin, N 2018, 'Influence of Different Resolutions Data on Regional Simulation of Crop Model', Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, vol. 49, no. 2, pp. 241-251.View/Download from: Publisher's site
© 2018, Chinese Society of Agricultural Machinery. All right reserved. Crop model is constructed on the field scale. There are simulated errors due to the up-scaling when it is applied from filed scale to larger scale. Regional applications of crop model are becoming universal methodologies to explore the interactions between crop, climate and management in agriculture systems to provide policy and decision making for food production. A spatial resolution should be determined before using crop model to simulate yield in the regional scale. There is a dilemma in considering the spatial resolution. A high spatial resolution simulation needs more hardware resource and expensive computing cost while a coarse resolution simulation would result in loss of spatial detail of variability. Therefore, exploring the uncertainties of regional simulation of crop model due to different spatial resolutions is essential to application of crop model in large scale. A WOFOST regional simulation platform was constructed at different spatial resolutions to quantify the simulation errors by spatial resolution of model force data. Five spatial resolution meteorological data (5 km, 10 km, 25 km and 50 km) were interpolated by the thin plate smoothing spline method which was provided by the software ANUSPLIN. The corresponding resolution soil parameters were extracted from a fine resolution soil database by spatial aggregation. Spatial management and crop cultivar parameters were calculated from observed agro-meteorological sites and then extended to different resolutions by Thiessen polygon method. The simulated yields were compared at different resolutions and statistical yields, and it was found that the average value of anthesis, maturity date, total above ground production and yield at potential yield level and water limited level did not have significant difference. However, there were more extreme values in the high resolution. Each simulation of four resolutions can perform the s...
He, L, Li, J, Harahap, M & Yu, Q 2018, 'Scale-Specific Controller of Carbon and Water Exchanges Over Wheat Field Identified by Ensemble Empirical Mode Decomposition', International Journal of Plant Production, vol. 12, no. 1, pp. 43-52.View/Download from: Publisher's site
© 2017, Springer International Publishing AG, part of Springer Nature. The exchange of carbon and water in the ecosystem is influenced not only by weather and climatic perturbations but also by vegetation dynamics. The relationship between carbon and water exchange and environment in agro-ecosystem across different temporal scales is not very often been quantified. Spectral analysis of eddy covariance measurements can identify the interactions between environmental and biological factors at multi-temporal scales. Here, we used a new method, ensemble empirical mode decomposition (EEMD), to study the temporal covariance between ecosystem exchange of carbon dioxide (NEE), latent heat flux (LE) and environmental factors in a winter wheat cropping system located at the North China Plain. The results showed that the NEE, LE and environmental factors can be decomposed into 12 significant quasi-period oscillations on various time-scales i.e. hourly, diurnal, weekly and seasonal timescales. Variance of NEE in diurnal, hourly, seasonal, weekly scale was 58.9, 29.6, 4.7, 0.6%, respectively. Variance of LE in diurnal, hourly, seasonal, weekly scale was 55.2, 15.5, 5.1, 1.8%, respectively. The largest of variance contribution is at diurnal time-scale from net radiation (Rn), wind speed (μ) and vapor pressure deficit (VPD) due to daily rhythms in solar radiation. The soil water content varied significantly at a relatively longer time-scale i.e. weekly and seasonal scale. Large variance contribution of ambient temperature (T) (63.4%) and VPD (33.6%) is in trend term due to the significant increasing seasonal trend from winter to summer. The correlation analysis indicated that NEE and LE was correlated highly with net radiation (Rn) at all time-scale, as well as with VPD, ambient temperature (T), and wind speed (μ) in diurnal scale and with soil water in seasonal time-scales. This implied that solar radiation contributed the main variation of carbon and water in short time-scale...
He, L, Wu, M, Hou, Y, Zhao, G, Jin, N & Yu, Q 2018, 'Statistical characteristics of heat stress in early rice based on extreme value distribution in China', Chinese Journal of Eco-Agriculture, vol. 26, no. 11, pp. 1601-1612.View/Download from: Publisher's site
© 2018 Chinese Journal of Eco-Agriculture. All rights reserved. Rice is one of the most important staple foods globally, eaten by more than half the world population. China is the largest producer of rice, accounting for 18.5% of the rice planted area globally and 28% of the global rice production. Rice is easily exposed to heat stress because of highly frequent heat-stress events in recent climate warming. Heat-stress is one of the main meteorological disasters causing yield loss in agriculture. Thus, it is essential to explore spatial and temporal characteristics along with extreme heat-wave distribution in early rice so as to develop measures for agricultural adaptation to climate change and to prevent and reduce natural disasters. Studies on heat-stress in rice have mainly focused on spatial and/or temporal distributions of heat-stress at provincial or catchment scales and on the relationship between heat-stress and yield production. However, spatial and temporal distributions of heat-stress at national scale and extreme heat-wave distribution have remained rarely explored. Extreme-value (outlier) theory is a branch of statistical deviation of median probability distribution, which is widely used in structural engineering, hydrology and traffic prediction. Here, we introduced extreme-value theory to analyze heat-stress in early rice and hypothesized that heat-stress in rice obeyed specific outlier distribution. Thus, using 214 meteorological data on early rice region in China, we studied spatial and temporal characteristics along with extreme-value distribution of heat-stress in early rice. Non-parametric methods (such as the Mann-Kendal trend test and extreme-value distribution) were used in this study. We found that: 1) mean values of two heat-stress indices - ADHS (cumulative heat-stress days) and HDD (heat-stress degree days) - used to determine the extent of heat-stress were larger in the south and central Hunan Province, central Jiangxi Province, centra...
Hu, Z, Shi, H, Cheng, K, Wang, Y-P, Piao, S, Li, Y, Zhang, L, Xia, J, Zhou, L, Yuan, W, Running, S, Li, L, Hao, Y, He, N, Yu, Q & Yu, G 2018, 'Joint structural and physiological control on the interannual variation in productivity in a temperate grassland: A data-model comparison.', Global change biology, vol. 24, no. 7, pp. 2965-2979.View/Download from: Publisher's site
Given the important contributions of semiarid region to global land carbon cycle, accurate modeling of the interannual variability (IAV) of terrestrial gross primary productivity (GPP) is important but remains challenging. By decomposing GPP into leaf area index (LAI) and photosynthesis per leaf area (i.e., GPP_leaf), we investigated the IAV of GPP and the mechanisms responsible in a temperate grassland of northwestern China. We further assessed six ecosystem models for their capabilities in reproducing the observed IAV of GPP in a temperate grassland from 2004 to 2011 in China. We observed that the responses to LAI and GPP_leaf to soil water significantly contributed to IAV of GPP at the grassland ecosystem. Two of six models with prescribed LAI simulated of the observed IAV of GPP quite well, but still underestimated the variance of GPP_leaf, therefore the variance of GPP. In comparison, simulated pattern by the other four models with prognostic LAI differed significantly from the observed IAV of GPP. Only some models with prognostic LAI can capture the observed sharp decline of GPP in drought years. Further analysis indicated that accurately representing the responses of GPP_leaf and leaf stomatal conductance to soil moisture are critical for the models to reproduce the observed IAV of GPP_leaf. Our framework also identified that the contributions of LAI and GPP_leaf to the observed IAV of GPP were relatively independent. We conclude that our framework of decomposing GPP into LAI and GPP_leaf has a significant potential for facilitating future model intercomparison, benchmarking and optimization should be adopted for future data-model comparisons.
Jin, N, Ren, W, Tao, B, He, L, Ren, Q, Li, S & Yu, Q 2018, 'Effects of water stress on water use efficiency of irrigated and rainfed wheat in the Loess Plateau, China.', The Science of the total environment, vol. 642, pp. 1-11.View/Download from: Publisher's site
The Loess Plateau, the largest arid and semi-arid zone in China, has been confronted with more severe water resource pressure and a growing demand for food production under global changes. For developing sustainable agriculture in this region, it is critical to learn spatiotemporal variations in water use efficiency (WUE) of main crops (e.g. winter wheat in this region) under various water management practices. In this study, we classified irrigated and rainfed wheat areas based on MODIS data, and calculated the winter wheat yield by using an improved light use efficiency model. The actual evapotranspiration (ETa) of winter wheat and the evapotranspiration drought index (EDI) were also investigated. Then we mainly examined the synergistic relationship between crop yield, ETa, and WUE, and analyzed the variations in WUE of irrigated and rainfed wheat under water stress during the 2010-2011 growing season. The results suggested that winter wheat in the Loess Plateau was primarily dominated by rainfed wheat. The average yield of irrigated wheat was 3928.4 kg/ha, 22.2% more than that of rainfed wheat. High spatial heterogeneities of harvest index (HI) and maximum light use efficiency (εmax) were found in the Loess Plateau. The ETa of irrigated wheat was 10.2% more than that of rainfed wheat. The ratio of irrigated and rainfed wheat under no water stress was 31.55% and 17.16%, respectively. With increasing water stress, the WUE of rainfed wheat decreased more quickly than that of irrigated wheat. The WUE variations in winter wheat under water stress depended strongly on the synergistic effects of two WUE components (crop yield and ETa) and their response to environmental conditions as well as water management practices (irrigated or rainfed). Our findings enhance our current understanding of the variations in WUE as affected by water stress under various water use conditions in arid and semi-arid areas.
Li, L, Wang, YP, Eamus, D, Yu, Q, Huete, A, Cleverly, J, Shi, H, Cheng, L & Zhang, L 2018, 'Evaluating global land surface models in CMIP5: analysis of ecosystem water- and light-use efficiences, and rainfall partitioning', Journal of Climate, vol. 31, no. 8, pp. 2995-3008.View/Download from: Publisher's site
Li, Y, Shi, H, Zhou, L, Eamus, D, Huete, A, Li, L, Cleverly, J, Hu, Z, Harahap, M, Yu, Q, He, L & Wang, S 2018, 'Disentangling Climate and LAI Effects on Seasonal Variability in Water Use Efficiency Across Terrestrial Ecosystems in China', Journal of Geophysical Research: Biogeosciences, vol. 123, no. 8, pp. 2429-2443.View/Download from: Publisher's site
©2018. American Geophysical Union. All Rights Reserved. Water use efficiency (WUE), the ratio of gross primary productivity (GPP) over evapotranspiration (ET), is a critical ecosystem function. However, it is difficult to distinguish the individual effects of climatic variables and leaf area index (LAI) on WUE, mainly due to the high collinearity among these factors. Here we proposed a partial least squares regression-based sensitivity algorithm to confront the issue, which was first verified at seven ChinaFlux sites and then applied across China. The results showed that across all biomes in China, monthly GPP (0.42–0.65), ET (0.33–0.56), and WUE (0.01–0.31) showed positive sensitivities to air temperature, particularly in croplands in northeast China and forests in southwest China. Radiation exerted stronger effects on ET (0.55–0.78) than GPP (0.19–0.65), resulting in negative responses (−0.44 to 0.04) of WUE to increased radiation among most biomes. Increasing precipitation stimulated both GPP (0.06–0.17) and ET (0.05–0.12) at the biome level, but spatially negative effects of excessive precipitation were also found in some grasslands. Both monthly GPP (−0.01 to 0.29) and ET (0.02–0.12) showed weak or moderate responses to vapor pressure deficit among biomes, resulting in weak response of monthly WUE to vapor pressure deficit (−0.04 to 0.08). LAI showed positive effects on GPP (0.18–0.60), ET (0–0.23), and WUE (0.13–0.42) across biomes, particularly on WUE in grasslands (0.42 ± 0.30). Our results highlighted the importance of LAI in influencing WUE against climatic variables. Furthermore, the sensitivity algorithm can be used to inform the design of manipulative experiments and compare with factorial simulations for discerning effects of various variables on ecosystem functions.
Shen, J, Huete, A, Tran, NN, Devadas, R, Ma, X, Eamus, D & Yu, Q 2018, 'Diverse sensitivity of winter crops over the growing season to climate and land surface temperature across the rainfed cropland-belt of eastern Australia', Agriculture, Ecosystems and Environment, vol. 254, pp. 99-110.View/Download from: Publisher's site
© 2017 Elsevier B.V. The rainfed cropland belt in Australia is of great importance to the world grain market but has the highest climate variability of all such regions globally. However, the spatial-temporal impacts of climate variability on crops during different crop growth stages across broadacre farming systems are largely unknown. This study aims to quantify the contributions of climate and Land Surface Temperature (LST) variations to the variability of the Enhanced Vegetation Index (EVI) by using remote sensing methods. The datasets were analyzed at an 8-day time-scale across the rainfed cropland of eastern Australia. First, we found that EVI values were more variable during the crop reproductive growth stages than at any other crop life stage within a calendar year, but nevertheless had the highest correlation with crop grain yield (t ha−1). Second, climate factors and LST during the crop reproductive growth stages showed the largest variability and followed a typical east-west gradient of rainfall and a north-south temperature gradient across the study area during the crop growing season. Last, we identified two critical 8-day periods, beginning on day of the year (DoY) 257 and 289, as the key 'windows' of crop growth variation that arose from the variability in climate and LST. Our results show that the sum of the variability of the climate components within these two 8-day 'windows' explained >88% of the variability in the EVI, with LST being the dominant factor. This study offers a fresh understanding of the spatial-temporal climate-crop relationships in rainfed cropland and can serve as an early warning system for agricultural adaptation in broadacre rainfed cropping practices in Australia and worldwide.
Tang, J, Wang, J, Wang, E, Yu, Q, Yin, H, He, D & Pan, X 2018, 'Identifying key meteorological factors to yield variation of potato and the optimal planting date in the agro-pastoral ecotone in North China', Agricultural and Forest Meteorology, vol. 256-257, pp. 283-291.View/Download from: Publisher's site
© 2018 Elsevier B.V. Precipitation is the key yield–determining factor for rainfed agricultural production such as the agro-pastoral ecotone in North China with high variation in precipitation. However, the yield–precipitation relationship depends on the distribution and amount of precipitation over the crop growth period. Understanding crop yield responses to precipitation can help develop appropriate measures to ensure stable crop production in the agro-pastoral ecotone. In this study, an experiment was conducted consisting of five planting dates each year across four years and three planting dates in one year, to investigate the potato yield response to precipitation at a representative site (Wuchuan) in the ecotone. The optimal planting date, with the highest potato yield, varied substantially in different years during the experimental period. It was found that potato yield had the highest correlation with the ratio of precipitation to potential evapotranspiration during the tuberization stage (PT/ETpT) (R2 = 0.51, P < 0.01), followed by the effective precipitation during the post-tuber bulking period (EPpoTB) (R2 = 0.43, P < 0.01) and during the entire growth period (EPgp) (R2 = 0.28, P < 0.05). The potato yield was positively related to total solar radiation during the growth period (Sgp) (R2 = 0.37, P < 0.01), especially during the pre-tuber bulking period (SprTB) (R2 = 0.44, P<0.01), while growth-period maximum temperature (Tmaxgp) had a negative effect on potato yield (R2 = 0.27, P < 0.05). The multiple linear regression equation of potato yield and meteorological factors during the potato growth period showed that the variation in PT/ETpT, EPpoTB and SprTB could explain 71% of the variation in potato yield. The optimal planting dates, based on the 80 t h percentile of the highest yield related to PT/ETpT, EPpoTB and SprTB within the potential planting window from 1961 to 2010, were found to be May 27–June 12 for a wet year, May 3–May 26 for a normal yea...
Tian, H, Lu, C, Pan, S, Yang, J, Miao, R, Ren, W, Yu, Q, Fu, B, Jin, FF, Lu, Y, Melillo, J, Ouyang, Z, Palm, C & Reilly, J 2018, 'Optimizing resource use efficiencies in the food–energy–water nexus for sustainable agriculture: from conceptual model to decision support system', Current Opinion in Environmental Sustainability, vol. 33, pp. 104-113.View/Download from: Publisher's site
© 2018 Elsevier B.V. Increased natural and anthropogenic stresses have threatened the Earth's ability to meet growing human demands of food, energy and water (FEW) in a sustainable way. Although much progress has been made in the provision of individual component of FEW, it remains unknown whether there is an optimized strategy to balance the FEW nexus as a whole, reduce air and water pollution, and mitigate climate change on national and global scales. Increasing FEW conflicts in the agroecosystems make it an urgent need to improve our understanding and quantification of how to balance resource investment and enhance resource use efficiencies in the FEW nexus. Therefore, we propose an integrated modeling system of the FEW nexus by coupling an ecosystem model, an economic model, and a regional climate model, aiming to mimic the interactions and feedbacks within the ecosystem–human–climate systems. The trade-offs between FEW benefit and economic cost in excess resource usage, environmental degradation, and climate consequences will be quantitatively assessed, which will serve as sustainability indicators for agricultural systems (including crop production, livestock and aquaculture). We anticipate that the development and implementation of such an integrated modeling platform across world's regions could build capabilities in understanding the agriculture-centered FEW nexus and guiding policy and land management decision making for a sustainable future.
Wang, B, Liu, DL, O'Leary, GJ, Asseng, S, Macadam, I, Lines-Kelly, R, Yang, X, Clark, A, Crean, J, Sides, T, Xing, H, Mi, C & Yu, Q 2018, 'Australian wheat production expected to decrease by the late 21st century.', Global change biology, vol. 24.View/Download from: Publisher's site
Climate change threatens global wheat production and food security, including the wheat industry in Australia. Many studies have examined the impacts of changes in local climate on wheat yield per hectare, but there has been no assessment of changes in land area available for production due to changing climate. It is also unclear how total wheat production would change under future climate when autonomous adaptation options are adopted. We applied species distribution models to investigate future changes in areas climatically suitable for growing wheat in Australia. A crop model was used to assess wheat yield per hectare in these areas. Our results show that there is an overall tendency for a decrease in the areas suitable for growing wheat and a decline in the yield of the northeast Australian wheat belt. This results in reduced national wheat production although future climate change may benefit South Australia and Victoria. These projected outcomes infer that similar wheat-growing regions of the globe might also experience decreases in wheat production. Some cropping adaptation measures increase wheat yield per hectare and provide significant mitigation of the negative effects of climate change on national wheat production by 2041-2060. However, any positive effects will be insufficient to prevent a likely decline in production under a high CO2 emission scenario by 2081-2100 due to increasing losses in suitable wheat-growing areas. Therefore, additional adaptation strategies along with investment in wheat production are needed to maintain Australian agricultural production and enhance global food security. This scenario analysis provides a foundation towards understanding changes in Australia's wheat cropping systems, which will assist in developing adaptation strategies to mitigate climate change impacts on global wheat production.
Wang, B, Liu, DL, Waters, C & Yu, Q 2018, 'Quantifying sources of uncertainty in projected wheat yield changes under climate change in eastern Australia', Climatic Change, vol. 151, no. 2, pp. 259-273.View/Download from: Publisher's site
© 2018, Springer Nature B.V. Future climate projections and impact analyses are pivotal to evaluate the potential change in crop yield under climate change. Impact assessment of climate change is also essential to prepare and implement adaptation measures for farmers and policymakers. However, there are uncertainties associated with climate change impact assessment when combining crop models and climate models under different emission scenarios. This study quantifies the various sources of uncertainty associated with future climate change effects on wheat productivity at six representative sites covering dry and wet environments in Australia based on 12 soil types and 12 nitrogen application rates using one crop model driven by 28 global climate models (GCMs) under two representative concentration pathways (RCPs) at near future period 2021–2060 and far future period 2061–2100. We used the analysis of variance (ANOVA) to quantify the sources of uncertainty in wheat yield change. Our results indicated that GCM uncertainty largely dominated over RCPs, nitrogen rates, and soils for the projections of wheat yield at drier locations. However, at wetter sites, the largest share of uncertainty was nitrogen, followed by GCMs, soils, and RCPs. In addition, the soil types at two northern sites in the study area had greater effects on yield change uncertainty probably due to the interaction effect of seasonal rainfall and soil water storage capacity. We concluded that the relative contributions of different uncertainty sources are dependent on climatic location. Understanding the share of uncertainty in climate impact assessment is important for model choice and will provide a basis for producing more reliable impact assessment.
Wang, B, Zheng, L, Liu, DL, Ji, F, Clark, A & Yu, Q 2018, 'Using multi-model ensembles of CMIP5 global climate models to reproduce observed monthly rainfall and temperature with machine learning methods in Australia', International Journal of Climatology, vol. 38, no. 13, pp. 4891-4902.View/Download from: Publisher's site
© 2018 Royal Meteorological Society Global climate models (GCMs) are useful tools for assessing climate change impacts on temperature and rainfall. Although climate data from various GCMs have been increasingly used in climate change impact studies, GCMs configurations and module characteristics vary from one to another. Therefore, it is crucial to assess different GCMs to confirm the extent to which they can reproduce the observed temperature and rainfall. Rather than assessing the interdependence of each GCM, the purpose of this study is to compare the capacity of four different multi-model ensemble (MME) methods (random forest [RF], support vector machine [SVM], Bayesian model averaging [BMA] and the arithmetic ensemble mean [EM]) in reproducing observed monthly rainfall and temperature. Of these four methods, the RF and SVM demonstrated a significant improvement over EM and BMA in terms of performance criteria. The relative importance of each GCM based on the RF ensemble in reproducing rainfall and temperature could also be ranked. We compared the GCMs importance and Taylor skill score and found that their correlation was 0.95 for temperature and 0.54 for rainfall. Our results also demonstrated that the number of GCMs ensemble simulations could be reduced from 33 to 25 in RF model while maintaining predictive error less than 2%. Having such a representative subset of simulations could reduce computational costs for climate impact modelling and maintain the quality of ensemble at the same time. We conclude that machine learning MME could be efficient and useful with improved accuracy in reproducing historical climate variables.
Yang, X, McMaster, GS & Yu, Q 2018, 'Spatial Patterns of Relationship Between Wheat Yield and Yield Components in China', International Journal of Plant Production, vol. 12, no. 1, pp. 61-71.View/Download from: Publisher's site
© 2018, Springer International Publishing AG, part of Springer Nature. The considerable plasticity of wheat (Triticum aestivum L.) in reaching final yield is dynamically determined by three yield components: spike number m−2 (SN), kernel number spike−1 (KN) and 1000-kernel weight (KW). Understanding the contribution of yield components to the variation of grain yield under different production environments is essential for designing breeding programs and increasing grain production. This study analyzed 2 years of experimental data from the Chinese Variety Evaluation Program to explore the relationship between grain yield and yield components in four main winter wheat production regions. Correlation and path analysis were the main methods used in this paper. Yield and yield components were restricted by high temperature and lower sunshine hours at southern regions (Upper Yangtze Valleys, UY and Middle and Lower Yangtze Valleys, MLY). No relationship between yield and climate elements was found at northern region (Yellow and Huai Valleys, YH and Northern Land, NL). Yield in the YH region was the greatest with both higher SN and KN, and SN had strong negative relationships with KN and KW. SN was the main factor correlated the variation of yield, especially in low yielding regions (UY and NL), suggesting breeding efforts should emphasize increasing SN in these environments. The role of KW and KN became increasingly important in high yielding region (YH), indicating that all yield components should be considered in breeding for high yielding environments.
Yang, XY, Li, J, Jiang, XD, Tong, XJ & Yu, Q 2018, 'Relationships between diffuse radiation fraction and light use efficiency and gross primary productivity of winter wheat', Chinese Journal of Agrometeorology, vol. 39, no. 7, pp. 462-467.View/Download from: Publisher's site
© 2018 Editorial Board of Chinese Journal of Agrometeorology. All rights reserved. The quantitative relationships between the diffuse radiation fraction (DF) and light use efficiency (LUE) and gross primary productivity (GPP) from jointing to milky maturity of winter wheat (from April 1, 2004 to May 20 and from April 10, 2005 to May 31) were analyzed in this research on the basis of field CO2 flux observation. The research results can improve the simulation accuracy of LUE model and crop model. The results indicated that the relationship between DF and LUE was significantly positive linear (P＜0.001), and the relationship between DF and GPP was significantly parabolic curve (P＜0.001). LUE increased linearly with the increasing of DF, while GPP increased first and then decreased. Observational experiments on 2004 and 2005 showed that the GPP of winter wheat reached the highest under the condition of moderate solar radiation, with the average values of DF and photosynthetic active radiation (PAR) were 0.57, 27.7molm−2d−1, respectively. The quantitative equations between DF and LUE and GPP in two years were different. The differences were mainly attributed to the different PAR level and the distribution frequency of DF from jointing to milky maturity of winter wheat during the two years.
Zhao, CS, Shao, NF, Yang, ST, Xiang, H, Lou, HZ, Sun, Y, Yang, ZY, Zhang, Y, Yu, XY, Zhang, CB & Yu, Q 2018, 'Identifying the principal driving factors of water ecosystem dependence and the corresponding indicator species in a pilot City, China', Journal of Hydrology, vol. 556, pp. 488-499.View/Download from: Publisher's site
© 2017 Elsevier B.V. The world's aquatic ecosystems yield numerous vital services, which are essential to human existence but have deteriorated seriously in recent years. By studying the mechanisms of interaction between ecosystems and habitat processes, the constraining factors can be identified, and this knowledge can be used to improve the success rate of ecological restoration initiatives. At present, there is insufficient data on the link between hydrological, water quality factors and the changes in the structure of aquatic communities to allow any meaningful study of driving factors of aquatic ecosystems. In this study, the typical monitoring stations were selected by fuzzy clustering analysis based on the spatial and temporal distribution characteristics of water ecology in Jinan City, the first pilot city for the construction of civilized aquatic ecosystems in China. The dominant species identification model was used to identify the dominant species of the aquatic community. The driving effect of hydrological and water quality factors on dominant species was analyzed by Canonical Correspondence Analysis. Then, the principal factors of aquatic ecosystem dependence were selected. The results showed that there were 10 typical monitoring stations out of 59 monitoring sites, which were representative of aquatic ecosystems, 9 dominant fish species, and 20 dominant invertebrate species. The selection of factors for aquatic ecosystem dependence in Jinan were highly influenced by its regional conditions. Chemical environmental parameters influence the temporal and spatial variation of invertebrate much more than that of fish in Jinan City. However, the methodologies coupling typical monitoring stations selection, dominant species determination and driving factors identification were certified to be a cost-effective way, which can provide in-deep theoretical and technical directions for the restoration of aquatic ecosystems elsewhere.
Zhao, F, Lei, J, Wang, R, Wang, H, Zhang, K & Yu, Q 2018, 'Determining agricultural drought for spring wheat with statistical models in a semi-arid climate', JOURNAL OF AGRICULTURAL METEOROLOGY, vol. 74, no. 4, pp. 162-172.View/Download from: Publisher's site
Zu, Q, Mi, C, Liu, DL, He, L, Kuang, Z, Fang, Q, Ramp, D, Li, L, Wang, B, Chen, Y, Li, J, Jin, N & Yu, Q 2018, 'Spatio-temporal distribution of sugarcane potential yields and yield gaps in Southern China', European Journal of Agronomy, vol. 92, pp. 72-83.View/Download from: Publisher's site
© 2017 Elsevier B.V. The sustainability and production capacity of sugarcane (Saccharum officinarum (L.)) in Southern China is essential to ensure sugar security in China, yet potential crop yield and yield gap (the difference between actual and potential crop yield) of sugarcane is poorly known. In this study, the sugarcane growth and development model, QCANE, was validated for sugarcane phenology, stalk height, and yields, then used to simulate potential yields and yield gaps of sugarcane in Southern Chine (SC) between 1970 and 2014. Simulated potential yields decreased as longitude and latitude increased, driven by spatial variation in solar radiation and maximum temperature. The gap between potential and water-limited yields was noticeably larger in Yunnan province because of the prevalence of seasonal water deficiency. However, nitrogen stress was the dominant driver of the yield gap, given the abundant precipitation in SC. Across SC, large variation in the yield gap between water-and-nitrogen limited yields and on-farm yields was observed for different counties, a difference that was usually larger than the local yield gap. Averaged across SC, on-farm sugarcane yields were only 27% of potential yields, 31% of water-limited yields, and 52% of nitrogen-limited yields. This result highlights considerable potential to significantly increase sugarcane production by improving varieties, government support, effective management measures such as fertilization, irrigation, and mechanization.
Zhao, C, Zhang, Y, Yang, S, Xiang, H, Sun, Y, Yang, Z, Yu, Q & Lim, RP 2018, 'Quantifying effects of hydrological and water quality disturbances on fish with food-web modeling', Journal of Hydrology, vol. 560, pp. 1-10.View/Download from: Publisher's site
© 2018 Elsevier B.V. Accurately delineating the effects of hydrological and water quality habitat factors on the aquatic biota will significantly assist the management of water resources and restoration of river ecosystems. However, current models fail to comprehensively consider the effects of multiple habitat factors on the development of fish species. In this study, a dynamic framework for river ecosystems was set up to explore the effects of multiple habitat factors in terms of hydrology and water quality on the fish community in rivers. To achieve this the biomechanical forms of the relationships between hydrology, water quality, and aquatic organisms were determined. The developing processes of the food web without external disturbance were simulated by 208 models, constructed using Ecopath With Ecosim (EWE). These models were then used to analyze changes in biomass (ΔB) of two representative fish species, Opsariichthys bidens and Carassius auratus, which are widely distributed in Asia, and thus have attracted the attention of scholars and stakeholders, due to the consequence of habitat alteration. Results showed that the relationship between the changes in fish biomass and key habitat factors can be expressed in a unified form. T-tests for the unified form revealed that the means of the two data sets of simulated and observed ΔB for these two fish species (O. bidens and C. auratus) were equal at the significance level of 5%. Compared with other ecological dynamic models, our framework includes theories that are easy to understand and has modest requirements for assembly and scientific expertise. Moreover, this framework can objectively assess the influence of hydrological and water quality variance on aquatic biota with simpler theory and little expertise. Therefore, it is easy to be put into practice and can provide a scientific support for decisions in ecological restoration made by river administrators and stakeholders across the world.
Dong, J, Li, L, Shi, H, Chen, X, Luo, G & Yu, Q 2017, 'Robustness and Uncertainties of the "temperature and Greenness" Model for Estimating Terrestrial Gross Primary Production', Scientific Reports, vol. 7, pp. 1-8.View/Download from: Publisher's site
© 2017 The Author(s). Terrestrial gross primary production (GPP) plays a vital role in offsetting anthropogenic CO 2 emission and regulating global carbon cycle. Various remote sensing approaches for estimating GPP have attracted considerable scientific attentions, yet their robustness and uncertainties remain unclear. Here we evaluate the performance of the "temperature and greenness" (TG) model, a representative remote sensing model in estimating GPP, using the global FLUXNET GPP based on parameter sensitive analysis and optimization strategies. The results show that the minimum (x n ) and optimum (x o ) temperatures for photosynthesis are sensitive parameters but maximum temperature (x m ) not. Optimized x n and x o differ largely from their defaults for more than half of 12 plant functional types (PFTs). Parameter optimization significantly improves the TG's performance in forest ecosystems where temperature or solar radiation has significant contribution to GPP. For water-limited ecosystems where GPP are strongly dependent of EVI and EVI are sensitive to precipitation, parameter optimization has limited effects. These results imply that the TG model, and most likely for other kind of GPP models using same methodology, can't be significantly improved for all PFTs through parameter optimization only, and other key climatic variables should be incorporated into the model for better predicting terrestrial ecosystem GPP.
Fang, Q, Ma, L, Ahuja, LR, Trout, TJ, Malone, R, Zhang, H, Gui, D & Yu, Q 2017, 'Long-term simulation of growth stage-based irrigation scheduling in maize under various water constraints in Colorado, USA', Frontiers of Agricultural Science and Engineering, vol. 4, no. 2, pp. 172-184.View/Download from: Publisher's site
© The Author(s) 2017. Due to varying crop responses to water stress at different growth stages, scheduling irrigation is a challenge for farmers, especially when water availability varies on a monthly, seasonal and yearly basis. The objective of this study was to optimize irrigation between the vegetative (V) and reproductive (R) phases of maize under different available water levels in Colorado. Longterm (1992-2013) scenarios simulated with the calibrated Root Zone Water Quality Model were designed to meet 40%-100% of crop evapotranspiration (ET) requirements at V and R phases, subject to seasonal water availabilities (300, 400, 500 mm, and no water limit), with and without monthly limits (total of 112 scenarios). The most suitable irrigation between Vand R phases of maize was identified as 60/100, 80/100, and 100/100 of crop ET requirement for the 300, 400, 500 mm water available, respectively, based on the simulations from 1992 to 2013. When a monthly water limit was imposed, the corresponding suitable irrigation targets between V and R stages were 60/100, 100/100, and 100/100 of crop ET requirement for the above three seasonal water availabilities, respectively. Irrigation targets for producing higher crop yield with reduced risk of poor yield were discussed for projected five-year water availabilities.
Fang, QX, Ma, L, Qi, Z, Shen, YJ, He, L, Xu, SH, Kisekka, I, Sima, M, Malone, RW & Yu, Q 2017, 'Optimizing ET-based irrigation scheduling for wheat and maize with water constraints', Transactions of the ASABE, vol. 60, no. 6, pp. 2053-2065.
© 2017 American Society of Agricultural and Biological Engineers. Deficit irrigation has been shown to increase crop water use efficiency (WUE) under certain conditions, even though the yield is slightly reduced. In this study, the Root Zone Water Quality Model (RZWQM) was first calibrated with measured data from a large weighing lysimeter from 1998 to 2003 at the Yucheng Experimental Station in the North China Plain for daily evapotranspiration (ET), soil water storage (0-120 cm), leaf area index (LAI), aboveground biomass, and grain yield. The calibrated model was then used to explore crop responses to ET-based irrigation management using weather data from 1958 to 2015 and identify the most suitable ET-based irrigation schedules for the area. Irrigation amount was determined by constraining irrigation to a percentage of potential crop ET (40%, 60%, 80%, and 100% ET c ) at the various growth stages of wheat [planting to before winter dormancy (P-D), green up to booting (G-B), booting to flowering (B-F), and flowering to maturity (F-M)] and of maize [planting to silking (P-S) and silking to maturity (S-M)] , subject to seasonal water availability limits of 100/50, 200/100, 300/150, and 400/200 mm and no water limit for wheat/maize seasons, respectively. In general, wheat was more responsive to irrigation than maize, while greater influence of weather variation was simulated on maize than on wheat. For wheat with seasonal water limits, the highest average WUE was simulated with the highest targeted ET c levels at both the G-B and B-F stages and lower targeted ET c levels at the P-D and F-M stages. However, the highest average grain yield was simulated with the highest targeted ET c levels at all four growth stages for no water limit and the 400 mm water limit, or at both the G-B and B-F stages for the 300 and 200 mm water limits. For maize, lower targeted ET c levels after silking did not significantly affect maize production due to the high season rainfall, but i...
Li, L, Wang, Y-P, Beringer, J, Shi, H, Cleverly, J, Cheng, L, Eamus, D, Huete, A, Hutley, L, Lu, X, Piao, S, Zhang, L, Zhang, Y & Yu, Q 2017, 'Responses of LAI to rainfall explain contrasting sensitivities to carbon uptake between forest and non-forest ecosystems in Australia', Science China Life Sciences, vol. 7, no. 1.View/Download from: Publisher's site
Non-forest ecosystems (predominant in semi-arid and arid regions) contribute significantly to the increasing trend and interannual variation of land carbon uptake over the last three decades, yet the mechanisms are poorly understood. By analysing the flux measurements from 23 ecosystems in Australia, we found the the correlation between gross primary production (GPP) and ecosystem respiration (Re) was significant for non-forest ecosystems, but was not for forests. In non-forest ecosystems, both GPP and Re increased with rainfall, and, consequently net ecosystem production (NEP) increased with rainfall. In forest ecosystems, GPP and Re were insensitive to rainfall. Furthermore sensitivity of GPP to rainfall was dominated by the rainfall-driven variation of LAI rather GPP per unit LAI in non-forest ecosystems, which was not correctly reproduced by current land models, indicating that the mechanisms underlying the response of LAI to rainfall should be targeted for future model development.
Liu, J, Pan, T, Chen, D, Zhou, X, Yu, Q, Flerchinger, GN, Liu, DL, Zou, X, Linderholm, HW, Du, J, Wu, D & Shen, Y 2017, 'An Improved Angstrom-Type Model for Estimating Solar Radiation over the Tibetan Plateau', ENERGIES, vol. 10, no. 7.View/Download from: Publisher's site
Shi, H, Li, L, Eamus, D, Huete, A, Cleverly, J, Tian, X, Yu, Q, Wang, S, Montagnani, L, Magliulo, V, Rotenberg, E, Pavelka, M & Carrara, A 2017, 'Assessing the ability of MODIS EVI to estimate terrestrial ecosystem gross primary production of multiple land cover types', Ecological Indicators, vol. 72, pp. 153-164.View/Download from: Publisher's site
tTerrestrial ecosystem gross primary production (GPP) is the largest component in the global carbon cycle.The enhanced vegetation index (EVI) has been proven to be strongly correlated with annual GPP withinseveral biomes. However, the annual GPP-EVI relationship and associated environmental regulationshave not yet been comprehensively investigated across biomes at the global scale. Here we exploredrelationships between annual integrated EVI (iEVI) and annual GPP observed at 155 flux sites, whereGPP was predicted with a log-log model: ln(GPP) = a × ln(iEVI) + b. iEVI was computed from MODISmonthly EVI products following removal of values affected by snow or cold temperature and withoutcalculating growing season duration. Through categorisation of flux sites into 12 land cover types, theability of iEVI to estimate GPP was considerably improved (R2from 0.62 to 0.74, RMSE from 454.7 to368.2 g C m−2yr−1). The biome-specific GPP-iEVI formulae generally showed a consistent performancein comparison to a global benchmarking dataset (R2= 0.79, RMSE = 387.8 g C m−2yr−1). Specifically, iEVIperformed better in cropland regions with high productivity but poorer in forests. The ability of iEVI inestimating GPP was better in deciduous biomes (except deciduous broadleaf forest) than in evergreendue to the large seasonal signal in iEVI in deciduous biomes. Likewise, GPP estimated from iEVI was ina closer agreement to global benchmarks at mid and high-latitudes, where deciduous biomes are morecommon and cloud cover has a smaller effect on remote sensing retrievals. Across biomes, a significant andnegative correlation (R2= 0.37, p < 0.05) was observed between the strength (R2) of GPP-iEVI relationshipsand mean annual maximum leaf area index (LAImax), and the relationship between the strength andmean annual precipitation followed a similar trend. LAImaxalso revealed a scaling effect on GPP-iEVIrelationships. Our results suggest that iEVI provides a very simple but robust approach to ...
Tong, X, Li, J, Nolan, RH & Yu, Q 2017, 'Biophysical controls of soil respiration in a wheat-maize rotation system in the North China Plain', AGRICULTURAL AND FOREST METEOROLOGY, vol. 246, pp. 231-240.View/Download from: Publisher's site
Wang, B, Liu, DL, Asseng, S, Macadam, I & Yu, Q 2017, 'Modelling wheat yield change under CO2increase, heat and water stress in relation to plant available water capacity in eastern Australia', European Journal of Agronomy, vol. 90, pp. 152-161.View/Download from: Publisher's site
© 2017 Elsevier B.V. Increasing heat and water stress are important threats to wheat growth in rain-fed conditions. Using climate scenario-based projections from the Coupled Model Intercomparison Project phase 5 (CMIP5), we analysed changes in the probability of heat stress around wheat flowering and relative yield loss due to water stress at six locations in eastern Australia. As a consequence of warmer average temperatures, wheat flowering occurred earlier, but the probability of heat stress around flowering still increased by about 3.8%–6.2%. Simulated potential yield across six sites increased on average by about 2.5% regardless of the emission scenario. However, simulated water-limited yield tended to decline at wet and cool locations under future climate while increased at warm and dry locations. Soils with higher plant available water capacity (PAWC) showed a lower response of water-limited yield to rainfall changes except at very dry sites, which means soils with high PAWC were less affected by rainfall changes compared with soils with low PAWC. Our results also indicated that a drought stress index decreased with increasing PAWC and then stagnated at high PAWC. Under high emission scenario RCP8.5, drought stress was expected to decline or stay about the same due to elevated CO 2 compensation effect. Therefore, to maintain or increase yield potential in response to the projected climate change, increasing cultivar tolerance to heat stress and improving crop management to reduce impacts of water stress on lower plant available water holding soils should be a priority for the genetic improvement of wheat in eastern Australia.
Wang, B, Liu, DL, Asseng, S, Macadam, I, Yang, X & Yu, Q 2017, 'Spatiotemporal changes in wheat phenology, yield and water use efficiency under the CMIP5 multimodel ensemble projections in eastern Australia', Climate Research, vol. 72, no. 2, pp. 83-99.View/Download from: Publisher's site
© Inter-Research 2017. The New South Wales (NSW) wheat belt is one of the most important regions for winter crops in Australia; however, its agricultural system is significantly affected by water stress and ongoing climate change. Statistically downscaled scenarios from 13 selected global climate models with RCP4.5 and RCP8.5 scenarios were combined with crop simulation models to simulate wheat productivity and water use. We projected that multi-model median yields could increase by 0.2% for RCP4.5 and 9.0% for RCP8.5 by 2061-2100. Although RCP4.5 showed a small decrease in median yield in the dry southwestern parts of the wheat belt, the higher CO 2 concentration in RCP8.5 compensated some of the negative effects, resulting in 12.6% yield increase. Our results show that drier areas would benefit more from elevated CO 2 than would the wetter areas. Without the increase in CO 2 concentration, wheat yields decrease rapidly under RCP4.5 by 2061-2100 and much more so under RCP8.5 compared to the present. A decline in growing season length and a decrease in rainfall resulted in reduced crop water consumption. As a consequence, simulated evapotranspiration decreased by 10.2% for RCP4.5 and 16.9% for RCP8.5 across the NSW wheat belt. Increasing yields combined with decreasing evapotranspiration resulted in a simulated increase in water use efficiency by 9.9% for RCP4.5 and 29.7% for RCP8.5. Wheat production in water-limited, low-yielding environments appears to be less negatively impacted or in some cases even positively affected under future climate and CO 2 changes, compared to other growing environments in the world.
Whitley, R, Beringer, J, Hutley, LB, Abramowitz, G, De Kauwe, MG, Evans, B, Haverd, V, Li, L, Moore, C, Ryu, Y, Scheiter, S, Schymanski, SJ, Smith, B, Wang, Y-P, Williams, M & Yu, Q 2017, 'Challenges and opportunities in land surface modelling of savanna ecosystems', BIOGEOSCIENCES, vol. 14, no. 20, pp. 4711-4732.View/Download from: Publisher's site
Xie, XJ, Zhang, YH, Wang, L, Yang, XH, Yu, Q & Bao, YX 2017, 'Effect of asymmetric warming on rice (Oryza sativa) growth characteristics and yield components under a free air temperature increase apparatus', Indian Journal of Agricultural Sciences, vol. 87, no. 10.
Climate warming shows great diurnal variations with higher warming rate at nighttime, and consequently causes significant impacts on rice growth and grain yield. The objective of this study was to determine the effects of asymmetric warming (all-day warming, AW; daytime warming from 7:00 to 19:00, DW; and nighttime warming from 19:00 to 7:00, NW; and a control, CK) on rice growth characteristics andyield. Two bucket warming experiments were performed in Nanjing in Jiangsu Province, China under Free Air Temperature Increases (FATI) in 2013 and 2014.< The daily mean temperatures in the rice canopy in the AW, DW and NW plots were 2.0°C, 1.1°C and 1.3°C higher, respectively, than those in the CK plots. Asymmetric warming reduced the maximum tillers and effective tillers in the order CK>DW>NW>AW. In the AW, DW and NW treatments, the effective tillers were decreased by18.57%-37.77% in both years. Asymmetric warming also decreased plant height, the Absolute Growth Rate (AGR), the Soil and Plant Analyzer Development (SPAD) value, the Leaf Area Index (LAI) and the Net Photosynthetic Rate (Pn). The order of the plant height and Pn values were also in the order CK>DW>NW>AW. The warming treatments affect the length of rice growth. The length from the transplanting date to the heading date was shortened by 3.5 days, 2.5 days and 3.0 days on average in the AW, DW and NW plots, respectively, in both years, while the length from the heading date to the maturation date did not show obvious changes. The aboveground biomass in the maturation stage declined by 13.38%, 3.56% and 6.22%, and the grain yield was decreased by 10.07%, 5.06% and 7.89% on average in the AW, DW and NW plots, respectively, in both years. There was a decreasing trend in the panicle number, grain number per panicle and grain filling rate, whereas irregular changes in the 1000-grain weight were observed in the warmed plots. Our results suggested that under the predicted climate warming, rice productivity would b...
Xing, H, Liu, DL, Li, G, Wang, B, Anwar, MR, Crean, J, Lines-Kelly, R & Yu, Q 2017, 'Incorporating grain legumes in cereal-based cropping systems to improve profitability in southern New South Wales, Australia', Agricultural Systems, vol. 154, pp. 112-123.View/Download from: Publisher's site
© 2017 Elsevier Ltd Grain legumes, such as lupins and field peas, are one of key rotation components in Australian agricultural systems, supplying nitrogen (N) to following crops, and potentially increasing farm profitability. In this study, we used a modelling approach to investigate the profitability of incorporating field pea (Pisum sativum) and narrowleaf lupin (Lupinus angustifolius) in cereal-based (wheat/canola) cropping systems in southern New South Wales (NSW), Australia. We calibrated and validated the Agricultural Production Systems sIMulator (APSIM) with three-year's experimental data to predict yields of field pea and lupin, and N contribution of grain legumes in cereal-based (wheat/canola) crop rotations. We conducted a gross margin analysis to analyse the profitability of adding grain legumes into cereal-based crop rotations at both crop and rotation levels. The simulated results showed that field pea and lupin could contribute 30–65 kg N ha − 1 to the next crop and 60–110 kg N ha − 1 to subsequent crops (wheat/canola) for two years, corresponding to 30–55% and 60–86% of net N inputs of legume-fixed N, respectively. This greatly increased the yields and profitability of wheat/canola in the following two years. Including grain legumes in cereal-based crop rotations was more profitable than non-legume crop rotations, even though the grain legumes were less profitable than wheat/canola in the year of growing. However, N and economic ben efits would be reduced to zero if N fertilizer applied to wheat/canola was over the optimal level, i.e. 100–125 kg N ha − 1 in terms of N benefit, or 75 kg N ha − 1 for farm-economic profit. In general, incorporation of grain legumes into cereal-based crop rotations offers an obvious N benefit to subsequent crops and provides an economic benefit for farmers (reduced N applications). This suggests that the contribution of grain legumes to cereal-based cropping systems should be assessed as part of a rotation rather than...
Zhang, Y, Gao, Y & Yu, Q 2017, 'Diffuse nitrogen loss simulation and impact assessment of stereoscopic agriculture pattern by integrated water system model and consideration of multiple existence forms', JOURNAL OF HYDROLOGY, vol. 552, pp. 660-673.View/Download from: Publisher's site
Zhao, CS, Zhang, CB, Yang, ST, Liu, CM, Xiang, H, Sun, Y, Yang, ZY, Zhang, Y, Yu, XY, Shao, NF & Yu, Q 2017, 'Calculating e-flow using UAV and ground monitoring', Journal of Hydrology, vol. 552, pp. 351-365.View/Download from: Publisher's site
Cleverly, J, Eamus, D, Luo, Q, Coupe, NR, Kljun, N, Ma, X, Ewenz, C, Li, L, Yu, Q & Huete, A 2016, 'The importance of interacting climate modes on Australia's contribution to global carbon cycle extremes', SCIENTIFIC REPORTS, vol. 6.View/Download from: Publisher's site
Cleverly, J, Eamus, D, Restrepo Coupe, N, Chen, C, Maes, W, Li, L, Faux, R, Santini, NS, Rumman, R, Yu, Q & Huete, A 2016, 'Soil moisture controls on phenology and productivity in a semi-arid critical zone', Science of the Total Environment.View/Download from: Publisher's site
© 2016 Elsevier B.V. The Earth's Critical Zone, where physical, chemical and biological systems interact, extends from the top of the canopy to the underlying bedrock. In this study, we investigated soil moisture controls on phenology and productivity of an Acacia woodland in semi-arid central Australia. Situated on an extensive sand plain with negligible runoff and drainage, the carry-over of soil moisture content (θ) in the rhizosphere enabled the delay of phenology and productivity across seasons, until conditions were favourable for transpiration of that water to prevent overheating in the canopy. Storage of soil moisture near the surface (in the top few metres) was promoted by a siliceous hardpan. Pulsed recharge of θ above the hardpan was rapid and depended upon precipitation amount: 150mm storm-1 resulted in saturation of θ above the hardpan (i.e., formation of a temporary, discontinuous perched aquifer above the hardpan in unconsolidated soil) and immediate carbon uptake by the vegetation. During dry and inter-storm periods, we inferred the presence of hydraulic lift from soil storage above the hardpan to the surface due to (i) regular daily drawdown of θ in the reservoir that accumulates above the hardpan in the absence of drainage and evapotranspiration; (ii) the dimorphic root distribution wherein most roots were found in dry soil near the surface, but with significant root just above the hardpan; and (iii) synchronisation of phenology amongst trees and grasses in the dry season. We propose that hydraulic redistribution provides a small amount of moisture that maintains functioning of the shallow roots during long periods when the surface soil layer was dry, thereby enabling Mulga to maintain physiological activity without diminishing phenological and physiological responses to precipitation when conditions were favourable to promote canopy cooling.
Cleverly, J, Eamus, D, Van Gorsel, E, Chen, C, Rumman, R, Luo, Q, Coupe, NR, Li, L, Kljun, N, Faux, R, Yu, Q & Huete, A 2016, 'Productivity and evapotranspiration of two contrasting semiarid ecosystems following the 2011 global carbon land sink anomaly', AGRICULTURAL AND FOREST METEOROLOGY, vol. 220, pp. 151-159.View/Download from: Publisher's site
Eamus, D, Chen, C, Cleverly, J, Zhang, L & Yu, Q 2016, 'Modelling Seasonal and Inter-annual Variations in Carbon and Water Fluxes in an arid zone Acacia savanna woodland 1981 - 2012', Ecosystems, vol. 19, no. 2, pp. 625-644.View/Download from: Publisher's site
Changes in climatic characteristics such as seasonal and inter-annual variability may affect ecosystem structure and function, hence alter carbon and water budgets of ecosystems. Studies of modelling combined with field experiments can provide essential information to investigate
interactions between carbon and water cycles and climate. Here we present a first attempt to investigate the long-term climate controls on seasonal patterns and inter-annual variations in water and carbon exchanges in an arid-zone savanna-woodland ecosystem using a detailed mechanistic soil-plant-atmosphere model (SPA), driven by leaf area index (LAI) simulated by an ecohydrological model (WAVES) and observed climate data during 1981−2012. The SPA was tested against almost three years of eddy covariance flux measurements in terms of gross primary productivity (GPP) and evapotranspiration (ET). The model was able to explain 80% and 71% of the variability of observed daily GPP and ET, respectively. Long-term simulations showed that
carbon accumulation rates and ET ranged from 20.6 g C m-2 mon-1 in the late dry season to 45.8 g C m-2 mon-1 in the late wet season, respectively, primarily driven by seasonal variations in LAI and
soil moisture. Large climate variations resulted in large seasonal variation in ecosystem water-use efficiency (eWUE). Simulated annual GPP varied between 146.4 and 604.7 g C m-2 yr-1. Variations in annual ET coincided with that of GPP, ranging from 110.2 to 625.8 mm yr-1. Annual variations in GPP and ET were driven by the annual variations in precipitation and vapour pressure deficit (VPD) but not temperature. The linear coupling of simulated annual GPP and ET resulted in eWUE having relatively small year-to-year variation.
Gu, C, Mu, X, Zhao, G, Gao, P, Sun, W & Yu, Q 2016, 'Changes in Stream Flow and Their Relationships with Climatic Variations and Anthropogenic Activities in the Poyang Lake Basin, China', WATER, vol. 8, no. 12.View/Download from: Publisher's site
He, L, Hou, Y, Zhao, G, Wu, D & Yu, Q 2016, 'Parameters optimization of WOFOST model by integration of global sensitivity analysis and Bayesian calibration method', Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, vol. 32, no. 2, pp. 169-179.View/Download from: Publisher's site
© 2016, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved. Crop model calibration and validation are essential for model evaluation and application. It is important for model application to accurately estimate the values of crop model parameters and further improve the capacity of model prediction. In the previous researches, trial-and-error method was widely used in model calibration and validation. The deficiency of this method was subjective selection of parameter values and time-consuming processes. To overcome these issues, the optimization methods such as general likelihood uncertainty estimation (GLUE), genetic algorithm (GA) and shuffled complex evolution (SCE-UA) algorithm were alternative method for model calibration and validation. However, it is a problem to decide which parameters for optimization. It is essential to select the most sensitive parameters among hundreds of parameters in the crop model for optimization. To avoid subjective selection of parameters for calibration and validation, we used the global sensitivity analysis method of model parameters and the Markov Chain Monte Carlo (MCMC) method based on Bayesian theory to optimize the crop genetic parameters in the WOFOST (world food studies), and the data of three-year winter wheat field experiment in Luancheng in the North China Plain were adopted. The main objectives were: 1) to analyze the sensitivity and uncertainty of WOFOST brought by 55 crop genetic parameters using the extended Fourier amplitude sensitivity test; 2) to calibrate and validate the WOFOST using the MCMC method after sensitivity analysis. We found that: 1) The most sensitive parameters for maximum leaf area index (MAXLAI) in the crop growth period were successively: specific leaf area at development stage of 0, 0.5, 0.6, and 0.75, maximum CO2 assimilation rate at development stage of 1.5, and maximum relative increase in LAI (RGTLAI); 2) The most sensitive pa...
Huang, MX, Wang, J, Tang, JZ, Yu, Q, Zhang, J, Xue, QY, Chang, Q & Tan, MX 2016, 'Suitability of four stomatal conductance models in agro-pastoral ecotone in North China: A case study for potato and oil sunflower', Chinese Journal of Applied Ecology, vol. 27, no. 11, pp. 3585-3592.View/Download from: Publisher's site
© 2016, Science Press. All right reserved.The suitability of four popular empirical and semi-empirical stomatal conductance models (Jarvis model, Ball-Berry model, Leuning model and Medlyn model) was evaluated based on parallel observation data of leaf stomatal conductance, leaf net photosynthetic rate and meteorological factors during the vigorous growing period of potato and oil sunflower at Wuchuan experimental station in agro-pastoral ecotone in North China. It was found that there was a significant linear relationship between leaf stomatal conductance and leaf net photosynthetic rate for potato, whereas the linear relationship appeared weaker for oil sunflower. The results of model evaluation showed that Ball-Berry model performed best in simulating leaf stomatal conductance of potato, followed by Leuning model and Medlyn model, while Jarvis model was the last in the performance rating. The root-mean-square error (RMSE) was 0.0331, 0.0371, 0.0456 and 0.0794 mol·m-2·s-1, the normalized root-mean-square error (NRMSE) was 26.8%, 30.0%, 36.9% and 64.3%, and R-squared (R2 ) was 0.96, 0.61, 0.91 and 0.88 between simulated and observed leaf stomatal conductance of potato for Ball-Berry model, Leuning model, Medlyn model and Jarvis model, respectively. For leaf stomatal conductance of oil sunflower, Jarvis model performed slightly better than Leuning model, Ball-Berry model and Medlyn model. RMSE was 0.2221, 0.2534, 0.2547 and 0.2758 mol·m-2 ·s-1, NRMSE was 40.3%, 46.0%, 46.2% and 50.1%, and R2 was 0.38, 0.22, 0.23 and 0.20 between simulated and observed leaf stomatal conductance of oil sunflower for Jarvis model, Leuning model, Ball-Berry model and Medlyn model, respectively. The path analysis was conducted to identify effects of specific meteorological factors on leaf stomatal conductance. The diurnal variation of leaf stomatal conductance was principally affected by vapour pressure saturation deficit for both potato and oil sunflower. The model evaluation suggest...
Jin, N, Tao, B, Ren, W, Feng, M, Sun, R, He, L, Zhuang, W & Yu, Q 2016, 'Mapping Irrigated and Rainfed Wheat Areas Using Multi-Temporal Satellite Data', REMOTE SENSING, vol. 8, no. 3.View/Download from: Publisher's site
Li, X, Philp, J, Cremades, R, Roberts, A, He, L, Li, L & Yu, Q 2016, 'Agricultural vulnerability over the Chinese Loess Plateau in response to climate change: Exposure, sensitivity, and adaptive capacity.', Ambio, vol. 45, no. 3, pp. 350-360.View/Download from: Publisher's site
Understanding how the vulnerability of agricultural production to climate change can differ spatially has practical significance to sustainable management of agricultural systems worldwide. Accordingly, this study developed a conceptual framework to assess the agricultural vulnerability of 243 rural counties on the Chinese Loess Plateau. Indicators representing the climate/agriculture interface were selected to describe exposure and sensitivity, while stocks of certain capitals were used to describe adaptive capacity. A vulnerability index for each county was calculated and the spatial distribution was mapped. Results showed that exposure, sensitivity, and adaptive capacity occur independently, with most contributing indicator values concentrated in a narrow range after normalization. Within the 49 most vulnerable counties, which together encompass 81 % of the vulnerability index range, 42 were characterized by high exposure and sensitivity but low adaptive capacity. The most vulnerable area was found to be located in the central northeast-southwest belt of Loess Plateau. Adaptation measures for both ecological restoration and economic development are needed and potential adaptation options need further investigation.
Wang, B, Liu, DL, Macadam, I, Alexander, LV, Abramowitz, G & Yu, Q 2016, 'Multi-model ensemble projections of future extreme temperature change using a statistical downscaling method in south eastern Australia', Climatic Change, vol. 138, pp. 85-98.View/Download from: Publisher's site
© 2016 Springer Science+Business Media DordrechtProjections of changes in temperature extremes are critical to assess the potential impacts of climate change on agricultural and ecological systems. Statistical downscaling can be used to efficiently downscale output from a large number of general circulation models (GCMs) to a fine temporal and spatial scale, providing the opportunity for future projections of extreme temperature events. This paper presents an analysis of extreme temperature data downscaled from 7 GCMs selected from the Coupled Model Intercomparison Project phase 5 (CMIP5) using a skill score based on spatial patterns of climatological means of daily maximum and minimum temperature. Data for scenarios RCP4.5 and RCP8.5 for the New South Wales (NSW) wheat belt, south eastern Australia, have been analysed. The results show that downscaled data from most of the GCMs reproduces the correct sign of recent trends in all the extreme temperature indices (except the index for cold days) for 1961–2000. An independence weighted mean method is used to calculate uncertainty estimates, which shows that multi-model ensemble projections produce a consistent trend compared to the observations in most extreme indices. Great warming occurs in the east and northeast of the NSW wheat belt by 2061–2100 and increases the risk of exposure to hot days around wheat flowering date, which might result in farmers needing to reconsider wheat varieties suited to maintain yield. This analysis provides a first overview of projected changes in climate extremes from an ensemble of 7 CMIP5 GCM models with statistical downscaling data in the NSW wheat belt.
Whitley, R, Beringer, J, Hutley, LB, Abramowitz, G, De Kauwe, MG, Duursma, R, Evans, B, Haverd, V, Li, L, Ryu, Y, Smith, B, Wang, YP, Williams, M & Yu, Q 2016, 'A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas', Biogeosciences, vol. 13, no. 11, pp. 3245-3265.View/Download from: Publisher's site
ï¿½ Author(s) 2016. CC Attribution 3.0 License. The savanna ecosystem is one of the most dominant and complex terrestrial biomes, deriving from a distinct vegetative surface comprised of co-dominant tree and grass populations. While these two vegetation types co-exist functionally, demographically they are not static but are dynamically changing in response to environmental forces such as annual fire events and rainfall variability. Modelling savanna environments with the current generation of terrestrial biosphere models (TBMs) has presented many problems, particularly describing fire frequency and intensity, phenology, leaf biochemistry of C3 and C4 photosynthesis vegetation, and root-water uptake. In order to better understand why TBMs perform so poorly in savannas, we conducted a model inter-comparison of six TBMs and assessed their performance at simulating latent energy (LE) and gross primary productivity (GPP) for five savanna sites along a rainfall gradient in northern Australia. Performance in predicting LE and GPP was measured using an empirical benchmarking system, which ranks models by their ability to utilise meteorological driving information to predict the fluxes. On average, the TBMs performed as well as a multi-linear regression of the fluxes against solar radiation, temperature and vapour pressure deficit but were outperformed by a more complicated nonlinear response model that also included the leaf area index (LAI). This identified that the TBMs are not fully utilising their input information effectively in determining savanna LE and GPP and highlights that savanna dynamics cannot be calibrated into models and that there are problems in underlying model processes. We identified key weaknesses in a model's ability to simulate savanna fluxes and their seasonal variation, related to the representation of vegetation by the models and root-water uptake. We underline these weaknesses in terms of three critical areas for development. First, prescribe...
Xu, B, Li, J, Liu, Q, Huete, AR, Yu, Q, Zeng, Y, Yin, G, Zhao, J & Yang, L 2016, 'Evaluating Spatial Representativeness of Station Observations for Remotely Sensed Leaf Area Index Products', IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 7, pp. 3267-3282.View/Download from: Publisher's site
Continuous leaf area index (LAI) observations from global ground stations are an important reference dataset for the validation of remotely sensed LAI products. In this study, a pragmatic approach is presented for evaluating the spatial representativeness of station-observed LAI dataset in the product pixel grid. Three evaluation indicators, including dominant vegetation type percent (DVTP), relative absolute error (RAE) and coefficient of sill (CS), were established to quantify different levels of spatial representativeness. The DVTP was used to evaluate whether the station-observed vegetation type was the dominant one in the pixel grid, and the RAE and CS were applied to quantify the point-to-area consistency for a given station observation and the spatial heterogeneity caused by the different density of vegetation within the pixel, respectively. The proposed approach was applied to 25 stations from the Chinese Ecosystem Research Network, and results show significant differences of representativeness errors at different levels. The spatial representativeness for different stations varied seasonally with different vegetation growth stages due to temporal changes in heterogeneity, but the spatial representativeness remained consistent at interannual timeframes due to the relatively stable vegetation structure and pattern between adjacent years. A large error can occur in MOD15A2 product validation when the representativeness level of station LAI observations is low. This approach can effectively distinguish various levels of spatial representativeness for the station-observed LAI dataset at the pixel grid scale, which can consequently improve the reliability of LAI product validation by selecting LAI observations with a high degree of representativeness.
Zhuang, W, Cheng, L, Whitley, R, Shi, H, Beringer, J, Wang, Y, He, L, Cleverly, J, Eamus, D & Yu, Q 2016, 'How energy and water availability constrain vegetation water-use along the North Australian Tropical Transect', International Journal of Plant Production, vol. 10, no. 3, pp. 403-424.
Guo, LP, Kang, HJ, Ouyang, Z, Zhuang, W & Yu, Q 2015, 'Photosynthetic parameter estimations by considering interactive effects of light, temperature and CO2 concentration', INTERNATIONAL JOURNAL OF PLANT PRODUCTION, vol. 9, no. 3, pp. 321-345.
He, L, Asseng, S, Zhao, G, Wu, D, Yang, X, Zhuang, W, Jin, N & Yu, Q 2015, 'Impacts of recent climate warming, cultivar changes, and crop management on winter wheat phenology across the Loess Plateau of China', AGRICULTURAL AND FOREST METEOROLOGY, vol. 200, pp. 135-143.View/Download from: Publisher's site
He, L, Zhao, G, Jin, N, Zhuang, W & Yu, Q 2015, 'Global sensitivity analysis of APSIM-Wheat parameters in different climate zones and yield levels', Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, vol. 31, no. 14, pp. 148-157.View/Download from: Publisher's site
©, 2015, Chinese Society of Agricultural Engineering. All right reserved. Uncertainties of crop model are mainly from model structure, parameters' sensitivity and input error. It is essential to quantify the parameters' sensitivity and the results' uncertainties of crop model for model calibration and application. Furthermore, uncertainty and sensitivity analysis can improve the reliability of model prediction. There are 2 categories of parameter sensitivity analysis methods, i.e. the local sensitivity and the global sensitivity. Local sensitivity analysis is called derivative-based or one-at-a-time method, which changes only one parameter at a time around a basis point while keeping other parameters constant. It cannot detect the interactions among the parameters and suffers some shortcomings such as a heavy dependence on the input parameters and instability for non-linear models. Global sensitivity analysis is a better method for exploring the entire multi-dimensional parameters simultaneously. It can quantify the influence of single parameter and the interactions among different parameters. Several global sensitivity methods including Morris, variance-based, linear regression, FAST (Fourier amplitude sensitivity test) and EFAST (extended Fourier amplitude sensitivity test) are widely used in the parameter analysis. EFAST is robust and has lower computational cost than the others. Previous studies of sensitivity analysis focused on a single site. However, the performance of crop model is variable in different climatic zones due to the heterogeneity of climate and soil characteristics. In this study, we collected crop experimental data in the locations of Luancheng, Hebei Province Changwu in the Chinese Loess Plateau, Yanting in the Sichuan Basin and Wulanwusu in Xinjiang Autonomous Region. And then using the global sensitivity analysis method i.e. EFAST, we analyzed the sensitivity and uncertainty of crop model (APSIM-Wheat) brought by the cultivar, soil and bi...
Jiang, B, Yang, SY, Yang, XB, Ma, YH, Chen, XL, Zuo, HF, Fan, DF, Gao, L, Yu, Q & Yang, W 2015, 'Effect of controlled drainage in the wheat season on soil CH4 and N2O emissions during the rice season', International Journal of Plant Production, vol. 9, no. 2, pp. 273-290.
The effect of draining crop fields during the wheat season on the soil CH4 and N2O emissions during the rice season in this article. There were four treatments: traditional cultivation during the wheat season+cultivation without fertilization during the rice season (CK1 field), traditional cultivation during the wheat season + traditional cultivation during the rice season (CK2 field), draining the fields through shallow furrows + traditional cultivation during the rice season (CQ field) and draining the fields through deep furrows + traditional cultivation during the rice season (CS field). The results are listed as follows. (1) Draining the field through furrows during the wheat season significantly reduced the CH4 and N2O emissions during the rice season. Compared with the CK1 field, the total CH4 emissions from the CQ and CS fields decreased by 43.1% and 39.9%, respectively; compared with the CK2 field, the total CH4 emissions from the CQ and CS fields decreased by 58.1% and 55.7%, respectively; compared.
Jiang, C, Wu, ZF, Cheng, J, Yu, Q & Rao, XQ 2015, 'Impacts of urbanization on net primary productivity in the pearl river delta, China', International Journal of Plant Production, vol. 9, no. 4, pp. 581-598.
© 2015, Gorgan Univ Agricultural Sciences and Natural Resources. All rights reserved. Great changes in land use/land cover from rapid urbanization have occurred in the Pearl River Delta, China. As the primary cause of land development in the urbanization process, urban expansion has mostly occurred on land with higher NPP, significantly impacting the regional ecosystems. The primary purpose of this study was to reveal the impacts of urban expansion on the regional NPP. The land cover datasets and three types of urban lands (urban, peri-urban and non-urban areas) were obtained to quantify the urban expansion of the Pearl River Delta from 2000 to 2010. The Carnegie-Ames-Stanford-Approach (CASA) model was driven by the land cover types, NDVI data and climate data to calculate the NPP for the study area and analyze its spatial-temporal variations, as well as the impacts on NPP from urban expansion. The results showed: cropland and forest with higher NPP values and wetland were the major source of urban expansion, which generally reduced the regional NPP values, primarily by replacing vegetation with urban land. The conversion of land to urban use resulted in a reduction of 0.103TgC from 2000 to 2005 and 0.034TgC from 2005 to 2010, cropland and forest accounted for the largest proportion of the total NPP losses. In spatial distribution, the NPP losses occurring in urban and peri-urban areas accounted for 89.63% and 75.04%, respectively, which was primarily a result of the massive vegetation with high productivity being replaced with impervious surfaces during the rapid urbanization process. These results provided an indicator to understand and evaluate ecosystem changes in urban regions.
Liu, J, Linderholm, H, Chen, D, Zhou, X, Flerchinger, GN, Yu, Q, Du, J, Wu, D, Shen, Y & Yang, Z 2015, 'Changes in the relationship between solar radiation and sunshine duration in large cities of China', Energy, vol. 82, pp. 589-600.View/Download from: Publisher's site
Based on the linear relationship between solar radiation and sunshine duration, the Angstrom model is widely used to estimate solar radiation from routinely observed meteorological variables for energy exploitation. However, the relationship may have changed in quickly developing regions in the recent decades under global "dimming" and "brightening" context, with increasing aerosols due to industrial pollutions. Solar radiation stations under different climate conditions in six large cities in China are selected to test this hypothesis. Analysis of the related meteorological items shows that Guiyang has the lowest solar radiation with the average annual value of 10.5MJm-2d-1, while Lhasa on the Tibetan Plateau has the highest of 20.1MJm-2d-1. Both radiation and sunshine hours decreased from 1961 to 2010, but at different rates. A moving linear regression method is used to investigate the changes in the relationship between radiation and sunshine duration, the results indicate an abrupt change in the correlation coefficients in 1980-1990s, which can be attributed to the aerosol load resulting from air pollution caused by the industrial development in 1980s under China's Open Door Policy. The sky condition has been changing from clean to dirty, thus the relationship between solar radiation and duration changes in the 1980's and has recovered in the recent decades. This finding implies that it might not necessarily be right to use long data sets for model calibration. Further investigation confirms that the Angstrom model performs the best with higher NSE (nash-sutcliffe efficiency) of 0.914 and lower MAPE (mean absolute percentage error) and RMSE (root mean square error) values of 13.7w/m2 and 23.9w/m2 respectively, when calibrated with a 10-year data set. In contrast, the model performs worst when it is calibrated with a 40-year data set, with NSE, MAPE and RMSE values of 0.891, 15.1w/m2 and 25.3w/m2, respectively. Based on the findings of this research, a 10-year...
Wang, B, Chen, C, Liu, DL, Asseng, S, Yu, Q & Yang, X 2015, 'Effects of climate trends and variability on wheat yield variability in eastern Australia', CLIMATE RESEARCH, vol. 64, no. 2, pp. 173-186.View/Download from: Publisher's site
Wang, B, Liu, DL, Asseng, S, Macadam, I & Yu, Q 2015, 'Impact of climate change on wheat flowering time in eastern Australia', AGRICULTURAL AND FOREST METEOROLOGY, vol. 209, pp. 11-21.View/Download from: Publisher's site
Wang, N, Wang, J, Wang, E, Yu, Q, Shi, Y & He, D 2015, 'Increased uncertainty in simulated maize phenology with more frequent supra-optimal temperature under climate warming', EUROPEAN JOURNAL OF AGRONOMY, vol. 71, pp. 19-33.View/Download from: Publisher's site
Zhao, G, Bryan, BA, King, D, Luo, Z, Wang, E & Yu, Q 2015, 'Sustainable limits to crop residue harvest for bioenergy: maintaining soil carbon in Australia's agricultural lands', GLOBAL CHANGE BIOLOGY BIOENERGY, vol. 7, no. 3, pp. 479-487.View/Download from: Publisher's site
Zhao, CS, Yang, ST, Liu, CM, Dou, TW, Yang, ZL, Yang, ZY, Liu, XL, Xiang, H, Nie, SY, Zhang, JL, Mitrovic, SM, Yu, Q & Lim, RP 2015, 'Linking hydrologic, physical and chemical habitat environments for the potential assessment of fish community rehabilitation in a developing city', JOURNAL OF HYDROLOGY, vol. 523, pp. 384-397.View/Download from: Publisher's site
Zhao, CS, Yang, ST, Xiang, H, Liu, CM, Zhang, HT, Yang, ZL, Zhang, Y, Sun, Y, Mitrovic, SM, Yu, Q & Lim, RP 2015, 'Hydrologic and water-quality rehabilitation of environments for suitable fish habitat', JOURNAL OF HYDROLOGY, vol. 530, pp. 799-814.View/Download from: Publisher's site
Ma, X, Huete, A, Yu, Q, Restrepo-Coupe, N, Beringer, J, Hutley, LB, Kanniah, KD, Cleverly, J & Eamus, D 2014, 'Parameterization of an ecosystem light-use-efficiency model for predicting savanna GPP using MODIS EVI', REMOTE SENSING OF ENVIRONMENT, vol. 154, pp. 253-271.View/Download from: Publisher's site
Bai, J, Chen, X, Li, L, Luo, G & Yu, Q 2014, 'Quantifying the contributions of agricultural oasis expansion, management practices and climate change to net primary production and evapotranspiration in croplands in arid northwest China', Journal Of Arid Environments, vol. 100-101, pp. 31-41.View/Download from: Publisher's site
Chen, C, Eamus, D, Cleverly, J, Boulain, N, Cook, P, Zhang, L, Cheng, L & Yu, Q 2014, 'Modelling vegetation water-use and groundwater recharge as affected by climate variability in an arid-zone Acacia savanna woodland', JOURNAL OF HYDROLOGY, vol. 519, pp. 1084-1096.View/Download from: Publisher's site
Chen, X, Su, Z, Ma, Y, Liu, S, Yu, Q & Xu, Z 2014, 'Development of a 10-year (2001-2010) 0.1 degrees data set of land-surface energy balance for mainland China', ATMOSPHERIC CHEMISTRY AND PHYSICS, vol. 14, no. 23, pp. 13097-13117.View/Download from: Publisher's site
Cheng, L, Zhang, L, Wang, YP, Yu, Q & Eamus, D 2014, 'Quantifying the effects of elevated CO2 on water budgets by combining FACE data with an ecohydrological model', Ecohydrology, vol. 7, no. 6, pp. 1574-1588.View/Download from: Publisher's site
© 2014 John Wiley & Sons, Ltd. Response of leaf area index (LAI) is the key determinant for predicting impacts of the elevated CO 2 (eCO 2 ) on water budgets. Importance of the changes in functional attributes of vegetation associated with eCO 2 for predicting responses of LAI has rarely been addressed. In this study, the WAter Vegetation Energy and Solute (WAVES) model was applied to simulate ecohydrological effects of the eCO 2 at two free-air CO 2 enrichment (FACE) experimental sites with contrasting vegetation. One was carried out by the Oak Ridge National Laboratory on the forest (ORNL FACE). The other one was conducted by the University of Minnesota on the grass (BioCON FACE). Results demonstrated that changes in functional attributes of vegetation (including reduction in specific leaf area, changes in carbon assimilation and allocation characteristics) and availability of nutrients are important for reproducing the responses of LAI, transpiration and soil moisture at both sites. Predicted LAI increased slightly at both sites because of fertilization effects of the eCO 2 . Simulated transpiration decreased 10·5% at ORNL site and 13·8% at BioCON site because of reduction in the stomatal conductance. Predicted evaporation from interception and soil surface increased slightly ( < 1·0mmyear -1 ) at both sites because of increased LAI and litter production, and increased soil moisture resulted from reduced transpiration. All components of run-off were predicted to increase because of significant decrease in transpiration. Simulated mean annual evapotranspiration decreased about 8·7% and 10·8%, and mean annual run-off increased about 11·1% (59·3mmyear -1 ) and 9·5% (37·6mmyear -1 ) at the ORNL and BioCON FACE sites, respectively.
Cheng, L, Zhang, L, Wang, Y-P, Yu, Q, Eamus, D & O'Grady, A 2014, 'Impacts of elevated CO2, climate change and their interactions on water budgets in four different catchments in Australia', JOURNAL OF HYDROLOGY, vol. 519, pp. 1350-1361.View/Download from: Publisher's site
Fang, Q, Ma, L, Flerchinger, GN, Qin, Z, Ahuja, LR, Xing, H, Li, J & Yu, Q 2014, 'Modeling evapotranspiration and energy balance in a wheat-maize cropping system using the revised RZ-SHAW model', Agricultural and Forest Meteorology, vol. 194, pp. 218-229.View/Download from: Publisher's site
Correctly simulating evapotranspiration (ET) and surface energy balance is essential to simulating crop growth under water and heat stress conditions in agricultural systems. The revised hybrid model (RZ-SHAW), combining the Root Zone Water Quality Model (RZWQM) and Simultaneous Heat and Water (SHAW) model, was evaluated for simulating ET and surface energy balance components against observed data from an eddy covariance system in a wheatmaize double cropping system in the North China Plain (NCP), after it was calibrated for soil water content and crop growth. The average daily ET was slightly under-simulated by 0.05 mm in the wheat seasons and over-simulated by 0.23 mm in the maize seasons, compared with the observed latent heat flux (LE) from 2003 to 2005. The root mean squared error (RMSE) and model efficiency (ME) of simulated daily ET were 0.59 mm and 0.86 for the three years. The goodness of simulation for Rn (net radiation), LE, H (sensible heat flux) and canopy temperature was better in the middle crop seasons than in the early crop seasons. The RMSE values for simulated Rn, H, LE, G (ground heat flux), and canopy temperature were 31.9, 37.2, 37.9, 21.8 W m-2, and 1.37?C, respectively, for middle wheat seasons and were 29.2, 27.1, 29.7, 19.7 W m-2, and 1.22?C, respectively, for middle maize seasons. These simulation results were comparable with previous modeling studies, indicating that the revised hybrid model is reasonable for simulating ET, surface energy balance as well as crop growth in the double cropping system.
He, L, Cleverly, J, Chen, C, Yang, X, Li, J, Liu, W & Yu, Q 2014, 'Diverse responses of winter wheat yield and water use to climate change and variability on the semiarid Loess Plateau in China', Agronomy Journal, vol. 106, pp. 1169-1178.View/Download from: Publisher's site
Crop production and water use in rainfed cropland are vulnerable to climate change. This study was to quantify diverse responses of winter wheat (Triticum aestivum L.) yield and water use to climate change on the Loess Plateau (LP) under different combinations of climatic variables. The crop model APSIM was validated against field experimental data and applied to calculate yield and water use at 18 sites on the LP during 1961 to 2010. The coefficient of variation of yield ranged from 12 to 66%, in which the vulnerability of yield increased from the southeast (12%) to the northwest (66%). This change was attributed to the gradual increase in precipitation variation from the southeast to the northwest. An obvious warming trend during 1961 to 2010 resulted in a significant decrease in the growth duration by 1 to 5 d decade1. The yield at 12 sites was significantly reduced by 120 to 720 kg ha1 decade1. Evapotranspiration was significantly decreased by 1 to 26 mm decade1; however, water use efficiency at most sites showed no significant trend. Eighteen sites were classified into three climatic zones by cluster analysis: high temperaturehigh precipitationlow radiation (HHL), medium temperaturemedium precipitationmedium radiation (MMM), and low temperaturelow precipitationhigh radiation (LLH). The trend of decreasing yield was smallest in the HHL cluster because of a minimal reduction in precipitation, while decreasing trends in yield and evapotranspiration were larger in the LLH and MMM because of larger reductions in precipitation. The results imply that among strategies such as breeding for long duration or drought tolerance, modification of the planting date will be necessary to avoid high temperatures associated with climate change.
Li, X, Zhao, G, Yu, X & Yu, Q 2014, 'A comparison of forest fire indices for predicting fire risk in contrasting climates in China', Natural Hazards, vol. 70, pp. 1339-1356.View/Download from: Publisher's site
The relationships between fire danger indices and fire risk have been extensively studied in many regions of the world. This work uses partial effect analysis in semiparametric logistic regression models to assess the nonlinear relationships among location, day, altitude, fire danger indices, normalized difference vegetation index (NDVI), and fire ignition from 1996 to 2008 in four different climatic regions in China. The four regions are North China (NR), Northeast China (NE), Southeast China (SE), and Southwest China (SW). The three main results are as follows: First, different fire danger indices are selected as significant variables dependent on the region. The inter-regional difference could be partially explained by difference in local weather and vegetation conditions. Second, spatial location exerts highly significant effects in all four regions. NDVI values are selected as explained variable for NR, NE, and SE on fire ignitions. On a daily scale, altitude influences fire ignition for NR, SE, and SW. Third, the robustness of the probability models used in NE, SE, and SW is better than that in NR on a daily scale. The semiparametric logistic regression model used in this study is useful for assessing the ability of fire danger indices to estimate probabilities of fire ignition on a daily scale. This study encourages further research on assessing the predictive ability of fire danger indices developed at other temporal and spatial scales in China.
Shi, H, Li, L, Eamus, D, Cleverly, J, Huete, A, Beringer, J, Yu, Q, van Gorsel, E & Hutley, L 2014, 'Intrinsic climate dependency of ecosystem light and water-use-efficiencies across Australian biomes', Environmental Research Letters, vol. 9, no. 10, pp. 104002-104002.View/Download from: Publisher's site
The sensitivity of ecosystem gross primary production (GPP) to availability of water and photosynthetically active radiation (PAR) differs among biomes. Here we investigated variations of ecosystem light-use-efficiency (eLUE: GPP/PAR) and water-use-efficiency (eWUE: GPP/evapotranspiration) among seven Australian eddy covariance sites with differing annual precipitation, species composition and temperature. Changes to both eLUE and eWUE were primarily correlated with atmospheric vapor pressure deficit (VPD) at multiple temporal scales across biomes, with minor additional correlations observed with soil moisture and temperature. The effects of leaf area index on eLUE and eWUE were also relatively weak compared to VPD, indicating an intrinsic dependency of eLUE and eWUE on climate. Additionally, eLUE and eWUE were statistically different for biomes between summer and winter, except eWUE for savannas and the grassland. These findings will improve our understanding of how light- and water-use traits in Australian ecosystems may respond to climate change.
Tong, X, Li, J, Yu, Q & Lin, Z 2014, 'Biophysical controls on light response of net co2 exchange in a winter wheat field in the North China Plain', PLoS One, vol. 9, no. 2, pp. 1-13.View/Download from: Publisher's site
To investigate the impacts of biophysical factors on light response of net ecosystem exchange (NEE), CO2 flux was measured using the eddy covariance technique in a winter wheat field in the North China Plain from 2003 to 2006. A rectangular hyperbolic function was used to describe NEE light response. Maximum photosynthetic capacity (Pmax) was 46.664.0 mmol CO2 m22 s21 and initial light use efficiency (a) 0.05960.006 mmol mmol21 in April2May, two or three times as high as those in March. Stepwise multiple linear regressions showed that Pmax increased with the increase in leaf area index (LAI), canopy conductance (gc) and air temperature (Ta) but declined with increasing vapor pressure deficit (VPD) (P,0.001). The factors influencing Pmax were sorted as LAI, gc, Ta and VPD. a was proportional to ln(LAI), gc, Ta and VPD (P,0.001). The effects of LAI, gc and Ta on a were larger than that of VPD. When Ta.25uC or VPD.1.121.3 kPa, NEE residual increased with the increase in Ta and VPD (P,0.001), indicating that temperature and water stress occurred. When gc was more than 14 mm s21 in March and May and 26 mm s21 in April, the NEE residuals decline disappeared, or even turned into an increase in gc (P,0.01), implying shifts from stomatal limitation to non-stomatal limitation on NEE. Although the differences between sunny and cloudy sky conditions were unremarkable for light response parameters, simulated net CO2 uptake under the same radiation intensity averaged 18% higher in cloudy days than in sunny days during the year 200322006. It is necessary to include these effects in relevant carbon cycle models to improve our estimation of carbon balance at regional and global scales.
Tong, X, Li, J, Yu, Q & Lin, Z 2014, 'Erratum: Biophysical controls on light response of net CO2 exchange in a winter wheat field in the North China plain (PLoS ONE (2014) 9, 2 (e89469) DOI: 10.1371/journal.pone.0089469)', PLoS ONE, vol. 9, no. 7.View/Download from: Publisher's site
Yu, Q, Li, L, Luo, Q, Eamus, D, Xu, S, Chen, C, Wang, E, Liu, J & Nielsen, DC 2014, 'Year patterns of climate impacts on wheat yields', International Journal of Climatology, vol. 34, pp. 518-528.View/Download from: Publisher's site
Rainfall, temperature, and solar radiation are important climate factors, which determine crop growth, development and yield from instantaneous to decadal scales. We propose to identify year patterns of climate impact on yield on the basis of rain and non-rain weather. There are inter-related impacts of climatic factors on crop production within a specific pattern. Historical wheat yield data in Queensland during 18892004 were used. The influence of meteorological conditions on wheat yields was derived from statistical yield data which were detrended by 9-year-smoothing averages to remove the effects of technological improvements on wheat yields over time. Climate affects crop growth and development differently over different growth stages. Therefore, we considered the climate effects at both vegetative and reproductive stages (before and after flowering date, respectively) on yield. Cluster analysis was employed to identify the year patterns of climate impact. Five patterns were significantly classified. Precipitation during the vegetative stage was the dominant and beneficial factor for wheat yields while increasing maximum temperature had a negative influence. Crop yields were strongly dependent on solar radiation under normal rainfall conditions.
Zhu, J, Yu, J, Wang, P, Yu, Q & Eamus, D 2014, 'Variability in groundwater depth and composition and their impacts on vegetation succession in the lower Heihe River Basin, north-western China', Marine and Freshwater Research, vol. 65, pp. 206-217.View/Download from: Publisher's site
Plant-community structure and groundwater attributes were investigated in Ejina Delta in north-western China to understand spatial variability of groundwater depth and composition and their impacts on vegetation succession. Geostatistical methods and ordination analysis were performed to analyse the data. In addition, we tried to obtain vegetation successional series by using an approach of spatial sequences instead of temporal sequences. The findings of the present study were as follows: (1) the coefficient of variation for groundwater depth (GWD), salinity (SAL), total dissolved solids (TDS), electrical conductivity (EC), pH, Ca2þ , Mg2þ , K þ , Na þ , SO4 2 , HCO3 , NO3 , Cl and F ranged from 0.04 to 1.53; (2) GWD, Mg2þ , TDS, EC, Ca2þ , HCO3 , NO3 and pH showed strong spatial autocorrelation, whereas K þ and SAL showed moderate spatial autocorrelation; (3) canonical correspondence analysis revealed that groundwater heterogeneity, especially GWD, followed by pH, SAL, TDS, EC and HCO3 , had an important impact on vegetation succession, and thus showed a prevalence of groundwater attributes-based niche differentiation among plant communities; and (4) there were two vegetation successional processes (drought and salinisation) in the lower Heihe River Basin, and salinisation processes increased with drought processes. Our results indicated that high spatial variability of groundwater attributes contributes to promoting maintenance of species and landscape diversity in the lower Heihe River Basin.
Ma, X, Huete, A, Yu, Q, Restrepo Coupe, N, Davies, KP, Broich, M, Ratana, P, Beringer, J, Hutley, LB, Cleverly, J, Boulain, NP & Eamus, D 2013, 'Spatial patterns and temporal dynamics in savanna vegetation phenology across the North Australian Tropical Transect', Remote Sensing of Environment, vol. 139, no. 1, pp. 97-115.View/Download from: Publisher's site
The phenology of a landscape is a key parameter in climate and biogeochemical cycle models and its correct representation is central to the accurate simulation of carbon, water and energy exchange between the land surface and the atmosphere. Whereas biogeographic phenological patterns and shifts have received much attention in temperate ecosystems, much less is known about the phenology of savannas, despite their sensitivity to climate change and their coverage of approximately one eighth of the global land surface. Savannas are complex assemblages of multiple tree, shrub, and grass vegetation strata, each with variable phenological responses to seasonal climate and environmental variables. The objectives of this study were to investigate biogeographical and inter-annual patterns in savanna phenology along a 1100 km ecological rainfall gradient, known as North Australian Tropical Transect (NATT), encompassing humid coastal Eucalyptus forests and woodlands to xeric inland Acacia woodlands and shrublands. Key phenology transition dates (start, peak, end, and length of seasonal greening periods) were extracted from13 years (20002012) of Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) data using Singular Spectrum Analysis (SSA). Two distinct biogeographical patterns in phenology were observed, controlled by different climate systems. The northern (mesic) portion of the transect, from 12°S, to around 17.7°S, was influenced by the Inter-Tropical Convergence Zone (ITCZ) seasonal monsoon climate system, resulting in strong latitudinal shifts in phenology patterns, primarily associated with the functional response of the C4 grass layer.
Cleverly, J, Boulain, NP, Villalobos-Vega, R, Grant, NM, Faux, R, Wood, C, Cook, P, Yu, Q, Leigh, A & Eamus, D 2013, 'Dynamics of component carbon fluxes in a semi-arid Acacia woodland, central Australia', Journal of Geophysical Research: Biogeosciences, vol. 118, no. 3, pp. 1168-1185.View/Download from: Publisher's site
Vast areas in the interior of Australia are exposed to regular but infrequent periods of heavy rainfall, interspersed with long periods at high temperatures, but little is known of the carbon budget of these remote areas or how they respond to extreme precipitation. In this study, we applied three methods to partition net ecosystem photosynthesis into gross primary production (GPP) and ecosystem respiration (Re) during two years of contrasting rainfall. The first year was wet (>250 mm above average rainfall), while little precipitation fell during the second year (>100 mmbelow average). During the first year of study, rates of GPP were large (793 g C m_2 yr_1) in this semi-arid Mulga (Acacia aneura) and grass savanna due to complementary photosynthetic responses by the canopy and C4 understorey to cycles of heavy rainfall. Patterns in GPP during the summer and autumn matched those in leaf area index (LAI), photosynthetic activity, and autotrophic respiration. During the dry year, small but positive photosynthetic uptake by Mulga contributed to the neutral carbon budget (GPP / Re = 1.06 ± 0.03). Small rates of photosynthesis by evergreen Mulga when dry were supported by storage of soil moisture above a relatively shallow hardpan. Little soil organic matter (1.1%) was available to support heterotrophic respiration (Rh) without input of fresh substrate. The two largest sources of Re in this study were autotrophic respiration by the seasonal understorey and Rh through decomposition of fresh organic matter supplied by the senescent understorey.
Cleverly, J, Chen, C, Boulain, NP, Villalobos-Vega, R, Faux, R, Grant, NM, Yu, Q & Eamus, D 2013, 'Aerodynamic resistance and Penman-Monteith evapotranspiration over a seasonally two-layered canopy in semi-arid central Australia', Journal of Hydrometeorology, vol. 14, no. 1, pp. 1562-1570.View/Download from: Publisher's site
Accurate prediction of evapotranspiration E depends upon representative characterization of meteoro- logical conditions in the boundary layer. Drag and bulk transfer coefficient schemes for estimating aero- dynamic resistance to vapor transfer were compared over a semiarid natural woodland ecosystem in central Australia. Aerodynamic resistance was overestimated from the drag coefficient, resulting in limited E at intermediate values of vapor pressure deficit. Large vertical humidity gradients were present during the summer, causing divergence between momentum and vapor transport within and above the canopy surface. Because of intermittency in growth of the summer-active, rain-dependent understory and physiological re- sponses of the canopy, leaf resistance varied from less than 50 sm21 to greater than 106 sm21, in which the particularly large values were obtained from inversion of drag coefficient resistance. Soil moisture limitations further contributed to divergence between actual and reference E. Unsurprisingly, inclusion of site-specific meteorological (e.g., vertical humidity gradients) and hydrological (e.g., soil moisture content) information improved the accuracy of predicting E when applying PenmanMonteith analysis. These results apply re- gardless of canopy layering (i.e., even when the understory was not present) wherever atmospheric humidity gradients develop and are thus not restricted to two-layer canopies in semiarid regions.
Fang, Q, Ma, L, Yu, Q, Hu, C, Li, X, Malone, RJ & Ahuja, LR 2013, 'Quantifying climate and management effects on regional crop yield and nitrogen leaching in the North China Plain', Journal of Environmental Quality, vol. 42, no. 5, pp. 1466-1479.View/Download from: Publisher's site
Better water and nitrogen (N) management requires better understanding of soil water and N balances and their effects on crop yield under various climate and soil conditions. In this study, the calibrated Root Zone Water Quality Model (RZWQM2) was used to assess crop yield and N leaching under current and alternative management practices in a double-cropped wheat (Triticum aestivum L.) and maize (Zea mays L.) system under longterm weather conditions (19702009) for dominant soil types at 15 locations in the North China Plain. The results provided quantitative long-term variation of deep seepage and N leaching at these locations, which strengthened the existing qualitative knowledge for site-specific management of water and N. In general, the current management practices showed high residual soil N and N leaching in the region, with the amounts varying between crops and from location to location and from year to year. Seasonal rainfall explained 39 to 84% of the variability in N leaching (19702009) in maize across locations, while for wheat, its relationship with N leaching was significant (P < 0.01) only at five locations. When N and/or irrigation inputs were reduced to 40 to 80% of their current levels, N leaching generally responded more to N rate than to irrigation, while the reverse was true for crop yield at most locations. Matching N input with crop requirements under limited water conditions helped achieve lower N leaching without considerable soil N accumulation. Based on the long-term simulation results and water resources availability in the region, it is recommended to irrigate at 60 to 80% of the current water levels and fertilize only at 40 to 60% of the current N rate to minimizing N leaching without compromising crop yield.
Li, X, Zhao, G, Yu, X & Yu, Q 2013, 'Probability models of forest fire risk based on ecology factors in different vegetation regions over China', Shengtai Xuebao/ Acta Ecologica Sinica, vol. 33, no. 4, pp. 1219-1229.View/Download from: Publisher's site
Forest fires are considered an important disturbance factor for forest ecosystems. Forest fires are influenced by ecological factors. There are different relationships between diverse ecological factors and forest fires in disparate vegetation regions in China. The objectives of this study were two-fold: i) to assess relationships between ecological factors (NDVI and weather elements) and probability of occurrence of fires (i. e. fire risk), and, ii) to establish fire probability models in four contrasting vegetation regions across China. This study covers the monsoonal region where plenty of rainfall is received but significant seasonal variation within dry and wet seasons are characterised by air mass transitions between inland air and oceanic air. The study area was divided into four sub-regions according to their distinct biomes: i) north China plain with a dominant vegetation of deciduous broad- leaved trees; ii) north-east of China dominated by cool temperate coniferous forest; iii) southeast of China dominated by mixed evergreen broadleaf and deciduous broad-leaved forest, and iv) southwest of China dominated by tropical rain forest. Fire data were extracted from the Along Track Scanning Radiometer of the European Space Agency. Daily values of weather elements from 245 stations covering majority of the four climatic regions above were obtained from China Meteorological Administration. Normalized Difference Vegetation Index (NDVI) was applied as a measure of vegetation status. We linked vegetation with location, time, altitude, weather elements, and fire characteristics during 1998-2007 in the four regions above using semi-parametric logistic (SPL) regression models. Non-linear relationships between different ecological factors and fire risk (i. e. probability of fire ignition and occurrence of large fire events) were assessed by semi-parametric logistic regression models. We analyzed characteristics of forest fire activity in the four contrasting vegetatio...
Yang, X, Asseng, S, Wong, MT, Yu, Q, Li, J & Liu, E 2013, 'Quantifying the interactive impacts of global dimming and warming on wheat yield and water use in China', Agricultural and Forest Meteorology, vol. 182-183, no. 1, pp. 342-351.View/Download from: Publisher's site
Solar radiation has been declining across many parts of the world over the last 50 years as a consequence of industrialization increasing atmospheric aerosols, known as 'global dimming'. This study evaluatesthe impact of 'global dimming' and climate change on wheat yield and water use in China during thepast decades using the Agricultural Production Systems Simulator. Three regions, Beijing, Chengdu andUrumqi were selected to represent three different patterns of climate-light environments in China. Thedecline in solar radiation was in conjunction with a warming trend during the past decades. Solar radiationduring the wheat season declined by 20, 27 and 10% at Beijing, Chengdu and Urumqi, respectively, duringthe past four decades. Minimum temperature increased during the same period by 3.9, 1.5 and 2.3?C,respectively. The reduction in solar radiation had no significant impact on simulated wheat yields in theBeijing region while simulated grain yields in the Chengdu region decreased by 32%. Variation of solarradiation explained 74% of changes in grain yield at Chengdu. Simulated grain yields in the Urumqi regionincreased by 24% during the last decades due to increasing minimum temperature and rainfall. Simulatedevapotranspiration declined with the decline of solar radiation. Water use efficiency increased at Beijingand Urumqi, with no significant change at Chengdu. Declining solar radiation from high radiation levelshad no effect on wheat yield but improved water use efficiency, while under low radiation levels grainyields decreased significantly.
Zhao, C, Liu, C, Zhao, J, Xia, J, Yu, Q & Eamus, D 2013, 'Zooplankton in highly regulated rivers: Changing with water environment', Ecological Engineering, vol. 58, no. 1, pp. 323-334.View/Download from: Publisher's site
The Huai River Basin (HRB) of China is well-known globally for the extent of severe human activities (e.g., waste disposal and water project construction) which have resulted in severe water pollution and subsequently degraded water ecosystem quality in recent decades. However, influence of water pollution on water ecosystems has not yet been fully realized due to lack of water ecosystem data. In food webs of freshwater ecosystems, zooplankton occupy a critical position but they are highly susceptible to pollutants and temperature which in turn impact the community structure and biodiversity of zooplankton to a great extent. This paper aimed to assess impact of water chemistry variation on zooplankton through ecological-niche models and spatial heterogeneity of zooplankton along with water chemistry in the HRB. We investigated the impacts of nine dominant water chemistry indicators on zooplankton distribution and composition via ecological niche models based on water chemistry status and zooplankton communities at 71 typical sites of the HRB. A fuzzy clustering method (FCM) was employed to help study the impact characteristics and the spatial heterogeneity. Results indicate that across the nine water chemistry indicators, changes in water temperature has minimal impact on the zooplankton community of the Huai River while small variation in ammonianitrogen exerts significant stress on the community; with respect to water temperature and total phosphorous zooplankton species in the HRB are coexisting with little competition; as to spatial heterogeneity of zooplankton communities, communities in the southwest and southeast mountainous regions may adapt well to habitat variations, while those in the middle and northeast areas have a weak adaptability to habitat changes.
Zhao, G, Bryan, BA, King, D, Luo, Z, Wang, E, Michl, UB, Song, X & Yu, Q 2013, 'Large-scale, high-resolution agricultural systems modeling using a hybrid approach combining grid computing and parallel processing', Environmental Modelling & Software, vol. 41, no. 1, pp. 231-238.View/Download from: Publisher's site
The solution of complex global challenges in the land system, such as food and energy security, requires information on the management of agricultural systems at a high spatial and temporal resolution over continental or global extents. However, computing capacity remains a barrier to large-scale, highresolution agricultural modeling. To model wheat production, soil carbon, and nitrogen dynamics in Australia's cropping regions at a high resolution, we developed a hybrid computing approach combining parallel processing and grid computing. The hybrid approach distributes tasks across a heterogeneous grid computing pool and fully utilizes all the resources of computers within the pool. We simulated 325 management scenarios (nitrogen application rates and stubble management) at a daily time step over 122 years, for 12,707 climateesoil zones using the Windows-based Agricultural Production Systems SIMulator (APSIM). These simulations would have taken over 30 years on a single computer. Our hybrid high performance computing (HPC) approach completed the modeling within 10.5 daysda speed-up of over 1000 timesdwith most jobs finishing within the first few days. The approach utilizes existing idle organization-wide computing resources and eliminates the need to translate Windows-based models to other operating systems for implementation on computing clusters. There are however, numerous computing challenges that need to be addressed for the effective use of these techniques and there remain several potential areas for further performance improvement. The results demonstrate the effectiveness of the approach in making high-resolution modeling of agricultural systems possible over continental and global scales.
Zhao, G, Bryan, BA, King, D, Luo, Z, Wang, E, Song, X & Yu, Q 2013, 'Impact of agricultural management practices on soil organic carbon: simulation of Australian wheat systems', Global Change Biology, vol. 19, no. 1, pp. 1585-1597.View/Download from: Publisher's site
Quantifying soil organic carbon (SOC) dynamics at a high spatial and temporal resolution in response to different agricultural management practices and environmental conditions can help identify practices that both sequester carbon in the soil and sustain agricultural productivity. Using an agricultural systems model (the Agricultural Production Systems sIMulator), we conducted a high spatial resolution and long-term (122 years) simulation study to identify the key management practices and environmental variables influencing SOC dynamics in a continuous wheat cropping system in Australia's 96 million ha cereal-growing regions. Agricultural practices included five nitrogen application rates (0-200 kg N ha-1 in 50 kg N ha-1 increments), five residue removal rates (0-100% in 25% increments), and five residue incorporation rates (0-100% in 25% increments). We found that the change in SOC during the 122-year simulation was influenced by the management practices of residue removal (linearly negative) and fertilization (nonlinearly positive) and the environmental variables of initial SOC content (linearly negative) and temperature (nonlinearly negative). The effects of fertilization were strongest at rates up to 50 kg N ha-1, and the effects of temperature were strongest where mean annual temperatures exceeded 19 °C. Reducing residue removal and increasing fertilization increased SOC in most areas except Queensland where high rates of SOC decomposition caused by high temperature and soil moisture negated these benefits. Management practices were particularly effective in increasing SOC in south-west Western Australia - an area with low initial SOC. The results can help target agricultural management practices for increasing SOC in the context of local environmental conditions, enabling farmers to contribute to climate change mitigation and sustaining agricultural production.
Zhao, ZJ, Shen, GZ, Tan, LY, Kang, DW, Wang, MJ, Kang, W, Guo, WX, Zeppel, MJB, Yu, Q & Li, JQ 2013, 'Treeline dynamics in response to climate change in the Min Mountains, southwestern China', Botanical Studies, vol. 54, no. 1.View/Download from: Publisher's site
Background: Abies faxoniana is the dominant plant species of the forest ecosystem on the eastern edge of Qinghai-Tibet Plateau, where the treeline is strongly defined by climate. The tree-ring chronologies and age structure of Abies faxoniana were developed in the treeline ecotones on the northwestern and southeastern aspects of the Min Mountains in the Wanglang Nature Reserve to examine the treeline dynamics of recent decades in response to climate change. Results: On the northwestern aspect, correlation analysis showed that the radial growth was significantly and positively correlated with precipitation in current January and monthly mean temperature in current April, but significantly and negatively correlated with monthly mean temperature in previous August. On the southeastern aspect, the radial growth was significantly negatively correlated with monthly mean temperature in previous July and August. Conclusions: The different responses of radial growth to climatic variability on both the aspects might be mainly due to the micro-environmental conditions. The recruitment benefited from the warm temperature in current April, July and September on the northwestern aspect. The responses of radial growth and recruitment to climatic variability were similar on the northwestern slope. Recruitment was greatly restricted by competition with dense bamboos on the southeastern aspect. © 2013 Zhao et al.; licensee Springer.
Zhu, J, Yu, J, Wang, P, Yu, Q & Eamus, D 2013, 'Distribution patterns of groundwater-dependent vegetation species diversity and their relationship to groundwater attributes in northwestern China', Ecohydrology, vol. 6, no. 2, pp. 191-200.View/Download from: Publisher's site
The study of the patterns of plant species diversity and the factors influencing these patterns is the basis of ecology and is also fundamental to conservation biology. Groundwater-dependent vegetation (GDV) must have access to groundwater to maintain their growth and function, and this is especially common in arid and semi-arid regions, including north-western China. In this paper, plant species diversity and groundwater attributes (composition and depth) were investigated in 31 plots in the Ejina Delta in north-western China to determine whether groundwater attributes influenced patterns species diversity in GDV. Detrended canonical correspondence analyses and generalised additive models were performed to analyse the data. A total of 29 plant species were recorded in the 31 plots; perennial herbs with deep roots had an advantage over all other groups, and GDV species diversity was primarily affected by groundwater depth (GWD), salinity (SAL) and total dissolved solids (TDS), HCO3, Ca2+, pH, and SO42. The herb layer species diversity and total species diversity reached their maximum in similar, moderate environmental conditions. The diversity of the tree species was influenced by SAL and TDS and was maximal at large values of GWD and low values of SAL and TDS. The diversity of shrub species was affected by Ca2+ and Mg2+ and was maximal low GWD and high SAL and TDS. Patrick's and ShannonWiener's index of the total community diversity presented a bimodal pattern along gradients of GWD and SAL, whilst Simpson's and Pielou's index showed a partially unimodal pattern. On the basis of field investigation and the analysis of field data, we concluded that the perfect combination of GWD and SAL for GDV species diversity is 2m and 1 center dot 8gl1, respectively. The appropriate combination range is 25m and 1 center dot 84 center dot 2gl1, and the critical combination for the damaged GDV species diversity is 5m and 4 center dot 2gl1.
Food security is an issue of global concern, which is tightly linked with water supply issues as regional demands for water are dominated by agricultural water use. This special issue of Agricultural Water Management focuses on crop-water use in China, especially in the North China Plain (NCP) and Loess Plateau and surrounding areas, where intensive agriculture (e.g., wheat-maize double cropping) with limited water is practiced to meet the large demand for grains. Such intensive agriculture raises concerns for agricultural sustainability due to limited water supply and effects on water quality, which may be aggravated by projected climate change and its variability across the region and over time. Addressing these issues requires basic understanding of crop-water relationships in water-limited agricultural systems, methods to quantify water demand and actual crop-water use over multiple scales, and strategies to improve water use efficiency (WUE, or water productivity). Advances in crop breeding (selection) and agronomic management, such as irrigation and nutrient management, and tools to assess and improve WUE at multiple scales are addressed for a range of cropping systems in China. Water supplies within a basin (regional scale) must be managed in view of the patterns of water demand in space and time determined by soil and climatic conditions.
Langtry, TN, Chew, KL, Zinder, Y, Yu, Q & Li, L 2012, 'Estimation of biochemical parameters from leaf photosynthesis', ANZIAM Journal, vol. 53, no. EMAC2011, pp. C218-C235.View/Download from: Publisher's site
The objective of measuring leaf photosynthesis using infrared gas analysis is to determine key indicators of plant eco-physiology, including light and CO2 compensation and saturation points, and critical thresholds of temperature. These and other biochemical parameters in photosynthesis models define specific response curves of photosynthetic rate to environmental variables, such as light intensity, temperature, and CO2. Since these parameters cannot regularly be measured in the field, modellers normally adopt laboratory values as universal ones even though the values of these parameters may vary across plant species. This study investigates the identification of parameter values from data sets obtained from field measurement
Li, L, Wang, Y, Yu, Q, Pak, B, Eamus, D, Yan, J, van Gorsel, E & Baker, IT 2012, 'Improving the responses of the Australian community land surface model (CABLE) to seasonal drought', Journal of Geophysical Research: Biogeosciences, vol. 117, p. G04002.View/Download from: Publisher's site
Correct representations of root functioning, such as root water uptake and hydraulic redistribution, are critically important for modeling the responses of vegetation to droughts and seasonal changes in soil moisture content. However, these processes are poorly represented in global land surface models. In this study, we incorporated two root functions: a root water uptake function which assumes root water uptake efficiency varies with rooting depth, and a hydraulic redistribution function into a global land surface model, CABLE. The water uptake function developed by Lai and Katul (2000) was also compared with the default one (see Wang et al., 2010) that assumes that efficiency of water uptake per unit root length is constant. Using eddy flux measurements of CO2 and water vapor fluxes at three sites experiencing different patterns of seasonal changes in soil water content, we showed that the two root functions significantly improved the agreement between the simulated fluxes of net ecosystem exchange and latent heat flux and soil moisture dynamics with those observed during the dry season while having little impact on the model simulation during the wet seasons at all three sites. Sensitivity analysis showed that varying several model parameters influencing soil water dynamics in CABLE did not significantly affect the model's performance. We conclude that these root functions represent a valuable improvement for land surface modeling and should be implemented into CABLE and other land surface models for studying carbon and water dynamics where rainfall varies seasonally or interannually.
Liu, D, Li, J, Yu, Q, Tong, X & Ouyang, Z 2012, 'Energy balance closure and its effects on evapotranspiration measurements with the eddy covariance technique in a cropland', Shengtai Xuebao/ Acta Ecologica Sinica, vol. 32, no. 17, pp. 5309-5317.View/Download from: Publisher's site
The eddy covariance (EC) technique is generally regarded as a standard method for crop evapotranspiration measurements. However the imbalance of energy closure prevails in the EC observations. Evaluating the effect of energy balance closure on EC measurement is critical for improving the accuracy of this method. In this paper a weighting method (the Lysimeter method) was used as reference to evaluate the effect of energy balance ratio (EBR) on EC evapotranspiration. The results revealed that daytime EBR varied seasonally in the field where wheat and maize were rotated in the winter and summer respectively. The EBR was higher in autumn and winter but lower in the spring and summer. For the wheat field mean daytime EBR varied from 0. 26 to 2. 84 with an average of 1. 15. As for the maize field EBR varied from 0. 19 to 2. 59 with a mean value of 0. 78. The evapotranspiration (ET) using EC (ETec) was clearly lower than derived by Lysimeter (ETL). The mean ratio of ETec to ETL(ETec/ETL) was 0. 61 and 0. 50 during the wheat growing season and the maize season respectively. The ET observed with these two approaches significantly correlated with each other (P < 0. 01) with their characteristics of seasonal variation performing in a similar manner. The ETec/ETL was found to be proportional to EBR (P < 0. 01) in both the winter wheat field and the summer maize field. Furthermore the effect of the leaf area index (LAI) on the relationship between ET ratios and EBR was significant in the even crop field during the entire growing season of winter wheat and the maize growing stage when the LAI was higher than 1. However the effect was insignificant in the uneven maize field when the LAI was less than 1. On the other hand, friction velocity (u*) exerted a strong impact on EBR and its relationship with ET ratios. EBR was observed to be proportional to u* in both the winter wheat field and the summer maize field. ET ratios were proportional to EBR when u* was small. Nonetheless t...
Liu, J, Liu, J, Linderholm, HW, Chen, D, Yu, Q, Wu, D & Haginoya, S 2012, 'Observation and calculation of the solar radiation in the Tibetan Plateau', Energy Conversion and Management, vol. 57, pp. 23-32.View/Download from: Publisher's site
Distribution of solar radiation is vital to locate the most suitable regions for harvesting solar energy, but solar radiation is only observed at few stations due to high costs and difficult maintenance. From 2001 to 2005, a set of pyranometer instruments were set up in Gaize, on the Tibetan Plateau, to test the hypothesis of high solar-radiation levels in this region, and find a suitable method for estimating the radiation. Over the 5-year observation period, the average daily radiation was 21 MJ m(-2)day(-1) with maximum daily values of 27 MJ m(-2)day(-1) occurring in June and minimum values of 14 MJ m(-2)day(-1) in December, which is much higher than those measured in other regions at similar latitudes. The observational data were used to validate a set of radiation models: five sunshine based and three temperature based. The results showed that of the five sunshine-based models, a newly developed "comprehensive" model performed the best, but that the "vapor revised Angstrom model" was recommended to use for its simplicity and easy operation. The temperature-based models performed worse than the sunshine-based ones, where the Wu model is to be preferred if a temperature-based model is the only option. Moreover, it was shown that when estimating the solar radiation based on time-dependent coefficients, consideration of the seasonal variation of the coefficients has little predictive value and is thus unnecessary. Based on the results of this study, a strategy for the calculation of solar radiation on the Tibetan Plateau was made for potential users.
Luo, Q & Yu, Q 2012, 'Developing higher resolution climate change scenarios for agricultural risk assessment: progress, challenges and prospects', International Journal of biometeorology, vol. 56, no. 4, pp. 557-568.View/Download from: Publisher's site
Climate change presents perhaps the greatest economic and environmental challenge we have ever faced. Climate change and its associated impacts, adaptation and vulnerability have become the focus of current policy, business and research. This paper provi
Ye, ZP, Yu, Q & Kang, HJ 2012, 'Evaluation Of Photosynthetic Electron Flow Using Simultaneous Measurements Of Gas Exchange And Chlorophyll Fluorescence Under Photorespiratory Conditions', Photosynthetica, vol. 50, no. 3, pp. 472-476.View/Download from: Publisher's site
Simultaneous measurements of leaf gas exchange and chlorophyll fluorescence for Koelreuteria paniculata Laxm. at 380 +/- 5.6 and 600 +/- 8.5 mu mol mol(-1) were conducted, and the photosynthetic electron flow via photosystem II (PSII) to photosynthesis,
Zhao, C, Liu, C, Xia, J, Zhang, Y, Yu, Q & Eamus, D 2012, 'Recognition of key regions for restoration of phytoplankton communities in the Huai River basin, China', Journal Of Hydrology, vol. 420-421, pp. 292-300.View/Download from: Publisher's site
Healthy phytoplankton communities are the basis of healthy water ecosystems, and form the foundation of many freshwater food webs. Globally many freshwater ecosystems are degraded because of intensive human activities, so water ecosystem restoration is a
Zhao, G, Bryan, B, King, D, Song, X & Yu, Q 2012, 'Parallelization And Optimization Of Spatial Analysis For Large Scale Environmental Model Data Assembly', Computers and Electronics in Agriculture, vol. 89, pp. 94-99.View/Download from: Publisher's site
Spatial-temporal modelling of environmental systems such as agriculture, forestry, and water resources requires high resolution input data. Assembling and summarizing this data in the appropriate format for model input often requires a series of spatial
Zhao, Z, Eamus, D, Yu, Q, Li, Y, Yang, H & Li, J 2012, 'Climate constraints on growth and recruitment patterns of Abies faxoniana over altitudinal gradients in the Wanglang Natural Reserve, eastern Tibetan Plateau', Australian Journal Of Botany, vol. 60, no. 7, pp. 602-614.View/Download from: Publisher's site
The radial growth and recruitment patterns of trees in subalpine areas are subject to the influence of changing environmental conditions associated with changes in elevation. To investigate responses of fir radial growth and recruitment to climate factors at different elevations, tree-ring width chronologies and age structures of Abies faxoniana were developed from five sampling sites at ~28003300 m elevation on the north-western and south-eastern aspects in the Wanglang Natural Reserve on the eastern edge of Tibetan Plateau. Statistical characteristics of the chronologies indicated that expressed population signal and signal-to-noise ratio increased with increasing elevation in the north-western aspect; the reverse was observed on the south-eastern aspect. Correlation analysis between chronologies and climate variables showed that fir radial growth was negatively correlated with previous growing season mean temperatures and was positively correlated with January precipitation in all plots. The amount of precipitation in the growing season (June and July) greatly influenced radial growth in the two lower sites of both the aspects. The three plots on the north-western aspect were characterised by significant rates of tree recruitment in the past five decades.
Zhu, J, Li, X, Zhang, X, Yu, Q & Lin, L 2012, 'Leaf nitrogen allocation and partitioning in three groundwater-dependent herbaceous species in a hyper-arid desert region of north-western China', Australian Journal Of Botany, vol. 60, no. 1, pp. 61-67.View/Download from: Publisher's site
Groundwater-dependent vegetation (GDV) is useful as an indicator of watertable depth and water availability in north-western China. Nitrogen (N) is an essential limiting resource for growth of GDV. To elucidate how leaf N allocation and partitioning influence photosynthesis and photosynthetic N-use efficiency (PNUE), three typical GDV species were selected, and their photosynthesis, leaf N allocation and partitioning were investigated in the Taklamakan Desert. The results showed that Karelinia caspica (Pall.) Less. and Peganum harmala L. had lower leaf N content, and allocated a lower fraction of leaf N to photosynthesis. However, they were more efficient in photosynthetic N partitioning among photosynthetic components. They partitioned a higher fraction of the photosynthetic N to carboxylation and showed higher PNUE, whereas Alhagi sparsifolia Shap. partitioned a higher fraction of the photosynthetic N to light-harvesting components. For K. caspica and P. harmala, the higher fraction of leaf N was allocated to carboxylation and bioenergetics, which led to a higher maximum net photosynthetic rate, and therefore to a higher PNUE, water-use efficiency (WUE), respiration efficiency (RE) and so on. In the desert, N and water are limiting resources; K. caspica and P. harmala can benefit from the increased PNUE and WUE. These physiological advantages and their higher leaf-area ratio (LAR) may contribute to their higher resource-capture ability.
Zhu, J, Yu, J, Wang, P, Zhang, Y & Yu, Q 2012, 'Interpreting the groundwater attributes influencing the distribution patterns of groundwater-dependent vegetation in northwestern China', Ecohydrology, vol. 5, no. 5, pp. 628-638.View/Download from: Publisher's site
Groundwater-dependent vegetation (GDV) must have access to groundwater to maintain their growth and function. GDV distribution patterns are an important issue in arid vegetation ecology. Using groundwater attributes to explore the distribution patterns of GDV have been very limited. In this article, we selected the Ejina Desert Oasis as an area to investigate GDV and groundwater attributes. Twenty plant species and 31 plant plots of data were collected. Two-way indicator species analysis (TWINSPAN) was performed to determine GDV types. Detrended correspondence analysis (DCA) and detrended canonical correspondence analysis (DCCA) were performed to analyse the relationships between GDV and groundwater attributes. The results indicated that (1) six plant community types were classified by TWINSPAN; (2) DCA ordination analyses showed that the groundwater depth (Dep) was the main factor restricting the distribution patterns of GDV, and the distribution of the dominant species and corresponding vegetation types had strong similarities; (3) in the DCCA diagram, the first axis represented variations of Dep, while the second axis was related to the pH values; (4) with increased Dep, the community types made the transition from I to VI; and (5) the DCCA diagram was similar to the DCA. However, the distribution patterns of GDV were more compact in the DCCA, while the DCA showed that each association group appeared within a limited range and had a clear border against other communities. This study shows that ordination methods can be used to explain the relationships between the distribution patterns of GDV and groundwater attributes
Chen, C, Baethgen, WE, Wang, E & Yu, Q 2011, 'Characterizing spatial and temporal variability of crop yield caused by climate and irrigation in the North China Plain', Theoretical and Applied Climatology, vol. 106, no. 3-4, pp. 365-381.View/Download from: Publisher's site
Grain yields of wheat and maize were obtained from national statistics and simulated with an agricultural system model to investigate the effects of historical climate variability and irrigation on crop yield in the North China Plain (NCP). Both observed and simulated yields showed large temporal and spatial variability due to variations in climate and irrigation supply. Wheat yield under full irrigation (FI) was 8 t ha(-1) or higher in 80% of seasons in the north, it ranged from 7 to 10 t ha(-1) in 90% of seasons in central NCP, and less than 9 t ha(-1) in 85% of seasons in the south. Reduced irrigation resulted in increased crop yield variability. Wheat yield under supplemental irrigation, i.e., to meet only 50% of irrigation water requirement [supplemental irrigation (SI)] ranged from 2.7 to 8.8 t ha(-1) with the maximum frequency of seasons having the range of 4-6 t ha(-1) in the north, 4-7 t ha(-1) in central NCP, and 5-8 t ha(-1) in the south. Wheat yield under no irrigation (NI) was lower than 1 t ha(-1) in about 50% of seasons. Considering the NCP as a whole, simulated maize yield under FI ranged from 3.9 to 11.8 t ha(-1) with similar frequency distribution in the range of 6-11.8 t ha(-1) with the interval of 2 t ha(-1). It ranged from 0 to 11.8 t ha(-1), uniformly distributed into the range of 4-10 t ha(-1) under SI, and NI. The results give an insight into the levels of regional crop production affected by climate and water management strategies.
Li, J, Lee, X, Yu, Q, Tong, X, Qin, Z & Macdonald, B 2011, 'Contributions of agricultural plants and soils to N2O emission in a farmland', Biogeosciences Discussion, vol. 8, no. 3, pp. 5505-5535.View/Download from: Publisher's site
The goal of this study was to quantify the roles of plants and soil in the N2O budget of a cropland in North China. Plant and soil N2O fluxes were measured with transparent and dark plant chambers and soil chambers, respectively, in three adjacent fields of fertilized cotton, fertilized maize and unfertilized soybean. During the observation period, the soil flux was 448 ± 89, 230 ± 74 and 90 ± 14 µg N2O m-2 h-1 in cotton, maize and soybean fields, respectively. The plant flux was 54 ± 43 and 16 ± 41 µg N2O m-2 h-1, about 10 % and 26 % to the total ecosystem flux, for the cotton and the soybean field, respectively. Ignoring the contribution of plants would cause an obvious underestimation on the ecosystem N2O flux. The influence of sunlight on plant N2O flux was insignificant. However, in the cotton field, the responses of the plant N2O flux to air temperature and soil ammonium content were significant under sunlight but insignificant under darkness, suggesting that stomatal activity might influence the release process. In the cotton field, temperature sensitivity of plant N2O emission was 1.13, much lower than the value of soil flux (5.74). No relationship was found between plant N2O flux and soil nitrate content. It was implied that nitrate reduction in plants might not be the main source of plant N2O emission under field conditions. The seasonal patterns of the soil and plant N2O emissions were similarly affected by fertilization, indicating that plants might serve as a passive conduit transporting N2O produced in the soil.
Pan, G, OuYang, Z, Luo, Q, Yu, Q & Wang, J 2011, 'Water use patterns of forage cultivars in the North China Plain', International Journal Of Plant Production, vol. 5, no. 2, pp. 181-194.
Water shortage is the primary limiting factor for crop production and long-term agricultural sustainability of the North China Plain. Forage cultivation emerged recently in this region. A fiveryear field experiment studies were conducted at Yucheng Integrated Experiment Station to quantify the water requirement and water use efficiency of seven forage varieties under climate variability, that is five annuals, i.e., ryegrass (Secale cereale L.), triticale (×Triticosecale Wittmack), sorghum hybrid sudangrass (Sorghum biolor × Sorghum Sudanense c.v.), ensilage corn (Zea mays L.), prince`s feather (Amaranthus paniculatus L.) and two perennials alfalfa (Medicago sativa L.) and cup plant (Silphium perfoliatum L.). Average ET for five annual varieties ranged from 333 to 371 mm, significantly lower than that of the perennial varieties. ET of alfalfa is 789 mm, which is higher than that of cup plant. Ryegrass and triticale need 1.5 to 2.0 mm water per day, while others 2.9-4.4 mm. Ensilage corn and Sorghum hybrid sudangrass performed better as their irrigation demand is smaller in the dry seasons than others. Ryegrass needs 281 mm irrigation requirement, which is higher than triticale in dry years. Prince's feather is sensitive to climate change and it can be selected when rainfall is greater than 592.9 mm in the growing season. Mean WUE for prince's feather is 20 Kg ha-1 mm-1, for ensilage corn is 41 Kg ha-1 mm-1 and others is close to 26 Kg ha-1 mm-1. Our experiments indicate that excessive rain will reduce the production of alfalfae. The results of this experiment have implications for researchers and policy makers with water management strategy of forage cultivars and it also very useful in addressing climate change impact and adaptation issues.
Xing, H, Wang, E, Smith, C, Rolston, D & Yu, Q 2011, 'Modelling nitrous oxide and carbon dioxide emission from soil in an incubation experiment', Geoderma, vol. 167-168, pp. 328-339.View/Download from: Publisher's site
Nitrous oxide (N2O), one of the primary green house gases (GHG), is an important contributor to the radiative forcing and chemistry of the atmosphere. Nitrous oxide emissions from soil are mainly due to denitrification. In this paper, we test sub-modules in the APSIM and DAYCENT models to simulate denitrification. The models were tested by comparison of predicted and measured N2O emission from an incubation experiment using 8.2 L soil cores. The N gas sub-modules in DAYCENT were based on the leaky pipe metaphor, that is, total N gas emissions are proportional to N cycling and gas diffusivity in the soil determines the relative amounts of N gas species emitted. The same approach was added to APSIM to enable simulation of N2O emission. The soil monoliths were irrigated three times during a two-week period and set on tension tables to control the suction at the base of each core. The results show that APSIM underestimates denitrification, whereas DAYCENT better predicted N2O emission from denitrification. In contrast, predictions of CO2 emissions were better from APSIM than DAYCENT. Modification to the temperature response for denitrification in APSIM improved the simulation significantly. The use of multiple soil layers in the simulations improved predictions, especially at low soil moisture content. Under these conditions, the layered approach better captures the impact of soil moisture distribution. Reducing the time step to hourly improve the prediction of N2O peaks and the daily total emissions, but there were still temporal mismatches between simulated and observed values. The denitrification algorithms in DAYCENT, combined with APSIM simulated CO2, together with an hourly time step and a layered approach, produced the best results. These results highlight the need for improvement to the APSIM denitrification sub-model.
Yang, X, Chen, C, Luo, Q, Li, L & Yu, Q 2011, 'Climate change effects on wheat yield and water use in oasis cropland', International Journal Of Plant Production, vol. 5, no. 1, pp. 83-94.
Agriculture of the inland arid region in Xinjiang depends on irrigation, which forms oasis of Northwest China. The production and water use of wheat, a dominant crop there, is significantly affected by undergoing climate variability and change. The objective of this study is to quantify interannual variability of wheat yield and water use from 1955 to 2006. The farming systems model APSIM (Agricultural Production Systems Simulator) was used to evaluate crop yield, evapotranspiration (ET), and water use efficiency of winter and spring wheat (Triticum aestivum L.) in Xinjiang from 1955 to 2006. The APSIM model was first calibrated and validated using 6 years of experimental data. The validated model was then applied to simulated wheat yield and ET using climatic and soil data for present crop cultivar. Simulated wheat yield under full irrigation have no significant decreasing trend from 1955 to 2006. Simulated growth duration of winter wheat was significantly decreased. Simulated ET of winter wheat was significantly correlated with measured pan evaporation. Simulated ET of winter wheat decreased significantly during the 52 years, with a decrease rate of 0.813 mm year-1. Cluster analysis showed that the variations of ET were mainly determined by solar radiation, nothing to do with the changes in temperature. The results identified the change trend of field ET under historical climate change, and determined the main meteorological factors which affect ET in this oasis. These results provide a measure for water demand, crop production and irrigation management under climate change in the oasis.
Chen, C, Wang, E & Yu, Q 2010, 'Modeling Wheat And Maize Productivity As Affected By Climate Variation And Irrigation Supply In North China Plain', Agronomy Journal, vol. 102, no. 3, pp. 1037-1049.View/Download from: Publisher's site
A modeling approach was used to analyze the response of crop productivity to irrigation in the North China Plain (NCP), where excessive use of water for irrigation has caused rapid decline in groundwater table. We calibrated and evaluated the farming sys
Chen, C, Wang, E & Yu, Q 2010, 'Modelling the effects of climate variability and water management on crop water productivity and water balance in the North China Plain', Agricultural Water Management, vol. 97, pp. 1175-1184.View/Download from: Publisher's site
In the North China Plain (NCP), while irrigation using groundwater has maintained a high-level crop productivity of the wheatmaize double cropping systems, it has resulted in rapid depletion of groundwater table. For more efficient and sustainable utilization of the limited water resources, improved understanding of how crop productivity and water balance components respond to climate variations and irrigation is essential. This paper investigates such responses using a modelling approach. The farming systems model APSIM (Agricultural Production Systems Simulator) was first calibrated and validated using 3 years of experimental data. The validated model was then applied to simulate crop yield and field water balance of the wheatmaize rotation in the NCP. Simulated dryland crop yield ranged from 0 to 4.5 t ha-1 for wheat and 0 to 5.0 t ha-1 for maize. Increasing irrigation amount led to increased crop yield, but irrigation required to obtain maximum water productivity (WP) was much less than that required to obtain maximum crop yield. To meet crop water demand, a wide range of irrigation water supply would be needed due to the inter-annual climate variations. The range was simulated to be 140420 mm for wheat, and 0170 mm for maize. Such levels of irrigation applications could potentially lead to about 1.5 m year-1 decline in groundwater table when other sources of groundwater recharge were not considered. To achieve maximum WP, one, two and three irrigations (i.e., 70, 150 and 200 mm season-1) were recommended for wheat in wet, medium and dry seasons, respectively. For maize, one irrigation and two irrigations (i.e., 60 and 110 mm season-1) were recommended in medium and dry seasons, while no irrigation was needed in wet season.
Chen, C, Wang, E, Yu, Q & Zhang, Y 2010, 'Quantifying The Effects Of Climate Trends In The Past 43 Years (1961-2003) On Crop Growth And Water Demand In The North China Plain', Climatic Change, vol. 100, no. 3-4, pp. 559-578.View/Download from: Publisher's site
This paper explores changes in climatic variables, including solar radiation, rainfall, fraction of diffuse radiation (FDR) and temperature, during wheat season (October to May) and maize season (June to September) from 1961 to 2003 at four sites in the
Fang, Q, Ma, L, Green, T, Yu, Q, Wang, TD & Ahuja, LR 2010, 'Water Resources And Water Use Efficiency In The North China Plain: Current Status And Agronomic Management Options', Agricultural Water Management, vol. 97, no. 8, pp. 1102-1116.View/Download from: Publisher's site
Serious water deficits and deteriorating environmental quality are threatening agricultural sustainability in the North China Plain (NCP). This paper addresses spatial and temporal availability of water resources in the NCP, identifies the effects of soi
Fang, Q, Ma, L, Yu, Q, Ahuja, LR, Malone, RW & Hoogenboom, G 2010, 'Irrigation strategies to improve the water use efficiency of wheat-maize double cropping systems in North China Plain', Agricultural Water Management, vol. 97, no. 8, pp. 1165-1174.View/Download from: Publisher's site
Water is the most important limiting factor of wheat (Triticum aestivum L.) and maize (Zea mays L.) double cropping systems in the North China Plain (NCP). A two-year experiment with four irrigation levels based on crop growth stages was used to calibrate and validate RZWQM2, a hybrid model that combines the Root Zone Water Quality Model (RZWQM) and DSSAT4.0. The calibrated model was then used to investigate various irrigation strategies for high yield and water use efficiency (WUE) using weather data from 1961 to 1999. The model simulated soil moisture, crop yield, above-ground biomass and WUE in responses to irrigation schedules well, with root mean square errors (RMSEs) of 0.029 cm3 cm-3, 0.59 Mg ha-1, 2.05 Mg ha-1, and 0.19 kg m-3, respectively, for wheat; and 0.027 cm3 cm-3, 0.71 Mg ha-1, 1.51 Mg ha-1 and 0.35 kg m-3, respectively, for maize. WUE increased with the amount of irrigation applied during the dry growing season of 20012002, but was less sensitive to irrigation during the wet season of 20022003. Long-term simulation using weather data from 1961 to 1999 showed that initial soil water at planting was adequate (at 82% of crop available water) for wheat establishment due to the high rainfall during the previous maize season. Preseason irrigation for wheat commonly practiced by local farmers should be postponed to the most sensitive growth stage (stem extension) for higher yield and WUE in the area. Preseason irrigation for maize is needed in 40% of the years. With limited irrigation available (100, 150, 200, or 250 mm per year), 80% of the water allocated to the critical wheat growth stages and 20% applied at maize planting achieved the highest WUE and the least water drainage overall for the two crops.
Flerchinger, GN, Marks, DJ, Reba, M, Yu, Q & Seyfried, M 2010, 'Surface Fluxes And Water Balance Of Spatially Varying Vegetation Within A Small Mountainous Headwater Catchment', Hydrology And Earth System Sciences, vol. 14, no. 6, pp. 965-978.View/Download from: Publisher's site
Precipitation variability and complex topography often create a mosaic of vegetation communities in mountainous headwater catchments, creating a challenge for measuring and interpreting energy and mass fluxes. Understanding the role of these communities
Li, L, Nielsen, DC, Yu, Q, Ma, L & Ahuja, LR 2010, 'Evaluating the Crop Water Stress Index and its correlation with latent heat and CO2 fluxes over winter wheat and maize in the North China plain', Agricultural Water Management, vol. 97, pp. 1146-1155.View/Download from: Publisher's site
Plant water status is a key factor impacting crop growth and agricultural water management. Crop water stress may alter canopy temperature, the energy balance, transpiration, photosynthesis, canopy water use efficiency, and crop yield. The objective of this study was to calculate the Crop Water Stress Index (CWSI) from canopy temperature and energy balance measurements and evaluate the utility of CWSI to quantify water stress by comparing CWSI to latent heat and carbon dioxide (CO2) flux measurements over canopies of winter wheat (Triticum aestivum L.) and summer maize (Zea mays L.). The experiment was conducted at the Yucheng Integrated Agricultural Experimental Station of the Chinese Academy of Sciences from 2003 to 2005. Latent heat and CO2 fluxes (by eddy covariance), canopy and air temperature, relative humidity, net radiation, wind speed, and soil heat flux were averaged at half-hour intervals. Leaf area index and crop height were measured every 7 days. CWSI was calculated from measured canopy-air temperature differences using the Jackson method. Under high net radiation conditions (greater than 500 W m-2), calculated values of minimum canopy-air temperature differences were similar to previously published empirically determined non-water-stressed baselines. Valid measures of CWSI were only obtained when canopy closure minimized the influence of viewed soil on infrared canopy temperature measurements (leaf area index was greater than 2.5 m2 m-2). Wheat and maize latent heat flux and canopy CO2 flux generally decreased linearly with increases in CWSI when net radiation levels were greater than 300 W m-2. The responses of latent heat flux and CO2 flux to CWSI did not demonstrate a consistent relationship in wheat that would recommend it as a reliable water stress quantification tool.
Qin, Z, Su, G, Zhang, J, Ouyang, Y, Yu, Q & Li, J 2010, 'Identification Of Important Factors For Water Vapor Flux And Co2 Exchange In A Cropland', Ecological Modelling, vol. 221, no. 4, pp. 575-581.View/Download from: Publisher's site
Water vapor flux and carbon dioxide (CO2) exchange in croplands are crucial to water and carbon cycle research as well as to global warming evaluation. In this study, a standard three-layer feed-forward back propagation neural network technique associate
Sun, H, Shen, Y, Yu, Q, Flerchinger, GN, Liu, C & Zhang, X 2010, 'Effect of precipitation change on water balance and WUE of the winter wheat-summer maize rotation in the North China Plain', Agricultural Water Management, vol. 97, no. 8, pp. 1139-1145.View/Download from: Publisher's site
Limited precipitation restricts crop yield in the North China Plain, where high level of production depends largely on irrigation. Establishing the optimal irrigation scheduling according to the crop water requirement (CWR) and precipitation is the key factor to achieve rational water use. Precipitation data collected for about 40 years were employed to analyze the long-term trend, and weather data from 1984 to 2005 were used to estimate the CWR and irrigation water requirements (IWR). Field experiments were performed at the Luancheng Station from 1997 to 2005 to calculate the soil water consumption and water use efficiency (WUE). The results showed the CWR for winter wheat and summer maize were similar and about 430 mm, while the IWR ranged from 247 to 370 mm and 0 to 336 mm at the 25% and 75% precipitation exceedance probabilities for winter wheat and summer maize, respectively. The irrigation applied varied in the different rainfall years and the optimal irrigation amount was about 186, 161 and 99 mm for winter wheat and 134, 88 and 0 mm for summer maize in the dry, normal and wet seasons, respectively. However, as precipitation reduces over time especially during the maize growing periods, development of water-saving management practices for sustainable agriculture into the future is imperative.
Wang, J, Zhao, T, Wang, E, Yu, Q, Yang, X, Feng, L & Pan, X 2010, 'Measurement and simulation of diurnal variations in water use efficiency and radiation use efficiency in an irrigated wheat-maize field in the North China Plain', New Zealand Journal of Crop and Horticultural Science, vol. 38, no. 2, pp. 119-135.View/Download from: Publisher's site
Quantifying diurnal patterns of water use efficiency (WUE) and radiation use efficiency (RUE) for wheat and maize is important for assessing water use by plants and crop productivity. Water and carbon dioxide fluxes from an irrigated wheat-maize double-crop field from November 2002 to October 2003 were measured using the Eddy Covariance method. Evident differences were observed between the diurnal patterns of WUE for wheat and maize. The WUE values of wheat peaked near 9, 15 and 12 mg CO2 g H2O in the morning, and then decreased linearly with time and recovered in the late afternoon (4:00pm) before sunset in March, April and May, respectively. The WUE of maize increased after sunrise and retained stable values of 6, 14 and 12 mg CO2 g H2O from mid-morning to mid-afternoon (10:00am 2:00pm) and then decreased slowly with time until sunset in July, August and September, respectively. Similar patterns were observed in the RUE of wheat and maize. Over the three months of the study, averaged RUE was 1.76 g C MJ-1 for the wheat crop and 1.87 g C MJ-1 for the maize crop. A coupled photosynthesis and transpiration model was used to simulate the diurnal variations in WUE under variable climate conditions. Measurement results and sensitivity analysis show that the difference in the diurnal variation pattern in WUE between wheat and maize resulted from the different carbon fixing mechanisms of wheat and maize.
Xiao, W, Lee, X, Griffis, T, Kim, K, Welp, L & Yu, Q 2010, 'A Modeling Investigation Of Canopy-Air Oxygen Isotopic Exchange Of Water Vapor And Carbon Dioxide In A Soybean Field', Journal of Geophysical Research: Biogeosciences, vol. 115, pp. 1-17.View/Download from: Publisher's site
The oxygen isotopes of CO2 and H2O (O-18-CO2 and O-18-H2O) provide unique information regarding the contribution of terrestrial vegetation to the global CO2 and H2O cycles. In this paper, a simple isotopic land surface model was used to investigate proce
Ye, ZP, Kang, HJ, Tao, YL & Yu, Q 2010, 'Some problems on photosynthetic parameters calculated by photosynthesis assistant', Plant Physiology Communications, vol. 46, no. 1, pp. 67-70.
Flerchinger, GN, Xaio, W, Marks, D, Sauer, TJ & Yu, Q 2009, 'Comparison of algorithms for incoming atmospheric long-wave radiation', Water resources research, vol. 45, pp. 1-13.View/Download from: Publisher's site
While numerous algorithms exist for predicting incident atmospheric long-wave radiation under clear (L clr ) and cloudy skies, few comparisons have been published to assess the accuracy of the different algorithms. Virtually no comparisons have been made for both clear and cloudy skies across multiple sites. This study evaluates the accuracy of 13 algorithms for predicting incident long-wave radiation under clear skies, ten cloud correction algorithms, and four algorithms for all-sky conditions using data from 21 sites across North America and China.
Flerchinger, GN, Xiao, W, Sauer, TJ & Yu, Q 2009, 'Simulation of within-canopy radiation exchange', NJAS Wageningen Journal of Life Sciences, vol. 57, no. 1 Special Issue, pp. 5-15.View/Download from: Publisher's site
Radiation exchange at the surface plays a critical role in the sui face energy balance, plant microclimate, and plant growth. The ability to simulate the surface energy balance and the microclimate within the plant canopy is contingent upon simulation of the surface radiation exchange. A validation and modification exercise of the Simultaneous Heat and Water (SHAW) model was conducted for simulating the sui face short-wave and long-wave radiation exchange over and within wheat, maize and soya bean plant canopies using data collected at Yucheng in the North China Plain and neat Ames. Iowa Whereas model testing was limited to monocultures and mixed canopies of green and senesced leaves, methodologies were developed for simulating short-wave and long-wave radiation fluxes applicable to a multi-species, multi-layer plant canopy Although the original SHAW model slightly under predicted reflected solar radiation with a mean bias en or (MBE) of -5 to -10 W m(-2), one would conclude that the simulations were quite reasonable if within-canopy measurements were not available However, within-canopy short-wave radiation was considerably under estimated (MBE of approximately -20 W m(-2)) by the original SHAW model Additionally, leaf temperatures tended to be overpredicted (MBE = +0 76 degrees C) near the top of the canopy and underpredicted near the bottom (MBE = -1 12 degrees C) Modification to the SHAW model reduced MBE of above canopy reflected radiation to -1 to -6 W m(-2) and within-canopy radiation simulations to approximately -6 W m(-2). bias in leaf temperature was reduced to less than 0 4 degrees C Model modifications resulted in essentially no change in simulated evapotranspiration lot wheat. 4.5% lower for maize and 1% higher for soya bean.
Li, L, Yu, Q, Su, Z & van der Tol, C 2009, 'A simple method using climatic variables to estimate canopy temperature, sensible and latent heat fluxes in a winter wheat field on the North China Plain', Hydrological Processes, vol. 23, no. 5, pp. 665-674.View/Download from: Publisher's site
Estimation of evapotranspiration from a crop field is of great importance for detecting crop water status and proper irrigation scheduling. The Penman-Monteith equation is widely viewed as the best method to estimate evapotranspiration but it requires canopy resistance, which is very difficult to determine in practice. This paper presents a simple method simplified from the Penman-Monteith equation for estimating canopy temperature (Tc). The proposed method is a biophysically-sound extended version of that proposed by Todorovic. The estimated canopy temperature is used to calculate sensible heat flux, and then latent heat flux is calculated as the residual of the surface energy balance. An eddy covariance (EC) system and an infrared thermometer (IRT) were installed in an irrigated winter wheat field on the North China Plain in 2004 and 2005, to measure Tc, and sensible and latent heat fluxes were used to test the modified Todorovic model (MTD). The results indicate that the original Todorovic model (TD) severely underestimates Tc and sensible heat flux, and hence severely overestimates the latent heat flux. However, the MTD model has good capability for estimating Tc, and gives acceptable results for latent heat flux at both half-hourly and daily scales. The MTD model results also agreed well with the evapotranspiration calculated from the measured Tc.
Tong, X, Li, J, Yu, Q & Qin, Z 2009, 'Ecosystem water use efficiency in an irrigated cropland in the North China Plain', Journal Of Hydrology, vol. 374, no. 3-4, pp. 329-337.View/Download from: Publisher's site
The eddy covariance technique and the cuvette method were used to investigate water use efficiency in an irrigated winter wheat (Triticum asetivum L.)/summer maize (Zea mays L.) rotation system in the North China Plain. The results show that ecosystem water use efficiency (WUEe) changed diurnally and season, ally. Daily maximal WUEe appeared in the morning. WUEe generally peaked in late April in wheat field and in late July/early August in maize field. From 2003 to 2006, seasonal mean WUEe was 6.7-7.4 mg CO2 g(-1) H2O for wheat and 8.4-12.1 mg CO2 g(-1) H2O for maize. WUEe was much lower than canopy water use efficiency (WUEc) under small leaf area index (LAI) but very close to WUEc under large LAI. With the increase in LAI, WUEe enlarged rapidly under low LAI but slowly when LAI was higher than one. WUEe was greater on the cloudy days than on the sunny days. Under the same solar radiation, WUEe was higher in the morning than in the afternoon. The ratio of internal to ambient CO2 partial pressure (Ci/Ca) decreased significantly with the increase in photosynthetically active radiation (PAR) when PAR was lower than the critical values (around 500 and 1000 mu mol m(-2) s(-1) for wheat and maize, respectively). Beyond critical PAR, C-i/C-a was approximately constant at 0.69 for wheat and 0.42 for maize Therefore., when LAI and solar radiation was large enough, WUEe has negative correlation with vapor pressure deficit in both of irrigated wheat and maize fields.
Fang, Q, Ma, L, Yu, Q, Malone, RW, Saseendran, SA & Ahuja, LR 2008, 'Modeling nitrogen and water management effects in a wheat-maize double-cropping system', Journal of Environmental Quality, vol. 37, no. 6, pp. 2232-2242.View/Download from: Publisher's site
Excessive N and water use in agriculture causes environmental degradation and can potentially jeopardize the sustainability of the system. A field study was conducted from 2000 to 2002 to study the effects of four N treatments (0, 100, 200, and 300 kg N ha1 per crop) on a wheat (Triticum aestivum L.) and maize (Zea mays L.) double cropping system under 70 ± 15% field capacity in the North China Plain (NCP). The root zone water quality model (RZWQM), with the crop estimation through resource and environment synthesis (CERES) plant growth modules incorporated, was evaluated for its simulation of crop production, soil water, and N leaching in the double cropping system. Soil water content, biomass, and grain yield were better simulated with normalized root mean square errors (NRMSE, RMSE divided by mean observed value) from 0.11 to 0.15 than soil NO3N and plant N uptake that had NRMSE from 0.19 to 0.43 across these treatments. The long-term simulation with historical weather data showed that, at 200 kg N ha1 per crop application rate, auto-irrigation triggered at 50% of the field capacity and recharged to 60% field capacity in the 0- to 50-cm soil profile were adequate for obtaining acceptable yield levels in this intensified double cropping system. Results also showed potential savings of more than 30% of the current N application rates per crop from 300 to 200 kg N ha1, which could reduce about 60% of the N leaching without compromising crop yields.
Jiang, J, Zhang, Y, Wegehenkel, M, Yu, Q & Xia, J 2008, 'Estimation of soil water content and evapotranspiration from irrigated cropland on the North China Plain', Journal Of Plant Nutrition And Soil Science-Zeitschrift Fur Pflanzenernahrung Und Bodenkunde Journal Of ..., vol. 171, no. 5, pp. 751-761.View/Download from: Publisher's site
For nearly 30 y, cropland on the North China Plain (NCP) has been irrigated primarily by pumping groundwater with no sustainable management strategy. This has caused a continuous decline of the water table. A sustainable groundwater management and irrigation strategy must be established in order to prevent further decline of the water table; to do this, one must quantify soil water content and daily rates of deep percolation and locate evapotranspiration from irrigated cropland. For that purpose, we developed a three-layer soil-water balance (SWB) model based on an approach described by Kendy et al. (2003). In this model, the unsaturated soil zone is divided into three layers: a surface active layer, a middle active soil layer, and a lowest passive soil layer. The middle and the lowest layers dynamically change with the development of crop rooting depth. A simple "tipping bucket" routine and an exponential equation are used to redistribute soil water in the three soil layers. The actual evapotranspiration estimated is partitioned into soil evaporation and crop transpiration using a dual crop coefficient reference approach. At first, the model was calibrated using data obtained from five deficiently irrigated field plots located at an experimental site in the NCP between 1998 and 2003. Then, the model was validated by comparing estimated soil water contents with measured ones at three other plots with nondeficient irrigation.
Li, J, Tong, X, Yu, Q, Dong, Y & Peng, C 2008, 'Micrometerological measurements of nitrous oxide exchange in a cropland', Atmospheric Environment, vol. 42, no. 29, pp. 6992-7001.View/Download from: Publisher's site
N2O fluxes in a wheat/maize rotation system were measured using flux gradient methods combined with gas chromatograph (GC) technique. The mean precision of two repeated GC analyses for N2O concentration achieved to 0.270.46 ppbv, which could resolve N2O concentration differences in a low range of 0.390.65 ppbv. To maximize measurable N2O concentration differences, gradient measurements were conducted only after fertilization or under low wind conditions. During observation period, N2O flux ranged from 4.41 to 4.84 mgN2Om2 h1 for maize field, and from 2.82 to 3.59 mgN2Om2 h1 for wheat field. When gradient observation changed from two layers to four layers, the temporal variation of N2O flux reduced but the mean value changed less. Many negative N2O fluxes were found in maize and wheat fields even after fertilization. Nearly all of them were caused by negative N2O concentration differences. During four days observation in maize field, a mean N2O flux of 0.75 mgN2Om2 h1 was found in the daytime and could not be simply attributed to the temporal variation of N2O flux. N2O flux determined by the aerodynamic method (Fa) and the Bowen ratio/energy balance method (Fb) were in a good agreement and statistically significant. The ratio of Fa to Fb increased linearly with energy balance ratio (EBR) obtained by the aerodynamic method in the daytime when EBR is larger than 0.3. It is the first time to give a quantitative description for the impact of energy closure on N2O flux, and show a possible way to improve the data quality under the condition of poor energy balance.
Li, L, Malone, RW, Kasper, TC, Jaynes, DB, Saseendran, SA, Thorp, KR, Yu, Q & Ahuja, LR 2008, 'Winter cover crop effects on nitrate leaching in subsurface drainage as simulated by RZWQM-DSSAT', American Society of Agricultural and Biological Engineers, vol. 51, no. 5, pp. 1575-1583.
Planting winter cover crops such as winter rye (Secale cereale L.) after corn and soybean harvest is one of the more promising practices to reduce nitrate loss to streams from tile drainage systems without negatively affecting production. Because availability of replicated tile-drained field data is limited and because use of cover crops to reduce nitrate loss has only been tested over a few years with limited environmental and management conditions, estimating the impacts of cover crops under the range of expected conditions is difficult. If properly tested against observed data, models can objectively estimate the relative effects of different weather conditions and agronomic practices (e.g., various N fertilizer application rates in conjunction with winter cover crops). In this study, an optimized winter wheat cover crop growth component was integrated into the calibrated RZWQM-DSSAT hybrid model, and then we compared the observed and simulated effects of a winter cover crop on nitrate leaching losses in subsurface drainage water for a corn-soybean rotation with N fertilizer application rates over 225 kg N ha-1 in corn years.
Li, L, McMaster, G, Yu, Q & Du, J 2008, 'Simulating winter wheat development response to temperature: modifying Malo's exponential sine equation', Computers and Electronics in Agriculture, vol. 63, no. 2, pp. 274-281.View/Download from: Publisher's site
Predicting crop developmental events is fundamental to simulation models and crop management decisions. Many approaches to predict developmental events have been developed, however, most only simulate the mean time for reaching a developmental event. An exponential sine equation developed by Malo [Malo, J.E., 2002. Modelling unimodal flowering phenology with exponential sine equation. Funct. Ecol. 16, 413418] to predict flower number over time was modified to incorporate the response of crop development rate to temperature. The revised model (ExpSine model) uses the base, optimum, and maximum cardinal temperatures specific to a crop or genotype. Most model parameters were estimated from the literature, and four of the five model parameters have physiological significance. Model evaluation for winter wheat (Triticum aestivum L.) was based on two controlled environment studies from the literature and two field experiments conducted in the North China Plain (NCP) and the Tibet Plateau (TPC).
Lu, P, Yu, Q, Wang, E, Liu, J & Xu, S 2008, 'Effects of climatic variation and warming on rice development across South China', Climate Research, vol. 36, no. 1, pp. 79-88.View/Download from: Publisher's site
Rice Oryza sativa L. development-and also its response to climatic change - is mainly determined by temperature and photoperiod. An experiment was conducted to study the influence of meteorological factors on growth and development of hybrid rice in Sout
Qin, Z, Ouyang, Y, Su, G, Yu, Q, Li, J, Zhang, J & Wu, Z 2008, 'Characterization of CO(2) and water vapor fluxes in a summer maize field with wavelet analysis', Ecological Modelling, vol. 3, no. 6, pp. 397-409.View/Download from: Publisher's site
Knowledge of water vapor and carbon dioxide (CO2) fluxes in agricultural lands is crucial to estimate carbon and water cycles as well as to investigate global warming potentials. In this study, the continuous wavelet transform technique along with cross-wavelet and wavelet coherence methods was applied to characterize half-hourly CO2 flux (Fc) and water vapor (LE) flux data obtained with the eddy covariance technique in a summer maize field located in the North China Plain. Our motivation was to highlight the multiple time scale properties and to exam the possible connections between the flux exchanges and the concurrent micro- meteorological variations. Results show that both Fc and LE could be characterized by the wavelet coefficients for the time scale ranged from 60110 days. Peaks of CO2 exchange were corresponded to the in-phase trough points of water vapor flux exchange rates on the 110 day, 64 day and 32 day time scales. Intra-seasonal oscillations in both water and CO2 flux exchanges were associated with the patterns of photosynthetically active radiation, air temperature, vapor pressure deficient, and precipitation. Our study also showed that wavelet transforms had prospect in making a physical explanation of the temporal structure of the flux exchanges between the crop biosphere and atmosphere in response to ambient variables. This study suggests that cross-wavelet analysis and wavelet coherence could be powerful methods for probing the dynamical relationship between the flux exchange and the dominant modes of climate variability.
Wang, E, Cresswell, H, Yu, Q & Verburg, K 2008, 'Summer forage cropping as an effective way to control deep drainage in south-eastern Australia - A simulation study', Agriculture Ecosystems & Environment, vol. 125, no. 1-4, pp. 127-136.View/Download from: Publisher's site
Excessive drainage of water beyond the root zone of agricultural plants is complicit in causing extensive dryland salinity in southern Australia. Opportunistically sowing summer forage crops within winter cereal rotations could be a flexible means of red
Wang, E, Yu, Q, Wu, D & Xia, J 2008, 'Climate, agricultural production and hydrological balance in the North China Plain', International Journal of Climatology, vol. 28, no. 14, pp. 1959-1970.View/Download from: Publisher's site
The North China Plain (NCP) is the largest agricultural production area in China. The extensive use of groundwater for irrigation agriculture under variable climatic conditions has resulted in the rapid decline of the groundwater table especially in area
Wang, J, Yu, Q, Pan, XB, Yin, H & Zhang, YQ 2008, 'A review on water, heat and CO2 fluxes simulation models', Shengtai Xuebao/ Acta Ecologica Sinica, vol. 28, no. 6, pp. 2843-2853.
Accurate modeling of water, heat and carbon dioxide fluxes is of importance in understanding the energy and mass exchange processes between land surface and atmosphere. This paper focuses on the advance in processes-based water, heat and CO2 fluxes simulation model and reviews the development of statistic, integrated and remote sensing-based models for estimating water, heat and carbon dioxide fluxes in the soil-plant-atmosphere continuum. The reviewed statistic models included models that estimate water and heat fluxes based on temperature, humidity and radiation, and models that simulate carbon dioxide flux based on climatic factors, evapotranspiration and light use efficiency. Reviewed processes-based models covered the big-leaf model, two-source model, multi-source model and multi-layer models for water and heat transfer as well as leaf-level to canopy level models for carbon dioxide flux. Integrated models included biophysical, biochemical and biogeographic models. The statistic models are applied widely in directing the simulation of water, heat and CO2 fluxes at large-scale level because of simple form and because the required data are obtained easily. While the process-based models describe the physical and physiological processes of water, heat and CO2 flux transfer accurately and have been the foundation of large-scale integrated models. The future development of flux models is to integrate various method and technology for multi-scale network measuring and large-scale mechanism modeling.
Wu, D, Yu, Q, Wang, E & Hengsdijk, H 2008, 'Impact of spatial-temporal variations of climatic variables on summer maize yield in North China Plain', International Journal Of Plant Production, vol. 2, no. 1, pp. 71-88.
Summer maize (Zea mays L.) is one of the dominant crops in the North China Plain (NCP). Its growth is greatly influenced by the spatial-temporal variation of climatic variables, especially solar radiation, temperature and rainfall. The WOFOST (version 7.
The model couples stomatal conductance (g s) and net photosynthetic rate (P N) describing not only part of the curve up to and including saturation irradiance (I max), but also the range above the saturation irradiance. Maximum stomatal conductance (g smax) and I max can be calculated by the coupled model. For winter wheat (Triticum aestivum) the fitted results showed that maximum P N (P max) at 600 µmol mol-1 was more than at 350 µmol mol-1 under the same leaf temperature, which can not be explained by the stomatal closure at high CO2 concentration because g smax at 600 µmol mol-1 was less than at 350 µmol mol-1. The irradiance-response curves for winter wheat had similar tendency, e.g. at 25 °C and 350 µmol mol-1 both P N and g s almost synchronously reached the maximum values at about 1 600 µmol m-2 s-1. At 25 °C and 600 µmol mol-1 the I max corresponding to P max and g smax was 2 080 and 1 575 µmol m-2 s-1, respectively.
Yu, Q, Wang, E & Smith, CJ 2008, 'A modelling investigation into the economic and environmental values of "perfect" climate forecasts for wheat production under contrasting rainfall condition', International Journal of Climatology, vol. 28, no. 2, pp. 255-266.View/Download from: Publisher's site
With increased investment in improving climate forecasting techniques, it is essential to find ways of quantifying the maximum benefit of climate forecasts for a given industry. This paper describes an approach to quantify the value of perfect climate forecasts to direct nitrogen management in a wheat-cropping system at two Australian locations with contrasting annual rainfall. For annual wheat-cropping systems, and compared with the N management based on optimal N rate derived from long-term climatic conditions, N management based on perfect climate forecasts can lead to an average benefit of $ 65.2/ha/year at Walbundrie (annual rainfall 560.0 mm) and $ 66.5/ha/year at Wanbi (annual rainfall 314.5 mm). Generally, the economic benefit is highest in extreme (wet and dry) years and lowest in normal years. At the high rainfall site Walbundrie, where average N-application rate is high, the maximum yearly benefit was from significant saving through reduction in N application in driest years. At the low rainfall site Wanbi, where average N rates are low, the highest benefit was from both yield increases in the wettest years and saving of management and fertilizer cost in the driest years. Such optimized nitrogen management has little impact on excess drainage, but it can have significant impact on reduction of excess nitrogen, especially in high rainfall areas. An excess N reduction of 1314 kg N/ha at Wanbi and 1538 kg N/ha at Walbundrie can be achieved in 114 years. The significant reduction in N excess at Walbundrie may have profound environmental implications.
Zhang, Y, Yu, Q, Jiang, J & Tang, Y 2008, 'Calibration of Terra/MODIS gross primary production over an irrigated cropland on the North China Plain and an alpine meadow on the Tibetan Plateau', Global Change Biology, vol. 14, no. 4, pp. 757-767.View/Download from: Publisher's site
This paper evaluated the MODerate resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) product (MOD17) by using estimated GPP from eddy-covariance flux measurements over an irrigated winter wheat and maize double-cropping field on
Fang, Q, Chen, Y, Yu, Q, Zhu, Q, Li, Q & Yu, S 2007, 'Much improved irrigation use efficiency in an intensive wheat-maize double cropping system in the North China Plain', Journal of integrative plant biology, vol. 49, no. 10, pp. 1517-1526.View/Download from: Publisher's site
Crop yield and water use efficiency (WUE) in a wheat-maize double cropping system are influenced by short and uneven rainfalls in the North China Plain (NCP). A 2-year experiment was conducted to investigate the effects of irrigation on soil water balance, crop yield and WUE to improve irrigation use efficiency in the cropping system. Soil water depletion (SWS) by crop generally decreased with the increase of irrigation and rainfall, while SWS for the whole rotation was relatively stable among these irrigation treatments. High irrigations in wheat season increased initial soil moisture and SWS for subsequent maize especially in the drought season. Initial soil water influenced mainly by the irrigation and rainfall in the previous crop season, is essential to high yield in such cropping systems. Grain yield decreased prior to evapotranspiration (ET) when ET reached about 300mm for wheat, while maize showed various WUEs with similar seasonal ET. For whole rotation, WUE declined when ET exceeded about 650mm. These results indicate great potential for improving irrigation use efficiency in such wheat-maize cropping system in the NCP. Based on the present results, reasonable irrigation schedules according to different annual rainfall conditions are presented for such a cropping system.
Flerchinger, GN & Yu, Q 2007, 'Simplified expressions for radiation scattering in canopies with ellipsoidal leaf angle distributions', Agricultural and Forest Meteorology, vol. 144, no. 3-4, pp. 230-235.View/Download from: Publisher's site
The ability to simulate the surface energy balance and microclimate within a plant canopy is contingent upon accurate simulation of radiation exchange within the canopy. Accurate radiation simulations require some assumption of leaf angle distribution to compute transmissivity, reflection and scattering of radiation. The ellipsoidal leaf angle density function can very closely approximate real plant canopies but requires complex integrations for different combinations of leaf area index, incident radiation angle, and density function. This paper presents close approximations (R2 > 0.99) to compute the transmissivity and scattering functions for elliptical leaf angle distributions that can be more easily implemented into simulation models.
Li, L & Yu, Q 2007, 'Quantifying the effects of advection on canopy energy budgets and water use efficiency in an irrigated wheat field in the North China Plain', Agricultural Water Management, vol. 89, no. 1-2, pp. 116-122.View/Download from: Publisher's site
Competing demands for water with increasing population calls for developing strategies for increasing the crop water use efficiency (WUE) of irrigated crops, especially in the semiarid regions of the world. In this context, it is important to quantify the various factors that control the WUE of irrigated crops in these regions. Advection is an important factor that can have significant effects on the energy exchange in irrigated fields of arid regions, and hence control the crop canopy WUE (CWUE). An eddy covariance system was applied to measure water and heat fluxes and then to quantify advection in an irrigated winter wheat filed at the Yucheng Integrated Experiment Station, Chinese Academy of Sciences in the North China Plain (NCP) (36°57?N, 116°36?E, 28 m a.s.l.) in 2004. PriestleyTaylor parameter and canopyair temperature differences were employed to identify the occurrence of advection. Effects of advection on canopy energy budgets and CWUE were examined by computing the equilibrium and advective evapotranspiration. It was found that enhanced advection occurs when the crop canopyair temperature differences are negative or when the PriestleyTaylor parameter takes on values >1.5. Due to enhanced advection, the percentage of latent and sensible heat flux exchange contribution to the total water loss from the fields through evapotranspiration can exceed 50%, and CWUE decreased remarkably. Advection in the experiments probably resulted from drier soil regimes in the upwind areas.
The Qinghai-Tibet Railway (QTR) was built during China's Tenth 5-Year Plan (2001-05) and, in China, is considered a landmark project (1). The QTR, completed in October 2005 and in trial operation since 1 July 2006, is the world's highest-elevation railway and the longest highland railway, extending over 1956 km from Xining (Qinghai's capital in northwestern China) to Lhasa, the capital city of the Tibet Autonomous Region (see figure, right). The Chinese government has invested an unprecedented amount of money to protect the area's ecology. A total of 26.2 billion yuan (U.S. $3.39 billion) was budgeted, and 1.54 billion yuan was allocated to ecosystem restoration and environmental protection.
Wang, J, Yu, Q & Lee, X 2007, 'Simulation of crop growth and energy and carbon dioxide fluxes at different time steps from hourly to daily', Hydrological Processes, vol. 21, no. 18, pp. 2474-2492.View/Download from: Publisher's site
Understanding the exchange processes of energy and carbon dioxide (CO2) in the soil-vegetation-atmosphere system is important for assessing the role of the terrestrial ecosystem in the global water and carbon cycle and in climate change. We present a soil-vegetation-atmosphere integrated model (ChinaAgrosys) for simulating energy, water and CO2 fluxes, crop growth and development, with ample supply of nutrients and in the absence of pests, diseases and weed damage. Furthermore, we test the hypotheses of whether there is any significant difference between simulations over different time steps. CO2, water and heat fluxes were estimated by the improving parameterization method of the coupled photosynthesis-stomatal conductance-transpiration model. Soil water evaporation and plant transpiration were calculated using a multilayer water and heat-transfer model. Field experiments were conducted in the Yucheng Integrated Agricultural Experimental Station on the North China Plain. Daily weather and crop growth variables were observed during 1998-2001, and hourly weather variables and water and heat fluxes were measured using the eddy covariance method during 2002-2003. The results showed that the model could effectively simulate diurnal and seasonal changes of net radiation, sensible and latent heat flux, soil heat flux and CO2 fluxes. The processes of evapotranspiration, soil temperature and leaf area index agree well with the measured values. Midday depression of canopy photosynthesis could be simulated by assessing the diurnal change in canopy water potential. Moreover, the comparisons of simulated daily evapotranspiration and net ecosystem exchange (NEE) under different time steps indicated that time steps used by a model affect the simulated results.
Wang, L, Zheng, YF, Yu, Q & Wang, EL 2007, 'Applicability of Agricultural Production Systems Simulator (APSIM) in simulating the production and water use of wheat-maize continuous cropping system in North China Plain', Chinese Journal of Applied Ecology, vol. 18, no. 11, pp. 2480-2486.
The Agricultural Production Systems Simulator ( APSIM ) was applied to simulate the 1999-2001 field experimental data and the 2002-2003 water use data at the Yucheng Experiment Station under Chinese Ecosystem Research Network, aimed to verify the applicability of the model to the wheat-summer maize continuous cropping system in North China Plain. The results showed that the average errors of the simulations of leaf area index (LAI), biomass, and soil moisture content in 1999-2000 and 2000-2001 field experiments were 27.61%, 24.59% and 7.68%, and 32.65%, 35.95% and 10.26%, respectively, and those of LAI and biomass on the soils with high and low moisture content in 2002-2003 were 26.65 % and 14.52 %, and 23.91 % and 27.93%, respectively. The simulations of LAI and biomass accorded well with the measured values, with the coefficients of determination being > 0. 85 in 1999-2000 and 2002-2003, and 0. 78 in 2000-2001, indicating that APSIM had a good applicability in modeling the crop biomass and soil moisture content in the continuous cropping system, but the simulation error of LAI was a little larger.
Xiaojuan, T, Jun, L, Xinshi, Z, Yu, Q & Zhilin, Z 2007, 'Mechanism and bio-environmental controls of ecosystem respiration in a cropland in the North China Plains', New Zealand Journal of Agricultural Research, vol. 50, no. 5, pp. 1347-1358.
CO2 flux was measured continuously using the eddy covariance technique in a wheat-maize rotation system in the North China Plains from October 2002 to October 2006. The annual and seasonal variation of ecosystem respiration and the bio-environmental controls on them were investigated. The results show that ecosystem respiration (Rec) in the cropland increased exponentially with soil temperature at 5 cm depth. The temperature sensitivity coefficient (Q10) for ecosystem respiration varied from 3.5 to 5.4 for wheat and from 2.4 to 4.5 for maize. In the wheat growing season, monthly average R0 (ecosystem respiration at 0°C) increased linearly with soil temperature and logarithmically with leaf area index (LAI). Monthly average Q10 decreased logarithmically with R0. Residual Rec was significantly correlated with LAI. After considering LAI, the modified Q10 model could estimate Rec better than before. The simulation results show that annual ecosystem respiration in the wheat-maize rotation system in the North China Plains was 1327, 1348, 1040 and 1171 gC m-2 yr-1 for the 4 years of the study. As a 4-year average, seasonal mean ecosystem respiration in wheat (2.60 gC m-2 day-') was much lower than in maize (6.09 gC m-2 day-'). However, integrated ecosystem respiration for the wheat growing season (566 gC m -2) was slightly higher than that for maize (520 gC m-2). These account for 46.4 and 42.6% of the annual values, respectively.
Yu, Q, Flerchinger, GN, Xu, S, Kozak, J, Ma, L & Ahuja, LR 2007, 'Energy balance simulation of a wheat canopy using the RZ-SHAW (RZWQM-SHAW) model', American Society of Agricultural and Biological Eng..., vol. 50, no. 5, pp. 1507-1516.
RZ-SHAW is a new hybrid model coupling the Root Zone Water Quality Model (RZWQM) and the Simultaneous Heat and Water (SHAM model to extend RZWQM applications to conditions of frozen soil and crop residue cover RZ-SHAW offers the comprehensive land management options of RZWQM with the additional capability to simulate diurnal changes in energy balance needed for simulating the near-surface microclimate and leaf temperature. The objective of this study was to evaluate RZ-SHAW for simulations of radiation balance and sensible and latent heat fluxes overplant canopies. Canopy energy balance data were collected at various growing stages of winter wheat in the North China Plain (36 degrees 57'N, 116 degrees 6'E, 28 m above sea level). RZ-SHAW and SHAW simulations using hourly meteorological data were compared with measured net radiation, latent heat flux, sensible heat flux and soil heat flux. RZ-SHAW provided similar goodness-of-prediction statistics as the original SHAW model for all the energy balance components when using observed plant growth input data. The root mean square error (RMSE) for simulated net radiation, latent heat, sensible heat, and soil heat fluxes was 29.7, 30.7, 29.9, and 25.9 W m(-2) for SHAW and 30.6, 32.9, 34.2, and 30.6 W m-2 for RZ-SHAW, respectively. Nash-Sutcliffe R-2 ranged from 0.67 for sensible heat flux to 0.98 for net radiation. Subsequently, an analysis was performed using the plant growth component of RZ-SHAW instead of inputting LAI and plant height. The model simulation results agreed with measured plant height, yield, and LAI very well. As a result, RMSE for the energy balance components were very similar to the original RZ-SHAW simulation, and latent, sensible, and soil heat fluxes were actually simulated slightly better RMSE for simulated net radiation, latent heat, sensible heat, and soil heat fluxes was 31.5, 30.4, 30.2, and 2 7.6 W m(-2). respectively.
Yu, Q, Xu, S, Wang, J & Lee, X 2007, 'Influence of leaf water potential on diurnal changes in CO2 and water vapour fluxes', Boundary-Layer Meteorology, vol. 124, no. 2, pp. 161-181.View/Download from: Publisher's site
Mass and energy fluxes between the atmosphere and vegetation are driven by meteorological variables, and controlled by plant water status, which may change more markedly diurnally than soil water. We tested the hypothesis that integration of dynamic changes in leaf water potential may improve the simulation of CO2 and water fluxes over a wheat canopy. Simulation of leaf water potential was integrated into a comprehensive model (the ChinaAgrosys) of heat, water and CO2 fluxes and crop growth. Photosynthesis from individual leaves was integrated to the canopy by taking into consideration the attenuation of radiation when penetrating the canopy. Transpiration was calculated with the Shuttleworth-Wallace model in which canopy resistance was taken as a link between energy balance and physiological regulation. A revised version of the Ball-Woodrow-Berry stomatal model was applied to produce a new canopy resistance model, which was validated against measured CO2 and water vapour fluxes over winter wheat fields in Yucheng (36°57? N, 116°36? E, 28 m above sea level) in the North China Plain during 1997, 2001 and 2004. Leaf water potential played an important role in causing stomatal conductance to fall at midday, which caused diurnal changes in photosynthesis and transpiration. Changes in soil water potential were less important. Inclusion of the dynamics of leaf water potential can improve the precision of the simulation of CO2 and water vapour fluxes, especially in the afternoon under water stress conditions.
Yue, TX, Wang, W, Yu, Q, Zhu, ZL, Zhang, SH, Zhang, RH & Du, ZP 2007, 'Simulation of vertical wind profile under neutral conditions', International journal of remote sensing, vol. 28, no. 10, pp. 2207-2219.View/Download from: Publisher's site
After analysing formulations of the horizontal wind velocity above a nonuniform underlying surface, it is found that the mean height of roughness elements, fractional vegetation cover and leaf area index are the most essential parameters of vertical wind profile under neutral conditions. By using Landsat-5 data, every-10-days observed data in the field, the every-10-days Normalized Difference Vegetation Index (NDVI) data from NOAA-14 meteorological satellite, 1 : 10000 land-use data, and 1 : 10000 topographical data, the mean height, leaf area index and fractional vegetation cover of wheat at Yucheng Integrated Agricultural Experiment Station are simulated as functions of NDVI. Then, hourly horizontal wind velocity at a height of 4m during the period from 21:05 on 5 March 2000 to 7:05 on 24 May 2000 is calculated, for which hourly observed horizontal wind velocity at a height of 2m is first used to simulate the wheat parameter of the dimensionless constant. The results show that the simulated velocity is almost identical to the observation velocity at a height of 4 m.
Fang, Q, Yu, Q, Wang, E, Chen, Y, Zhang, G, Wang, J & Li, L 2006, 'Soil nitrate accumulation, leaching and crop nitrogen use as influenced by fertilization and irrigation in an intensive wheat-maize double cropping system in the North China Plain', Plant and Soil, vol. 284, no. 1-2, pp. 335-350.View/Download from: Publisher's site
There is a growing concern about excessive nitrogen (N) and water use in agricultural systems in North China due to the reduced resource use efficiency and increased groundwater pollution. A two-year experiment with two soil moisture by four N treatments was conducted to investigate the effects of N application rates and soil moisture on soil N dynamics, crop yield, N uptake and use efficiency in an intensive wheatmaize double cropping system (wheatmaize rotation) in the North China Plain. Under the experimental conditions, crop yield of both wheat and maize did?not?increase significantly at N rates above 200 kg N ha-1. Nitrogen application rates affected little on ammonium-N (NH4-N) content in the 0100 cm soil profiles. Excess nitrate-N (NO3-N), ranging from 221 kg N ha-1 to 620 kg N ha-1, accumulated in the 0100 cm soil profile at the end of second rotation in the treatments with N rates of 200 kg N ha-1 and 300 kg N ha-1. In general, maize crop has higher N use efficiency than wheat crop. Higher NO3-N leaching occurred in maize season than in wheat season due to more water leakage caused by the concentrated summer rainfall. The results of this study indicate that the optimum N rate may be much lower than that used in many areas in the North China Plain given the high level of N already in the soil, and there is great potential for reducing N inputs to increase N use efficiency and to mitigate N leaching into the groundwater. Avoiding excess water leakage through controlled irrigation and matching N application to crop N demand is the key to reduce NO3-N leaching and maintain crop yield. Such management requires knowledge of crop water and N demand and soil N dynamics as they change with variable climate temporally and spatially. Simulation modeling can capture those interactions and is considered as a powerful tool to assist in?the?future optimization of N and irrigation managements.
Jiang, Z, Yu, Q, Lei, S, Wang, T, Sun, X & Zhang, R 2006, 'Comparative analysis of temperature and CO2 fluxes for winter wheat in Tibetan Plain and North China Plain using the EMD method', Progress in Natural Science, vol. 16, no. 10, pp. 1066-1071.View/Download from: Publisher's site
Comparative study of spectral properties of temperature and CO2 fluxes measured by eddy covariance method at Yucheng (36 degrees 57'N, 116 degrees 36'E, 28 m a. s. l., in the North China Plain) and at Lhasa (29 degrees 41'N, 91 degrees 20'E, 3688 m a. s. l., on the Tibetan Plateau) is described using the empirical mode decomposition (EMD) method. The main results are: (1) The intrinsic oscillation modes or intrinsic mode functions (IMFs) were extracted from data of temperature (T) and CO2 fluxes (F) measured at Yucheng (T-1 and F-1) and Lhasa (T-2 and F-2). (2) Hilbert transform was applied to these IMF components, then the Hilbert-Huang spectra and the marginal spectra of these data were obtained. (3) Comparison of temperature and CO2 fluxes in North China Plain and on Tibetan Plain illustrated that the characteristic frequencies corresponding to T-1, F-1, T-2 and F-2 are 0.05 Hz, 0.03 Hz, 0.014 Hz and 0.005 Hz, respectively.
Jiang, Z, Yu, Q, Wang, T, Sun, X & Zhang, R 2006, 'Continuous wavelet transform and discrete multi-resolution analysis of surface fluxes and atmospheric stability', Progress in Natural Science, vol. 16, no. 4, pp. 403-409.View/Download from: Publisher's site
Jun, L, Yu, Q, Sun, X, Xiaojuan, T, Ren, C, Wang, J, Liu, E, Zhu, Z & Yu, G 2006, 'Carbon dioxide exhange and the mechanism of environmental control in a farmland ecosystem in North China Plain', Science in China Series D Earth Science, vol. 49, no. 2, pp. 226-240.
CO2 flux was measured continuously in a wheat and maize rotation system of North China Plain using the eddy covariance technique to study the characteristic of CO2 exchange and its response to key environmental factors. The results show that nighttime net ecosystem exchange (NEE) varied exponentially with soil temperature. The temperature sensitivities of the ecosystem (Q(10)) were 2.94 and 2.49 in years 2002-2003 and 2003-2004, respectively. The response of gross primary productivity (GPP) to photosynthetically active radiation (PAR) in the crop field can be expressed by a rectangular hyperbolic function. Average A(max) and a for maize were more than those for wheat. The values of a increased positively with leaf area index (LAI) of wheat. Diurnal variations of NEE were significant from March to May and from July to September, but not remarkable in other months. NEE, GPP and ecosystem respiration (Rep) showed significantly seasonal variations in the crop field. The highest mean daily CO2 uptake rate was -10.20 and -12.50 gC (.) m(-2 .) d(-1) in 2003 and 2004, for the maize field, respectively, and -8.19 and -9.50 gC (.) m(-2) (.) d(-1) in 2003 and 2004 for the wheat field, respectively. The maximal CO2 uptake appeared in April or May for wheat and mid-August for maize. During the main growing seasons of winter wheat and summer maize, NEE was controlled by GPP which was chiefly influenced by PAR and LAI. Rep reached its annual maximum in July when Rep and GPP contributed to NEE equally. NEE was dominated by Rep in other months and temperature became a key factor controlling NEE. Total NEE for the wheat field was -77.6 and -152.2 gC (.) m(-2 .) a(-1) in years 2002-2003 and 2003-2004, respectively, and -120.1 and -165.6 gC (.) m(-2) (.) a(-1) in 2003 and 2004 for the maize field, respectively.
Li, L, Yu, Q, Zheng, Y, Wang, J & Fang, Q 2006, 'Simulating the response of photosynthate partitioning during vegetative growth in winter wheat to environmental factors', Field Crops Research, vol. 96, no. 1, pp. 133-141.View/Download from: Publisher's site
Currently available models of photosynthate partitioning in crops are poorly developed compared to carbon and water balance models. This paper presents a dynamic photosynthate partitioning model (PPModel) that simulates the partitioning of crop biomass to leaf, stem and root through the interaction between carbon gain (assimilation less respiration) and transpiration, in relation to environmental factors. The central concept is the theory of plant functional equilibrium, in which transpirational loss and water uptake are balanced, within acceptable limits, by a dynamic partitioning of assimilates between shoot and root growth. The model was shown to perform effectively against experimental data for growth and partitioning of biomass in winter wheat (collected over a 2-year period), when environmental factors varied daily and water supply was controlled over a wide range
Lu, P, Yu, Q, Liu, J & He, Q 2006, 'Effects of changes in spring temperature on flowering dates of woody plants across China', Botanical Studies, vol. 47, no. 2, pp. 153-161.
In China, changes in the timing of plant phenological phases are influenced greatly by monsoonal climate fluctuations, and also vary with species and region. Observations of phenological phases of trees were conducted in the Phenological Observation Network of China from 1963 to 1988. Records of flowering dates of four species (Syringa oblata Lindl., Cercis chinensis Bunge, Robinia pseudoacacia L., Albizzia julibrissin Durazz) at ten sites, together with corresponding climate data, were used to investigate phenophase responses to variation in temperature. The ten sites extend over a wide area, with latitudes ranging from 25ºN to 46°N, and altitudes ranging from 17 to 1,922 m a.s.l. Spring temperature was significantly related to flowering date of the trees under the monsoonal climate in the eastern Eurasian Continent. The period during which temperature influences flowering time varies from 60 to 90 days for Robinia pseudoacacia in the south to 30 to 40 days in the north, due to the shorter warm period before flowering in the north. The three other species showed similar trends of changes with latitude in the length of the period of temperature influence. The flowering season for Cercis chinensis in response to a temperature increase 30-60 days prior to flowering advanced from 2.7 to 5.9 days/°C in the low plain, and in response to a temperature increase 60-90 days prior to flowering, advanced from 7.1 to 14.8 days/°C in the Yunnan-Guizhou Plateau. The flowering for Syringa oblata, Robinia pseudoacacia and Albizzia julibrissin, in response to a temperature increase advanced in the range 2.7-4.9, 2.5-6.5, and 2.4-6.0 days/°C in the low plain, respectively. Flowering advanced by 4.7-12.4 days/°C for Robinia pseudoacacia and 13.1 days/°C for Albizzia julibrissin in the plateau.
Lu, P, Yu, Q, Liu, J & Lee, X 2006, 'Advance of tree-flowering dates in response to urban climate change', Agricultural and Forest Meteorology, vol. 138, no. 1-4, pp. 120-131.View/Download from: Publisher's site
An increase in temperature due to greenhouse effects is manifest in the changes in diurnal, annual and inter-annual patterns, which may alter phenological events in plants. Flowering dates of four tree species, Prunus davidina, Prunus armeniaca, Robinia pseudoacacia and Syringa oblata, were significantly advanced in response to temperature increase over the years 19502004 in Beijing, China, due to the impact of urban climate warming. Because both climate warming and the urban heat island effect in winter and early-spring were more rapid than in late-spring and early summer, the dates in early flowering species advanced more quickly than in late flowering species. The early flowering species, P. davidina, advanced by 2.9 days/decade, while the other species advanced by 1.52.0 days/decade during 19502004. Therefore, the intervals between flowering dates of different species were expanded. P. davidina, flowering in early-spring, was much more sensitive to minimum and average temperatures (2.882.96 days/°C), but less sensitive to maximum temperature (2.46 days/°C). R. pseudoacacia, flowering late in the warmer season, was more sensitive to average and maximum temperatures (2.452.89 days/°C), but less sensitive to minimum temperature (1.91 days/°C). Statistical analysis showed that, in Beijing, plant flowering is most sensitive to average temperature over 30 days before average blossom date. On the basis of the temperature response curve, the goodness of fitting demonstrates that spring flowering dates can be predicted from the period when temperature is over 0 °C.
Lu, PL, Yu, Q & He, QT 2006, 'Responses of plant phenology to climatic change', Acta Ecologica Sinica, vol. 26, no. 3, pp. 923-929.
Changes in plant phenology directly manifests the change of climate, especially climate warming. The changes in rhythm of plant growth may alter plant-environment relationships, hence the mass cycles, such as water and carbon, in the ecosystem. Individual plant species respond to climatic changes differently, which may cause great changes in competition and dependence among different species and plant-animal interactions. In the past few years, many reports showed that the plant phonology toward early in spring and late in autumn in Europe, America, and Asia. The changes in plant phenology result in a lengthening growing season, and indicate a warming climate. Phenological model is an important component of ecosystem productivity models, which may play a key role in analysis of vegetation-atmosphere interactions.
Wang, J, Yu, Q, Li, J, Li, L, Li, X, Yu, G & Sun, X 2006, 'Simulation of diurnal variations of CO2, water and heat fluxes over winter wheat with a model coupled photosynthesis and transpiration', Agricultural and Forest Meteorology, vol. 137, no. 3-4, pp. 194-219.View/Download from: Publisher's site
A model was developed that couples canopy photosynthesis and transpiration of winter wheat. The model combined a two-layer evapotranspiration model with a coupled photosynthesisstomatal conductance model to study the diurnal variations of CO2, water and heat fluxes of winter wheat. Field experiments were conducted in Yucheng Comprehensive Experimental Station in the North China Plain to evaluate the model. Half-hourly data of weather variables and CO2, water and heat fluxes were measured by the eddy covariance method in 20022003. An analysis of measured flux data showed that there was an evident midday depression of photosynthesis, caused by stomatal closure due to high vapor water deficit and canopy temperature though the soil was well irrigated. There was a close agreement between simulated and measured net radiation, CO2 flux, sensible and latent heat fluxes, which proved the predictive power of the coupled photosynthesis and transpiration model. The response of CO2 flux, canopy conductance and latent heat flux to changes in climatic factors was discussed, which indicated the model could be used to predict CO2, water and heat fluxes of wheat not only in the North China Plain, but also in other climatic regions in China.
Wu, D, Yu, Q, Lu, C & Hengsdijk, H 2006, 'Quantifying production potentials of winter wheat in the North China Plain', European Journal Of Agronomy, vol. 24, no. 3, pp. 226-235.View/Download from: Publisher's site
The North China Plain (NCP) is one of the major winter wheat (Triticum aestivum L.) producing areas in China. Current wheat yields in the NCP stabilize around 5 Mg ha-1 while the demand for wheat in China is growing due to the increase in population and the change in diet. Since options for area expansion of winter wheat are limited, the production per unit of area need to be increased. The objective of this study is to quantify the production potential of winter wheat in the NCP taking into account the spatial and temporal variability caused by climate. We use a calibrated crop growth simulation model to quantify wheat yields for potential and water-limited production situations using 40 years of weather data from 32 meteorological stations in the NCP. Simulation results are linked to a Geographic Information System (GIS) facilitating their presentation and contributing to the identification of hotspots for interventions aimed at yield improvements. In the northern part of the NCP, average simulated potential yields of winter wheat go up to 9.7 Mg ha-1, while average water-limited yields only reach 3 Mg ha-1. In the southern part of the NCP, both average potential and water-limited yields are about 7.5 Mg ha-1. Rainfall is the limiting factor to winter wheat yields in the northern part of the NCP, while in the southern part, the joint effect of low radiation and high temperature are major limiting factors. Temporal variation in potential yields throughout the NCP is low in contrast with the temporal variation in water-limited yields, which is especially great in the northern part. The study calls for the collection of location-specific and disaggregated irrigated and rainfed wheat yield statistics in the NCP facilitating the identification of hotspots for improvement of current wheat yields
Xiao, W, Flerchinger, GN, Yu, Q & Zheng, Y 2006, 'Evaluation of the SHAW model in simulating the components of net all-wave radiation', American Society of Agricultural and Biological Engineers, vol. 49, no. 5, pp. 1351-1360.
Radiation exchange at the surface plays a critical role in the surface energy balance, plant microclimate, and plant growth. The ability to simulate the surface energy balance and the microclimate within the plant canopy is contingent upon accurate simulation of the surface radiation exchange. A validation exercise was conducted of the Simultaneous Heat and Water (SHAW) model for simulating the surface radiation exchange (including downward long-wave and upward short- and long-wave radiation) over a maize canopy surface using data collected at Yucheng in the North China Plain. The model simulated upward short-wave and net all-wave radiation well with model efficiencies (ME) equaling 0.97 and 0.98, respectively. Downward and upward long-wave radiation were overestimated by 12.1 and 8.3 W m-2 with ME equaling 0.68 and 0.89, respectively. Two modifications to the model were implemented and tested to improve the simulated long-wave radiation exchange. In one modification, alternative schemes were tested to simulate cloudy sky long-wave radiation, and the best algorithm was employed in the model.
Xiao, W, Yu, Q, Flerchinger, GN & Zheng, Y 2006, 'Evaluation of SHAW model in simulating energy balance, leaf temperature, and micrometeorological variables within a Maize canopy', Agronomy Journal, vol. 98, no. 3, pp. 722-729.View/Download from: Publisher's site
Received for publication May 2, 2005. Understanding and simulating plant canopy conditions can assist in better acknowledgment of plant microclimate characteristics, its effect on plant processes, and the influence of management and climate scenarios. The ability of the Simultaneous Heat and Water (SHAW) model to simulate the surface energy balance and profiles of leaf temperature and micrometeorological variables within a maize canopy and the underlying soil temperatures was tested using data collected during 1999 and 2003 at Yucheng, in the North China Plain. The SHAW model simulates the near-surface heat and water movement driven by input meteorological variables and observed plant characteristic (leaf area index [LAI], height, and rooting depth). For 1999, the model accurately simulated air temperature and relative humidity in the upper one-third of the canopy, but overpredicted midday temperature in the lower canopy. For 2003, although the surface energy balance was simulated quite well, radiometric canopy surface temperature and midday leaf temperature in the upper portion of the canopy were overpredicted, by approximately 5°C. Model efficiency (the fraction of variation in observed values explained by the model) for leaf temperature in the lower two-thirds of the canopy ranged from 0.82 to 0.90, but fell to 0.38 for the uppermost canopy layer. Weaknesses in the model were identified and potentially include: the use of K-theory to simulate turbulent transfer within the canopy; and simplifying assumptions with regard to long-wave radiation transfer within the canopy. Model modifications are planned to address these weaknesses.
Yu, Q, Saseendran, SA, Ma, L, Flerchinger, GN, Green, TR & Ahuja, LR 2006, 'Modeling a wheat-maize double cropping system in China using two plant growth modules in RZWQM', Agricultural Systems, vol. 89, pp. 457-477.View/Download from: Publisher's site
Agricultural system models are potential tools for evaluating soil-waternutrient management in intensive cropping systems. In this study, we calibrated and validated the Root Zone Water Quality Model (RZWQM) with both a generic plant growth module (RZWQM-G) and the CERES plant growth module (RZWQM-C) for simulating winter wheat (Triticum aestivum L.) and maize (Zea mays L.) double cropping systems in the Northern China Plain (NCP), China. Data were obtained from an experiment conducted at Yucheng Integrated Agricultural Experimental Station (36570N, 116360E, 28 m asl) in the North China Plain (NCP) from 1997 to 2001 (eight crop seasons) with field measurements of evapotranspiration, soil water, soil temperature, leaf area index (LAI), biomass and grain yield. Using the same soil water and nutrient modules, both plant modules were calibrated using the data from one crop sequence during 19981999 when detailed measurements of LAI and biomass growth were available. The calibrated models were then used to simulate maize and wheat production in other years. Overall simulation runs from 1997 to 2001 showed that the RZWQM-C model simulated grain yields with a RMSE of 0.94 Mg ha-1 in contrast to a RMSE of 1.23 Mg ha-1 with RZWQM-G. The RMSE for biomass simulation was 2.07 Mg ha-1 with RZWQM-G and 2.26 Mg ha-1 with RZWQM-C model. The RMSE values of simulated evapotranspiration, soil water, soil temperature and LAI were 1.4 mm, 0.046 m3 m-3, 1.75 C and 1.0 for RZWQM-G and 1.4 mm, 0.047 m3 m-3, 1.84 C and 1.1 for RZWQM-C, respectively. The study revealed that both plant models were able to simulate the intensive cropping systems once they were calibrated for the local weather and soil conditions. Sensitivity analysis also showed that a reduction of 25% of current water and N applications reduced N leaching by 2477% with crop yield reduction of 19% only.
Zhang, Y, Liu, C, Lei, Y, Tang, Y, Yu, Q, Shen, Y & Sun, H 2006, 'An integrated algorithm for estimating regional latent heat flux and daily evapotranspiration', International journal of remote sensing, vol. 27, no. 1-2, pp. 129-152.View/Download from: Publisher's site
Using remote-sensing data and ground-based data, we constructed an integrated algorithm for estimating regional surface latent heat flux (LE) and daily evapotranspiration (ETd). In the algorithm, we first used trapezoidal diagrams relating the surface temperature and fractional vegetation cover (fc) to calculate the surface temperaturevegetation cover index, a land surface moisture index with a range from 0.0 to 1.0. We then revised a sine function to assess ETd from LE estimated for the satellites overpass time. The algorithm was applied to farmland in the North China Plain using Landsat Thematic Mapper (TM)/ Enhanced Thematic Mapper Plus (ETM+ ) data and synchronous surfaceobserved data as inputs. The estimated LE and ETd were tested against measured data from a Bowen Ratio Energy Balance (BREB) system and a large-scale weighing lysimeter, respectively. The algorithm estimated LE with a root mean square error (RMSE) of 50.1Wm22 as compared to measurements with the BREB System, and ETd with an RMSE of 0.93mmd21 as compared with the measurement by the lysimeter. Sensitivity analysis showed that changing meteorological variables have some influence on LE, while variation of fc has little effect on LE. The test of the model in the study indicated that the improved algorithm provides an accurate and easy-to-handle approach for assessing regional surface LE and ETd. Further improvement can be achieved in the assessments if we increase the accuracy of some key parameters on a large regional scale, such as the minimum stomatal conductance and the atmospheric vapour pressure deficit.
Zhang, Y, Liu, C, Lei, Y, Tang, Y, Yu, Q, Shen, Y & Sun, H 2006, 'An integrated algorithm for estimating regional latent heat flux and daily evapotranspiration', INTERNATIONAL JOURNAL OF REMOTE SENSING, vol. 27, no. 1, pp. 129-152.View/Download from: Publisher's site
Li, J, Tong, XJ & Yu, Q 2005, 'Methane uptake and oxidation by unsaturated soil', Acta Ecologica Sinica, vol. 25, no. 1, pp. 141-147.
Unsaturated soils are the only known biogenic sinks of CH4. In this paper we summarized the CH4 oxidizing process in unsaturated soil and its influent factors. Methanotrophs can use atmospheric methane as the only source of carbon and energy because of the low critical concentration for methane oxidation. In General, CH4 absorption rate is inversely proportional to soil moisture. The activity of methanotrophs becomes small if the transfer of CH4 and O2 from atmosphere to soils is prevented when soil moisture is over high, or water stress occurs at low soil moisture conditions. The inhibitory effect of NH4+ on CH4 oxidation can be attributed to its competition with CH 4 for O2 by the methane monooxygenases, the transfer of oxidation to nitrification and the toxicity of NO2- produced. The inhibitory effect of NH4+ on CH4 oxidation is proportional to available nitrogen. Chemical fertilizers are stronger than manures, and ammonium are stronger than urea in inhibiting CH 4 oxidation. NO3- has no inhibitory effect on CH4 oxidation. High cation exchange capacity (CEC) can alleviate the inhibitory effect of NH4+ on CH4 oxidation. The high affinity of methanotrophs to atmospheric CH4 and low activation energy for CH4 oxidation leads to a small coefficient of temperature (Q10). When soil temperature is low, the ability of CH4 oxidation by soils is proportional to soil temperature. When soil temperature is higher than the optimal value, the activity of methanotrophs will decrease because it is difficult for methanotrophs to compete with nitrifiers and other microbes for the limited O2 in soil air. Methanotrophs are very insensitive to pH value. Good granular structure of soil favors the activity of CH4-oxidizing bacteria from being disturbed. The peak of CH 4-oxidizing rate in the undisturbed forest soil is usually in sub-topsoil (5-10cm). In farm soil, CH4-oxidizing rate increases obviously under the depth of farming layer (25cm) because tillage destroys the structure of t...
Qin, Z, Su, G, Yu, Q, Hu, B & Li, J 2005, 'Modeling water and carbon fluxes above summer maize field in North China Plain with back-propagation neural networks', Journal of Zhejiang University Science, vol. 6B, no. 5, pp. 418-426.
In this work, datasets of water and carbon fluxes measured with eddy covariance technique above a summer maize field in the North China Plain were simulated with artificial neural networks (ANNs) to explore the fluxes responses to local environmental variables. The results showed that photosynthetically active radiation (PAR), vapor pressure deficit (VPD), air temperature (T) and leaf area index (LAI) were primary factors regulating both water vapor and carbon dioxide fluxes. Three-layer back-propagation neural networks (BP) could be applied to model fluxes exchange between cropland surface and atmosphere without using detailed physiological information or specific parameters of the plant.
Qin, Z, Su, GL, Yu, Q, Hu, BM & Li, J 2005, 'Modeling water and carbon fluxes above summer maize field in North China Plain with back-propagation neural networks', Journal of Zhejiang University: Science, vol. 6 B, no. 5, pp. 418-426.View/Download from: Publisher's site
In this work, datasets of water and carbon fluxes measured with eddy covariance technique above a summer maize field in the North China Plain were simulated with artificial neural networks (ANNs) to explore the fluxes responses to local environmental variables. The results showed that photosynthetically active radiation (PAR), vapor pressure deficit (VPD), air temperature (T) and leaf area index (LAI) were primary factors regulating both water vapor and carbon dioxide fluxes. Three-layer back-propagation neural networks (BP) could be applied to model fluxes exchange between cropland surface and atmosphere without using detailed physiological information or specific parameters of the plant.
Qin, Z, Su, G-L, Yu, Q, Hu, B-M & Li, J 2005, 'Modeling water and carbon fluxes above summer maize field in North China Plain with back-propagation neural networks.', Journal of Zhejiang University. Science. B, vol. 6, no. 5, pp. 418-426.View/Download from: Publisher's site
In this work, datasets of water and carbon fluxes measured with eddy covariance technique above a summer maize field in the North China Plain were simulated with artificial neural networks (ANNs) to explore the fluxes responses to local environmental variables. The results showed that photosynthetically active radiation (PAR), vapor pressure deficit (VPD), air temperature (T) and leaf area index (LAI) were primary factors regulating both water vapor and carbon dioxide fluxes. Three-layer back-propagation neural networks (BP) could be applied to model fluxes exchange between cropland surface and atmosphere without using detailed physiological information or specific parameters of the plant.
Qin, Z, Yu, Q, Li, J, Wu, Z & Hu, B 2005, 'Application of least squares vector machines in modelling water vapor and carbon dioxide fluxes over a cropland', Journal of Zhejiang University Science, vol. 6B, no. 6, pp. 491-495.
Least squares support vector machines (LS-SVMs), a nonlinear kemel based machine was introduced to investigate the prospects of application of this approach in modelling water vapor and carbon dioxide fluxes above a summer maize field using the dataset obtained in the North China Plain with eddy covariance technique. The performances of the LS-SVMs were compared to the corresponding models obtained with radial basis function (RBF) neural networks. The results indicated the trained LS-SVMs with a radial basis function kernel had satisfactory performance in modelling surface fluxes; its excellent approximation and generalization property shed new light on the study on complex processes in ecosystem.
Qin, Z, Yu, Q, Li, J, Wu, Z-Y & Hu, B-M 2005, 'Application of least squares vector machines in modelling water vapor and carbon dioxide fluxes over a cropland.', Journal of Zhejiang University. Science. B, vol. 6, no. 6, pp. 491-495.View/Download from: Publisher's site
Least squares support vector machines (LS-SVMs), a nonlinear kemel based machine was introduced to investigate the prospects of application of this approach in modelling water vapor and carbon dioxide fluxes above a summer maize field using the dataset obtained in the North China Plain with eddy covariance technique. The performances of the LS-SVMs were compared to the corresponding models obtained with radial basis function (RBF) neural networks. The results indicated the trained LS-SVMs with a radial basis function kernel had satisfactory performance in modelling surface fluxes; its excellent approximation and generalization property shed new light on the study on complex processes in ecosystem.
Qin, Z, Yu, Q, Xu, S, Hu, B, Sun, X, Liu, E, Wang, J, Yu, G & Zhu, Z 2005, 'Water, heat fluxes and water use efficiency measurement and modeling above a farmland in the North China Plain', Science in China Series D Earth Science, vol. 48, no. 1, pp. 207-217.
Abstract: Net radiation (Rn), water vapor flux (LE), sensible heat flux (Hs) and soil heat flux (G) were measured above a summer maize field with the eddy-covariance technique, simulation and analysis of water, heat fluxes and crop water use efficiency were made with the RZ-SHAW model at the same time in this study. The results revealed significant diurnal and seasonal variability of water vapor flux for summer maize. Most part of Rn was consumed by the evapotranspiration of the summer maize. The proportion of water vapor flux to net radiation ((LE/Rn) increased with the crop development and peaked around milk-filling stage with a value of 60%, a slightly lower than that obtained by the RZ-SHAW model. Daily evapotranspiration estimated by the model agreed with the results measured with the eddy-covariance technique, indices of agreement (IA) for hourly water vapor fluxes simulated and measured were above 0.75, root mean square errors (RMSE) were no more than 1.0. Diurnal patterns of Hs showed the shape of inverted "U" shifted to the forenoon with a maximum value around 11:30 (Beijing time), while LE exhibited an inverted "V" with a maximum value at around 13:00, about an hour later than Hs. Diurnal change of CO2 showed an asymmetrical "V" curve and its maximal rates occurred at about 11:30. Variations of water use efficiency during the phonological stages of the summer maize showed a rapid increase with the photosynthetic photon flux density (PPFD) after sunrise, a state of equilibrium around 10:00 followed a decrease. Maximum values of water use efficiency were 24.3, and its average value ranged from 7.6 to 10.3 g kg-1.
Xiao, W, Zheng, YF & Yu, Q 2005, 'Evaluation of SHAW model in simulating energy balance, leaf temperature and micrometeorological variables within a maize canopy', Acta Ecologica Sinica, vol. 25, no. 7, pp. 1626-1634.
Yucheng is a typical city in the North China plain, which is one of the most important growing districts of grain. Research on it will benefit to the agriculture of the whole region. Furthermore, energy balance is the basis for simulating heat and water transfer in crop canopy. Temperature reflects the condition of plant objectively. Meteorological factors such as air temperature, humidity and wind speed as well as soil temperature are the ambient conditions that affect the activity of plants. Canopy temperature reflects the overall plant health. Understanding and simulating canopy conditions can assist in better acknowledgement of microclimate characteristics and management solutions. The Simultaneous Heat and Water (SHAW) model was used in this study to simulate the surface energy balance, profiles of leaf temperature and micrometeorological variables of a maize canopy and underlying soil temperatures using data collected in Yucheng. The results indicated that the model well simulated air temperature, relative humidity and wind speed in the upper layers rather than the lower, with model efficiency falling from about 0.95 to very small. Since poor simulation occurred especially for wind speed, modification was made to the model, and the simulation was improved accordingly. Energy balance of canopy surface was simulated throughout the growing season of maize using the modified model as above. The simulated net radiation mimicked with the measured, with model efficiency equaling 0.97. The simulations of latent and sensible heat flux were reasonable with model efficiency 0.81 and 0.78 respectively. But the bias of ground heat flux was obvious, which may due to the lack of measured energy balance closure. In addition, the simulation discovered that the precipitation influenced measurement significantly. The coefficient of simulated and measured radiometric temperature reached above 0.9, when the temperature was higher than 30°C, the simulated temperature was 0.34°C ...
Zhang, Y, Yu, Q, Liu, C & Wang, J 2005, 'Simulation of CO2 and latent heat fluxes in the North China Plain', Science in China, Series D: Earth Sciences, vol. 48, no. SUPPL.1, pp. 172-181.View/Download from: Publisher's site
We constructed a coupled model for simulating plant photosynthesis and evapotranspiration (CPCEM). In the model, non-rectangular hyperbola is used to simulate leaf photosynthesis rate that is scaled up to estimate canopy gross photosynthesis rate by an integral method. Whole canopy in the model is separated into multi-layers, each of which is divided into sunlit leaves and shade leaves. Canopy net photosynthesis rate is expressed as a function of canopy conductance which is coupled with evapotranspiration. Included the coupled function, evapotranspiration is estimated with a two-layer submodel. The main features of CPCEM are: (1) easy suitability, (2) good physiological base, and (3) simple calculation procedure. Simulated results of CPCEM were compared with those by an eddy covariance system that was installed in a winter wheat farmland of the North China Plain. CPCEM gave a quite well diurnal and seasonal dynamics of net ecosystem exchange, compared with the measurements. The root mean square error between simulation and measurements was only about 2.94 μ mol m-2 s-1. Diurnal and seasonal patterns of latent heat flux with the CPCEM were similar to those of measurements. Whereas, simulated latent heat flux was evidently higher than the measured. Copyright by Science in China Press 2005.
Zhang, Y, Yu, Q, Liu, C & Wang, J 2005, 'Simulation of CO2 and latent heat fluxes in the North China Plain', Science in China Series D Earth Science, vol. 48, no. 1, pp. 172-181.
We constructed a coupled model for simulating plant photosynthesis and evapotranspiration (CPCEM). In the model, non-rectangular hyperbola is used to simulate leaf photosynthesis rate that is scaled up to estimate canopy gross photosynthesis rate by an integral method. Whole canopy in the model is separated into multi-layers, each of which is divided into sunlit leaves and shade leaves. Canopy net photosynthesis rate is expressed as a function of canopy conductance which is coupled with evapotranspiration. Included the coupled function,evapotranspiration is estimated with a two-layer submodel. The main features of CPCEM are: (1)easy suitability, (2) good physiological base, and (3) simple calculation procedure. Simulated results of CPCEM were compared with those by an eddy covariance system that was installed in a winter wheat farmland of the North China Plain. CPCEM gave a quite well diurnal and seasonal dynamics of net ecosystem exchange, compared with the measurements. The root mean square error between simulation and measurements was only about 2.94 ? mol m-2 s-1. Diurnal and seasonal patterns of latent heat flux with the CPCEM were similar to those of measurements.Whereas, simulated latent heat flux was evidently higher than the measured.
Chen, S, Li, J, Lu, P, Wang, Y & Yu, Q 2004, 'Soil respiration characteristics in winter wheat field in North China Plain', Chinese Journal of Applied Ecology, vol. 15, no. 9, pp. 1552-1560.
Experiments were conducted at the Yucheng Comprehensive Experimental Station of the Chinese Academy of Sciences during 2002-2003 to investigate the respiration of a pulverous sandstone soil under cultivation of winter wheat over a growth season. The effluent CO 2 was collected and analyzed by the static-chamber/gas chromatography (GC) method at a frequency of once a week in spring and autumn, once two weeks in winter, twice a week for straw manure treatment, once a week for no straw manure treatment and nitrogen fertilization treatment in summer. The results indicated that diurnal variation of soil respiration rate showed a single peak in typical winter wheat farmlands in the North China Plain, and reached the highest at about 13 o'clock, and the lowest at about 4 o'clock in the early morning. In winter wheat growth season, the soil respiration rate was 31.23-606.85 mg · m-2 · h-1 under straw manure, 28.99-549.66 mg · m-1 under no straw manure, 10.46-590.86 mg · m-2 · h-1 N0, 16.11-349.88 mg · m-2 · h -1 in N100, 12.25-415.00 mg · m -2 · h-1 in N200, and 23.01-410.58 mg · m-2 · h-1 in N 300, showing a similar seasonal variation tendency with soil temperature. Among all treatments, the straw manure had the most distinct soil respiration, though the soil respiration also increased slightly with increasing nitrogen fertilization. Soil respiration increased exponentially with increasing soil temperature, and the correlation of soil temperature at the depth of 5 cm was the best. This relationship was usually described with the Q10 model, which represented the sensitivity of soil respiration to temperature. Q 10 was not a fixed value, which varied with the depth at which the temperaure was measured and the depth of the active soil layer and soil temperature. At same time, the Q10 value decreased with increasing soil temperature. Soil water content was another important factor affecting soil respiration rate, but in this region, the relationship between soa respiration ...
Fang, Q, Chen, Y, Li, Q, Yu, S, Luo, Y, Yu, Q & Ouyang, Z 2004, 'Effect of irrigation on water use efficiency of winter wheat', Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, vol. 20, no. 4, p. 34.
Lee, X, Yu, Q, Sun, X, Liu, J, Min, Q, Liu, Y & Zhang, X 2004, 'Micrometeorological fluxes under the influence of regional and local advection: a revisit', Agricultural and Forest Meteorology, vol. 122, no. 1-2, pp. 111-124.View/Download from: Publisher's site
This paper presents a new analysis of inequality of eddy diffusivities for sensible heat (KH) and water vapor (KW). It is shown that the same set of equations, established on the principle of dual-source diffusion, can be applied to both local and regional advection. Various advection scenarios are discussed using a formula that relates KH/KW to the Bowen ratio of the advective source and the observed gradient Bowen ratio (?g) near the ground surface. A similar analysis can also be performed for eddy diffusivities for trace gases. The ratio KH/KW, observed at a well-watered wheat field in the North China Plains, was mostly greater than unity when ?g was negative and smaller than unity when ?g was positive. The pattern was consistent with the theoretical analysis of the ratio under the influence of regional advection. Some degree of local advection was also suggested by the data. Despite inequality of the eddy diffusivities, there was little systematic bias between the evapotranspiration rates measured with a Bowen ratio/energy balance and an eddy covariance system.
Li, Q, Fang, Q, Chen, Y, Yu, S, Wang, J, Luo, Y & Yu, Q 2004, 'Effects of different soil moistures before sowing on water consumption characteristics and yield of summer maize', Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, vol. 20, no. 2, p. 93.
Qiu, X, Zeng, Y, Miao, Q & Yu, Q 2004, 'Estimation of annual actual evapotranspiration from nonsaturated land surfaces with conventional meteorological data', Science in China, Series D: Earth Sciences, vol. 47, no. 3, pp. 239-246.View/Download from: Publisher's site
Views diverge greatly on the relationship between actual evapotranspiration (AE) and potential evapotranspiration (PE). Penman showed that AE is determined in intensity by PE and changes proportionally as a function of PE. In contrast, Bouchet indicated that AE determines PE and varies inversely with PE. Based on nearly 30 years data from 432 weather stations and 512 hydrological stations in China, the two different theories, Penman's assumption and Bouchet's complementary relationship between AE and PE, were tested on nine river basins. With data integration technique, the complementary relationship between AE and PE was displayed entirely. A general model to estimate the actual evapotranspiration from nonsaturated surfaces by routine meteorological observations has been established on the basis of thorough analysis of the concept of PE. The results show that the calculations are all in error control of <10%, except for a few years over the Yellow River Basin. Copyright by Science in China Press 2004.
Qiu, X, Zhen, Y, Miao, Q & Yu, Q 2004, 'Estimation of annual actual evapotranspiration from non-saturated land surfaces with conventional meteorological data', Science in China Series D: Earth Sciences, vol. 47, no. 3, pp. 239-246.
Wang, J, Yu, Q, Li, X & Sun, X 2004, 'Diurnal variation of winter wheat water and heat fluxes of a simulation with photosynthesis-evapotranspiration coupled model', Chinese Journal of Applied Ecology, vol. 15, no. 11, pp. 2077-2082.
A coupled model of winter wheat photosynthesis-evapotranspiration was established based on SPAC theory. Sensible heat and latent heat fluxes were calculated by two-layer model proposed by Shuttle worth and Wallace, and photosynthesis and evapotranspiration were coupled by the parameterization of canopy resistance. The model was validated with the data measured by eddy covariance method. The results showed that the simulated and observed values were accordant, and the model could simulate the diurnal variation of sensible heat and latent heat fluxes very well. Sensitivity analysis indicated that the sensitive parameters of canopy transpiration were wilting point, stomata conductance, reflectivity of leaves to infrared radiation, and convexity of photosynthesis response to light, while the sensitive parameter of soil evaporation was soil resistance. The model could be used to study the interactions between water and heat fluxes and environmental factors, and to instruct the irrigation scheme in the field.
Yu, Q, Zhang, Y, Liu, Y & Shi, P 2004, 'Simulation of the stomatal conductance of winter wheat in response to light temperature and CO2 changes', Annals of Botany, vol. 93, no. 4, pp. 435-441.View/Download from: Publisher's site
Background and Aims The stomata are a key channel of the water cycle in ecosystems, and are constrained by both physiological and environmental elements. The aim of this study was to parameterize stomatal conductance by extending a previous empirical model and a revised BallBerry model. Methods Light and CO2 responses of stomatal conductance and photosynthesis of winter wheat in the North China Plain were investigated under ambient and free-air CO2 enrichment conditions. The photosynthetic photon flux density and CO2 concentration ranged from 0 to 2000 µmol m2 s1 and from 0 to 1400 µmol mol1, respectively. The model was validated with data from a light, temperature and CO2 response experiment. Key Results By using previously published hyperbolic equations of photosynthetic responses to light and CO2, the number of parameters in the model was reduced. These response curves were observed diurnally with large variations of temperature and vapour pressure deficit. The model interpreted stomatal response under wide variations in environmental factors. Conclusions Most of the model parameters, such as initial photon efficiency and maximum photosynthetic rate (Pmax), have physiological meanings. The model can be expanded to include influences of other physiological elements, such as leaf ageing and nutrient conditions, especially leaf nitrogen content.
Zhang, Y, Kendy, E, Yu, Q, Liu, C, Shen, Y & Sun, H 2004, 'Effect of soil water deficit on evapotranspiration crop yield, and water use efficiency in the North China Plain', Agricultural Water Management, vol. 64, no. 2, pp. 107-122.View/Download from: Publisher's site
In the North China Plain (NCP), excessive groundwater pumping is a serious problem. In this study, different groundwater irrigation schedules were applied. A simple soil water balance approach was introduced to evaluate crop evapotranspiration (ET) and water use efficiency (WUE). Under normal irrigation scheduling, groundwater mining occurs at a rate of over 200 mm per year from a rapidly depleting aquifer system. Severe soil water deficit (SWD) decreases grain yield (GY) of wheat (Triticum aestivum L.) and maize (Zea mays L.), while slight SWD in a growth stage from spring green up to grain-filling winter wheat did not evidently reduce GY and WUE. A severe or slight SWD significantly reduces ET, which mainly depends on irrigation amounts. Thus, it is possible to reduce ET somewhat without significantly decreasing GY. ET was correlated to GY in a parabolic function, and maximum yield for winter wheat occurred when optimal ET for winter wheat was about 447 mm. It was important for wheat and maize to be irrigated before sowing to improve soil water storage (SWS), and the effect of the irrigation apparently increased wheat GY.
Zhang, Y, Liu, C, Yu, Q, Shen, Y, Kendu, E, Kondoh, A, Tang, C & Sun, H 2004, 'Energy fluxes and the Priestley-Taylor parameter over winter wheat and maize in the North China Plain', Hydrological Processes, vol. 18, no. 12, pp. 2235-2246.View/Download from: Publisher's site
Surface energy fluxes above the canopies of well-irrigated winter wheat and maize in the North China Plain were measured by the Bowen-ratio energy balance technique in 1999-2000. Seasonal variation of the ratio of latent heat flux E to available energy Rn - G showed that the ratio of E to Rn - G exceeded 83% when leaf area index (LAI) varied from 2·0 to 6·0. The seasonal trend of evaporative fraction (EF) for winter wheat was similar to that of LAI before senescence stage, which is a critical factor controlling EF, which itself reflects the partitioning of available energy into E. The Priestley-Taylor parameter over the wheat and maize canopies changed greatly over the course of a growing season, and the seasonal average of winter wheat was 1·17 and 1·26, and that of maize was 1·06 and 1·09 in the two consecutive years. for winter wheat was exponentially correlated to 0-20 cm surface soil moisture, but not for maize and with the increase of soil depths, the correlation between and soil moisture was weak. Under different soil moisture conditions, a linear correlation between extractable soil water and leaf water potential for winter wheat was found
Zhang, Y, Yu, Q, Liu, C, Jiang, J & Zhang, X 2004, 'Estimation of winter wheat evapotranspiration under water stress with two semiempirical approaches', Agronomy Journal, vol. 96, no. 1, pp. 159-168.View/Download from: Publisher's site
Received for publication October 31, 2002. Winter wheat (Triticum aestivum L.) is one of most important crops in the North China Plain. However, soil water deficit (SWD) often occurs due to lack of precipitation in its growing season. In this study, we introduce two semiempirical approaches, a recharge model and the crop coefficient (Kc)reference evapotranspiration (ET0) approach, to estimate wheat actual evapotranspiration (ETa) under no SWD and slight and severe SWD conditions. The recharge model allocated ET0 to reference evaporation and reference transpiration as a function of leaf area index. In the model, ETa is limited by soil water content, and crop water extraction for ETa is distributed through the soil profile as exponential functions of soil and root depth. The KcET0 approach regarded ETa under the SWD condition as a logarithmic function of soil water availability. Under no SWD condition, the recharge model simulated 10-d ETa with a root mean square error (RMSE) of 5.58 mm and a bias of 0.95 mm compared with measurements from a large-scale weighing lysimeter. The two approaches both estimated seasonal evapotranspiration (ET) well compared with the adjusted ET (from the soil water balance and the recharge modelsimulated deep drainage). The recharge model, which simulated the seasonal ET with the RMSE of 27.8 mm and the bias of 8.0 mm, was better than the KcET0 approach (RMSE = 31.7 mm and bias = 33.1 mm). The seasonal pattern of soil water stress coefficient (Ks) showed that there were faster water losses at grain-filling stage than at other stages.
Liu, J, Zhou, X & Yu, Q 2003, 'Numerical analysis of the source-sink alternation of composite global warming potential of the paddy ecosystem in the Yangtze Delta', Science in China Series D: Earth Sciences, vol. 46, no. 4, pp. 385-396.
By coupling the biogeochemical model With plant ecological model, a model Was established to reveal the principle of the composite global warming potential transformation in the paddy ecosystem. Validation of the model with the observed data indicated that,the model can simulate both the crop growth processes and emissions of CH4, and N2O accurately. Some numerical analyses were made to identify the impacts of different fertilizer application on assimilation Of CO2 and emissions of CH4 and N2O, and the transformation principle of the composite global warming potential. Based on the results of the numerical analysis, the source-sink alternation of composite global warming potential in the paddy ecosystem was discovered, and some new conceptions of fertilizer index such as maximum-sink fertilizer, zero-emission fertilizer are put forward in this paper. The fertilizer scheme for Yangtze Delta was proposed to provide the important scientific basis for a sustainable agriculture in this region.
Liu, J, Zhou, X & Yu, Q 2003, 'Numerical simulation of the influence of O3, CO2 and spectrum variation on the photosynthesis of crop canopy', Acta Meteorologica Sinica, vol. 17, no. 4, pp. 428-439.
Coupled the photosynthesis with transpiration and adjustment of stoma, a dynamic ecological model for simulating the canopy photosynthesis of winter wheat was established by scaling up from the biochemical scale to canopy scale, in which the effects of O3, CO2 and solar spectrum on crop photosynthesis were fully considered. Validation of the model against the data measured with CI-301PS portable photosynthesis analyzer showed that the leaf photosynthesis model passed the correlation significance test and had a fairly high accuracy. Numerical analysis showed that the canopy photosynthesis rate would be reduced by 29% if the O3 concentration increases from 0 ppbv to 200 ppbv, whereas the canopy photosynthesis rate would increase by about 37% while the CO2 concentration increases from 330 ppmv to 660 ppmv, and the canopy photosynthesis rate would be reduced by 27% or so under the condition that the spectrum coefficient changed from 0. 5 to 0. 4. If the O3 concentration reached 200 ppbv at noon on the typical sunny day with higher radiation, the canopy photosynthesis will be reduced slightly in the suburb area where the pollution is serious and the photochemical fog is easy to be formed, contrast with that in the clear region and regardless of the climate change, due to the fact that the positive effect of CO2 on crop photosynthesis can not compensate the negative effect Of O3 on crop photosynthesis. The canopy photosynthesis will be reduced by 35% or so than the BASE value at present, when the spectrum of photosynthetic active radiation (PAR) reduces to 0. 4 or so.
Yu, Q, Liu, J, Zhang, Y & Li, J 2002, 'Simulation of rice biomass accumulation by an extended logistic model including influence of meteorological factors', International Journal of biometeorology, vol. 46, pp. 185-191.View/Download from: Publisher's site
Yu, Q, Liu, Y, Liu, J & Wang, T 2002, 'Simulation of leaf photosynthesis of winter wheat on Tibetan Plateau and in North China Plain', Ecological Modelling, vol. 155, pp. 205-216.View/Download from: Publisher's site
Zhang, Y, Shen, Y, Liu, C, Yu, Q, Sun, H, Jia, J, Tang, C & Akihiko, K 2002, 'Measurement and analysis of water, heat and CO2 flux from a farmland in the North China plain', Dili Xuebao/Acta Geographica Sinica, vol. 57, no. 3, pp. 333-342.
Surface energy fluxes including net radiation (Rn), latent heat flux (λ E), sensible heat flux (H), soil heat flux (G) and carbon dioxide flux (F∞2) were measured by Bowen-ratio energy balance technique and eddy correlation technique from a farmland at Luancheng Agro-ecosystem Station, Chinese Academy of Sciences in the North China Plain from 1999 to 2001. Seasonal variation of a ratio of latent heat flux (λ E) divided by net radiation flux (Rn) showed that Rn is mainly used to evapotranspirate by crops. λ E/Rn was all higher than 70% during the four observed seasons in the two years. λ E/Rn above maize canopy is slightly higher than that above winter wheat canopy. Seasonal average ratio of sensible heat flux (H) divided by Rn keeps about 15% above the field surface; seasonal average ratio of conductive heat flux (G) divided by Rn varies between 5% and 13%, and the average G/Rn from wheat canopy is evidently higher than that from maize canopy. Under given environmental conditions, when the available energy (Rn-G) is less than 200 W/m2, evaporative fraction (EF) decreases sharply; below Rn-G≈200 W/m2, EF decreases gradually until stabilizing at some specific value less than 1.0. The response process of EF to Rn-G under winter wheat field condtions is similar to that under the given conditions. With the increase of photosynthesis photo flux density (PPFD), carbon dioxide flux (F⊥2) changes according to the curve of Michaelis-Mente. Water use efficiency (WUE) does not show the maximum when PPFD is the maximum at noon. On the contrary, WUE gradually decreased with PPFD equal to 1500 μmol m-2 s-1.
Yu, Q, Goudriaan, J & Wang, T 2001, 'Modeling diurnal courses of photosynthesis and transpiration of leaves on the basis of stomatal and non-stomatal responses, including photoinhibition', Photosynthetica, vol. 39, pp. 43-51.
Yu, Q, Hengsdijk, H & Liu, JD 2001, 'Application of a progressive-difference method to identify climatic factors causing variation in the rice yield in the Yangtze Delta, China', International Journal of biometeorology, vol. 45, pp. 53-58.View/Download from: Publisher's site
Yu, Q, Liu, J & Luo, Y 2000, 'Applicability of some stomatal models to natural conditions', Acta Botanica Sinica, vol. 42, no. 2, pp. 203-206.
Under natural conditions, the use of vapor pressure deficit between mesophyll cell surface and ambient air (VPDs) instead of atmospheric humidity factors in some stomatal models may markedly promote the applicability of stomatal models. It has been pointed out from theoretical analysis that the expression of the responses of stomatal conductance to VPDs is equivalent to the expression of responses of stomatal conductance to water loss of transpiration in stomatal models.
Yu, Q & Wang, T 1998, 'Simulation of the physiological responses of C3 plant leaves to environmental factors by a model which combines stomatal conductance, photosynthesis and transpiration', Acta Botanica Sinica, vol. 40, no. 8, pp. 740-754.
Transpiration element is included in the integrated stomatal conductance-photosynthesis model by considering gaseous transfer processes, so the present model is capable to simulate the influence of boundary layer conductance. Leuning in his revised Ball's model replaced relative humidity with VPDs(the vapor pressure deficit from stomatal pore to leaf surface) and thereby made the relation with transpiration more straightforward, and made it possible for the regulation of transpiration and the influence of boundary layer conductance to be integrated into the combined model. If the differences in water vapor and CO2 concentration between leaf and ambient air are considered, VPDs, the evaporative demand, is influenced by stomatal and boundary layer conductance. The physiological responses of photosynthesis, transpiration, and stomatal function, and the changes of intercellular CO2 and water use efficiency to environmental factors, such as wind speed, photon flux density, leaf temperature and ambient CO2, are analyzed. It is shown that if the boundary layer conductance drops to a level comparable with stomatal conductance, the results of simulation by the model presented here differ significantly from those by the previous model, and, in some cases, are more realistic than the latter.
Liu, J, Fu, B, Jin, Z, Weixing, C & Yu, Q 1997, 'AN agrometeorological model of physiological thermal index for winter wheat development in early stage', Acta Meteorologica Sinica, vol. 11, no. 4.
Based on full consideration of the winter wheat biological characters, an agrometeorological model of physiological thermal index of winter wheat including vernalization and photoperiod response is established, in which the influence of diurnal variation of temperature, effective temperature and daylength on the development of winter wheat during the period from emergence to elongation are comprehensively considered. Validation of the model using the data taken from the experiments of wheat ecology in China shows that the model behaves well with mean error less than 3 days.
Shen, J, Tran, NN, Devadas, R, Huete, A, Zhang, H & Yu, Q 2016, 'Climate impacts on wheat phenology and production using mutisource data in NSW, Australia', International Geoscience and Remote Sensing Symposium (IGARSS), IEEE International Geoscience and Remote Sensing Symposium, IEEE, Beijing, China, pp. 6296-6299.View/Download from: Publisher's site
© 2016 IEEE.Wheat is the most important grain crop in Australia, which plays a significant role in world grain-trading market. However, climate warming, water shortage, as well as more frequent extreme weather events (e.g., heatwaves, droughts and floods), under pressure of food demand, would pose great risks to all aspects of wheat production worldwide, especially in Australia with high climate variability. This study aggregated multi-source observational data by using meteorological statistics, in-situ investigation data and the MODIS Enhanced Vegetation Index (EVI) product to explore and examine the correlation between climate variability and spatial-temporal patterns of wheat phenology metrics and productivity. The results from tests over 370 wheat trial sites showed: 1) narrower and earlier sowing and harvesting windows occurred in a drought year (2006) compared with a normal year (2005). Differences in sowing and harvesting window lengths were 9 and 5 days, respectively; 2) different weather patterns in each agro-climatic zone were followed by different remotely sensed crop EVI seasonality profiles. Crop growth was least affected by climate variability in agro-climate region E2, which is located in the south part of study area. This study reveals new information on cropland-climate relationships across the wheat belt in NSW in a changing climate.
Zhu, Q, Yang, X & Yu, Q 2016, 'Assess The Topographic Resolution Impact On Soil Loss', Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS),, EE International Geoscience and Remote Sensing Symposium (IGARSS),, IEEE, Beijing, China.View/Download from: Publisher's site
Soil erosion is one of the thorniest issues which has brought severe environmental problems such as degradation of water quality and soil productivity. Topographic factor, as known as slope length and steepness factor (LS) plays a vital role in soil erosion model, it is multiplied with rainfall erosivity (R), ground cover (C), soil erodibility (K) and soil conservation practices factor (P) to modelling soil loss via Revised Universal Soil Loss Equation (RUSLE). In this research, different resolution of elevation model products were used to calculate the LS factor of soil loss, and also compare with each other to access and determine the most appropriate interval to predict soil loss rate in Warrumbungle National Park (WNP). LS factor was calculated via the Digital Elevation Model (DEM) at 30m from Shuttle Radar Topography Mission (SRTM) and High Resolution Light Detection and Ranging (LiDAR) at 1m, 5m and 10m. Twelve soil sites were selected to collect field-based data, which would compare with the soil loss modelling results. GIS technique was applied to model and geo-visualize the LS factor map. Meanwhile, daily soil loss ratio was predicted from LS factor along with rainfall erosivity, groundcover, soil structure and composition.
Wang, B, Liu, DL, Macadam, I, Alexander, LV, Abramowitz, G & Yu, Q 2015, 'Multi-model ensemble projections of future extreme temperature change using a statistical downscaling method in eastern Australia', Proceedings - 21st International Congress on Modelling and Simulation, MODSIM 2015, pp. 1565-1571.
© 2020 Proceedings - 21st International Congress on Modelling and Simulation, MODSIM 2015. All rights reserved. Projections of changes in temperature extremes are critical to assess the potential impacts of climate change on agricultural and ecological systems. Statistical downscaling can be used to efficiently downscale output from a large number of general circulation models (GCMs) to a fine temporal and spatial scale, which now provides the opportunity for future projections of extreme temperature events. This paper presents an analysis of extreme temperature in data downscaled from ensembles of 13 selected GCMs, out of 28 GCMs, contributing to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR5) under two Representative Concentration Pathways (RCP4.5 and RCP8.5) in eastern Australia. The statistical downscaling procedure begins with spatial interpolation of the monthly gridded data to specific locations of interest using an inverse distance-weighted method, followed by a bias correction towards historical observed climate. Daily climate data for each location are then generated by a modified version of the WGEN stochastic weather generator. The extremes of temperature are described by eleven indices, namely, the annual maximum daily Tmax (TXx), the annual maximum daily Tmin (TNx), the annual minimum daily Tmax (TXn), the annual minimum daily Tmin (TNn), the number of hot days (HD) and frost days (FD), warm days (TX90p) and nights (TN90p), cold days (TX10p) and nights (TN10p) and extreme temperature range (ETR). The results show that downscaled data from most of the GCMs reproduced the correct sign of recent trends in all the extreme temperature indices (except TN10p) although there was much more variation between the individual model runs. An independence weighted mean method was used to calculate uncertainty estimates, which verified that multi-model ensemble projections produced a good consensus compared to the observation...
Yu, Q, Zhu, QG & Yang, XH 2015, 'Climate Change Impact On Bushfire Risk In New South Wales, Australia', Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, Milan, pp. 1413-1416.View/Download from: Publisher's site
Australia is one of the most vulnerable countries that influenced by climate change. IPCC proved that the circumstance of climate change has affected the frequency of extreme weather, such as bushfire, and extreme rainfall. Bushfire will not happen without one of the compulsory and necessary risk factors as below: fuel load, low fuel moisture, ignition source and fire weather. Vegetation in Australia is adapted to burn. Fire weather including four switches, lasting high temperature, less precipitation based on extreme hot wave, relative humidity and speedy wind . Both vegetation and fire weather result in the increasingly more severe fire regime across Australia. In this paper, Forest Fire Danger Index (FFDI) will be used for computing for fire danger rating and analysis relationships between climate change and bushfire risk
Ma, X, Huete, A, Yu, Q, Davies, KP & Restrepo Coupe, N 2012, 'Monitoring spatial patterns of vegetation phenology in an Australian tropical transect using MODIS EVI', International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXII International Society for Photogrammetry & Remote Sensing Congress., ISPRS Society, Melbourne, Australia, pp. 271-276.View/Download from: Publisher's site
Phenology is receiving increasing interest in the area of climate change and vegetation adaptation to climate. The phenology of a landscape can be used as a key parameter in land surface models and dynamic global vegetation models to more accurately simulate carbon, water and energy exchanges between land cover and atmosphere. However, the characterisation of phenology is lacking in tropical savannas which cover more than 30% of global land area, and are highly vulnerable to climate change. The objective of this study is to investigate the spatial pattern of vegetation phenology along the Northern Australia Tropical Transect (NATT) where the major biomes are wet and dry tropical savannas. For this analysis we used more than 11 years Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) product from 2000 to 2011. Eight phenological metrics were derived: Start of Season (SOS), End of Season (EOS), Length of Season (LOS), Maximum EVI (MaxG), Minimum EVI (MinG), annual amplitude (AMP), large integral (LIG), and small integral (SIG) were generated for each year and each pixel. Our results showed there are significant spatial patterns and considerable interannual variations of vegetation phenology along the NATT study area. Generally speaking, vegetation growing season started and ended earlier in the north, and started and ended later in the south, resulting in a southward decrease of growing season length (LOS). Vegetation productivity, which was represented by annual integral EVI (LIG), showed a significant descending trend from the northern part of NATT to the southern part. Segmented regression analysis showed that there exists a distinguishable breakpoint along the latitudinal gradient, at least in terms of annual minimum EVI (EVI), which is located between 18.84"S to 20.04"S.
Zhao, G, Song, X, Yan, C & Yu, Q 2012, 'Porting a process-based crop model to a high-performance computing environment for plant simulation', Proceedings - 2012 IEEE 4th International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications, PMA 2012, IEEE International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA), IEEE, Institute of Electrical and Electronics Engineers, Shanghai, China, pp. 462-465.View/Download from: Publisher's site
Increasing concerns about food security have stimulated integrated assessment of the sustainability of agricultural systems at regional, national and global scales with high-resolution. Traditionally, the process-based agricultural models are designed for field scale studies that obtain inputs, run the simulations and provide outputs through the graphic interface. The graphic interface based model dose not suit for modelling practices requiring a large number of simulations. Here, we developed a high performance approach which concurrently executed the Agricultural Production Systems sIMulator (APSIM) simulations using parallel programming techniques. In this approach, an APSIM simulation template with replaceable parameters was firstly designed, and new simulations based on the template was then constructed by dynamically replacing parameters of climate, soil and management options. We parallelized the batched running method in a shared-memory multiprocessor system using Python's Multiprocessing module. We tested the approach with a case study that simulated the productivity of continuous wheat cropping system during 20 years period along the Australian cereal-growing regions under management practices of 5 levels nitrogen application and 3 stubble management practices. More than 170 K runs were finished in 43h by using 64 workers, achieved a speedup ratio of 60. The parallelized method proposed in this study makes large-scale and high-resolution agricultural systems assessment possible. © 2012 IEEE.
Su, Z, Ma, Y, Menenti, M, Sobrino, J, Li, ZL, Verhoef, W, Jia, L, Wen, J, He, Y, Wan, L, Liu, QH, Yu, Q, Li, X, Van Der Velde, R, Dente, L, Zhong, L, Zeng, Y, Tian, X, Li, L, Qin, C, Wang, L, Van Helvoirt, M, Timmermans, W, Van Der Tol, C, Salama, MS, Vekerdy, Z & Ucer, M 2010, 'Drought monitoring, prediction and adaptation under climatic changes', European Space Agency, (Special Publication) ESA SP.
The objective of this project is to develop a quantitative and operational system for nationwide drought monitoring and drought impact assessment for application in agriculture, water resources and environmental management in China using ESA, Chinese and other relevant satellite data as major data source in combination with other data source (e.g. meteorological and drought statistics, etc.). An extension to drought prediction and adaptation to climate change will be made compared to the Dragon I drought monitoring project. In detail the project aims to generate: (1) a real time drought monitoring and prediction system, (2) improved understanding of land surface processes and land-atmosphere interactions over different terrains (e.g. agriculture land, forest, Gobi desert, high plateau, polar environment), (3) improved algorithms for estimation of land surface parameters and heat fluxes, (4) assessment of economic loss caused by drought and adaptation measures under climatic change, (5) training of young scientists in the area of water, climate and environment. In this contribution, progresses in retrievals of soil moisture using data from different methods are addressed, including in-situ observations, direct retrievals using data from satellite sensors and numerical modeling. The used sensors include ASAR, ASCAT, and AMSR-E. The accuracy of available soil moisture products are assessed using in-situ data collected by the Tibetan Plateau soil moisture monitoring network developed for this and other projects.
Xiao, W, Lee, X, Griffis, T, Kim, K, Welp, L & Yu, Q 2010, 'The Impact of Peclet Effect and Leaf Water Content Variation on Canopy-scale Leaf Water 18O-H2O Enrichment', International Conference on Application of Mathematics and Physics, World Academic Union, Nanjing, pp. 202-206.
Wang, E, Chen, C & Yu, Q 2009, 'Modeling the response of wheat and maize productivity to climate variability and irrigation in the North China Plain.', Interfacing Modelling and Simulation with Mathematical and Computational Sciences, Australia, Cairns, pp. 2742-2748.
The North China Plain (NCP) is the largest agricultural production area in China, accounting for about 50% of wheat and 30% of maize grain production in China, with a dominant wheat-maize double cropping system. Due to the concentrated summer monsoon rainfall and inter-annual climate variability, irrigation is required to support the high productivity of the wheat-maize system, especially for the wheat crop and in the northern part of the plain, where excessive use of ground- and surface water for irrigation has caused rapid decline of groundwater tables and severe reduction of available surface water from the Yellow River. The productivity of the double cropping system and its reliance on decreasing water supplies under the variable climate need to be assessed. There is still a lack of systematic studies on how the productivity of the wheat-maize system could respond to different levels of reduced irrigation water supply.
Flerchinger, GN, Xaio, W & Yu, Q 2006, 'Evaluation of the Shaw Model for Within-Canopy Radiation Exchange', ASABE Annual International Meeting, Portland, Orefon, USA.
Guo, J, Lu, W, Zhang, G, Qian, Y, Yu, Q & Zhang, J 2006, 'Incorporating remote sensing data in crop model to monitor crop growth and predict yield in regional area', Proceedings of SPIE - The International Society for Optical Engineering.View/Download from: Publisher's site
Accurate crop growth monitoring and yield predicting is very important to food security and agricultural sustainable development. Crop models can be forceful tools for monitoring crop growth status and predicting yield over homogeneous areas, however, their application to a larger spatial domains is hampered by lack of sufficient spatial information about model inputs, such as the value of some of their parameters and initial conditions, which may have great difference between regions even fields. The use of remote sensing data helps to overcome this problem. By incorporating remote sensing data into the WOFOST crop model (through LAI), it is possible to incorporate remote sensing variables (vegetation index) for each point of the spatial domain, and it is possible for this point to re-estimate new values of the parameters or initial conditions, to which the model is particularly sensitive. This paper describes the use of such a method on a local scale, for winter wheat, focusing on the parameters describing emergence and early crop growth. These processes vary greatly depending on the soil, climate and seedbed preparation, and affect yield significantly. The WOFOST crop model is calibrated under standard conditions and then evaluated under test conditions to which the emergence and early growth parameters of the WOFOST model are adjusted by incorporating remote sensing data. The inversion of the combined model allows us to accurately monitoring crop growth status and predicting yield on a regional scale.