Du, Z, Ge, L, Ng, AHM, Zhu, Q, Horgan, FG & Zhang, Q 2020, 'Risk assessment for tailings dams in Brumadinho of Brazil using InSAR time series approach', Science of the Total Environment, vol. 717.View/Download from: Publisher's site
© 2020 Tailings dams are usually ponds bounded by valleys or surrounding topography to store mining or other chemical industrial waste. On 25 January 2019, the collapse of a tailings dam at the Córrego do Feijao iron ore mine (Brumadinho, Minas Gerais, Brazil) released about 12 million m3 of tailings, killing over 240 people and posing a considerable and ongoing environmental threat. The stability of tailings dam monitoring is very important and in the present paper, a new InSAR (Synthetic Aperture Radar Interferometry) time series approach is proposed to derive ground displacement maps for use in dam safety monitoring. Compared with the other solutions, the unique feature of the proposed method is that: 1) the new Measurement Pixel (MP) selection criteria has the potential to include relatively more accurate MP pixels and build a more robust network, 2) the multi-level grading system makes it possible to add the MP pixels into the main network step-by-step with external control, and 3) the computing efficiency can be improved by strategically reducing the iteration times. The proposed approach was tested on both simulated and real data. Results show that the Simulated Annealing (SA) method normally has a more accurate estimation as compared to the Quasi-Newton (QN) method, despite its longer processing time. Detailed analysis of the displacement maps was conducted to determine the subsidence processes that result from dam construction.
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 & DEVELOPMENT.View/Download from: Publisher's site
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.
Du, Z, Ge, L, Ng, AHM, Zhu, Q, Zhang, Q, Kuang, J & Dong, Y 2019, 'Long-term subsidence in Mexico City from 2004 to 2018 revealed by five synthetic aperture radar sensors', Land Degradation and Development, vol. 30, no. 15, pp. 1785-1801.View/Download from: Publisher's site
© 2019 John Wiley & Sons, Ltd. Anthropogenic land subsidence is an example of changes to the natural environment due to human activities and is one of the key factors in causing land degradation at a range of scales. Previous studies assessing land subsidence in the Valley of Mexico either focused on regional scale or short (noncontinuous) temporal scale. In this study, long-term land subsidence (~15 years) is mapped in Mexico City (Mexico) using two interferometric synthetic aperture radar (InSAR) methods, namely, GEOS (Geoscience and Earth Observing Systems Group)-Advance Time-series Analysis and GEOS-Small Baseline Subset. An inverse distance weighted-based integration module and maximum likelihood regression-based M estimator are introduced to further enhance these two methods. The land subsidence was continuously mapped using ENVISAT (2004–2007), ALOS-1 (2007–2011), COSMO-SkyMed (2011–2014), ALOS-2 (2014–2018), and SENTINEL-1 (2015–2017) data sets. A comparison between InSAR time-series and GPS measurement shows that the subsidence rates are consistent over 2004–2018. The subsidence map over 15 years was generated finding a maximum subsidence over 4.5 m. By comparing our InSAR results with a land use map, we find that the subsidence centre in Mexico City is mostly located in the residential regions with the consumption of groundwater contributing considerably to the local subsidence rate. A total volume of 1.20 × 108 m3 of the land in Ciudad Nezahualcoyotl subsided/degraded. A continuing subsidence process limits the potential land use causing serious land degradation. Our results may be used to assist disaster reduction plans.
Shan, L, Yang, X & Zhu, Q 2019, 'Effects of DEM resolutions on LS and hillslope erosion estimation in a burnt landscape', SOIL RESEARCH, vol. 57, no. 7, pp. 797-804.View/Download from: Publisher's site
Tulau, MJ, McInnes-Clarke, SK, Yang, X, McAlpine, RA, Karunaratne, SB, Zhu, Q & Morand, DT 2019, 'The Warrumbungle Post-Fire Recovery Project—raising the profile of soils', Soil Use and Management, vol. 35, no. 1, pp. 63-74.View/Download from: Publisher's site
© 2018 British Society of Soil Science The impacts of a wildfire and subsequent rainfall event in 2013 in the Warrumbungle National Park in New South Wales, Australia were examined in a project designed to provide information on post-fire recovery expectations and options to land managers. A coherent suite of sub-projects was implemented, including soil mapping, and studies on soil organic carbon (SOC) and nitrogen (N), erosion rates, groundcover recovery and stream responses. It was found that the loss of SOC and N increased with fire severity, with the greatest losses from severely burnt sandstone ridges. Approximately 2.4 million t of SOC and ~74,000 t of N were lost from soil to a depth of 10 cm across the 56,290 ha affected. Soil loss from slopes during the subsequent rainfall event was modelled up to 25 t ha−1, compared to a long-term mean annual soil loss of 1.06 t ha−1 year−1. Groundcover averages generally increased after the fire until spring 2015, by which time rates of soil loss returned to near pre-fire levels. Streams were filled with sand to bank full levels after the fire and rainfall. Rainfall events in 2015–2016 shifted creek systems into a major erosive phase, with incision through the post-fire sandy bedload deposits, an erosive phase likely related to loss of topsoils over much of the catchment. The effectiveness of the research was secured by a close engagement with park managers in issue identification and a communications programme. Management outcomes flowing from the research included installation of erosion control works, redesign of access and monitoring of key mass movement hazard areas.
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.
Du, Z, Ge, L, Ng, AHM, Zhu, Q, Yang, X & Li, L 2018, 'Correlating the subsidence pattern and land use in Bandung, Indonesia with both Sentinel-1/2 and ALOS-2 satellite images', International Journal of Applied Earth Observation and Geoinformation, vol. 67, pp. 54-68.View/Download from: Publisher's site
© 2018 Elsevier B.V. Continuous research has been conducted in Bandung City, West Java province, Indonesia over the past two decades. Previous studies carried out in a regional-scale might be useful for estimating the correlation between land subsidence and groundwater extraction, but inadequate for local safety management as subsidence may vary over different areas with detailed characters. This study is focused primarily on subsidence phenomenon in local, patchy and village scales, respectively, with Sentinel-1 and ALOS-2 dataset acquired from September 2014 to July 2017. The Sentinel-1 derived horizontal movement map confirmed that the vertical displacement is dominant of the Line-of-Sight (LoS) subsidence. Moreover, both Sentinel-1 and ALOS-2 derived InSAR measurements were cross-validated with each other. In order to understand the subsidence in a more systematic way, six 10-cm subsidence zones have been selected known as Zone A–F. Further analyses conducted over multiple scales show that industrial usage of groundwater is not always the dominant factor that causes the land subsidence and indeed it does not always create large land subsidence either. Regions experiencing subsidence is due to a combined impact of a number of factors, e.g., residential, industrial or agricultural activities. The outcome of this work not only contributes to knowledge on efficient usage of the satellite-based monitoring networks, but also assists developing the best hazard mitigation plans. In the future work, as we cannot draw the conclusion which is the dominant factor within each sub-zone due to the lack of statistical data, e.g., the groundwater consumption rates per square kilometre for different land types, further datasets are still needed to examine the core factor.
Yang, X, Gray, J, Chapman, G, Zhu, Q, Tulau, M & McInnes-Clarke, S 2018, 'Digital mapping of soil erodibility for water erosion in New South Wales, Australia', Soil Research, vol. 56, no. 2, pp. 158-170.View/Download from: Publisher's site
© CSIRO 2018. Soil erodibility represents the soil's response to rainfall and run-off erosivity and is related to soil properties such as organic matter content, texture, structure, permeability and aggregate stability. Soil erodibility is an important factor in soil erosion modelling, such as the Revised Universal Soil Loss Equation (RUSLE), in which it is represented by the soil erodibility factor (K-factor). However, determination of soil erodibility at larger spatial scales is often problematic because of the lack of spatial data on soil properties and field measurements for model validation. Recently, a major national project has resulted in the release of digital soil maps (DSMs) for a wide range of key soil properties over the entire Australian continent at approximately 90-m spatial resolution. In the present study we used the DSMs and New South Wales (NSW) Soil and Land Information System to map and validate soil erodibility for soil depths up to 100cm. We assessed eight empirical methods or existing maps on erodibility estimation and produced a harmonised high-resolution soil erodibility map for the entire state of NSW with improvements based on studies in NSW. The modelled erodibility values were compared with those from field measurements at soil plots for NSW soils and revealed good agreement. The erodibility map shows similar patterns as that of the parent material lithology classes, but no obvious trend with any single soil property. Most of the modelled erodibility values range from 0.02 to 0.07 t ha h ha-1 MJ-1 mm-1 with a mean (± s.d.) of 0.035±0.007 t ha h ha-1 MJ-1 mm-1. The validated K-factor map was further used along with other RUSLE factors to assess soil loss across NSW for preventing and managing soil erosion.
Yang, X, Zhu, Q, Tulau, M, McInnes-Clarke, S, Sun, L & Zhang, X 2018, 'Near real-Time monitoring of post-fire erosion after storm events: A case study in Warrumbungle National Park, Australia', International Journal of Wildland Fire, vol. 27, no. 6, pp. 413-424.View/Download from: Publisher's site
© IAWF. Wildfires in national parks can lead to severe damage to property and infrastructure, and adverse impacts on the environment. This is especially pronounced if wildfires are followed by intense storms, such as the fire in Warrumbungle National Park in New South Wales, Australia, in early 2013. The aims of this study were to develop and validate a methodology to predict erosion risk at near real-Time after storm events, and to provide timely information for monitoring of the extent, magnitude and impact of hillslope erosion to assist park management. We integrated weather radar-based estimates of rainfall erosivity with the revised universal soil loss equation (RUSLE) and remote sensing to predict soil loss from individual storm events after the fire. Other RUSLE factors were estimated from high resolution digital elevation models (LS factor), satellite data (C factor) and recent digital soil maps (K factor). The accuracy was assessed against field measurements at twelve soil plots across the Park and regular field survey during the 5-year period after the fire (2013-17). Automated scripts in a geographical information system have been developed to process large quantity spatial data and produce time-series erosion risk maps which show spatial and temporal changes in hillslope erosion and groundcover across the Park at near real time.
Yang, X & Yu, B, 'Predicting Changes of Rainfall Erosivity and Hillslope Erosion across New South Wales, Australia', Journal of Earth Science & Climatic Change, vol. 07, no. 03.View/Download from: Publisher's site
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.
Zhu, Q, Yang, X, Yu, B & Sun, L 2016, 'Radar-based rainfall erosivity and hillslope erosion modelling in a burnt national park after storm events', 2016 IEEE International Geoscience & Remote Sensing Symposium, IEEE, Beijing, pp. 3094-3097.View/Download from: Publisher's site
Yang, X, Yu, B & Zhu, QG 2015, 'Climate change impacts on rainfall erosivity and hillslope erosion in NSW', Proceedings - 21st International Congress on Modelling and Simulation, MODSIM 2015, pp. 1572-1578.
© 2020 Proceedings - 21st International Congress on Modelling and Simulation, MODSIM 2015. All rights reserved. There are considerable seasonal and inter-annual changes in rainfall amount and intensity in South-East Australia (SEA), particularly in coastal New South Wales (NSW). Consequently, soil erosion rates may be expected to change in response to changes in the erosive power of rainfall or rainfall erosivity. Recently, the downscaled 10 km rainfall projections from New South Wales (NSW) and Australian Capital Territory (ACT) Regional Climate Modelling (NARCliM) project have become available for the SEA region for the baseline (1990-2009), near future (2020-2039) and far future (2060-2079) periods. The aim of this study was to model and assess the impacts of climate (rainfall) change on rainfall erosivity and hillslope erosion risk in SEA based on the NARCliM projections from all the 12 model member ensembles. Outcomes from this study are to assist the long-term climate change adaptation and regional planning such as NSW state planning regions (SPR). A daily rainfall erosivity model has been specifically developed and applied to calculate monthly and annual rainfall erosivity values from the NARCliM projected daily rainfall data for the baseline and future periods. Monthly and annual hillslope erosion risks for the same periods were estimated using the Revised Universal Soil Loss Equation (RUSLE). Finer scale (100 m) surfaces of rainfall erosivity and hillslope erosion have been produced using spatial interpolation techniques. Automated scripts in a geographic information system (GIS) have been developed to calculate the time-series rainfall erosivity and hillslope erosion so that the processes of large quantity NARCliM data are realistic, repeatable and portable. Adequate random sampling points (4991) were used to sample and assess the accuracy of the modelled rainfall erosivity from the NARCliM projections. The GIS modelled mean annual rainfall erosivity va...