Dynamic Modelling of Water and Wind Erosion in Australia over the Past Two Decades

• Published in: Remote sensing (Basel, Switzerland) Switzerland), 2022-11, Vol.14 (21), p.5437
• Main Authors: Zhang, Mingxi, Viscarra Rossel, Raphael A., Zhu, Qinggaozi, Leys, John, Gray, Jonathan M., Yu, Qiang, Yang, Xihua
• Format: Article
• Language: English
• Subjects: Approximation; Climate change; Datasets; Dynamic models; earth observation big data; Google Earth engine; Human influences; Land degradation; Land management; Land use planning; Performance evaluation; Precipitation; Productivity; Rain; Rainfall; Remote sensing; Sedimentation & deposition; Soil conditions; Soil erosion; Soil improvement; Soil water; Sustainability management; Vegetation; water and wind erosion; Water erosion; Wind erosion
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs14215437

Soil erosion caused by water and wind is a complicated natural process that has been accelerated by human activity. It results in increasing areas of land degradation, which further threaten the productive potential of landscapes. Consistent and continuous erosion monitoring will help identify the location, magnitude, and trends of soil erosion. This information can then be used to evaluate the impact of land management practices and inform programs that aim to improve soil conditions. In this study, we applied the Revised Universal Soil Loss Equation (RUSLE) and the Revised Wind Erosion Equation (RWEQ) to simulate water and wind erosion dynamics. With the emerging earth observation big data, we estimated the monthly and annual water erosion (with a resolution of 90 m) and wind erosion (at 1 km) from 2001 to 2020. We evaluated the performance of three gridded precipitation products (SILO, GPM, and TRMM) for monthly rainfall erosivity estimation using ground-based rainfall. For model validation, water erosion products were compared with existing products and wind erosion results were verified with observations. The datasets we developed are particularly useful for identifying finer-scale erosion dynamics, where more sustainable land management practices should be encouraged.