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Estimation of Spatial and Seasonal Variability of Soil Erosion in a Cold Arid River Basin in Hindu Kush Mountainous Region Using Remote Sensing

doi: 10.3390/su13031549
An approach is proposed in the present study to estimate the soil erosion in data-scarce Kokcha subbasin in Afghanistan. The Revised Universal Soil Loss Equation (RUSLE) model is used to estimate soil erosion. The satellite-based data are used to obtain the RUSLE factors. The results show that the slight (71.34%) and moderate (25.46%) erosion are dominated in the basin. In contrast, the high erosion (0.01%) is insignificant in the study area. The highest amount of erosion is observed in Rangeland (52.2%) followed by rainfed agriculture (15.1%) and barren land (9.8%) while a little or no erosion is found in areas with fruit trees, forest and shrubs, and irrigated agriculture land. The highest soil erosion was observed in summer (June–August) due to snow melting from high mountains. The spatial distribution of soil erosion revealed higher risk in foothills and degraded lands. It is expected that the methodology presented in this study for estimation of spatial and seasonal variability soil erosion in a remote mountainous river basin can be replicated in other similar regions for management of soil, agriculture, and water resources.
- Islamic Azad University Central Tehran Branch Iran (Islamic Republic of)
- Islamic Azad University of Falavarjan Iran (Islamic Republic of)
- Universiti Teknologi MARA Malaysia
- Luleå University of Technology Sweden
- Universiti Teknologi MARA Malaysia
Environmental effects of industries and plants, Afghanistan, TJ807-830, TA Engineering (General). Civil engineering (General), Geotechnical Engineering and Engineering Geology, Fluvisol, TD194-195, Renewable energy sources, Environmental sciences, remote sensing, data scarcity, RUSLE, GE1-350, Geoteknik och teknisk geologi
Environmental effects of industries and plants, Afghanistan, TJ807-830, TA Engineering (General). Civil engineering (General), Geotechnical Engineering and Engineering Geology, Fluvisol, TD194-195, Renewable energy sources, Environmental sciences, remote sensing, data scarcity, RUSLE, GE1-350, Geoteknik och teknisk geologi
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