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Simulating climate change impact on soil erosion using RUSLE model A case study in a watershed of mid-Himalayan landscape

  • Surya Gupta
  • Suresh KumarEmail author
Article

Abstract

Climate change, particularly due to the changed precipitation trend, can have a severe impact on soil erosion. The effect is more pronounced on the higher slopes of the Himalayan region. The goal of this study was to estimate the impact of climate change on soil erosion in a watershed of the Himalayan region using RUSLE model. The GCM (general circulation model) derived emission scenarios (HadCM3 A2a and B2a SRES) were used for climate projection. The statistical downscaling model (SDSM) was used to downscale the precipitation for three future periods, 2011–2040, 2041–2070, and 2071–2099, at large scale. Rainfall erosivity (R) was calculated for future periods using the SDSM downscaled precipitation data. ASTER digital elevation model (DEM) and Indian Remote Sensing data – IRS LISS IV satellite data were used to generate the spatial input parameters required by RUSLE model. A digital soil-landscape map was prepared to generate spatially distributed soil erodibility (K) factor map of the watershed. Topographic factors, slope length (L) and steepness (S) were derived from DEM. Normalised difference vegetation index (NDVI) derived from the satellite data was used to represent spatial variation vegetation density and condition under various land use/land cover. This variation was used to represent spatial vegetation cover factor. Analysis revealed that the average annual soil loss may increase by 28.38, 25.64 and 20.33% in the 2020s, 2050s and 2080s, respectively under A2 scenario, while under B2 scenario, it may increase by 27.06, 25.31 and 23.38% in the 2020s, 2050s and 2080s, respectively, from the base period (1985–2013). The study provides a comprehensive understanding of the possible future scenario of soil erosion in the mid-Himalaya for scientists and policy makers.

Keywords

Climate change soil erosion statistical downscaling model (SDSM) revised universal soil loss equation (RUSLE). 

Notes

Acknowledgements

Authors are sincerely thankful to Indian Space Research Organisation (ISRO) for providing financial support under Earth Observation Applications Mission (EOAM) project (ISRO/DOS) on ‘Mountain Ecosystem Processes and Services’ to carry out the research work. We are grateful to Department of Meteorology, Uttarakhand University of Horticulture and Forestry for Ranichauri (Uttarakhand) for providing weather data for used for validation. We sincerely thank Dr S K Saha, Ex-Dean (A) and Director, IIRS for encouraging the present research work.

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© Indian Academy of Sciences 2017

Authors and Affiliations

  1. 1.Indian Institute of Remote Sensing, Indian Space Research OrganisationDehradunIndia

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