Pixel-Based Soil Loss Estimation and Prioritization of North-Western Himalayan Catchment Based on Revised Universal Soil Loss Equation (RUSLE)

Abstract

Land degradation is a noteworthy environmental risk causing water quality issues, reservoir siltation, and loss of valuable arable lands, all of which negate sustainable development. Analysis of the effect of land use changes on erosion rate and sediment yield is particularly useful to identify critical areas and define catchment-area treatment plans. This study utilized remote sensing and geographical information system/science (GIS) techniques combined with the Revised Universal Soil Loss Equation (RUSLE) on a pixel basis to estimate soil loss over space and time and prioritized areas for action. The methodology was applied to the Sutlej catchment from the perspective of sedimentation of the Bhakra reservoir, which is leading to the loss of active storage capacity and performance and of the safety and efficiency of many existing hydroelectric projects in the Sutlej and its tributaries that drain the Himalayas. Soil loss estimation using RUSLE was first calibrated using data from three sites, and the calibrated model was then used to estimate catchment soil loss for 21 years (1995–2015). The number of land use/land cover (LULC) classes as 14 and the C factor as 0.63 for agriculture land were optimized using the observed data for the Sutlej catchment. Further, the linkage between soil erosivity and annual precipitation was also established. It was concluded that extensive control treatment would be necessary from the soil and water conservation point of view. Structures like check dams, terraces, bunds, and diversion drains in the upstream can overcome the issue of fragmentation of soil in the Sutlej catchment.