Erosion Area Prioritization for a Himalayan River Basin Using Entropy Weighting Multi-criteria Decision-Making (E-MCDM)

The vast Himalayan geography cannot be managed altogether for soil conservation practices. Therefore, identification of most severe areas is one way to proceed further. In this regard, this study has presented a watershed prioritization framework for the Himalayan Gandak River basin using morphological parameters and Multi-Criteria Decision-Making (MCDM) approach. In this study, twenty-three morphometric parameters related to linear, shape, basic, and landscape characteristics of watersheds have been derived using 30 m resolution digital elevation model (DEM) from Shuttle Radar Topographic Mission (SRTM) and GIS techniques. Among twenty-three, sixteen morphological parameters were used as input criteria for four MCDM methods viz. COPRAS, SAW, VIKOR, and TOPSIS. The weight of the criteria was determined using automated Entropy weighting method. The results of MCDM methods were compared using percentage of change (∆P) and intensity of change (∆I) statistical indicators which categorized TOPSIS as best MCDM method than others to prioritize the watersheds for soil erosion. The TOPSIS method categorized the watersheds, WS13 (Qi = 0.87) and WS8 (Qi = 0.78), into first and second rank and demarked them into very high severe soil erosion index. Also, COPRAS and SAW have categorized the watersheds into low, medium, and high soil erosion susceptibility priority index. However, VIKOR and TOPSIS have categorized the watersheds into low, medium, and high priority indices. Also, it has been found that the rank of the watersheds has negative power function with mean bifurcation and second-order polynomial relation with compactness coefficient (Cc) and relief ration (Rf). Overall, each MCDM method was able to identify the erosion-prone watersheds, however, TOPSIS had higher predictive accuracy than others. Therefore, the TOSIS MCDM method can categorize and identify the severe erosion-prone watersheds in the Himalayan region.