Watershed prioritization using morphometric analysis by MCDM approaches

Due to the highly complex nature of human and ecological systems, soil erosion has increased considerably. Therefore, understanding watersheds and future forecasting circumstances using a watershed approach must be developed significantly on a spatial dimension. It's crucial to understand the watershed's key zones with a lineage of soil erosion as they undergo stream displacement and soil erosion issues. So, there is a need for proper soil and water management treatments to overcome continuous soil loss by runoff and other ecological problems in the Pindar watershed. In this study, an attempt has been made to explore several morphometric characteristics of the Pindar River watershed, which is located in the Uttarakhand districts of Chamoli and Bageshwar, using Geographic Information System (GIS) and remote sensing techniques for prioritizing the sub-watersheds in order to develop a suitable management plan to combat land degradation in order to assist in future management and conservation by four Multi-Criteria Decision Making (MCDM) techniques, viz., Analytical Hierarchy Process (AHP), Fuzzy Analytic Hierarchy Process (FAHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Finally, the performance of MCDM prioritization techniques was evaluated. For this purpose, 13 morphometric characteristics, including basic, linear, form, and landscape, were extracted and analyzed using an SRTM DEM with a spatial resolution of 30 m. Sub-watersheds' prioritization revealed that, according to the AHP, FAHP, TOPSIS, and VIKOR models, sub-watershed 26 is the most prone to erosion. The findings demonstrated that morphometric criteria are highly effective at identifying erosion-prone locations. The evaluation of the MCDM approaches has been done based on the percentage of changes and the intensity of the changes. The results indicated that the FAHP, with a change percentage of 71.21, has more efficiency and accuracy than the VIKOR, AHP, and TOPSIS methods, with 62.89%, 62.88%, and 62.12%, respectively. The results of the evaluation of the intensity of changes showed that the FAHP model had the highest rate of change (1.22), whereas the AHP, TOPSIS, and VIKOR methods, with the intensity of changes of 1.09, 1.09, and 1.07, placed in the next rank. Concerning the values of the percentage of changes and the intensity, it can be stated that the FAHP model has been more accurate than the other models.