Prioritizing geographic parcels for improved catchment conservation using morphometry, landuse, and soil characteristics following statistical and MCDM techniques

The study presents a multi-faceted approach to prioritize sub-watersheds for catchment conservation, using morphometry, land use, and soil characteristics in a GIS-assisted framework. By integrating statistical techniques namely Principal Component Analysis for dimension reduction and CRITIC method, the study identifies the most influencing morphometric parameters and weighs them over each other which otherwise largely remains ambiguous. The framework is applied to the sub-basin in the Upper Ganga Basin, Uttar Pradesh where 11 sub-watersheds were analyzed. Morphometric indices namely the drainage density, stream frequency, and slope were prioritized. Additionally, land use and soil data were evaluated to develop a compounded prioritization strategy. The study reveals that around 69% (~ 21,636 sq. km) of the drainage area falls under high (39.70%) and very high (29.44%) priority classes for conservation interventions. The methodology offers an efficient, data-driven solution for identifying vulnerable areas for soil and water conservation, especially where fiscal and manpower constraints exist. However, it acknowledges limitations related to data granularity and static data inputs, recommending the adoption of semi-distributed hydrologic models to enhance precision in regions of relatively high priority. Withal, the presented work digresses from the contemporary approaches and contributes to the segment of water and soil conservation towards combating land degradation and Climate Change impacts.