Morphometric analysis for prioritizing critical areas of Urpash watershed in Sindh catchment of the lesser Himalayas using RS and GIS approach.

Effective soil and water conservation is critical in fragile watersheds prone to erosion. However, assessing erosion susceptibility in ungauged watersheds remains challenging due to the lack of observed hydrological data This study addresses this gap by employing a comprehensive morphometric analysis integrated with remote sensing (RS) and Geographic Information Systems (GIS) to prioritize erosion-prone sub-watersheds within the ecologically sensitive and data-scarce Urpash watershed. Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) data and ArcGIS 10.7 were used to analyze a 21.37 km² area. Key morphometric parameters-including linear, areal, and relief aspects-were assessed to understand watershed hydrology and erosion susceptibility. A total of 32 streams were identified, categorized into 1st to 3rd orders. Watershed shape indices, such as elongation ratio (Re = 0.65), form factor (Rf = 0.33) and circularity ratio (Rc = 0.295), indicate an elongated shape, indicative of reduced surface runoff and erosion potential, along with higher sub-soil permeability. However, drainage parameters like drainage density (Dd = 1.67 km/km2), stream frequency (Fs = 1.49 km-2) and drainage intensity (Di = 0.89 km-1) pointed to the watershed's susceptibility to flooding, gully erosion, and landslides due to slow surface runoff dispersion. Relief parameters such as basin relief (H = 1742.87 m), relief ratio (Rh = 0.22) and ruggedness number (Rn = 2.9) reflect the watershed's high relief and steep terrain, indicating a greater susceptibility to erosion. Using a compound parameter approach, the sub-watershed prioritisation ranked WS3 as the highest priority, followed by WS4, WS5, WS6, WS2, and WS1. By using RS and GIS-based morphometric analysis in an ungauged Urpash watershed, this study provides a geospatial framework for targeted soil and water conservation strategies, contributing to more precise watershed management in data-scarce and erosion-vulnerable regions.