Morphometric and hypsometric analysis with LULC assessment for prioritizing micro watersheds in the Kagemaduvu sub watershed of Kaveri River Basin India

Abstract Morphometric analysis, integrated with remote sensing (RS) and Geographic Information System (GIS), provides a critical framework for the assessment and prioritization particularly in data-scarce regions. The study aims to prioritize the five-micro-watersheds with in the 42.58 km 2 of Kagemaduvu sub-watershed of the Kaveri River Basin, Karnataka, India by integrating morphometric, hypsometric and land use land cover (LULC) information. The high-resolution CARTOSAT DEM (10 m) was used to delineate the drainage network, micro-watersheds and key morphometric parameters representing linear, areal and relief aspects were derived using ArcGIS 10.8.2. The sub-watershed exhibits a dendritic drainage pattern and the stream order ranges from first to fifth. Drainage density values ranged from 1.915 to 3.116 km/km², while HI values varied between 0.192 (old stage) and 0.383 (mature stage), indicating differences in geomorphic development and erosion susceptibility among the micro-watersheds. Unlike conventional Compound Factor (CF) studies, which report priority rankings without further checks, the CF-hypsometric ranking derived here was cross-validated against independent LULC evidence, and its sensitivity to the flow-accumulation threshold and equal-weighting assumptions was explicitly assessed — offering a replicable validation protocol for prioritization studies in ungauged basins. A compound factor based prioritization identified Arisinakunte and Kuthnagere micro-watersheds as the highest-priority micro-watersheds for soil and water conservation. The study highlights the value of morphometric analysis in the prioritization of sub-watersheds and supports the implementation of targeted management strategies such as afforestation, check dams and terracing. The findings offer critical insights for sustainable watershed development planning and can serve as a replicable model for similar ungauged basins. The integrated framework developed in this study provides a reliable basis for prioritizing erosion-prone micro-watersheds and supports informed decision-making for sustainable soil and water conservation.