Prioritising sub-watersheds using morphometric analysis, principal component analysis, and land use/land cover analysis in the Kinnerasani River basin, India

Due to the depletion of natural resources including land and water as a result of rapid population increase, industrialisation, and urbanisation, effective resource management is essential for long-term development. The Kinnerasani Watershed in Telangana State was chosen for the research based on morphological analysis, principal component analysis (PCA), and land use/land cover (LULC) analysis in this study. A catchment's morphometric characteristics, PCA, and LULC analysis can be estimated using geographic information system (GIS) and remote sensing (RS) approaches. The watershed generated 24 sub-watersheds (SWs) in all (SW1–SW24). SWs were ranked using morphometric features, PCA, and LULC features. To determine the final priority of SWs, several morphometric characteristics, including linear, shape, and relief aspects, have been estimated for each SW and given ranks based on compound parameter values. To prioritise SWs, the PCA was used to extract five parameters from morphometric characteristics. The LULC analysis used four characteristics to prioritise the SWs. SW3, SW9, and SW12 have been prioritised for morphometric analysis; SW2 and SW3 have been prioritised for PCA; and SW17, SW19, SW23, and SW24 have been prioritised for LULC analysis. The common SWs within each priority according to three different methodologies are SW4, SW6, SW10, SW13, SW15, and SW21. The results show that the high-priority locations have greater runoff and soil erosion issues, so it is essential to design and implement watershed management techniques such as check dams, construction of farm ponds, and construction of earthen embankments in these areas. The decision-making authorities might use the findings to plan and implement watershed management initiatives to minimise soil erosion in high-priority locations.