Exploring groundwater potential: Combining GIS techniques with OLS, GWR, and exploratory regression

Abstract

This study investigates groundwater potential in the Wular Lake Basin, Kashmir Valley, India. Utilizing GIS, remote sensing, Geographically Weighted Regression (GWR), and exploratory regression analysis, the research aims to map groundwater potential. By integrating topographical and hydrological indices with statistical methods, key factors influencing groundwater potential, such as Channel Base Level (ChNBL), Valley Depth (ValleyD), and Topographic Wetness Index (TWI), were identified. The study focuses on the Wular Lake Basin in the Kashmir Valley, India, known for its complex topography and significant hydrological dynamics. This area's unique characteristics require a thorough analysis to understand groundwater potential and guide sustainable management strategies. The study presents a detailed groundwater potential map, categorizing the basin into zones with varying recharge potential. Validation through an Ordinary Least Squares (OLS) regression model ensures the model's robustness and absence of multicollinearity. These potential zones offer insights for sustainable groundwater management and resource planning. The research also highlights the applicability of this framework to similar regions, providing a valuable approach for groundwater resource assessment and management. The findings emphasize integrated water resource strategies to address environmental challenges in the region. • Key predictors: Channel Base Level, Valley Depth, Topographic Wetness Index. • Groundwater map zones enhance sustainable management and resource planning. • Model robustness ensured through OLS regression validation. • Framework is valuable for groundwater assessment in similar regions.