Demarcation of Potential Groundwater Recharge Zones Through REMOTE Sensing, GIS, and MCDA: A Case Study of the Aji River Basin in Saurashtra, Gujarat, India

Abstract

Groundwater is an important and valuable natural resource. Due to extensive agricultural practices and industrial developments, groundwater resources have recently been overexploited and depleted. Therefore, there is a need to adopt sustainable water resource management practices to augment groundwater recharge. This study uses advanced geospatial technologies to identify potential groundwater recharge zones in the Aji River Basin in the Saurashtra region of Gujarat, India. The primary objective was to enhance potential groundwater recharge zones in the Aji River basin region. Therefore, various parameters affecting groundwater availability, including lineament, geology, soil, density, slope, rainfall, land use/land cover, geomorphology, and drainage density, were considered for delineating potential groundwater recharge zones. The integrated approach, using remote sensing (RS), geographical information system (GIS), and multi-criteria decision analysis (MCDA), was employed to achieve this. The influence factor was determined through Satty`s analytic hierarchy process (AHP) method. The sub-parameters were ranked according to the AHP scale, and a weighted overlay analysis tool in ArcGIS software was utilized to map the potential groundwater recharge zones in the basin. The concluding map was categorized into five distinct zones based on potential groundwater recharge zones: ‘Excellent’ (50.50 km2, 2.36 %), ‘Good’ (1376.78 km2, 64.56 %), ‘Moderate’ (599.14 km2, 28.09 %), ‘Poor’ (90.67 km2, 4.25 %), and ‘Very Poor’ (15.32 km2,0.718 %). The SCS-Curve number method was employed to assess the potential for rainfall-induced runoff. The Aji River basin exhibited a weighted mean rainfall and runoff of 622.68 mm and 241.07 mm, respectively. The estimated weighted runoff for the Aji River basin was 514.07 million cubic meters (MCM), with a 75 % exceedance probability, resulting in a runoff of 152.97 MCM. This study concludes that integrating remote sensing, GIS, and MCDA techniques effectively identifies and delineates potential groundwater recharge zones, which is crucial for sustainable water resource management.