Abstract

Decline in groundwater level in recent years is the serious threat that needs attention. To address this an effective management approach is required. Highlighting the groundwater potential zones is the key factor in which the region where optimal extraction and augmentation of existing resources can be carried out. This works elaborates the Groundwater Potential (GWP) mapping for the Arkavathi sub-watershed having an area of 866 km2 which encompasses two extensively urbanized regions: Bangalore rural and Bangalore urban. The existence of groundwater along with its origin and movement was controlled by several factors like geomorphology, geology, soil, drainage density, lineament density, slope, land use, and rainfall variation. These factors were created as thematic layers from satellite images and other real-time data sources that are geo-rectified and projected to UTM (43 N) for easy handling of data in a GIS environment. The Analytical Hierarchy Process (AHP) a Multi-Criteria Decision Making (MCDM) based method has been adopted for weight determination, assigned for the corresponding thematic layers. The resultant groundwater potential zone (GWP) zone map of the Arkavathi sub-watershed was obtained by performing an overlay analysis of these layers. The final GWP map has been categorized into five classes, namely Very good, Good, Moderate, Poor, and Very poor based on the index value. From the results it was observed that the very high potential zone comprises 8.614% (74.29 km2), high 23.872% (205.89 km2), moderate 31.40% (270.84 km2), poor 23.86% (205.85 km2) and 12.24% (105.58 km2) very poor, respectively. Besides, the derived GWP zone map was validated with the groundwater fluctuation data collected from 14 pumping well from Central Ground Water Board (CGWB), based on the results the performance of the model results found satisfactory. Hence the results obtained can be utilized by the local and government authorities to identify a suitable zone for the exploration of new groundwater wells without affecting future sustainability.

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