Groundwater assessment through an integrated approach using remote sensing, GIS and resistivity techniques: a case study from a hard rock terrain

Satellite data have been widely used in conjunction with Geographic Information System (GIS) techniques in groundwater resource management. Satellite data are useful for extracting various thematic maps required for groundwater assessment. In this study, Indian Remote Sensing (IRS) 1D LISS III and Landsat Thematic Mapper (TM)/Enhanced TM (ETM+) digital data, and digital elevation models (DEMs) from the Shuttle Radar Topography Mission (SRTM) along with other collateral data were analysed to create various thematic maps (geomorphology, landuse, lithology, lineament, soil, drainage density, river gradient and slope maps) required for groundwater modelling in a hard rock terrain of Bargarh district, Orissa, India. These thematic maps were assigned suitable weights and different rankings to the individual classes within each thematic map using Saaty's Analytical Hierarchy Process (AHP). A raster-based empirical GIS model was developed for integrating the thematic maps to locate suitable groundwater prospective zones. The integrated thematic maps were in turn used to compute the Groundwater Potential Index (GWPI). GWPI values calculated in the study area were found to vary from 0.175 to 0.940. These GWPI values have been classified into various classes: very poor (< 0.4), poor (0.4-0.5), moderate (0.5-0.6), good (0.6-0.7), very good (0.7-0.8) and excellent (> 0.8). A final map showing very poor to excellent groundwater prospective zones was prepared. The results thus obtained were subsequently cross-checked with resistivity survey and pumping test data. Very poor GWPI zones show low yields of 0.5 lps from weathered granite of resistivity 20-100 Omega m and thickness 0.5-6 m, while excellent GWPI zones show high yields of 5-7 lps from highly fractured granite of resistivity 100-300 Omega m and thickness 14-31 m. The results obtained from integration of the various thematic maps on the GIS platform produced a good match with the resistivity and pumping test data.