Vertical electrical sounding survey and resistivity inversion using genetic algorithm optimization technique

Abstract

Summary Growing water scarcity in West Midnapore district of West Bengal, India, is threatening sustainable agricultural production as well as sanitation of the inhabitants. Because of its several inherent qualities, groundwater can play an important role in ensuring sustainable water supply in the district. This study was carried out to assess groundwater condition in the Salboni Block of West Midnapore district using surface resistivity method. Vertical electrical sounding (VES) surveys were carried out at 38 sites using the Schlumberger array. The apparent resistivity-depth datasets (henceforth called ‘VES data’) thus obtained were interpreted by the genetic algorithm (GA) optimization technique. A GA-based stand-alone computer program was developed for optimizing subsurface layer parameters (true resistivity and thickness) from the VES data. The optimal layer parameters were then correlated with the available well logs to identify aquifer and confining layers. Moreover, a groundwater potential map was created by integrating the thematic layers of aquifer resistivity and thickness in a GIS environment. In order to explore the spatial variation of layer resistivity at a particular depth, resistivity contour maps of the study area for different depths were prepared using ArcView software. The GA technique yielded layer parameters with reasonably low values of root mean square error (0.36–9.75 Ω m) for most VES datasets. It was found that shallow aquifers exist at depths ranging from 4 to 19 m and relatively deep aquifers from 24 to 60 m below the ground surface. The study area is classified into ‘very good’, ‘good’, ‘moderate’ and ‘poor’ groundwater potential zones, with a majority of the area having good to moderate groundwater prospect. The resistivity contour maps for different depths revealed that deeper aquifers are prevalent in the study area. It is concluded that the GA technique is efficient and reliable for determining subsurface layer parameters from the VES data and that the developed groundwater potential map is useful for effective groundwater development in the study area.