Abstract
Remote sensing and GIS play a vital role in exploration and assessment of groundwater and has wide application in detection, monitoring, assessment, conservation and various other fields of groundwater-related studies. In this research work, delineation of groundwater potential zone in Birbhum district has been carried out. Various thematic layers viz. geology, geomorphology, soil type, elevation, lineament and fault density, slope, drainage density, land use/land cover, soil texture, and rainfall are digitized and transformed into raster data in ArcGIS 10.3 environment as input factors. Thereafter, multi-influencing factor (MIF) technique is employed where ranks and weights, assigned to each factor are computed statistically. Finally, groundwater potential zones are classified into four categories namely low, medium, high and very high zone. It is observed that 18.41% (836.86 km2) and 34.41% (1563.98 km2) of the study area falls under ‘low’ and ‘medium’ groundwater potential zone, respectively. Approximately 1601.19 km2 area accounting for 35.23% of the study area falls under ‘high’ category and ‘very high’ groundwater potential zone encompasses an area of 542.98 km2 accounting for 11.95% of the total study area. Finally, the model generated groundwater potential zones are validated with reported potential yield data of various wells in the study area. Success and prediction rate curve reveals an accuracy achievement of 83.03 and 78%, respectively. The outcome of the present research work will help the local authorities, researchers, decision makers and planners in formulating better planning and management of groundwater resources in the study area in future perspectives.
Highlights
In India demand of groundwater resources continuously increases with the advent of industrialisation and population expansions
Various techniques have been adopted by various researchers such as, frequency ratio (Manap et al 2014; Razandi et al 2015), multi-criteria decision evaluation (MCDE) (Murthy and Mamo 2009; Machiwal and Singh 2015; Jothibasu and Anbazhagan 2016), artificial neural network (ANN) (Lee et al 2012b), random forest model (Naghibi et al 2016; Zabihi et al 2016) logistic regression model (Pourtaghi and Pourghasemi 2014) and analytic hierarchy process (AHP) (Adiat et al 2012)
The present study aims to elucidate the groundwater potential zone within Birbhum district with the help of remote sensing, and multi-influencing factor (MIF) techniques
Summary
In India demand of groundwater resources continuously increases with the advent of industrialisation and population expansions. Over-exploitation of groundwater has led to fluoride contamination in both water table aquifer and confined aquifer of groundwater in some parts of the Birbhum district (PHED report 2007; Mondal et al 2014; Thapa et al 2016). In this context, demarcating groundwater potential zone is essential to locate high groundwater potential areas for future consumptive use. Several blocks in Birbhum district are affected with fluoride occurrence in groundwater (PHED 2007; Mondal et al 2014; Thapa et al 2016)
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