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 km 2 ) and 34.41% (1563.98 km 2
The assessment of groundwater vulnerability is essential especially in developing areas, where agriculture is the main source of the population. In the present study, four different overlay and index method, namely, DRASTIC, modified DRASTIC, pesticide DRASTIC and modified pesticide DRASTIC are implemented with a view to identifying the most appropriate method that predicts the vulnerable zone to groundwater pollution. Sensitivity analysis reveals that net recharge is the most influential parameter of the vulnerability index. Cross comparison of model output shows the highest similarity of 97% is observed between drastic and modified drastic while the maximum difference in models prediction of 49% is observed between modified drastic and pesticide drastic. Reported nitrate concentrations in groundwater are considered for validation of model-generated final output map. The prediction power of the models are assessed using success and prediction rate method and it highlights DRASTIC model as the most suitable model with 89.69% and 84.54% of the area under area under the curve (AUC) for success and prediction rate respectively.
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