Use of geospatial technology for delineating groundwater potential zones with an emphasis on water-table analysis in Dwarka River basin, Birbhum, India

Thapa, Raju; Gupta, Srimanta; Gupta, Arindam; Reddy, D.V.; Kaur, Harjeet

Use of geospatial technology for delineating groundwater potential zones with an emphasis on water-table analysis in Dwarka River basin, Birbhum, India | Utilisation de la technologie géospatiale pour la délimitation des zones aquifères potentiels en mettant l’accent sur l’analyse du niveau piézométrique dans le bassin de la rivière Dwarka, Birbhum, Inde Utilización de la tecnología geoespacial para la definición de zonas potenciales de agua subterránea con énfasis en el análisis de los niveles freáticos en la cuenca del río Dwarka, Birbhum, India 利用地质空间技术描述印度比尔普姆地区Dwarka河流域地下水潜力带,重点进行水位分析 Uso de tecnologia geoespacial para delinear zonas potenciais para águas subterrâneas com uma ênfase em análise do lençol freático na bacia do Rio Dwarka, Birbhum, Índia

2018

Thapa, Raju | Gupta, Srimanta | Gupta, Arindam | Reddy, D.V. | Kaur, Harjeet

Dwarka River basin in Birbhum, West Bengal (India), is an agriculture-dominated area where groundwater plays a crucial role. The basin experiences seasonal water stress conditions with a scarcity of surface water. In the presented study, delineation of groundwater potential zones (GWPZs) is carried out using a geospatial multi-influencing factor technique. Geology, geomorphology, soil type, land use/land cover, rainfall, lineament and fault density, drainage density, slope, and elevation of the study area were considered for the delineation of GWPZs in the study area. About 9.3, 71.9 and 18.8% of the study area falls within good, moderate and poor groundwater potential zones, respectively. The potential groundwater yield data corroborate the outcome of the model, with maximum yield in the older floodplain and minimum yield in the hard-rock terrains in the western and south-western regions. Validation of the GWPZs using the yield of 148 wells shows very high accuracy of the model prediction, i.e., 89.1% on superimposition and 85.1 and 81.3% on success and prediction rates, respectively. Measurement of the seasonal water-table fluctuation with a multiplicative model of time series for predicting the short-term trend of the water table, followed by chi-square analysis between the predicted and observed water-table depth, indicates a trend of falling groundwater levels, with a 5% level of significance and a p-value of 0.233. The rainfall pattern for the last 3 years of the study shows a moderately positive correlation (R ² = 0.308) with the average water-table depth in the study area.

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