Assessment of groundwater utilization status and prediction of water table depth using different heuristic models in an Indian interbasin

Abstract

The knowledge of fluctuation of water table depth is highly required for proper planning and sustainable development of available water resources. This study intends to study groundwater behaviour under changing scenario in the lower part of Ganga–Ramganga interbasin. It also investigates the comparative performance of soft computing techniques, i.e. co-active neuro-fuzzy inference system (CANFIS), fuzzy logic and radial basis function network (RBFN), which are used for prediction of water table depth in the study area. Components of groundwater recharge and discharge along with seasonal water table depth covering a period of 23 years (1990–2012) are used to develop four combination sets of input variables. Different CANFIS structures, fuzzy logic rules and RBFN structures are applied to these combinations of input variables, and the best combinations are selected on the basis of the values of different performance indicators such as coefficient of determination (R2), mean absolute deviation, root mean square error, coefficient of variation of error residuals, Nash–Sutcliff efficiency, correlation coefficient (r), absolute prediction error and performance index. The result of this study indicates the superiority of fuzzy logic rule-based model than of CANFIS models and RBFN model in predicting water table depth.