Development of hierarchical fuzzy model for groundwater vulnerability to pollution assessment

Abstract

There is a need to develop new modelling techniques that assess groundwater vulnerability with less extensive data and which are robust when data are uncertain and incomplete. In this present study, a hierarchical fuzzy system (HFS) model was developed to systematically quantify uncertainties associated with hydro-geological conditions of the site in groundwater vulnerability assessment. The need for hierarchical fuzzy expert systems can occur frequently for higher number of input variables. The HFS model was designed for seven input variables viz. depth to water table (D), net recharge (R), aquifer media (A), soil media (S), topography (T), impact of vadose zone (I), and hydraulic conductivity (C). The model was validated by the observed nitrate concentrations in groundwater. The HFS model was applied to groundwater vulnerability assessment in Ranchi district, Jharkhand, India. Sensitivity analysis of model was also demonstrated and compared the results with that of the existing method (DRASTIC model). It was observed that HFS model are better sensitive to the input parameters in comparison to that of the DRASTIC model. The present study offers a unique tool to policy makers for decision makings in groundwater management.