Fuzzy vulnerability mapping of urban groundwater systems to nitrate contamination. (October 2017) - Asadi, Parisa; Hosseini, Seiyed Mossa; Ataie-Ashtiani, Behzad; Simmons, Craig T.
Abstract: The aim of this study is to develop a new fuzzy optimization model to find the optimal factor weights of modified DRASTIC index for groundwater vulnerability mapping an urban aquifer to nitrate contamination. Eight factors including water table depth, recharge, aquifer media, soil media, topography, impact of vadose zone, hydraulic conductivity, and land use are considered and rated. A fuzzy linear regression is formulated between the values of eight factors and corresponding nitrate concentration in groundwater. An optimization model based on real code genetic algorithm with objective of minimizing the sum of the fuzzy spread of the regression coefficients is implemented. Aquifer of Mashhad metropolis (northeast of Iran) is chosen to evaluate the proposed model. The results show the proposed model is a promising tool for weighting the factors with avoiding the subjectivity and also ambiguities accompanied by parameters to produce an accurate specific vulnerability mapping of an urban aquifer. Highlights: We applied fuzzy linear optimization model for the first time to find the optimal factor weights of modified DRASTIC index. The proposed model outperforms the customary overlay/index methods in vulnerability mapping of urban aquifer. Land use plays significant role in producing vulnerability groundwater map in the urban areas. Proposed model solves the subjectivity disadvantage of overlay/index methods by assigning weights to DRASTIC attributes.