TY - JOUR
T1 - Fuzzy vulnerability mapping of urban groundwater systems to nitrate contamination
AU - Asadi, Parisa
AU - Hosseini, Seiyed Mossa
AU - Ataie-Ashtiani, Behzad
AU - Simmons, Craig T.
PY - 2017/10
Y1 - 2017/10
N2 - 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.
AB - 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.
KW - Fuzzy set theory
KW - Modified DRASTIC index
KW - Nitrate contamination
KW - Specific vulnerability mapping
KW - Urban aquifer
UR - http://www.scopus.com/inward/record.url?scp=85021786959&partnerID=8YFLogxK
U2 - 10.1016/j.envsoft.2017.06.043
DO - 10.1016/j.envsoft.2017.06.043
M3 - Article
SN - 1364-8152
VL - 96
SP - 146
EP - 157
JO - Environmental Modelling and Software
JF - Environmental Modelling and Software
ER -