TY - JOUR
T1 - Groundwater risk assessment based on optimization framework using DRASTIC method
AU - Jafari, Seyedeh Mahboobeh
AU - Nikoo, Mohammad Reza
N1 - Publisher Copyright:
© 2016, Saudi Society for Geosciences.
PY - 2016/12/1
Y1 - 2016/12/1
N2 - Due to anthropogenic influences and large amounts of pollutant released into the groundwater, it is vital to investigate groundwater quality and to characterize susceptible areas to contamination. In this paper, a new optimization-based methodology is proposed for determining groundwater risk using DRASTIC model based on genetic algorithm optimization model and Wilcoxon test. The correlation coefficient between DRASTIC/modified DRASTIC indices and nitrate concentrations in monitoring wells is used as a criteria for evaluating the efficiency of the proposed models. In this regard, because of the unsatisfactory original DRASTIC’s result, sensitivity analysis, genetic algorithm (GA), and Wilcoxon test (1945) are carried out to tackle the subjectivity associated with the original DRASTIC model and obtain better and reliable results. The results indicate that application of Wilcoxon test and GA optimization outperforms the others. Consequently, the correlation coefficient increased remarkably as compared to the original DRASTIC model (from 0.57 to 0.82). The proposed optimization process is adaptable to be applied in different case studies; mainly since it has the ability to optimize the weights of the model based on hydrogeological characteristics of the aquifer. Finally, the risk maps of the models are prepared using ArcGIS® to determine the most vulnerable areas.
AB - Due to anthropogenic influences and large amounts of pollutant released into the groundwater, it is vital to investigate groundwater quality and to characterize susceptible areas to contamination. In this paper, a new optimization-based methodology is proposed for determining groundwater risk using DRASTIC model based on genetic algorithm optimization model and Wilcoxon test. The correlation coefficient between DRASTIC/modified DRASTIC indices and nitrate concentrations in monitoring wells is used as a criteria for evaluating the efficiency of the proposed models. In this regard, because of the unsatisfactory original DRASTIC’s result, sensitivity analysis, genetic algorithm (GA), and Wilcoxon test (1945) are carried out to tackle the subjectivity associated with the original DRASTIC model and obtain better and reliable results. The results indicate that application of Wilcoxon test and GA optimization outperforms the others. Consequently, the correlation coefficient increased remarkably as compared to the original DRASTIC model (from 0.57 to 0.82). The proposed optimization process is adaptable to be applied in different case studies; mainly since it has the ability to optimize the weights of the model based on hydrogeological characteristics of the aquifer. Finally, the risk maps of the models are prepared using ArcGIS® to determine the most vulnerable areas.
KW - Genetic algorithm
KW - Groundwater risk
KW - Modified DRASTIC
KW - Shiraz plain
KW - Spearman’s correlation
KW - Wilcoxon test
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U2 - 10.1007/s12517-016-2756-4
DO - 10.1007/s12517-016-2756-4
M3 - Article
AN - SCOPUS:85002551744
SN - 1866-7511
VL - 9
JO - Arabian Journal of Geosciences
JF - Arabian Journal of Geosciences
IS - 20
M1 - 742
ER -