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• W4320481188 endingPage "49874" @default.
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• W4320481188 abstract "Abstract This study evaluated the susceptibility to groundwater pollution using a modified DRASTIC model. A novel hybrid multi-criteria decision-making (MCDM) model integrating Interval Rough Numbers (IRN), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Analytical Network Process (ANP) was used to investigate the interrelationships between critical hydrogeologic factors (and determine their relative weights) via a novel vulnerability index based on the DRASTIC model. The flexibility of GIS in handling spatial data was employed to delineate thematic map layers of the hydrogeologic factors and to improve the DRASTIC model. The hybrid MCDM model results show that net recharge (a key hydrogeologic factor) had the highest priority with a weight of 0.1986. In contrast, the topography factor had the least priority, with a weight of 0.0497. A case study validated the hybrid model using Anambra State, Nigeria. The resultant vulnerability map shows that 12.98% of the study area falls into a very high vulnerability class, 31.90% falls into a high vulnerability, 23.52% falls into the average vulnerability, 21.75% falls into a low vulnerability, and 9.85% falls into very low vulnerability classes, respectively. In addition, nitrate concentration was used to evaluate the degree of groundwater pollution. Based on observed nitrate concentration, the modified DRASTIC model was validated and compared to the traditional DRASTIC model; interestingly, the spatial model of the modified DRASTIC model performed better. This study is thus critical for environmental monitoring and implementing appropriate management interventions to protect groundwater resources against indiscriminate sources of pollution." @default.
• W4320481188 created "2023-02-14" @default.
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• W4320481188 date "2023-02-14" @default.
• W4320481188 modified "2023-09-27" @default.
• W4320481188 title "Groundwater vulnerability to pollution assessment: an application of geospatial techniques and integrated IRN-DEMATEL-ANP decision model" @default.
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• W4320481188 doi "https://doi.org/10.1007/s11356-023-25447-1" @default.
• W4320481188 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36781674" @default.
• W4320481188 hasPublicationYear "2023" @default.
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