Groundwater vulnerability to pollution assessment : an application of geospatial techniques and integrated IRN-DEMATEL-ANP decision model

dc.contributor.authorChukwuma, Emmanuel Chibundo
dc.contributor.authorOkonkwo, Chris Chris
dc.contributor.authorAfolabi, Oluwasola Olakunle Daniel
dc.contributor.authorPham, Quoc Bao
dc.contributor.authorAnizoba, Daniel Chinazom
dc.contributor.authorOkpala, Chikwunonso Divine
dc.date.accessioned2024-05-28T11:39:43Z
dc.date.available2024-05-28T11:39:43Z
dc.date.issued2023-04
dc.descriptionDATA AVAILABILITY : In addition to the supplementary material, all other data and materials are available upon request.en_US
dc.description.abstractThis study evaluated the susceptibility to groundwater pollution using a modified DRASTIC model. A novel hybrid multicriteria 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.en_US
dc.description.departmentFuture Africaen_US
dc.description.librarianam2024en_US
dc.description.sdgSDG-06:Clean water and sanitationen_US
dc.description.urihttps://www.springer.com/journal/11356en_US
dc.identifier.citationChukwuma, E.C., Okonkwo, C.C., Afolabi, O.O.D. et al. 2023, 'Groundwater vulnerability to pollution assessment: an application of geospatial techniques and integrated IRN-DEMATEL-ANP decision model', Environmental Science and Pollution Research, vol. 30, pp. 49856-49874. https://DOI.org/10.1007/s11356-023-25447-1.en_US
dc.identifier.issn0944-1344 (print)
dc.identifier.issn1614-7499 (online)
dc.identifier.other10.1007/s11356-023-25447-1
dc.identifier.urihttp://hdl.handle.net/2263/96271
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rights© The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License.en_US
dc.subjectGroundwater pollutionen_US
dc.subjectDecision-making modelen_US
dc.subjectDrastic modelen_US
dc.subjectEnvironmental monitoringen_US
dc.subjectSDG-06: Clean water and sanitationen_US
dc.subjectMulticriteria decision-making (MCDM)en_US
dc.subjectAnalytical network process (ANP)en_US
dc.subjectInterval rough numbers (IRN)en_US
dc.subjectDecision making trial and evaluation laboratory (DEMATEL)en_US
dc.subjectGeographic information system (GIS)en_US
dc.titleGroundwater vulnerability to pollution assessment : an application of geospatial techniques and integrated IRN-DEMATEL-ANP decision modelen_US
dc.typeArticleen_US

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