Evaluating the contamination susceptibility of groundwater resources through anthropogenic activities in Islamabad, Pakistan: a GIS-based DRASTIC approach
Abstract The problem of access to clean water has been highlighted by the United Nation’s Sustainable Development Goals, and in areas such as Islamabad, Pakistan, water pollution is more of an immediate concern. The impact of excessive use of fertilizers coupled with improper waste management has ha...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-03-01
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| Series: | Applied Water Science |
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| Online Access: | https://doi.org/10.1007/s13201-025-02374-9 |
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| author | Fayaz Ullah Shinwari Mumtaz Ali Khan Syed Mamoon Siyar Urooj Liaquat George Kontakiotis Mohamed Zhran Muhammad Shahab Fahad Alshehri |
| author_facet | Fayaz Ullah Shinwari Mumtaz Ali Khan Syed Mamoon Siyar Urooj Liaquat George Kontakiotis Mohamed Zhran Muhammad Shahab Fahad Alshehri |
| author_sort | Fayaz Ullah Shinwari |
| collection | DOAJ |
| description | Abstract The problem of access to clean water has been highlighted by the United Nation’s Sustainable Development Goals, and in areas such as Islamabad, Pakistan, water pollution is more of an immediate concern. The impact of excessive use of fertilizers coupled with improper waste management has harmed aquifers. This necessitates the need for tools to map out regions of concern and assist with clean-up strategies. This paper uses an amalgamation of the DRASTIC model and GIS capabilities to evaluate the contamination threat to aquifers in Islamabad. The model involves seven components: depth to water, recharge, aquifer media, soil media, topography, impact of the vadose zone, and hydraulic conductivity, and formulates an index of susceptibility within the range of 275–900. The areas were classified into five categories according to their level of susceptibility: very low (275–400; 22 km2, 2%), low (400–525; 306 km2, 28%), moderate (525–650; 500 km2, 47%), high (650–775; 221 km2, 21%), and very high (775–900; 26 km2, 2%). Twenty-eight of the samples had nitrate concentrations ranging from − 0.72 ppm to 2.8 ppm which helped calibrate the model and did not show a high correlation with the DRASTIC index. This suggests that the contamination was limited and did not originate from widespread sources. The results highlight the importance of focusing measures on high-risk areas, such as Rawal Lake and the National Agricultural Research Center, where risks of contamination are severe. The baseline that the present study has developed is useful in terms of safe groundwater extraction and also offers a workable methodology for urban groundwater management practices in the world. Its usefulness is enhancing policies aimed at protecting clean water resources and reducing the risk of environmental degradation in sensitive areas worldwide. |
| format | Article |
| id | doaj-art-b3ea882b5efb4b11aa96e34e95fe1f69 |
| institution | OA Journals |
| issn | 2190-5487 2190-5495 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Applied Water Science |
| spelling | doaj-art-b3ea882b5efb4b11aa96e34e95fe1f692025-08-20T02:28:10ZengSpringerOpenApplied Water Science2190-54872190-54952025-03-0115412110.1007/s13201-025-02374-9Evaluating the contamination susceptibility of groundwater resources through anthropogenic activities in Islamabad, Pakistan: a GIS-based DRASTIC approachFayaz Ullah Shinwari0Mumtaz Ali Khan1Syed Mamoon Siyar2Urooj Liaquat3George Kontakiotis4Mohamed Zhran5Muhammad Shahab6Fahad Alshehri7Department of Earth and Environmental Sciences, Bahria University IslamabadDepartment of Earth and Environmental Sciences, Bahria University IslamabadDepartment of Geology, University of MalakandAbdullah Alrushaid Chair for Earth Science Remote Sensing Research, Geology and Geophysics Departmenta, King Saud UniversityDepartment of Historical Geology-Paleontology, Faculty of Geology and Geoenvironment, School of Earth Sciences, National and Kapodistrian University of AthensPublic Works Engineering Department, Faculty of Engineering, Mansoura UniversityAbdullah Alrushaid Chair for Earth Science Remote Sensing Research, Geology and Geophysics Departmenta, King Saud UniversityAbdullah Alrushaid Chair for Earth Science Remote Sensing Research, Geology and Geophysics Departmenta, King Saud UniversityAbstract The problem of access to clean water has been highlighted by the United Nation’s Sustainable Development Goals, and in areas such as Islamabad, Pakistan, water pollution is more of an immediate concern. The impact of excessive use of fertilizers coupled with improper waste management has harmed aquifers. This necessitates the need for tools to map out regions of concern and assist with clean-up strategies. This paper uses an amalgamation of the DRASTIC model and GIS capabilities to evaluate the contamination threat to aquifers in Islamabad. The model involves seven components: depth to water, recharge, aquifer media, soil media, topography, impact of the vadose zone, and hydraulic conductivity, and formulates an index of susceptibility within the range of 275–900. The areas were classified into five categories according to their level of susceptibility: very low (275–400; 22 km2, 2%), low (400–525; 306 km2, 28%), moderate (525–650; 500 km2, 47%), high (650–775; 221 km2, 21%), and very high (775–900; 26 km2, 2%). Twenty-eight of the samples had nitrate concentrations ranging from − 0.72 ppm to 2.8 ppm which helped calibrate the model and did not show a high correlation with the DRASTIC index. This suggests that the contamination was limited and did not originate from widespread sources. The results highlight the importance of focusing measures on high-risk areas, such as Rawal Lake and the National Agricultural Research Center, where risks of contamination are severe. The baseline that the present study has developed is useful in terms of safe groundwater extraction and also offers a workable methodology for urban groundwater management practices in the world. Its usefulness is enhancing policies aimed at protecting clean water resources and reducing the risk of environmental degradation in sensitive areas worldwide.https://doi.org/10.1007/s13201-025-02374-9Groundwater contaminationNitrate concentrationGroundwater susceptibility evaluationGeographic information systemGeographic information system-based DRASTIC |
| spellingShingle | Fayaz Ullah Shinwari Mumtaz Ali Khan Syed Mamoon Siyar Urooj Liaquat George Kontakiotis Mohamed Zhran Muhammad Shahab Fahad Alshehri Evaluating the contamination susceptibility of groundwater resources through anthropogenic activities in Islamabad, Pakistan: a GIS-based DRASTIC approach Applied Water Science Groundwater contamination Nitrate concentration Groundwater susceptibility evaluation Geographic information system Geographic information system-based DRASTIC |
| title | Evaluating the contamination susceptibility of groundwater resources through anthropogenic activities in Islamabad, Pakistan: a GIS-based DRASTIC approach |
| title_full | Evaluating the contamination susceptibility of groundwater resources through anthropogenic activities in Islamabad, Pakistan: a GIS-based DRASTIC approach |
| title_fullStr | Evaluating the contamination susceptibility of groundwater resources through anthropogenic activities in Islamabad, Pakistan: a GIS-based DRASTIC approach |
| title_full_unstemmed | Evaluating the contamination susceptibility of groundwater resources through anthropogenic activities in Islamabad, Pakistan: a GIS-based DRASTIC approach |
| title_short | Evaluating the contamination susceptibility of groundwater resources through anthropogenic activities in Islamabad, Pakistan: a GIS-based DRASTIC approach |
| title_sort | evaluating the contamination susceptibility of groundwater resources through anthropogenic activities in islamabad pakistan a gis based drastic approach |
| topic | Groundwater contamination Nitrate concentration Groundwater susceptibility evaluation Geographic information system Geographic information system-based DRASTIC |
| url | https://doi.org/10.1007/s13201-025-02374-9 |
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