Application of integrated artificial intelligence geographical information system in managing water resources: A review
Climate change has exacerbated the water resources situation by producing erratic rainfall patterns, fading away ice sheets, increasing sea levels, floods, and droughts. Rising temperatures affect precipitation patterns and the entire water cycle, exacerbating water scarcity and water-related danger...
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| Format: | Review |
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Elsevier B.V.
2025
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| _version_ | 1833412110119337984 |
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| author | Sapitang M. Dullah H. Latif S.D. Ng J.L. Huang Y.F. Malek M.B.A. Elshafie A. Ahmed A.N. |
| author2 | 57215211508 |
| author_facet | 57215211508 Sapitang M. Dullah H. Latif S.D. Ng J.L. Huang Y.F. Malek M.B.A. Elshafie A. Ahmed A.N. |
| author_sort | Sapitang M. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Climate change has exacerbated the water resources situation by producing erratic rainfall patterns, fading away ice sheets, increasing sea levels, floods, and droughts. Rising temperatures affect precipitation patterns and the entire water cycle, exacerbating water scarcity and water-related dangers including floods and droughts. As a result, modelling these water resources conundrums based on the various hydrological and meteorological variables has been challenging to ensure effective water management. The target subject of this reviewed study concerns the forecasting of water resources using artificial intelligence and/or geographical information systems, which can be useful in addressing the challenges mentioned. This study presents a few methodologies that have been proposed for modelling the processes that eventually are related to water resources availability, in 70 scientific publications published between 2019 and 2023, such as the Random Forest, Support Vector Machine, Multilayer Perceptron Neural Networks, and the Long Short-Term Memory, on various water-related aspects such as groundwater potential mapping, rainfall prediction, surface water assessment, and flood risk assessment and a host of others. There are limitations to the studies that have been reviewed, such as a lack of comprehensive historical data and the need for comparative analyses. Overall, this reviewed study emphasizes the variety of water resource modelling potentials and issues covering improving modelling accuracy and speed, as well as a thorough evaluation of the application of AI and GIS for water resource management. ? 2024 Elsevier B.V. |
| format | Review |
| id | my.uniten.dspace-36452 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2025 |
| publisher | Elsevier B.V. |
| record_format | dspace |
| spelling | my.uniten.dspace-364522025-03-03T15:42:30Z Application of integrated artificial intelligence geographical information system in managing water resources: A review Sapitang M. Dullah H. Latif S.D. Ng J.L. Huang Y.F. Malek M.B.A. Elshafie A. Ahmed A.N. 57215211508 57199323863 57216081524 57192698412 55807263900 55636320055 16068189400 57214837520 Climate change has exacerbated the water resources situation by producing erratic rainfall patterns, fading away ice sheets, increasing sea levels, floods, and droughts. Rising temperatures affect precipitation patterns and the entire water cycle, exacerbating water scarcity and water-related dangers including floods and droughts. As a result, modelling these water resources conundrums based on the various hydrological and meteorological variables has been challenging to ensure effective water management. The target subject of this reviewed study concerns the forecasting of water resources using artificial intelligence and/or geographical information systems, which can be useful in addressing the challenges mentioned. This study presents a few methodologies that have been proposed for modelling the processes that eventually are related to water resources availability, in 70 scientific publications published between 2019 and 2023, such as the Random Forest, Support Vector Machine, Multilayer Perceptron Neural Networks, and the Long Short-Term Memory, on various water-related aspects such as groundwater potential mapping, rainfall prediction, surface water assessment, and flood risk assessment and a host of others. There are limitations to the studies that have been reviewed, such as a lack of comprehensive historical data and the need for comparative analyses. Overall, this reviewed study emphasizes the variety of water resource modelling potentials and issues covering improving modelling accuracy and speed, as well as a thorough evaluation of the application of AI and GIS for water resource management. ? 2024 Elsevier B.V. Final 2025-03-03T07:42:30Z 2025-03-03T07:42:30Z 2024 Review 10.1016/j.rsase.2024.101236 2-s2.0-85193004491 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193004491&doi=10.1016%2fj.rsase.2024.101236&partnerID=40&md5=76ffb6b31b0c75a3a91ed5872b0495e7 https://irepository.uniten.edu.my/handle/123456789/36452 35 101236 Elsevier B.V. Scopus |
| spellingShingle | Sapitang M. Dullah H. Latif S.D. Ng J.L. Huang Y.F. Malek M.B.A. Elshafie A. Ahmed A.N. Application of integrated artificial intelligence geographical information system in managing water resources: A review |
| title | Application of integrated artificial intelligence geographical information system in managing water resources: A review |
| title_full | Application of integrated artificial intelligence geographical information system in managing water resources: A review |
| title_fullStr | Application of integrated artificial intelligence geographical information system in managing water resources: A review |
| title_full_unstemmed | Application of integrated artificial intelligence geographical information system in managing water resources: A review |
| title_short | Application of integrated artificial intelligence geographical information system in managing water resources: A review |
| title_sort | application of integrated artificial intelligence geographical information system in managing water resources: a review |
| url_provider | http://dspace.uniten.edu.my/ |