Groundwater Depletion and Sustainability
A Methodology Utilizing Artificial Intelligence and Earth Observation Systems
Springer
ISBN 978-3-032-09920-4
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Bibliografische Daten
Fachbuch
Buch. Hardcover
2026
Format (B x L): 15,5 x 23,5 cm
Verlag: Springer
ISBN: 978-3-032-09920-4
Weiterführende bibliografische Daten
Das Werk ist Teil der Reihe: Advances in Geographic Information Science
Produktbeschreibung
AI and Earth observation-based methods support effective water resource management by identifying suitable areas for artificial groundwater recharge (AGR) and assessing the impact of pollution on water resources. These techniques help formulate conservation policies and sustainable water management strategies. Various AI techniques, including ANN, SVM, KNN, and decision trees, have been applied to model groundwater quality and predict water quality indices. These models capture complex relationships between hydro chemical parameters and groundwater quality, enabling accurate predictions and informed decision-making.
The application of AI and Earth observation systems in groundwater quality prediction contributes to the sustainability of water resources. Identifying pollution sources, assessing water quality, and guiding decision-making processes support preserving and managing water resources in arid and semi-arid regions.
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