A systematic review of neural network applications for groundwater level prediction

A systematic review of neural network applications for groundwater level prediction

Abstract Physical models have long been employed for groundwater level (GWL) prediction. Recently, artificial intelligence (AI), particularly neural networks (NNs), has gained widespread use in forecasting GWL. Forecasting of GWL is essential to enable the analysis, quantifying, and management of gr...

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Main Authors: Samuel K. Afful, Cyril D. Boateng, Emmanuel Ahene, Jeffrey N. A. Aryee, David D. Wemegah, Solomon S. R. Gidigasu, Akyana Britwum, Marian A. Osei, Jesse Gilbert, Haoulata Touré, Vera Mensah
Format: Article
Language:English
Published: Springer 2025-08-01
Series:Discover Applied Sciences
Subjects:
Review
Neural networks (NNs)
Artificial neural networks (ANNs)
Groundwater level (GWL) forecasting
Climate variables
Online Access:https://doi.org/10.1007/s42452-025-06817-5
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https://doi.org/10.1007/s42452-025-06817-5

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