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Recently, there has been an increase in the use of machine learning (ML) and deep learning (DL) models in hydrogeology to estimate GWL in monitoring wells. This study presents a novel technique for predicting GWL changes that uses three independent datasets: historical GWL and climatic variables (CVs) data such as rainfall and temperature influencing groundwater dynamics. In our experimental research, the models\u2019 prediction output on real\u2010world datasets ensures that the model\u2019s significant patterns are recorded while taking into account the noise in the data, resulting in a perfect balance of bias and variance. The DL models\u2019 results show a significant score of root mean square error (RMSE) between 2.20 and 12.40 and coefficient of determination (\n                    <jats:italic>R<\/jats:italic>\n                    \u2010squared between 0.84\u20130.99), showing a significant improvement in RMSE and mean absolute error (MAE) in the testing and validation categories, when compared to the current state\u2010of\u2010the\u2010art methods. This study improves our understanding of GWL modeling and provides decision\u2010makers with a reliable tool for controlling change. The study advances environmental modeling by exhibiting methodological complexity and emphasizes the importance of comprehensive data analysis in water resource management.\n                  <\/jats:p>","DOI":"10.1155\/acis\/7641994","type":"journal-article","created":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T08:19:19Z","timestamp":1741681159000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Impact of Climate Change on Groundwater Level Changes: An Evaluation Based on Deep Neural Networks"],"prefix":"10.1155","volume":"2025","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9308-3137","authenticated-orcid":false,"given":"Stephen","family":"Afrifa","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2317-644X","authenticated-orcid":false,"given":"Tao","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6098-4537","authenticated-orcid":false,"given":"Peter","family":"Appiahene","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1621-2337","authenticated-orcid":false,"given":"Xin","family":"Zhao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3752-7220","authenticated-orcid":false,"given":"Vijayakumar","family":"Varadarajan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3679-854X","authenticated-orcid":false,"given":"Thomas","family":"Atta-Darkwah","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4837-7857","authenticated-orcid":false,"given":"Yanzhang","family":"Geng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9406-5873","authenticated-orcid":false,"given":"Daniel","family":"Gyamfi","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8087-5207","authenticated-orcid":false,"given":"Rose-Mary","family":"Owusuaa Mensah Gyening","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2025,3,11]]},"reference":[{"key":"e_1_2_11_1_2","doi-asserted-by":"publisher","DOI":"10.2166\/h2oj.2024.110"},{"key":"e_1_2_11_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00704-021-03771-1"},{"key":"e_1_2_11_3_2","doi-asserted-by":"publisher","DOI":"10.2166\/h2oj.2024.099"},{"key":"e_1_2_11_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11053-020-09634-2"},{"key":"e_1_2_11_5_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10040-018-1866-3"},{"key":"e_1_2_11_6_2","doi-asserted-by":"publisher","DOI":"10.2166\/h2oj.2024.107"},{"key":"e_1_2_11_7_2","doi-asserted-by":"publisher","DOI":"10.3390\/fi14090259"},{"key":"e_1_2_11_8_2","doi-asserted-by":"publisher","DOI":"10.31083\/j.ceog5012271"},{"key":"e_1_2_11_9_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-28770-2"},{"key":"e_1_2_11_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2019.135539"},{"key":"e_1_2_11_11_2","doi-asserted-by":"publisher","DOI":"10.3390\/hydrology10010001"},{"key":"e_1_2_11_12_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11069-021-05019-7"},{"key":"e_1_2_11_13_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00477-023-02593-z"},{"key":"e_1_2_11_14_2","doi-asserted-by":"publisher","DOI":"10.5194\/hess-25-3397-2021"},{"key":"e_1_2_11_15_2","doi-asserted-by":"publisher","DOI":"10.1177\/02560909211059992"},{"key":"e_1_2_11_16_2","doi-asserted-by":"publisher","DOI":"10.3390\/w15234129"},{"key":"e_1_2_11_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhydrol.2021.127092"},{"key":"e_1_2_11_18_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11269-022-03070-y"},{"key":"e_1_2_11_19_2","doi-asserted-by":"publisher","DOI":"10.1002\/2016WR019933"},{"key":"e_1_2_11_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhydrol.2015.09.038"},{"key":"e_1_2_11_21_2","doi-asserted-by":"crossref","unstructured":"KayhomayoonZ. 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