AI and Machine Learning in Hydrogeology
A special issue of Geosciences (ISSN 2076-3263).
Deadline for manuscript submissions: 28 February 2026 | Viewed by 29
Special Issue Editors
Interests: subsurface energy; machine learning; explainable AI; uncertainty quantification; inverse modeling; scientific computing
Special Issues, Collections and Topics in MDPI journals
Interests: reactive transport; fluid–rock–(microbe) interactions; rock mechanics; geothermal energy; underground hydrogen storage
Special Issue Information
Dear Colleagues,
This Special Issue focuses on the transformative role of artificial intelligence (AI) and machine learning (ML) in hydrogeology and hydrological systems, spanning both surface and subsurface domains. We welcome contributions that address applications in groundwater modeling, surface water management, contaminant transport, subsurface energy systems, oil and gas recovery, geological carbon storage, geothermal energy, and hydrogen storage. Emphasis is placed not only on traditional ML techniques but also on emerging AI paradigms such as generative models (e.g., diffusion models), large language models (LLMs), and graph neural networks.
The issue covers a range of topics including forward and inverse modeling, uncertainty quantification, real-time decision support, and deep learning architectures designed for hydrological processes. Particular attention is given to challenges in multi-source data integration, model interpretability, and physics-informed learning. Through this interdisciplinary collection, we aim to demonstrate how cutting-edge AI tools can improve predictive capabilities, support sustainable resource management, and deepen our understanding of complex environmental systems.
Dr. Ming Fan
Dr. Chaojie Cheng
Dr. Linqi Zhu
Guest Editors
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Geosciences is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- water resource management
- surface hydrology
- subsurface energy
- forward modeling
- inverse modeling
- uncertainty quantification
- deep learning
- explainable AI
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