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Retrospective on hot topics in hydrogeological intelligent computing in 2025
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Donglin DONG1, Yupeng YAO1, Wanqiu ZHANG1, Gang LIN2, 3, *
Science & Technology Review | 2026, 44(1) : 70 - 77
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Science & Technology Review | 2026, 44(1): 70-77
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Retrospective on hot topics in hydrogeological intelligent computing in 2025
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Donglin DONG1, Yupeng YAO1, Wanqiu ZHANG1, Gang LIN2, 3, *
Affiliations
  • 1School of Geosciences and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
  • 2Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • 3College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China
Published: 2026-01-13 doi: 10.3981/j.issn.1000-7857.2025.12.00058
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Hydrogeological intelligent computing represents an emerging scientific paradigm that integrates physical principles with artificial intelligence. An analysis of key 2025 research trends reveals that in core applied fields such as groundwater resource assessment, mine water hazard prevention, and contaminant transport remediation, hydrogeology is transitioning from traditional data−driven approaches toward physics−informed fusion. This shift moves beyond isolated technological breakthroughs toward constructing a comprehensive technical system encompassing "data sensing, knowledge extraction, and simulation−driven decision−making". Although challenges remain in mechanism modeling, data quality, and standardization, intelligent computing has significantly enhanced prediction accuracy and decision reliability in complex scenarios such as groundwater flow simulation and surface–subsurface water coupling. Looking ahead to 2026, deeper integration of artificial intelligence and large−scale models into mechanistic research is expected to enable more accurate, interpretable, and trustworthy intelligent simulation systems and early−warning decision−support frameworks.

hydrogeology  /  groundwater assessment  /  multimodal data fusion  /  mining area digital twin  /  multi−process coupling
Donglin DONG, Yupeng YAO, Wanqiu ZHANG, Gang LIN. Retrospective on hot topics in hydrogeological intelligent computing in 2025[J]. Science & Technology Review, 2026 , 44 (1) : 70 -77 . DOI: 10.3981/j.issn.1000-7857.2025.12.00058
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doi: 10.3981/j.issn.1000-7857.2025.12.00058
  • Receive Date：2025-12-09
  • Online Date：2026-02-03
  • Published：2026-01-13
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  • Received：2025-12-09
  • Revised：2025-12-18
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Affiliations
    1School of Geosciences and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
    2Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    3College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China
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多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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