人工智能驱动的地下水数值模拟研究进展

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（School of Environmental and Chemical Engineering，Shanghai University，Shanghai 2O0444，China）

AbstractGroundwater is a critical resource for maintaining ecological security and sustainable development， yet it faces dual challnges of fluctuant quantityand deteriorating quality. While process-based models can describe groundwater flow and contaminant transport，they are highly dependent on precise parameter inputs and computationally intensive，making them lesssuited for dynamic simulations in complex，heterogeneous environments.Artificial Intelligence（AI）technologies，with their strengths in nonlinear modeling，predictive optimization，and high-dimensional feature extraction，offr novel solutions to overcome botlenecks in complex system modeling. This article provides a comprehensive review of recent advancements in AI applications for groundwater modeling，covering key areas such as water level prediction， contaminant transport simulation， and remediation optimization.The results indicate that AI models perform well in dynamic forecasting，pollutant identification，and optimization of remediation strategies.Hybrid modeling approaches demonstrate strong robustness in modeling complex variable interactions，while deep learning frameworks show significant advantages in spatiotemporal feature extraction. However，AI models stillface challenges such as limited generalization capabilities and a lack of physical consistency.Future research should focus on the folowing aspects ： ① developing multi-scale data fusion and scale-transfer mechanisms to enhance model stability and adaptability; ② Improving the transferability and reusability of same-scale models，with reduced reliance on data from the target site; ③ shifting the paradigm from " big data" to " effective data" to strengthen modeling capabilities under small-sample conditions ; ④ embedding physical constraints to improve the reliability and physical consistency of surrogate models ; ⑤ constructing intelligent systems that integrate the Internet of Things and edge computing to enable efficient groundwater sensing，modeling，and real-time decision-making，thereby advancing groundwater management into a new era of intelligent operation.

Keywordsartificial intelligence; groundwater; numerical modeling; contaminants

地下水是维系生态健康和人类社会可持续发展的重要自然资源[1-2]。（剩余24630字）