Machine learning-based identification of multi-source recharges and enrichment mechanism of karst groundwater

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies Pub Date : 2025-10-02 DOI:10.1016/j.ejrh.2025.102830

Haitao Yang , Fengxin Kang , Yi Liu , Jialong Li , Yanshan Dong , Tingting Zheng , Peng Qin

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引用次数: 0

Abstract

Study region

The Changxiao karst water system, southwestern area of Jinan, China

Study focus

This study focused on the Changxiao karst water system, employing an integrated approach combining hydrochemical methods, PCA-APCS-MLR receptor modeling, and machine learning to identify groundwater sources and spatial distribution patterns. The enrichment mechanisms were investigated through systematic analysis of geomorphological features, geological structures, lithostratigraphic characteristics, and hydrodynamic conditions.

New hydrological insights

The hydrochemical types of groundwater in the Changxiao karst system are primarily derived from rock weathering and leaching processes. SOM-K-means clustering analysis revealed a triple mixing characteristic in the Collecting and discharging zone (CDZ), integrating contributions from the Southern replenishment area (SRA), Western lateral runoff area (WLR), and Yellow River (YR) infiltration, confirming their close hydraulic connectivity. The CDZ exhibits well-developed fracture-karst systems, receiving combined recharge from the SRA, WLR, and YR. This area possesses well-developed conduits, substantial fracture-karst storage, and convergent recharge pathways—establishing fundamental prerequisites for groundwater accumulation in carbonate aquifers. By integrating artificial intelligence, hydrochemical analysis, and statistical models, this study constructs a multiscale analytical framework for karst groundwater research, offering novel insights for optimizing water source protection and urban water supply strategies.

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基于机器学习的岩溶地下水多源补给与富集机理识别

本研究以济南市西南长晓岩溶水系为研究对象，采用水化学方法、PCA-APCS-MLR受体建模和机器学习相结合的综合方法，识别地下水水源和空间分布格局。通过系统分析地貌特征、地质构造、岩石地层特征和水动力条件，探讨了富集机制。长啸岩溶系统地下水的水化学类型主要来源于岩石风化和淋滤过程。SOM-K-means聚类分析结果显示，南侧补给区（SRA）、西侧径流区（WLR）和黄河入渗区（YR）对流域的贡献具有“三重混合”特征，三者具有密切的水力连通性。CDZ具有发育良好的裂缝-岩溶系统，可接受SRA、WLR和YR的联合补给。该区域具有发育良好的管道、丰富的裂缝-岩溶储层和收敛的补给路径，为碳酸盐岩含水层的地下水聚集奠定了基本先决条件。本研究结合人工智能、水化学分析和统计模型，构建了岩溶地下水研究的多尺度分析框架，为优化水源保护和城市供水策略提供了新的见解。

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来源期刊

Journal of Hydrology-Regional Studies Earth and Planetary Sciences-Earth and Planetary Sciences (miscellaneous)

CiteScore

6.70

自引率

8.50%

发文量

284

审稿时长

60 days

期刊介绍： Journal of Hydrology: Regional Studies publishes original research papers enhancing the science of hydrology and aiming at region-specific problems, past and future conditions, analysis, review and solutions. The journal particularly welcomes research papers that deliver new insights into region-specific hydrological processes and responses to changing conditions, as well as contributions that incorporate interdisciplinarity and translational science.