Hydrogeological flow patterns and hydrochemical driving forces of groundwater in a typical coastal hilly region of the Jinjiang watershed,Southeast China:Recommendations for water pollution control and managementOA
Coastal groundwater(CGW)systems in rapidly urbanizing regions face critical challenges in achieving Sustainable Development Goal(SDG),where anthropogenic pressures intersect with hydrogeological vulnerability.This study employs coupled isotopic-hydrogeochemical analysis and geostatistics to unravel hydrochemical driving forces compromising groundwater quality in the Jinjiang Downstream Watershed(DJW),Southeast China.The results indicated that groundwater was predominantly recharged from local atmospheric precipitation and lateral recharge from the adjacent boundaries.Hydrochemical distributions exhibited a distinct pattern,transitioning from HCO_(3)-Ca to HCO_(3)·Cl-Ca,and then to Cl-Mg·Ca/Na·Ca,reflecting processes ranging from freshwater recharge to seawater intrusion(SWI).Elevated nitrates were primarily attributed to domestic sewage leakage and septic tank leaching.Additionally,preferential flow posed a risk to deep groundwater quality,by facilitating the rapid transport of contaminants through rock fractures.Key driving forces of hydrochemistry included silicate dissolution with local runoff paths,SWI,and human activities.The study advocates for a governance paradigm integrating electrochemical sensor networks with machine learning-driven contaminant prediction and phased membrane bioreactor deployment,which synergistically reduce nitrate fluxes while maintaining aquifer freshening processes.This integrated approach establishes a scalable model for SDG-aligned groundwater management in vulnerable coastal zones,demonstrating how process-based insights can bridge scientific discovery and water security implementation.
Zhong-shuang Cheng;Chen Su;Wen-zhong Wang;Bing-yan Li;En-de Zuo;Yu-meng Tian;Zhao-xian Zheng
Institute of Hydrogeology and Environmental Geology,Chinese Academy of Geological Sciences,China Geological Survey,Ministry of Natural Resources,Xiamen 361021,China Key Laboratory of Groundwater Science and Engineering,Ministry of Natural Resource,Shijiazhuang 050061,China Fujian Provincial Key Laboratory of Water Cycling and Eco-Geological Processes,Xiamen 361021,ChinaInstitute of Hydrogeology and Environmental Geology,Chinese Academy of Geological Sciences,China Geological Survey,Ministry of Natural Resources,Xiamen 361021,China Key Laboratory of Groundwater Science and Engineering,Ministry of Natural Resource,Shijiazhuang 050061,ChinaInstitute of Hydrogeology and Environmental Geology,Chinese Academy of Geological Sciences,China Geological Survey,Ministry of Natural Resources,Xiamen 361021,China Key Laboratory of Groundwater Science and Engineering,Ministry of Natural Resource,Shijiazhuang 050061,ChinaInstitute of Hydrogeology and Environmental Geology,Chinese Academy of Geological Sciences,China Geological Survey,Ministry of Natural Resources,Xiamen 361021,China Key Laboratory of Groundwater Science and Engineering,Ministry of Natural Resource,Shijiazhuang 050061,ChinaInstitute of Hydrogeology and Environmental Geology,Chinese Academy of Geological Sciences,China Geological Survey,Ministry of Natural Resources,Xiamen 361021,China Key Laboratory of Groundwater Science and Engineering,Ministry of Natural Resource,Shijiazhuang 050061,ChinaCollege of Earth Sciences,Jilin University,Changchun 130061,ChinaInstitute of Hydrogeology and Environmental Geology,Chinese Academy of Geological Sciences,China Geological Survey,Ministry of Natural Resources,Xiamen 361021,China Key Laboratory of Groundwater Science and Engineering,Ministry of Natural Resource,Shijiazhuang 050061,China
资源环境
Groundwater flow patternAtmospheric precipitationHydrochemistryNitrateDriving forcesSeawater intrusionElectrochemical sensor networksMachine learningCoastal areaSustainable Development Goal(SDG)Groundwater managementHydrogeological survey engineering
《China Geology》 2026 (2)
P.316-332,17
supported by the project of the China Geological Survey(DD20230421)the Central Institutes Fundamental Research Project(SK202410)the National Natural Science Foundation of China(41702283).
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