江汉平原高砷地下水研究进展
Research Progress on High-Arsenic Groundwater in the Jianghan Plain
摘要: 江汉平原是我国湿润河湖平原原生高砷地下水研究的重要区域,其砷富集过程受沉积环境、含水层结构和地表水–地下水交换共同控制。本文梳理区域调查、长期监测、沉积物培养、同位素示踪及数值模拟等研究,评述砷的时空分布、载砷矿物转化、有机质作用和碳氮硫耦合过程。现有证据表明,含砷铁氧化物的还原溶解是主要释砷途径,有机质的来源与反应活性决定电子供给,微生物介导的铁硫转化同时控制砷的释放与再固定。水文扰动改变氧化剂和有机碳输入,使不同井深、场地和季节呈现差异化响应;甲基化、孔隙水非均一性及微塑料相关作用拓展了传统无机砷研究框架。目前,局部观测向区域规律外推、不同过程的通量分配及治理长期稳定性仍存在不足。未来应加强分层连续监测、多形态砷测定及实验与模型联合约束,推动由浓度分布描述向过程定量和动态风险管理转变。在综合不同研究结论的基础上,本文进一步从水文扰动驱动的Fe-S-C-N耦合角度提出统一的概念模型,并讨论由井点证据向区域风险推断进行尺度升级的可行路径。
Abstract: The Jianghan Plain is an important setting for studying geogenic arsenic enrichment in humid alluvial-lacustrine aquifers in China. This review synthesizes regional surveys, long-term monitoring, sediment incubation experiments, isotope tracing, and numerical modeling to evaluate arsenic distribution and the processes governing its mobilization. Reductive dissolution of arsenic-bearing iron oxides is a major release pathway, while organic matter sources and reactivity regulate electron supply. Microbially mediated iron and sulfur transformations can promote either arsenic release or sequestration. Hydrological disturbances alter the delivery of oxidants and organic carbon, producing contrasting responses across depths, sites, and seasons. Recent investigations of methylated arsenic, porewater heterogeneity, and potential microplastic-related effects extend the conventional inorganic arsenic framework. Key uncertainties concern regional extrapolation, quantitative allocation of process-specific fluxes, and the long-term stability of mitigation measures. Future work should integrate depth-resolved monitoring, arsenic speciation, and experimentally constrained transport models to support dynamic risk assessment and sustainable groundwater management. Synthesizing findings from various studies, this paper further develops a unified conceptual model from the perspective of Fe-S-C-N coupling driven by hydrological perturbations, and methodological pathways are discussed for upscaling from well-scale evidence to regional risk inference.
文章引用:沈力. 江汉平原高砷地下水研究进展[J]. 地理科学研究, 2026, 15(5): 965-975. https://doi.org/10.12677/gser.2026.155087

参考文献

[1] Smedley, P.L. and Kinniburgh, D.G. (2002) A Review of the Source, Behaviour and Distribution of Arsenic in Natural Waters. Applied Geochemistry, 17, 517-568.
https://doi.org/10.1016/s0883-2927(02)00018-5
[2] Gan, Y., Wang, Y., Duan, Y., Deng, Y., Guo, X. and Ding, X. (2014) Hydrogeochemistry and Arsenic Contamination of Groundwater in the Jianghan Plain, Central China. Journal of Geochemical Exploration, 138, 81-93.
https://doi.org/10.1016/j.gexplo.2013.12.013
[3] Duan, Y., Gan, Y., Wang, Y., Deng, Y., Guo, X. and Dong, C. (2015) Temporal Variation of Groundwater Level and Arsenic Concentration at Jianghan Plain, Central China. Journal of Geochemical Exploration, 149, 106-119.
https://doi.org/10.1016/j.gexplo.2014.12.001
[4] Schaefer, M.V., Ying, S.C., Benner, S.G., Duan, Y., Wang, Y. and Fendorf, S. (2016) Aquifer Arsenic Cycling Induced by Seasonal Hydrologic Changes within the Yangtze River Basin. Environmental Science & Technology, 50, 3521-3529.
https://doi.org/10.1021/acs.est.5b04986
[5] Duan, Y., Gan, Y., Wang, Y., Liu, C., Yu, K., Deng, Y., et al. (2017) Arsenic Speciation in Aquifer Sediment under Varying Groundwater Regime and Redox Conditions at Jianghan Plain of Central China. Science of The Total Environment, 607, 992-1000.
https://doi.org/10.1016/j.scitotenv.2017.07.011
[6] Du, Y., Deng, Y., Ma, T., Lu, Z., Shen, S., Gan, Y., et al. (2018) Hydrogeochemical Evidences for Targeting Sources of Safe Groundwater Supply in Arsenic-Affected Multi-Level Aquifer Systems. Science of The Total Environment, 645, 1159-1171.
https://doi.org/10.1016/j.scitotenv.2018.07.173
[7] 邬建勋, 余倩, 蒋庆肯, 等. 江汉平原高砷地下水与含水层沉积物的地球化学特征[J]. 地质科技情报, 2019, 38(1): 250-257.
[8] Sun, Y., Lan, J., Chen, X., Ye, H., Du, D., Li, J., et al. (2021) High Arsenic Levels in Sediments, Jianghan Plain, Central China: Vertical Distribution and Characteristics of Arsenic Species, Dissolved Organic Matter, and Microbial Community. Journal of Geochemical Exploration, 228, Article 106822.
https://doi.org/10.1016/j.gexplo.2021.106822
[9] Zheng, T., Deng, Y., Wang, Y., Jiang, H., Xie, X. and Gan, Y. (2020) Microbial Sulfate Reduction Facilitates Seasonal Variation of Arsenic Concentration in Groundwater of Jianghan Plain, Central China. Science of The Total Environment, 735, Article 139327.
https://doi.org/10.1016/j.scitotenv.2020.139327
[10] 袁晓芳, 李林倩, 张彦鹏, 等. 江汉平原地下水中甲基砷的富集过程: 碳同位素与溶解性有机质三维荧光光谱的指示[J]. 地球科学, 2024, 49(11): 3917-3929.
[11] Lan, Y., He, Y., Yu, Q. and Song, Q. (2025) Delineating Sources of Groundwater Recharge in an Arsenic‐Affected Aquifer in Jianghan Plain Using Stable Isotopes. Hydrological Processes, 39, e70050.
https://doi.org/10.1002/hyp.70050
[12] Duan, Y., Schaefer, M.V., Wang, Y., Gan, Y., Yu, K., Deng, Y., et al. (2019) Experimental Constraints on Redox-Induced Arsenic Release and Retention from Aquifer Sediments in the Central Yangtze River Basin. Science of The Total Environment, 649, 629-639.
https://doi.org/10.1016/j.scitotenv.2018.08.205
[13] Deng, Y., Zheng, T., Wang, Y., Liu, L., Jiang, H. and Ma, T. (2018) Effect of Microbially Mediated Iron Mineral Transformation on Temporal Variation of Arsenic in the Pleistocene Aquifers of the Central Yangtze River Basin. Science of The Total Environment, 619, 1247-1258.
https://doi.org/10.1016/j.scitotenv.2017.11.166
[14] 鲁宗杰, 邓娅敏, 杜尧, 等. 江汉平原高砷地下水中DOM三维荧光特征及其指示意义[J]. 地球科学, 2017, 42(5): 771-782.
[15] Yu, K., Gan, Y., Zhou, A., Liu, C., Duan, Y., Han, L., et al. (2018) Organic Carbon Sources and Controlling Processes on Aquifer Arsenic Cycling in the Jianghan Plain, Central China. Chemosphere, 208, 773-781.
https://doi.org/10.1016/j.chemosphere.2018.05.188
[16] Yang, Y., Yuan, X., Deng, Y., Xie, X., Gan, Y. and Wang, Y. (2020) Seasonal Dynamics of Dissolved Organic Matter in High Arsenic Shallow Groundwater Systems. Journal of Hydrology, 589, Article 125120.
https://doi.org/10.1016/j.jhydrol.2020.125120
[17] Ye, H., Yang, Z., Wu, X., Wang, J., Du, D., Cai, J., et al. (2017) Sediment Biomarker, Bacterial Community Characterization of High Arsenic Aquifers in Jianghan Plain, China. Scientific Reports, 7, Article No. 42037.
https://doi.org/10.1038/srep42037
[18] 高杰, 郑天亮, 邓娅敏, 等. 江汉平原高砷地下水原位微生物的铁还原及其对砷释放的影响[J]. 地球科学, 2017, 42(5): 716-726.
[19] 徐雨潇, 郑天亮, 高杰, 等. 江汉平原浅层含水层中土著硫酸盐还原菌对砷迁移释放的影响[J]. 地球科学, 2021, 46(2): 652-660.
[20] Gao, J., Zheng, T., Deng, Y. and Jiang, H. (2021) Microbially Mediated Mobilization of Arsenic from Aquifer Sediments under Bacterial Sulfate Reduction. Science of The Total Environment, 768, Article 144709.
https://doi.org/10.1016/j.scitotenv.2020.144709
[21] 张振超, 梁莹, 许洁, 等. 高砷地下水中氮循环对砷释放过程的影响[J]. 地球科学, 2024, 49(9): 3428-3439.
[22] Xu, Y., Liu, D., Yuan, X., Yang, Y., Li, T., Deng, Y., et al. (2024) Deciphering the Spatial Heterogeneity of Groundwater Arsenic in Quaternary Aquifers of the Central Yangtze River Basin. Science of The Total Environment, 929, Article 172405.
https://doi.org/10.1016/j.scitotenv.2024.172405
[23] Huang, K., Liu, Y., Yang, C., Duan, Y., Yang, X. and Liu, C. (2018) Identification of Hydrobiogeochemical Processes Controlling Seasonal Variations in Arsenic Concentrations within a Riverbank Aquifer at Jianghan Plain, China. Water Resources Research, 54, 4294-4308.
https://doi.org/10.1029/2017wr022170
[24] Zhang, Y., Yu, Q., Shi, C., Li, P. and Niu, H. (2023) Environmental Isotopes and Cl/Br Ratios Evidences for Delineating Arsenic Mobilization in Aquifer System of the Jianghan Plain, Central China. Journal of Earth Science, 34, 571-579.
https://doi.org/10.1007/s12583-020-1096-1
[25] Qiu, W., Ma, T., Du, Y., Zheng, B., Peng, Z., Shang, R., et al. (2025) Inhomogeneous Porewater Geochemistry in Unconsolidated Argillaceous Sediments: Implications for Porewater Extraction Protocols and Characterization of Solute Mobilization. Chemical Geology, 685, Article 122813.
https://doi.org/10.1016/j.chemgeo.2025.122813
[26] Qiu, W., Du, Y., Ma, T., Liu, W., Liu, Y., Bu, X., et al. (2026) Impact of Argillaceous Sediment Consolidation on Groundwater Quality Evolution: New Insights from Numerical Simulations of Porewater and Solute Release. Journal of Hydrology, 674, Article 135466.
https://doi.org/10.1016/j.jhydrol.2026.135466
[27] Liu, S., Li, C., Bundschuh, J., Gao, X., Li, H., Shi, W., et al. (2026) The Potential Role of Groundwater Microplastics on Arsenic Cycling in Alluvial Aquifers: Insights from Links of DOM Characteristics and Microbial Community. Environmental Pollution, 407, Article 128821.
https://doi.org/10.1016/j.envpol.2026.128821
[28] Yu, H., Ma, T., Du, Y., Shen, S. and Han, Z. (2022) Distribution, Bioavailability, and Human Health Risk Assessment of Arsenic in Groundwater-Soil-Rice System in the Jianghan Plain, Central China. Environmental Science and Pollution Research, 29, 16193-16202.
https://doi.org/10.1007/s11356-021-16497-4
[29] Xiao, T., Muhammad, A.M., Pan, X., Wang, Y., Guangming, H. and Tang, Z. (2022) Spatial Distribution and Risk Identification of Arsenic Contamination in Water and Soil through Gis-Based Interpolation Techniques in Jianghan Plain, Central China. Frontiers in Environmental Science, 10, Article ID: 1001862.
https://doi.org/10.3389/fenvs.2022.1001862
[30] Fan, R., Deng, Y., Du, Y. and Xie, X. (2024) Predicting Geogenic Groundwater Arsenic Contamination Risk in Floodplains Using Interpretable Machine-Learning Model. Environmental Pollution, 340, Article 122787.
https://doi.org/10.1016/j.envpol.2023.122787
[31] Luo, J., Ma, X., Ji, Y., Li, X., Song, Z. and Lu, W. (2023) Review of Machine Learning-Based Surrogate Models of Groundwater Contaminant Modeling. Environmental Research, 238, Article 117268.
https://doi.org/10.1016/j.envres.2023.117268
[32] Xu, R. and Zhang, D. (2024) Forward Prediction and Surrogate Modeling for Subsurface Hydrology: A Review of Theory-Guided Machine-Learning Approaches. Computers & Geosciences, 188, Article 105611.
https://doi.org/10.1016/j.cageo.2024.105611