Key Laboratory of Groundwater Resources and Environment (Ministry of Education), Jilin University, Changchun 130021, China; Jilin Provincial Key Laboratory of Water Resources and Environment, Jilin University, Changchun 130021, China; College of New Energy and Environment, Jilin University, Changchun 130021, China.
Shenyang Academy of Environmental Sciences, Shenyang 110167, China.
Ecotoxicol Environ Saf. 2024 Oct 15;285:117027. doi: 10.1016/j.ecoenv.2024.117027. Epub 2024 Sep 14.
Groundwater pollution risk evaluation is an important basis for developing groundwater protection measures and management strategies, and its accuracy directly affects the effectiveness of protection measures. The heterogeneity of the aquifer significantly affects the transport process of pollutants, increasing the uncertainty of pollutant risk assessment. However, in the actual site, borehole data that reveal aquifer heterogeneity are costly, and only a limited number of borehole data are available, which cannot accurately describe the heterogeneity of the aquifer, thus limiting the accuracy of groundwater pollution risk assessment. In order to overcome the above problems, this paper proposes a groundwater pollution risk assessment framework based on the stochastic and deterministic simulation of aquifer lithology. Based on the statistical characteristics of the change of lithology type in the actual borehole, the framework uses Markov chain to generate some sets of random lithology field and transforms them into heterogeneity parameter field, so as to realize the stochastic assessment of the pollution risk of groundwater resource wells. Furthermore, combined with the pumping test data, the parameter field that is most suitable for the actual situation is selected to evaluate the pollution risk deterministically. Finally, the stochastic and deterministic results are combined to comprehensively evaluate the pollution risk of groundwater resource wells. Through a case study in a river valley plain, the feasibility of the above framework is verified, and good application effects are achieved. This study provides a feasible method for accurately assessing groundwater pollution risk, which is helpful to reduce the impact of uncertain factors on pollution risk assessment, and thus provides a more reliable basis for groundwater management and decision-making.
地下水污染风险评价是制定地下水保护措施和管理策略的重要依据，其准确性直接影响保护措施的有效性。含水层的非均质性显著影响污染物的输运过程，增加了污染物风险评估的不确定性。然而，在实际场地中，揭示含水层非均质性的钻孔数据成本高昂，且仅有有限数量的钻孔数据可用，无法准确描述含水层的非均质性，从而限制了地下水污染风险评价的准确性。为了克服上述问题，本文提出了一种基于含水层岩性随机和确定性模拟的地下水污染风险评价框架。该框架基于实际钻孔中岩性类型变化的统计特征，利用马尔可夫链生成多组随机岩性场，并将其转化为非均质性参数场，从而实现对地下水水源井污染风险的随机评价。此外，结合抽水试验数据，选择最适合实际情况的参数场进行确定性污染风险评价。最后，将随机和确定性结果相结合，对地下水水源井的污染风险进行综合评价。通过河谷平原的案例研究，验证了上述框架的可行性，并取得了良好的应用效果。本研究为准确评估地下水污染风险提供了一种可行的方法，有助于减少不确定因素对污染风险评估的影响，从而为地下水管理和决策提供更可靠的依据。
