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Application of a link simulation optimization model utilizing quantification of hydrogeologic uncertainty to characterize unknown groundwater contaminant sources

机译:一种利用水文地质不确定性的链路仿真优化模型的应用,以特征在于未知的地下水污染源

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In existing groundwater contamination source characterization methodologies, simulation models estimate the contamination concentration in the study area. In order to obtain reliable solutions, it is essential to provide the simulation models with reliable hydrogeological properties. In real-life scenarios often high level of uncertainty and variability is associated with the hydrogeological properties. This study focuses on quantifying the hydrogeological parameter uncertainty to enhance the accuracy of identifying contamination release histories. Tracer experiment results at the Eastlakes Experimental Site, located in Botany Sands Aquifer, in New South Wales, Australia, are utilized to examine the performance and potential applicability of the methodology. In the selected study area, the hydrogeological heterogeneity in the microscopic scale, specifically the hydraulic conductivity, has substantial effect on the transport of pollutants. Among available tracer information, Bromide is studied as aconservative contaminant. Using possible realizations of the flow field, a coefficient of confidence (COC) is calculated for each field monitoring locations and times. Higher COC implies that the result of simulation models at that specific monitoring location and time is more reliable than other contaminant concentration data. Therefore, the optimization model should emphasise matching the corresponding estimated and observed contamination concentrations to accurately identify the contaminant release locations and histories. The linked simulation-optimisation method is utilised to optimally characterise the Bromide sources. Performance evaluation results demonstrate that the proposed methodology recovers pollution source characteristics more accurately compared to the methodology which does not consider the effect of hydrogeological parameter uncertainty.
机译:在现有地下水污染源表征方法中,仿真模型估计研究区域中的污染浓度。为了获得可靠的解决方案,必须提供具有可靠性水水电质性质的仿真模型。在现实生活中,这种情况通常很高的不确定性和变异性与水文地质性质有关。本研究致力于量化水文地质参数不确定性,以提高鉴定污染释放历史的准确性。在澳大利亚新南威尔士州的Eastlakes实验部位的Tracer实验结果在澳大利亚新南威尔士州的植物学含水层中,利用来检查方法的性能和潜在适用性。在所选研究区域中,微观规模中的水文后果异质性,特别是液压导电性,对污染物的运输具有实质性的影响。在可用的示踪信息中,溴化物被研究为Aconservative污染物。使用流场的可能的实现,针对每个现场监视位置和时间计算置信系数(COC)。较高的COC意味着在该特定监测位置和时间的模拟模型的结果比其他污染物浓度数据更可靠。因此,优化模型应该强调匹配相应的估计和观察到的污染浓度,以准确地识别污染物释放位置和历史。链接仿真优化方法用于最佳地表征溴化源。绩效评估结果表明,与不考虑水文地理参数不确定性的影响,更准确地将污染源特性更准确地恢复污染源特征。

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