基于不确定性分析的地下水污染超标风险预警
发布时间：2018-11-08 09:54
【摘要】：地下水污染预测可以通过地下水污染质运移数值模拟模型予以实现,为分析模型参数取值不确定性对模型输出结果的影响,本文运用蒙特卡洛方法对模型输出结果进行不确定性分析.为降低数值模拟模型复杂程度,运用灵敏度分析方法筛选对模型影响较大参数作为模型中随机变量;为减少重复调用数值模拟模型产生的计算负荷,在保证一定精度前提下,运用克里格方法建立模拟模型的替代模型完成模拟过程.结果表明:应用概率密度函数积分可以估计地下水遭受污染风险与不同置信程度下污染物浓度区间.污染羽分布图与分级污染超标风险预警图可以分别对研究区不同等级污染覆盖面积和研究区不同污染风险对应污染羽分布进行估计.基于污染质运移数值模拟不确定性分析的地下水污染超标风险预警可以更加客观地对地下水污染问题进行预测.
[Abstract]:Groundwater pollution prediction can be realized by numerical simulation model of groundwater pollution transport. In order to analyze the influence of uncertainty of model parameters on model output, In this paper, the Monte Carlo method is used to analyze the uncertainty of the model output. In order to reduce the complexity of the numerical simulation model, the sensitivity analysis method is used to screen the large parameters that affect the model as the random variables in the model. In order to reduce the computational load caused by repeated call of numerical simulation model, the simulation process is completed by using the Kriging method to establish the substitute model of the simulation model on the premise of certain precision. The results show that the probability density function integral can be used to estimate the contamination risk of groundwater and the pollutant concentration interval with different confidence levels. The pollution plume distribution map and the classified pollution risk warning map can be used to estimate the pollution plume distribution corresponding to the pollution plume distribution and the pollution coverage area of different grades of pollution in the study area. Based on the uncertainty analysis of numerical simulation of pollutant transport, the risk of groundwater pollution exceeding the standard can be predicted more objectively.
【作者单位】： 吉林大学地下水与资源环境教育部重点实验室;吉林大学环境与资源学院;
【基金】：国家自然科学基金资助项目(41372237);国家自然科学基金资助项目(41672232) 吉林大学研究生创新基金资助项目(2016100)
【分类号】：X523
本文编号：2318126
[Abstract]:Groundwater pollution prediction can be realized by numerical simulation model of groundwater pollution transport. In order to analyze the influence of uncertainty of model parameters on model output, In this paper, the Monte Carlo method is used to analyze the uncertainty of the model output. In order to reduce the complexity of the numerical simulation model, the sensitivity analysis method is used to screen the large parameters that affect the model as the random variables in the model. In order to reduce the computational load caused by repeated call of numerical simulation model, the simulation process is completed by using the Kriging method to establish the substitute model of the simulation model on the premise of certain precision. The results show that the probability density function integral can be used to estimate the contamination risk of groundwater and the pollutant concentration interval with different confidence levels. The pollution plume distribution map and the classified pollution risk warning map can be used to estimate the pollution plume distribution corresponding to the pollution plume distribution and the pollution coverage area of different grades of pollution in the study area. Based on the uncertainty analysis of numerical simulation of pollutant transport, the risk of groundwater pollution exceeding the standard can be predicted more objectively.
【作者单位】： 吉林大学地下水与资源环境教育部重点实验室;吉林大学环境与资源学院;
【基金】：国家自然科学基金资助项目(41372237);国家自然科学基金资助项目(41672232) 吉林大学研究生创新基金资助项目(2016100)
【分类号】：X523
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