Stochastic Modeling of Reactive Solute Transport in Heterogeneous Porous Media

非均质多孔介质中反应性溶质输运的随机模型

• 批准号: 9304481
• 负责人: Yoram Rubin
• 金额: $ 24万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-08-01 至 1998-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9304481&HistoricalAwards=false
• 关键词: Stochastic; Modeling; Reactive; Solute; Transport

9304481 Rubin Predictions of contaminant transport by groundwater, as well as monitoring and management, are based on quantitative models of solute motion. Present methods for prediction of contaminant transport are inadequate because they fail to account explicitly for measured data at its locations. They also do not account realistically for the effects of heterogeneity in the conductivity and temporal variability in pressure (or only under some simplifying assumptions), and they do not offer an economic means of designing a monitoring scheme where the observed data are used to update the predictive models. Furthermore, little attempt has been directed so far to obtain a better understanding of transport in highly heterogeneous geologic formations and the effects of chemical reactions on transport at the field scale. Lastly, current predictive methods fail to link the predictions with any criterion of goodness of fit. In this study, we propose to develop a modeling strategy which considers the aquifer hydraulic properties, the velocity field, and the solute concentration as random space functions, expressed in terms of initial/boundary conditions and various physical parameters, and which allow, both spatial variability and prediction uncertainty to be analyzed with probabilistic, quantitative tools. Three-dimensional random function models will be obtained for steady and unsteady nonuniform velocity fields and will be used for predicting the various moments of the concentration of reactive and non-reactive contaminants for anisotropic conductivity fields. Bayesian analysis will make the predictions locally conditioned. The model will be applied to two field studies. We plan to achieve a better understanding of transport phenomena at the fundamental level and obtain risk- qualified, locally-conditioned estimates of solute spreading in applications. We plan to generalize existing stochastic transport theories to account for higher-order variability i n the flow field, to investigate the influence of flow unsteadiness and nonuniformity, to evaluate the relevance of unsteadiness to the prediction of solute transport under typical conditions, and finally to suggest simplified methods to incorporate flow unsteadiness, flow nonuniformity and chemical reactions into predictions. ***

9304481鲁宾对地下水的污染物运输以及监测和管理的预测基于溶质运动的定量模型。 当前预测污染物传输的方法是不足的，因为它们无法明确考虑其位置的测量数据。 它们也不是现实地解释异质性在压力的电导率和时间变化（或仅在某些简化假设下）的影响，并且它们不提供经济方法来设计监视方案，其中使用了观察到的数据来更新预测模型。 此外，到目前为止，很少有尝试以更好地理解高度异质地质地层的运输以及化学反应对田间尺度运输的影响。 最后，当前的预测方法无法将预测与拟合优度的任何标准联系起来。 在这项研究中，我们建议制定一种建模策略，该策略考虑了含水层液压特性，速度场和溶质浓度作为随机空间功能，以初始/边界条件和各种物理参数表示，并允许在空间变异性和预测不确定性的情况下使用概率，定量工具分析。 对于稳定和不稳定的非均匀速度场，将获得三维随机函数模型，并将用于预测各向异性电导率场的反应性和非反应性污染物浓度的各种力矩。 贝叶斯分析将使预测在本地条件。 该模型将应用于两个现场研究。 我们计划在基本层面上更好地了解运输现象，并在应用中获得溶质扩散的风险合格，本地条件的估计。 我们计划概括现有的随机传输理论，以说明流场中的高阶变异性，以研究流动不稳定和不均匀性的影响，以评估不稳定与典型条件下溶质传输的相关性，最后提出简化方法以将流动性不稳定，流动性不一度，均匀反应和化学反应融入预测中。 ***