Baú Domenico A, Mayer Alex S
Department of Geological & Mining Engineering & Sciences, Michigan Technological University, Houghton, MI 49931, USA.
J Contam Hydrol. 2008 Aug 20;100(1-2):30-46. doi: 10.1016/j.jconhyd.2008.05.002. Epub 2008 May 17.
In this work, we present a stochastic optimal control framework for assisting the management of the cleanup by pump-and-treat of polluted shallow aquifers. In the problem being investigated, hydraulic conductivity distribution and dissolved contaminant plume location are considered as the uncertain variables. The framework considers the subdivision of the cleanup horizon in a number of stress periods over which the pumping policy implemented until that stage is dynamically adjusted based upon new information that has become available in the previous stages. In particular, by following a geostatistical approach, we study the idea of monitoring the cumulative contaminant mass extracted from the installed recovery wells, and using these measurements to generate conditional realizations of the hydraulic conductivity field. These realizations are thus used to obtain a more accurate evaluation of the initial plume distribution, and modify accordingly the design of the pump-and-treat system for the remainder of the remedial process. The study indicates that measurements of contaminant mass extracted from pumping wells retain valuable information about the plume location and the spatial heterogeneity characterizing the hydraulic conductivity field. However, such an information may prove quite soft, particularly in the instances where recovery wells are installed in regions where contaminant concentration is low or zero. On the other hand, integrated solute mass measurements may effectively allow for reducing parameter uncertainty and identifying the plume distribution if more recovery wells are available, in particular in the early stages of the cleanup process.
在这项工作中，我们提出了一个随机最优控制框架，以协助通过抽水-处理法管理受污染浅层含水层的清理工作。在所研究的问题中，水力传导率分布和溶解污染物羽流位置被视为不确定变量。该框架考虑将清理期细分为多个应力期，在这些应力期内，根据前一阶段获得的新信息动态调整直至该阶段实施的抽水策略。具体而言，通过采用地质统计学方法，我们研究了监测从已安装的抽水井中提取的累积污染物质量的想法，并利用这些测量结果生成水力传导率场的条件实现。这些实现结果因此被用于更准确地评估初始羽流分布，并相应地修改补救过程剩余阶段的抽水-处理系统设计。研究表明，从抽水井中提取的污染物质量测量保留了有关羽流位置和表征水力传导率场的空间非均质性的宝贵信息。然而，这样的信息可能相当模糊，特别是在抽水井安装在污染物浓度低或为零的区域的情况下。另一方面，如果有更多的抽水井，特别是在清理过程的早期阶段，综合溶质质量测量可以有效地减少参数不确定性并识别羽流分布。
