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首页> 外文期刊>Advances in Water Resources >Data-worth analysis for multiobjective optimal design of pump-and-treat remediation systems
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Data-worth analysis for multiobjective optimal design of pump-and-treat remediation systems

机译:泵处理系统多目标优化设计的数据价值分析

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The design and the management of pump-and-treat (PAT) remediation systems for contaminated aquifers under uncertain hydrogeo-logical settings and parameters often involve decisions that trade off cost optimality against reliability. Both design objectives can be improved by planning site characterization programs that reduce subsurface parameter uncertainty. However, the cost for subsurface investigation often weighs heavily upon the budget of the remedial action and must thus be taken into account in the trade-off analysis. In this paper, we develop a stochastic data-worth framework with the purpose of estimating the economic opportunity of subsurface investigation programs. Since the spatial distribution of hydraulic conductivity is most often the major source of uncertainty, we focus on the direct sampling of hydraulic conductivity at prescribed locations of the aquifer. The data worth of hydraulic conductivity measurements is estimated from the reduction of the overall management cost ensuing from the reduction in parameter uncertainty obtained from sampling. The overall cost is estimated as the expected value of the cost of installing and operating the PAT system plus penalties incurred due to violations of cleanup goals and constraints. The crucial point of the data-worth framework is represented by the so-called pre-posterior analysis. Here, the tradeoff between decreasing overall costs and increasing site-investigation budgets is assessed to determine a management strategy proposed on the basis of the information available at the start of remediation. The goal of the pre-posterior analysis is to indicate whether the proposed management strategy should be implemented as is, or re-designed on the basis of additional data collected with a particular site-investigation program. The study indicates that the value of information is ultimately related to the estimates of cleanup target violations and decision makers' degree of risk-aversion.
机译:在不确定的水文地质条件和参数下,用于受污染含水层的泵处理(PAT)修复系统的设计和管理通常需要权衡成本最优与可靠性之间的权衡决策。通过计划减少地下参数不确定性的现场表征程序,可以提高这两个设计目标。但是,地下调查的费用通常会严重影响补救措施的预算,因此必须在权衡分析中予以考虑。在本文中,我们开发了一个随机的数据有价值的框架,目的是估计地下调查程序的经济机会。由于水力传导率的空间分布通常是不确定性的主要来源,因此我们将重点放在对含水层规定位置的水力传导率进行直接采样。通过减少采样带来的参数不确定性,可以降低总体管理成本,从而估算出水力传导率测量的数据价值。总成本估算为安装和运行PAT系统成本的预期价值,加上因违反清理目标和限制而产生的罚款。数据价值框架的关键点是所谓的事后分析。在此,评估降低的总成本与增加的现场调查预算之间的权衡,以确定根据补救开始时可用的信息提出的管理策略。事后分析的目的是表明建议的管理策略应按原样实施,还是应根据通过特定场所调查计划收集的其他数据进行重新设计。研究表明,信息的价值最终与清理目标违规的估计以及决策者的风险规避程度有关。

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