Intera Inc, Austin, TX, 77478, USA.
US Geological Survey, Austin, TX, 78754, USA.
Ground Water. 2021 Jul;59(4):571-580. doi: 10.1111/gwat.13080. Epub 2021 Mar 10.
A popular and contemporary use of numerical groundwater models is to estimate the discrete relation between groundwater extraction and surface-water/groundwater exchange. Previously, the concept of a "capture map" has been put forward as a means to effectively summarize this relation for decision-making consumption. While capture maps have enjoyed success in the environmental simulation industry, they are deterministic, ignoring uncertainty in the underlying model. Furthermore, capture maps are not typically calculated in a manner that facilitates analysis of varying combinations of extraction locations and/or reaches. That is, they are typically constructed with focus on a single reach or group of reaches. The former of these limitations is important for conveying risk to decision makers and stakeholders, while the latter is important for decision-making support related to surface-water management, where future foci may include reaches that were not the focus of the original capture analysis. Herein, we use the concept of a response matrix to generalize the theory of the capture-map approach to estimate spatially discrete streamflow depletion potential. We also use first-order, second-moment uncertainty estimation techniques with the concept of "risk shifting" to place capture maps and streamflow depletion potential in a stochastic, risk-based framework. Our approach is demonstrated for an integrated groundwater/surface-water model of the lower San Antonio River, Texas, USA.
目前，地下水数值模型的一个流行且实用的用途是估计地下水抽取与地表水/地下水交换之间的离散关系。先前，“捕获图”的概念已被提出，作为用于决策消耗的有效总结这种关系的手段。虽然捕获图在环境模拟行业中取得了成功，但它们是确定性的，忽略了基础模型中的不确定性。此外，捕获图通常不是以有利于分析不同的抽取位置和/或河段组合的方式计算的。也就是说，它们通常是针对单个河段或一组河段进行构建的。前者对于向决策者和利益相关者传达风险很重要，而后者对于与地表水管理相关的决策支持很重要，因为未来的重点可能包括原始捕获分析中没有关注的河段。在此，我们使用响应矩阵的概念将捕获图方法的理论推广到估计空间离散的水流消耗潜力。我们还使用一阶、二阶矩不确定性估计技术和“风险转移”的概念将捕获图和水流消耗潜力置于随机的、基于风险的框架中。我们的方法在美国德克萨斯州圣安东尼奥河下游的地下水/地表水综合模型中进行了演示。
