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与源自非线性地下水流模型的捕获区地图相关的偏差评估

Evaluation of Bias Associated with Capture Maps Derived from Nonlinear Groundwater Flow Models.

作者信息

Nadler Cara, Allander Kip, Pohll Greg, Morway Eric, Naranjo Ramon, Huntington Justin

机构信息

U.S. Geological Survey, Carson City, NV, 89701.

Desert Research Institute, Reno, NV, 89512.

出版信息

Ground Water. 2018 May;56(3):458-469. doi: 10.1111/gwat.12597. Epub 2017 Sep 21.

Abstract

The impact of groundwater withdrawal on surface water is a concern of water users and water managers, particularly in the arid western United States. Capture maps are useful tools to spatially assess the impact of groundwater pumping on water sources (e.g., streamflow depletion) and are being used more frequently for conjunctive management of surface water and groundwater. Capture maps have been derived using linear groundwater flow models and rely on the principle of superposition to demonstrate the effects of pumping in various locations on resources of interest. However, nonlinear models are often necessary to simulate head-dependent boundary conditions and unconfined aquifers. Capture maps developed using nonlinear models with the principle of superposition may over- or underestimate capture magnitude and spatial extent. This paper presents new methods for generating capture difference maps, which assess spatial effects of model nonlinearity on capture fraction sensitivity to pumping rate, and for calculating the bias associated with capture maps. The sensitivity of capture map bias to selected parameters related to model design and conceptualization for the arid western United States is explored. This study finds that the simulation of stream continuity, pumping rates, stream incision, well proximity to capture sources, aquifer hydraulic conductivity, and groundwater evapotranspiration extinction depth substantially affect capture map bias. Capture difference maps demonstrate that regions with large capture fraction differences are indicative of greater potential capture map bias. Understanding both spatial and temporal bias in capture maps derived from nonlinear groundwater flow models improves their utility and defensibility as conjunctive-use management tools.

摘要

抽取地下水对地表水的影响是用水户和水资源管理者所关注的问题,在美国西部干旱地区尤为如此。捕获图是在空间上评估地下水抽取对水源(如河流流量减少)影响的有用工具,并且越来越多地用于地表水和地下水的联合管理。捕获图是使用线性地下水流模型得出的,依靠叠加原理来展示不同位置抽水对感兴趣资源的影响。然而,模拟水头依赖边界条件和潜水含水层通常需要非线性模型。使用叠加原理的非线性模型生成的捕获图可能会高估或低估捕获量和空间范围。本文提出了生成捕获差异图的新方法,该方法可评估模型非线性对捕获分数对抽水速率敏感性的空间影响,并计算与捕获图相关的偏差。探讨了捕获图偏差对美国西部干旱地区与模型设计和概念化相关的选定参数的敏感性。本研究发现,河流连续性、抽水速率、河流下切、井与捕获源的距离、含水层水力传导率以及地下水蒸发散消亡深度的模拟对捕获图偏差有重大影响。捕获差异图表明,捕获分数差异大的区域表明捕获图偏差的可能性更大。了解从非线性地下水流模型得出的捕获图中的空间和时间偏差,可提高其作为联合利用管理工具的实用性和可信度。

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