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A study on the hydro-geologic factors that affect streamflow depletion

机译:影响水流枯竭的水文地质因素研究

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摘要

Evaluation of streamflow depletion induced by groundwater pumping is important for watershed management. Many analytical and numerical solutions exist for estimating depletion for various hydro-geologic scenarios. Numerical models are time consuming and require significant data input, and moreover, are problem-specific. Analytical models are convenient because of their ease of use, minimum data requirements, and instantaneous solutions, but are only applicable for idealistic scenarios. In many cases, analytical models are used for decision making on water-withdrawal permits, because they are assumed to offer conservative estimates of depletion. However, a systematic study of the applicability of these analytical models has not been done. In this research, we critically evaluate the performance of the analytical models in complex hydro-geologic settings, and list the factors that most significantly impact depletions. On the basis of this study, we find that the analytical models perform satisfactorily as a screening-level tool, though there are some situations when they perform poorly. The factors that most significantly impact streamflow depletion are spatial variability in hydraulic conductivity and the presence of other sources of water, such as lakes and wetlands. The analytical models do make conservative predictions of streamflow depletion especially for the most vulnerable streams.
机译:评估地下水抽取引起的水流枯竭对流域管理很重要。存在许多用于估计各种水文地质情况的损耗的分析和数值解决方案。数值模型很耗时,需要大量的数据输入,而且是针对特定问题的。由于分析模型的易用性,最低数据要求和即时解决方案,因此它们很方便,但仅适用于理想情况。在许多情况下,分析模型被用于决策取水许可,因为它们被假定为提供了枯竭的保守估计。但是,尚未对这些分析模型的适用性进行系统研究。在这项研究中,我们严格评估了分析模型在复杂水文地质环境中的性能,并列出了对耗竭影响最大的因素。在这项研究的基础上,我们发现分析模型作为筛选级别的工具可以令人满意地运行,尽管在某些情况下它们的表现很差。影响水流枯竭的最主要因素是水力传导率的空间可变性以及其他水源的存在,例如湖泊和湿地。分析模型确实对水流枯竭做出了保守的预测,尤其是对于最脆弱的水流。

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