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Groundwater Pumping Impacts on Real Stream Networks: Testing the Performance of Simple Management Tools

分摊 地下水补给 水流 地下水 环境科学 含水层 水文学(农业) 航程(航空) 土壤科学 流域 地质学 地理 岩土工程 工程类 航空航天工程 地图学 法学 政治学
作者
Samuel C. Zipper,Tom Dallemagne,Tom Gleeson,Thomas C. Boerman,Andreas Hartmann
出处
期刊:Water Resources Research [Wiley]
卷期号:54 (8): 5471-5486 被引量:42
标识
DOI:10.1029/2018wr022707
摘要

Abstract Quantifying reductions in streamflow due to groundwater pumping (“streamflow depletion”) is essential for conjunctive management of groundwater and surface water resources. Analytical models are widely used to estimate streamflow depletion but include potentially problematic assumptions such as simplified stream‐aquifer geometry and rely on largely untested depletion apportionment equations to distribute depletion from a well among different stream reaches. Here, we use archetypal numerical models to evaluate the sensitivity of five depletion apportionment equations to stream networks with varying drainage densities, topographic relief, and groundwater recharge rates; and statistically evaluate the sources of error for each equation. We introduce a new depletion apportionment equation called web squared which considers stream network geometry, and find that it performs the best under most conditions tested. For all depletion apportionment equations, performance decreases with increases in drainage density, relief, or recharge rates, and all equations struggle to estimate depletion in short stream reaches. Poorly performing apportionment equations tend to underestimate streamflow depletion relative to numerical model results, leading to a negative bias and underpredicted variability, while error in the best performing apportionment equations tends to be due to imperfect correlation. From a management perspective, apportionment equations with error due to bias and variability are preferable as they correctly identify which reaches will be affected and can be statistically corrected. Overall, these results indicate that the web squared method introduced here, which explicitly considers stream geometry, performs the best over a range of real‐world conditions, and will be most accurate in flatter and drier environments.
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