Comparison of Surface Water‐Groundwater Exchange Fluxes Derived From Hydraulic and Geochemical Methods and a Regional Groundwater Model

支流 地下水 水文学(农业) 压力计 环境科学 地表水 地下水流 流域 水流 含水层 地质学 地图学 环境工程 岩土工程 地理
作者
Camille Bouchez,Peter G. Cook,Daniel Partington,Craig T. Simmons
出处
期刊:Water Resources Research [Wiley]
卷期号:57 (3) 被引量:12
标识
DOI:10.1029/2020wr029137
摘要

Abstract Intercomparison of surface water‐groundwater (SW‐GW) exchange fluxes at the regional scale is rarely undertaken, mainly because estimates are method and scale‐dependent and usually associated with large errors. In the present study, we compare SW‐GW exchange fluxes calculated from a multitracer mass balance in the river, an application of Darcy's law using near‐river piezometers and a surface‐subsurface flow model calibrated at the catchment scale. SW‐GW exchange fluxes are estimated for 7 km long reaches along the 140 km long Campaspe River, a tributary of the Murray River, Australia. Differences are found in the directions and magnitudes of the exchange fluxes estimated by the different methods. The application of Darcy's law in near‐river piezometers seems the most appropriate method to infer SW‐GW flow directions and temporal variability. The tracer mass balance is limited to gaining reaches but gives quantitative estimates of the fluxes. While numerical models should overcome deficiencies associated with some of the intrinsic assumptions of the two field‐methods, the regional‐scale calibration is subject to high uncertainties in the simulated heads near the river, resulting in uncertainty of SW‐GW exchange fluxes. In particular, we show that loosely quantified river abstractions and irrigation patterns directly impact the simulated SW‐GW fluxes. In gaining reaches, additional river chemistry data improved model calibration and SW‐GW flux estimates. While numerical models are crucial for water management, their reliability to estimate SW‐GW fluxes can be limited by their complexity and lacking data availability. Therefore, we recommend comparing numerical model results with easily implemented field‐based methods.
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