Streamflow depletion estimation for conjunctive water management in a heavily-stressed aquifer using analytical depletion functions

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Authors

Samuel C Zipper , Tom Gleeson , Qiang Li, Ben Kerr

Abstract

Groundwater pumping can lead to reductions in streamflow (‘streamflow depletion’) and estimating streamflow depletion is critical for conjunctive groundwater-surface water management. Streamflow depletion can be quantified using either analytical models, which have low data requirements but many simplifying assumptions, or numerical models, which represent physical processes more realistically but have high data, effort, and expertise requirements. Analytical depletion functions are a recently-developed tool that address some of the limitations of analytical models, but to date have only been evaluated under relatively simple conditions. Here, we evaluate eight different analytical depletion functions across a range of groundwater abstraction, physiographic, and hydrostratigraphic conditions via comparison to the Republican River Compact Administration groundwater model, a calibrated MODFLOW numerical model used for conjunctive water management in a heavily-stressed portion of the High Plains Aquifer (USA). We find mostly strong agreement between the analytical depletion functions and the MODFLOW model, though analytical depletion functions underestimate depletion for wells close to surface water features in high transmissivity environments. Compared to previous work, there is little variability among the eight analytical depletion functions, indicating that function formulation plays a minor role in this setting. Analytical depletion function performance is strongly influenced by hydrostratigraphic parameters (storativity and transmissivity) but performance is insensitive to pumping rate, confirming a key assumption of analytical models. Overall, analytical depletion functions provide comparable estimates of streamflow depletion to numerical models at a fraction of the time and data requirements. Accurate hydrostratigraphic data are essential to estimating streamflow depletion regardless of modeling approach.

DOI

https://doi.org/10.31223/osf.io/hqrmu

Subjects

Earth Sciences, Environmental Indicators and Impact Assessment, Environmental Sciences, Hydrology, Physical Sciences and Mathematics, Sustainability, Water Resource Management

Keywords

decision support, MODFLOW, streamflow depletion, Water management, analytical models, capture, irrigation

Dates

Published: 2020-03-26 06:44

Last Updated: 2020-06-20 11:29

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License

CC BY Attribution 4.0 International

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