Comparing Streamflow Depletion Estimation Approaches in a Heavily Stressed, Conjunctively Managed Aquifer. Issue 2 (23rd February 2021)

• Record Type: Journal Article
• Authors: Zipper, Samuel C.; Gleeson, Tom; Li, Qiang; Kerr, Ben
• Is Part Of: Water resources research. Volume 57:Issue 2(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-02-23
• Subjects: analytical models -- decision support -- MODFLOW -- streamflow depletion -- water management; Hydrology -- Periodicals; 333.91
• DOI: 10.1029/2020WR027591
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: Estimating reductions in streamflow caused by groundwater pumping ("streamflow depletion") is critical for conjunctive groundwater‐surface water management. Streamflow depletion can be quantified using 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 new tool that address some of the limitations of analytical models, but to date have only been evaluated in limited hydrogeological settings. Here, we compare eight different analytical depletion functions to streamflow depletion estimates from a calibrated MODFLOW numerical model used for conjunctive water management in the heavily stressed Republican River region of the High Plains Aquifer (USA). We find mostly strong agreement between the analytical depletion functions and the numerical model, though analytical depletion function estimates of depletion are lower for wells close to surface water features in high transmissivity settings. Compared to previous work, there is little variability among the eight analytical depletion functions, indicating that function formulation plays a minor role in this domain. Agreement between the modeling approaches is strongly influenced by hydrostratigraphic parameters (i.e., aquifer storage and transmissivity), suggesting accurate subsurface data are essential to estimating streamflow depletion regardless of modeling approach. Additionally, agreement between the two approaches 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. Plain Language Summary: Estimating the impacts of groundwater pumping on streamflow ("streamflow depletion") is challenging but essential for effectively managing water resources. In this study, we test a low‐cost, low‐effort approach (called an "analytical depletion function") to estimate streamflow depletion by comparing it to a more complex tool that is currently used for water management in a heavily irrigated setting in the central US. We find that there is general agreement between the analytical depletion function and the more complex approach. We also test whether analytical depletion function performance is better or worse for different conditions and find that performance is similar regardless of pumping rate but very sensitive to properties of the subsurface. Overall, our results indicate that analytical depletion functions could be useful tools for estimating streamflow depletion where more complex approaches are unavailable, but having accurate data about the subsurface is essential. Key Points: We compared streamflow depletion estimated by analytical depletion functions to a calibrated numerical model in a heavily stressed aquifer Analytical depletion functions had similar estimates of streamflow depletion with lower data and computational costs than numerical models Analytical depletion functions are a potential tool for decision making in settings where numerical models are not available