Lagged streamflow depletion due to pumping-induced stream drying: Incorporation into analytical streamflow depletion estimation methods

• Analytical depletion functions (ADFs) estimate streamflow depletion caused by pumping. • ADFs incorporating stream drying had strong agreement with observed streamflow. • Stream drying shifts timing of streamflow depletion due to hydrologic disconnection. • Modeling stream drying requires accurate estimates of non-depleted streamflow. • Strong ADF performance suggests potential use as a low-cost decision-support tool. Water management often requires accounting for reductions in streamflow caused by groundwater pumping (‘streamflow depletion’). Since streamflow depletion cannot be quantified from observational data, it is typically modeled. Analytical depletion functions (ADFs) are a low-cost, low-complexity approach for estimating streamflow depletion with utility for decision support, but ADFs adopt several simplifying assumptions, including an infinite supply of water within the stream. Here, we develop an approach to incorporate stream drying into ADFs to improve their estimation of streamflow and streamflow depletion. Using Scott Valley (California) as an example, we compare ADF results to observed streamflow data and the Scott Valley Integrated Hydrologic Model (SVIHM), a process-based numerical model. ADFs incorporating stream drying have strong agreement with observed streamflow and SVIHM results. Critically, ADFs with drying can simulate a temporal shift in streamflow depletion that occurs when summer stream drying causes stream network disconnections and a substantial fraction of streamflow depletion is lagged until the fall/winter, when the stream network rewets. Estimates of what streamflow would have been without groundwater pumping are required to incorporate stream drying into ADFs, and we evaluate the ability of a statewide statistical model of unimpaired monthly streamflow (the California Natural Flows Database [CNFD]) to meet this need. ADFs using CNFD data simulate appropriate temporal dynamics but overestimate streamflow. This suggests that regional unimpaired flow estimates combined with local bias-correction could provide a mechanism to apply ADFs in watersheds without local numerical models.

Authors

Institutions

Publication Details

Journal
Journal of Hydrology
Published
2026-01-04
DOI
https://doi.org/10.1016/j.jhydrol.2026.134909
Citations
1
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
18.04
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Lagged streamflow depletion due to pumping-induced stream drying: Incorporation into analytical streamflow depletion estimation methods

Ian Gambill, Leland Scantlebury, Claire Kouba, Monty Schmitt et al.
1 citations
Journal of Hydrology
Hydrology and Watershed Management Studies
18.04
article

Lagged streamflow depletion due to pumping-induced stream drying: Incorporation into analytical streamflow depletion estimation methods

Ian Gambill, Leland Scantlebury, Claire Kouba, Monty Schmitt, Thomas Harter, Nicholas P. Murphy, Sam Zipper
article en
1 citations

Abstract

• Analytical depletion functions (ADFs) estimate streamflow depletion caused by pumping. • ADFs incorporating stream drying had strong agreement with observed streamflow. • Stream drying shifts timing of streamflow depletion due to hydrologic disconnection. • Modeling stream drying requires accurate estimates of non-depleted streamflow. • Strong ADF performance suggests potential use as a low-cost decision-support tool. Water management often requires accounting for reductions in streamflow caused by groundwater pumping (‘streamflow depletion’). Since streamflow depletion cannot be quantified from observational data, it is typically modeled. Analytical depletion functions (ADFs) are a low-cost, low-complexity approach for estimating streamflow depletion with utility for decision support, but ADFs adopt several simplifying assumptions, including an infinite supply of water within the stream. Here, we develop an approach to incorporate stream drying into ADFs to improve their estimation of streamflow and streamflow depletion. Using Scott Valley (California) as an example, we compare ADF results to observed streamflow data and the Scott Valley Integrated Hydrologic Model (SVIHM), a process-based numerical model. ADFs incorporating stream drying have strong agreement with observed streamflow and SVIHM results. Critically, ADFs with drying can simulate a temporal shift in streamflow depletion that occurs when summer stream drying causes stream network disconnections and a substantial fraction of streamflow depletion is lagged until the fall/winter, when the stream network rewets. Estimates of what streamflow would have been without groundwater pumping are required to incorporate stream drying into ADFs, and we evaluate the ability of a statewide statistical model of unimpaired monthly streamflow (the California Natural Flows Database [CNFD]) to meet this need. ADFs using CNFD data simulate appropriate temporal dynamics but overestimate streamflow. This suggests that regional unimpaired flow estimates combined with local bias-correction could provide a mechanism to apply ADFs in watersheds without local numerical models.

Journal of HydrologyVol. 667
The Nature Conservancy (US), University of Kansas (US), Hydrologic Research Center (US), Yale University (US), University of California, Davis (US)
Clean water and sanitation
Openalex Percentile: Top 4%
Hydrology and Watershed Management Studies
18.04
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.