37 Innovations in Research of Groundwater-Surface Water Interactions over Multiple Spatio-Temporal Scales

This session will focus on fluxes of water and solutes between groundwater and surface water, which play a crucial role in freshwater supplies for humans and ecosystems.

Sunday, 19 October 2025
1:30 PM - 5:30 PM
HBGCC, 209

Quantifying Dynamic River Gains and Losses Using Inverse Temperature Modeling

Paper number: 37-1
Program: Technical Sessions
Time: 1:35 PM – 1:55 PM

Authors

  • Bethany Neilson Presenting Author
    Utah State University, Utah Water Research Laboratory, Civil and Environmental Engineering, Logan, UT
  • Hyrum Tennant
    Utah State University, Utah Water Research Laboratory, Civil and Environmental Engineering, Logan, UT
  • Devon Hill
    Utah State University, Utah Water Research Laboratory, Civil and Environmental Engineering, Logan, UT
  • Dennis Newell
    Utah State University, Geosciences, Logan, UT
  • Jim McNamara
    Boise State University, Geosciences, Boise, ID
  • Tianfang Xu
    Arizona State University, School of Sustainable Engineering and the Built Environment, Tempe, AZ

Abstract

Quantifying lateral gains and losses (gains/losses) to streamflow is essential for understanding the variability in flow regimes and instream water quality which can be critical for effective water resource management, particularly in systems with complex and substantial groundwater–surface water interactions. Traditional methods for estimating gains/losses often require significant resources and can be limited in temporal or spatial scope. A practical methodology that applies inverse, process-based water temperature modeling was combined with temperature and differential flow gaging data to estimate and confirm net gain/loss estimates at reach scales under steady flow conditions. To extend short, steady state time period estimates of gains/losses, the inverse modeling approach was repeated during 18 two-day periods and estimated gains/losses were interpolated over five-months. These estimates were then included in the temperature model and predictions were compared to temperature observations to confirm the accuracy of the method and impact of assumptions. Results highlight that the inverse model estimates match patterns of net gains/losses and approach reach scale gross gains/losses estimated from more expensive chemical synoptic sampling techniques. The utility of this relatively low-cost, scalable solution is its ability to estimate the magnitude of net exchanges at different spatial scales that can inform hydrologic modeling, stream ecology, and water management in systems where significant lateral gains/losses (surface or subsurface) alter system response.

Geological Society of America Abstracts with Programs. Vol. 57, No. 6

doi: 10.1130/abs/2025AM-412542

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