Articles | Volume 26, issue 10
https://doi.org/10.5194/hess-26-2779-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-2779-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Effects of spatial and temporal variability in surface water inputs on streamflow generation and cessation in the rain–snow transition zone
Department of Ecosystem Science and Sustainability, Colorado State
University, Fort Collins, CO, USA
Department of Geosciences, Idaho State University, Pocatello, ID, USA
Ernesto Trujillo
Department of Geosciences, Boise State University, Boise, ID,
USA
Northwest Watershed Research Center, USDA Agricultural Research Service, Boise, ID, USA
Andrew Hedrick
Northwest Watershed Research Center, USDA Agricultural Research Service, Boise, ID, USA
Scott Havens
Northwest Watershed Research Center, USDA Agricultural Research Service, Boise, ID, USA
Katherine Hale
Department of Geography, University of Colorado, Boulder, CO, USA
Institute of Arctic and Alpine Research, University of Colorado,
Boulder, CO, USA
Mark Seyfried
Northwest Watershed Research Center, USDA Agricultural Research Service, Boise, ID, USA
Stephanie Kampf
Department of Ecosystem Science and Sustainability, Colorado State
University, Fort Collins, CO, USA
Sarah E. Godsey
Department of Geosciences, Idaho State University, Pocatello, ID, USA
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Ernesto Trujillo, Andrew Hedrick, and Danny Marks
EGUsphere, https://doi.org/10.5194/egusphere-2025-3736, https://doi.org/10.5194/egusphere-2025-3736, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
This study uses 48 airborne lidar surveys and an energy balance snow model to investigate the spatial accumulation of snow water equivalent (SWE) in a large 1,180 km2 headwater catchment throughout hydrologically variable years. Results quantify the variability of the date of peak SWE storage across the basin and indicate that multiple lidar acquisitions throughout the accumulation and melt season provide the most optimal information for water supply forecasting applications.
Randall Bonnell, Daniel McGrath, Jack Tarricone, Hans-Peter Marshall, Ella Bump, Caroline Duncan, Stephanie Kampf, Yunling Lou, Alex Olsen-Mikitowicz, Megan Sears, Keith Williams, Lucas Zeller, and Yang Zheng
The Cryosphere, 18, 3765–3785, https://doi.org/10.5194/tc-18-3765-2024, https://doi.org/10.5194/tc-18-3765-2024, 2024
Short summary
Short summary
Snow provides water for billions of people, but the amount of snow is difficult to detect remotely. During the 2020 and 2021 winters, a radar was flown over mountains in Colorado, USA, to measure the amount of snow on the ground, while our team collected ground observations to test the radar technique’s capabilities. The technique yielded accurate measurements of the snowpack that had good correlation with ground measurements, making it a promising application for the upcoming NISAR satellite.
Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, and S. McKenzie Skiles
Geosci. Model Dev., 16, 233–250, https://doi.org/10.5194/gmd-16-233-2023, https://doi.org/10.5194/gmd-16-233-2023, 2023
Short summary
Short summary
Freshwater resupply from seasonal snow in the mountains is changing. Current water prediction methods from snow rely on historical data excluding the change and can lead to errors. This work presented and evaluated an alternative snow-physics-based approach. The results in a test watershed were promising, and future improvements were identified. Adaptation to current forecast environments would improve resilience to the seasonal snow changes and helps ensure the accuracy of resupply forecasts.
James W. Kirchner, Sarah E. Godsey, Madeline Solomon, Randall Osterhuber, Joseph R. McConnell, and Daniele Penna
Hydrol. Earth Syst. Sci., 24, 5095–5123, https://doi.org/10.5194/hess-24-5095-2020, https://doi.org/10.5194/hess-24-5095-2020, 2020
Short summary
Short summary
Streams and groundwaters often show daily cycles in response to snowmelt and evapotranspiration. These typically have a roughly 6 h time lag, which is often interpreted as a travel-time lag. Here we show that it is instead primarily a phase lag that arises because aquifers integrate their inputs over time. We further show how these cycles shift seasonally, mirroring the springtime retreat of snow cover to higher elevations and the seasonal advance and retreat of photosynthetic activity.
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Short summary
Climate change affects precipitation phase, which can propagate into changes in streamflow timing and magnitude. This study examines how variations in rainfall and snowmelt affect discharge. We found that annual discharge and stream cessation depended on the magnitude and timing of rainfall and snowmelt and on the snowpack melt-out date. This highlights the importance of precipitation timing and emphasizes the need for spatiotemporally distributed simulations of snowpack and rainfall dynamics.
Climate change affects precipitation phase, which can propagate into changes in streamflow...