Articles | Volume 29, issue 6
https://doi.org/10.5194/hess-29-1549-2025
© Author(s) 2025. 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-29-1549-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Economic valuation of subsurface water contributions to watershed ecosystem services using a fully integrated groundwater–surface-water model
Tariq Aziz
CORRESPONDING AUTHOR
Aquanty, 600 Weber St. N., Unit B, Waterloo, ON, Canada
Ecohydrology Research Group, Water Institute and Department of Earth and Environmental Sciences, University of Waterloo, Waterloo, ON, Canada
Steven K. Frey
Aquanty, 600 Weber St. N., Unit B, Waterloo, ON, Canada
Department of Earth and Environmental Sciences, University of Waterloo, Waterloo, ON, Canada
David R. Lapen
Agriculture and Agri-Food Canada, Ottawa Research and Development Centre, Ottawa, ON, Canada
Susan Preston
Environment and Climate Change Canada, Canadian Wildlife Service, Gatineau, QC, Canada
Hazen A. J. Russell
Geological Survey of Canada, Natural Resources Canada, 601 Booth St., Ottawa, ON, Canada
Omar Khader
Aquanty, 600 Weber St. N., Unit B, Waterloo, ON, Canada
Department of Water and Water Structural Engineering, Zagazig University, AlSharqia, Zagazig, Egypt
Andre R. Erler
Aquanty, 600 Weber St. N., Unit B, Waterloo, ON, Canada
Edward A. Sudicky
Aquanty, 600 Weber St. N., Unit B, Waterloo, ON, Canada
Department of Earth and Environmental Sciences, University of Waterloo, Waterloo, ON, Canada
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Stephanie Bringeland, Steven K. Frey, Georgia Fotopoulos, John Crowley, Bruce Xu, Omar Khader, Hyung Eum, Babak Farjad, Andre R. Erler, and Anil Gupta
EGUsphere, https://doi.org/10.5194/egusphere-2025-3522, https://doi.org/10.5194/egusphere-2025-3522, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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A HydroGeoSphere model which represents surface and groundwater is used to assess trends from 2002–019 in water resources in Alberta, Canada and the driving factors behind these changes. Satellite-derived gravity data is compared to HydroGeoSphere model results; a strong correlation is identified. Components of water storage are assessed, namely groundwater, soil moisture, surface water, and snow. Fluctuations in water storage in Southern Alberta are linked to global climatic indices.
Samaneh Sabetghadam, Christopher G. Fletcher, and Andre Erler
Hydrol. Earth Syst. Sci., 29, 887–902, https://doi.org/10.5194/hess-29-887-2025, https://doi.org/10.5194/hess-29-887-2025, 2025
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Snow water equivalent (SWE) is an environmental variable that represents the amount of liquid water if all the snow cover melted. This study evaluates the potential of the Weather Research and Forecasting (WRF) model to estimate the daily values of SWE over the mountainous South Saskatchewan River Basin in Canada. Results show that high-resolution WRF simulations can provide reliable SWE values as an accurate input for hydrologic modeling over a sparsely monitored mountainous catchment.
Aruna Kumar Nayak, Xiaoyong Xu, Steven K. Frey, Omar Khader, Andre R. Erler, David R. Lapen, Hazen A. J. Russell, and Edward A. Sudicky
Hydrol. Earth Syst. Sci., 29, 215–244, https://doi.org/10.5194/hess-29-215-2025, https://doi.org/10.5194/hess-29-215-2025, 2025
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Satellite remote sensing only measures the near-surface soil water content. We demonstrate that satellite-based near-surface soil water variability is a strong reflection of deeper subsurface water fluctuation and quantifies the response time differences between dynamics of satellite near-surface soil water and water in the deeper subsurface. Result support the use of satellite near-surface soil water measurements as indicators and/or predictors of water resources in the deeper subsurface.
Fraser King, Andre R. Erler, Steven K. Frey, and Christopher G. Fletcher
Hydrol. Earth Syst. Sci., 24, 4887–4902, https://doi.org/10.5194/hess-24-4887-2020, https://doi.org/10.5194/hess-24-4887-2020, 2020
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Snow is a critical contributor to our water and energy budget, with impacts on flooding and water resource management. Measuring the amount of snow on the ground each year is an expensive and time-consuming task. Snow models and gridded products help to fill these gaps, yet there exist considerable uncertainties associated with their estimates. We demonstrate that machine learning techniques are able to reduce biases in these products to provide more realistic snow estimates across Ontario.
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Short summary
This study determines the value of subsurface water for ecosystem services' supply in an agricultural watershed in Ontario, Canada. Using a fully integrated water model and an economic valuation approach, the research highlights subsurface water's critical role in maintaining watershed ecosystem services. The study informs on the sustainable use of subsurface water and introduces a new method for managing watershed ecosystem services.
This study determines the value of subsurface water for ecosystem services' supply in an...