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Managed aquifer recharge as a strategy to redistribute excess surface flow to baseflow in snowmelt hydrologic regimes

Ekim 9, 2024

Managed aquifer recharge as a strategy to redistribute excess
surface flow to baseflow in snowmelt hydrologic regimes

Stephen B. Ferencz *, Adam Mangel † and Frederick Day-Lewis
Earth Systems Science Division, Pacific Northwest National Laboratory, Richland, WA, United States

Water management in snowmelt hydrologic regimes, characterized by
large annual fluctuations in stream flow driven by seasonal snow melt, faces
the challenge of highly variable supply that often does not align with timing
of demand. Climate change may exacerbate management challenges by
significantly reducing snowpack or shifting snow melt earlier. Here, managed
aquifer recharge (MAR) is evaluated as a potential strategy to reallocate excess
early-season stream flow to time periods when less surface water is available.
This strategy differs from traditional MAR, where the goal is to minimize loss to
surface water. We assess how to site MAR operations such that groundwater
recharge flows back to the surface water system in a lagged manor to benefit water
management objectives, which we term “enhanced baseflow.” We use a regional
groundwater model for the Treasure Valley aquifer located in southwestern
Idaho, United States to demonstrate a generalizable approach using regional
groundwater models as tools to identify favorable baseflow enhancement
locations. Hypothetical MAR is simulated at 197 candidate locations, which are
then evaluated for how effectively they meet potential management objectives.
In addition to demonstrating the modeling and evaluation approach, we discuss
lessons learned from applying a pre-existing regional groundwater model to
MAR for enhanced baseflow and also describe important considerations,
such as the physical and institutional availability of surface flows and specific
management objectives, when assessing regional and site-specific suitability

to read the full article please click on

/wp-content/uploads/2026/07/Managed%20aquifer%20recharge%20.pdf

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Managed aquifer recharge as a strategy to redistribute excess
surface flow to baseflow in snowmelt hydrologic regimes

Stephen B. Ferencz *, Adam Mangel † and Frederick Day-Lewis
Earth Systems Science Division, Pacific Northwest National Laboratory, Richland, WA, United States

Water management in snowmelt hydrologic regimes, characterized by
large annual fluctuations in stream flow driven by seasonal snow melt, faces
the challenge of highly variable supply that often does not align with timing
of demand. Climate change may exacerbate management challenges by
significantly reducing snowpack or shifting snow melt earlier. Here, managed
aquifer recharge (MAR) is evaluated as a potential strategy to reallocate excess
early-season stream flow to time periods when less surface water is available.
This strategy differs from traditional MAR, where the goal is to minimize loss to
surface water. We assess how to site MAR operations such that groundwater
recharge flows back to the surface water system in a lagged manor to benefit water
management objectives, which we term “enhanced baseflow.” We use a regional
groundwater model for the Treasure Valley aquifer located in southwestern
Idaho, United States to demonstrate a generalizable approach using regional
groundwater models as tools to identify favorable baseflow enhancement
locations. Hypothetical MAR is simulated at 197 candidate locations, which are
then evaluated for how effectively they meet potential management objectives.
In addition to demonstrating the modeling and evaluation approach, we discuss
lessons learned from applying a pre-existing regional groundwater model to
MAR for enhanced baseflow and also describe important considerations,
such as the physical and institutional availability of surface flows and specific
management objectives, when assessing regional and site-specific suitability

to read the full article please click on

/wp-content/uploads/2026/07/Managed%20aquifer%20recharge%20.pdf

^

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