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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #358379
Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Quantifying the hydrological impacts of climate change on a watershed in northern Virginia

Author
item BARAN, A.A. - Virginia Tech
item Moglen, Glenn
item GODREJ, A.N. - Virginia Tech

Submitted to: Journal Hydrologic Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/31/2019
Publication Date: 9/28/2019
Citation: Baran, A., Moglen, G.E., Godrej, A. 2019. Quantifying the hydrological impacts of climate change on a watershed in northern Virginia. Journal Hydrologic Engineering. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001860.
DOI: https://doi.org/10.1061/(ASCE)HE.1943-5584.0001860

Interpretive Summary: Water availability for purposes of water supply or irrigation may change owing to trends in climate variability. Projections of future rainfall and temperature for the U.S. mid-Atlantic region from several general circulation models (GCMs) and regional climate models (RCMs) were downscaled using two common methods: delta change and quantile mapping. These projections were used to drive a hydrologic model (HSPF) to simulate future streamflow. In total this study examined 32 combinations of simulated streamflow - the product of 4 GCM/RCM pairs, 2 emission scenarios, 2 future periods (mid-21st and late-21st century), and 2 downscaling methods. Although variability/uncertainty could be associated with each element of the modeling combinations, the downscaling method emerged as the greatest source of variability. These findings inform the streamflow modeling process as it will affect water availability and serve to identify future research directions that will provide the greatest reductions in forecast uncertainty.

Technical Abstract: Water availability for purposes of water supply or irrigation may change owing to trends in climate variability. Projections of future rainfall and temperature for the U.S. mid-Atlantic region from several general circulation models (GCMs) and regional climate models (RCMs) were downscaled using two common methods: delta change and quantile mapping. These projections were used to drive a hydrologic model (HSPF) to simulate future streamflow. In total this study examined 32 combinations of simulated streamflow - the product of 4 GCM/RCM pairs, 2 emission scenarios, 2 future periods (mid-21st and late-21st century), and 2 downscaling methods. Although variability/uncertainty could be associated with each element of the modeling combinations, the downscaling method emerged as the greatest source of variability. These findings inform the streamflow modeling process as it will affect water availability and serve to identify future research directions that will provide the greatest reductions in forecast uncertainty.