Abstract
The Susquehanna River basin (SRB) is the largest U.S. watershed () draining to the Atlantic Coast. It encompasses portions of New York, Pennsylvania, and Maryland. Given that annual maximum flood events commonly result from either rain-on-snow or hurricanes/tropical storms, determining the potential impacts of climate change on flooding behavior is especially challenging. This paper presents a modeling system that captures these dominant flooding processes, which is well-suited for future research investigating the impacts of regional climate change. For this study, a coupled hydrologic-hydraulic model is developed and used to estimate hourly streamflow for the period from 2000 to 2008, capturing a range annual maximum discharge phenomenon (e.g., rain-on-snow, localized convective events, and hurricanes/tropical storms). The three-layer variable infiltration capacity (VIC-3L) model is used to generate surface runoff and the vertical flux of water through the root zone at a scale of 0.025° (about 2.8 km), which are used as inputs to the Hillslope River Routing (HRR) model that operates on an irregular grid with a mean length scale of 4.7 km to simulate lateral surface and subsurface transport and channel hydraulics. The coupled model is validated using USGS daily streamflow, snow water equivalent (SWE) derived from the advanced microwave scanning radiometer for EOS (AMSR-E) satellite and snow depth from in situ measurements. The coupled model (VIC-HRR) shows good performance for both seasonal baseflow patterns and large flood events (e.g., rain-on-snow and hurricane/tropical storms). Given the SRB is commonly subjected to two types of flood events, the role of snow processes is investigated. Comparing synthetic model scenarios with and without snow processes suggests that if future climate conditions reduce winter snowfall due to warmer temperatures, but maintain total precipitation levels, annual runoff will increase and mean annual peak discharge will decrease.
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Acknowledgments
This work was funded by FM Global and NASA’s Terrestrial Hydrology Program (Grant No. NNX12AQ36G and NNX14AD82G). The authors acknowledge data obtained from various NASA Earth Observing System (EOS) satellite missions, the U.S. Department of Agriculture, the U.S. Geological Survey, and the National Climate Data Center.
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Journal of Hydrologic Engineering
Volume 21 • Issue 9 • September 2016
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© 2016 American Society of Civil Engineers.
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Received: Apr 13, 2015
Accepted: Jan 22, 2016
Published online: Apr 6, 2016
Published in print: Sep 1, 2016
Discussion open until: Sep 6, 2016
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