Hurricanes and tropical storms are major geophysical disaster-causing agents, which are responsible for tremendous economic and property losses in the U.S. A large percentage of these losses have been due to flooding from intense storms. In order to minimize flood damages associated with large hurricane-season storms, it is important to be able to predict streamflow amount in response to storms for a range of hydroclimatological conditions. However, this is challenging considering that streamflow response exhibits appreciable variability even for storms that deliver similar precipitation amounts. In order to better understand the sources of this expressed streamflow variability, we use a physics-based, distributed hydrologic model and supporting hydrologic data sets to identify and evaluate dominant hydrologic controls on streamflow amount variability in a southeastern US watershed. Our analyses suggest that the dominant controls on the variability of streamflow amount are antecedent soil moisture condition near the ground surface, and evapotranspirative losses during post-event streamflow recession periods, which are in turn influenced by precipitation history and prevailing vegetation and meteorological conditions. Information regarding dominant controls could help prioritize measurements during observation campaigns and could aid in risk management to quickly evaluate flood responses given prior information about hurricane storm size.
Kumar, M., Chen, X., and McGlynn, B. (2014): Understanding the Variations in Flood Responses to Tropical-Storms and Hurricanes. American Geophysical Union annual meeting, San Francisco, California, December, 2014.
This Paper/Book acknowledges NSF CZO grant support.