Prospects for flash flood forecasting in mountainous regions – An investigation of Tropical Storm Fay in the Southern Appalachians

Jing Tao, Ana P. Barros
2013 Journal of Hydrology  
The sensitivity of Quantitative flash-Flood Estimates (QFEs) and Quantitative flash-Flood Forecasts (QFFs) to Quantitative Precipitation Estimates (QPEs) and Quantitative Precipitation Forecasts (QPFs) in mountainous regions was investigated for the passage of Tropical Storm Fay, 2008 over the Southern Appalachian Mountains in North Carolina, USA. QFEs and QFFs were generated by an uncalibrated high-resolution hydrologic model (250×250 m 2 ) with coupled surface-subsurface physics and rainfall
more » ... orcing from the National Severe Storms Laboratory Next Generation Multi-sensor QPE (Q2) spatial rainfall (1×1km 2 ) product, and from the operational QPF product from the National Weather Service National Digital Forecast Database (NDFD, 5×5 km 2 ). Optimal QPE products (Q2+) were derived by merging Q2 with rainfall observations from a high density raingauge network in the Great Smoky Mountains (GSMRGN) and subsequently used as "rainfall truth" to characterize operational QPF and QFE errors in three headwater catchments with different topographic and hydro-geomorphic characteristics. Deterministic QFE results agree well with observations regarding total water volume and peak flow, and with Nash-Sutcliffe coefficients 0.8-0.9 indicating that the distributed model without calibration captures well the dominant physical processes. The impact of Q2+ uncertainty with regard to the space-time structure of storm rainfall was subsequently evaluated through Monte Carlo replicates of the QPEs to generate QFE distributions. For long lasting events with several cells of heavy rainfall embedded in otherwise light to moderate rainfall such as Tropical Storms, the propagation of uncertainty from rainfall to flood response is highly non-linear, and exhibits strong dependence on basin physiography, soil moisture conditions (transient basin storage capacity), and runoff generation and conveyance mechanisms (overland flow, interflow and baseflow). The use of distributed physically-based models which can predict not only stream operational QPE/QPF could significantly improve the utility and precision of current operational QFF guidance, where the timing of heavy rainfall and satellite overpass are very close, but that the improvement depends strongly on storm-dependent and basin-specific rainfall-runoff dynamics.
doi:10.1016/j.jhydrol.2013.02.052 fatcat:vwo6gyak7nfpvn7tvi3trnnzme