A Distributed Real-Time Flash-Flood Forecasting Model for the Semi-Arid West
Much of the western United States is currently classified as semi-arid according to the Koppen climatic classification. Semi-arid regions are particularly affected by flash floods, caused mainly by convective storms. In the United States on an annual basis, floods kill more people than any other form of severe weather. Flash floods account for more than eighty percent of all flood related deaths.

Predicting flash-floods is difficult due to their short duration and the small geographic region over which they occur. A tool that will allow the local Weather Forecast Office to forecast the timing and magnitude of flash floods in small watersheds throughout the western United States is desired. An adequate predictive tool has to be based on a good geometric representation of the watershed, and be driven by high-resolution, spatially distributed and accurate precipitation measurements. To this end, we are developing a real-time version of the well established event-based rainfall-runoff model, KINEROS2. This is a spatially distributed kinematic wave model that represents the catchment as a cascade of overland plane and trapezoidal channel elements. The dynamic infiltration algorithm was developed to particularly represent the hydrologic characteristics of semi-arid regions, simulating processes like Hortonian overland flow and in-channel transmission losses in ephemeral streams. KINEROS2 has been restructured into discrete modules which can be configured to run in real-time mode for operational use.

The aim of this project is to develop a site specific flash-flood forecasting model for the Western Region. Besides aiding in flash-flood forecasting, the model has applicability in flood-related risk assessment and decision-making in semi-arid and arid regions of the West. Proof-of-concept results of KINEROS2 for several small watersheds in Western Region will be presented.

By Mike Schaffner (WFO Tucson), Hoshin Gupta (University of Arizona), Soni Yatheendradas (University of Arizona), Thorsten Wagener (Penn State), and Carl Unkrich (USDA-ARS)