Author(s): Pierre Julien; Jeff Jorgeson
Linked Author(s): Pierre Y. Julien
Keywords: CASC2D watershed model; Peak flow; Hassyampa watershed; Radar dat
Abstract: The computational speed of computers and availability of spatial hydrologic data make distributed watershed models a viable approach for many applications, including peak flow forecasting. A study is presented that examines the potential for increasing forecast lead-time using radar data and distributed modeling. The CASC2D watershed model is applied on the Hassyampa River watershed in central Arizona using radar based rainfall estimates from the National Weather Service WSR-88D weather radar as the precipitation input. An application of radar rainfall data as input to the CASC2D model is then presented in which precipitation forecasts are generated by extrapolation of precipitation patterns from radar images. The calibrated model is run under two scenarios for two rainfall events. The first scenario ignores any future or forecast precipitation, and the second scenario includes forecast precipitation from the extrapolation of radar precipitation patterns. Forecast lead-time was increased for the two precipitation events by as much as 6 hours through the inclusion of these precipitation forecasts.