A spatially distributed flash flood forecasting model

This paper presents a distributed model that is in operational use for forecasting flash floods in northern Austria. The main challenge in developing the model was parameter identification which was addressed by a modelling strategy that involved a model structure defined at the model element scale and multi-source model identification. The model represents runoff generation on a grid basis and lumped routing in the river reaches. Ensemble Kalman Filtering is used to update the model states (grid soil moisture) based on observed runoff. The forecast errors as a function of forecast lead time are evaluated for a number of major events in the 622 km2 Kamp catchment and range from 10% to 30% for 4–24 h lead times, respectively.