Model-based quantification of runoff generation processes at high spatial and temporal resolution

Heavy precipitation-induced flash floods are still a serious hazard and generate high damages. In the context of climate change, an increase of the occurrence of flash floods is very likely. To improve flash-flood predictions and allow measures to reduce damage in vulnerable catchments, the spatial dynamics of runoff generation at a high spatial resolution during extreme rainfall events need to be better predicted. The results of these models can then be included into hydraulic models to predict the surface water level and flow dynamics based on high-resolution topographic data. Long-term discharge data does generally not exist in the small headwaters mostly influenced by flash floods, which would allow to calibrate conventional rainfall-runoff models. But hydrological models predicting runoff generation processes without calibration based on available spatially distributed data sets are still lacking. Such a model [Runoff Generation Research (-RoGeR)] was developed for the state of Baden-Wurttemberg. It is based on an extensive collection of spatial data, including a digital elevation model of 1 x 1 m(2) resolution, degree of sealing of the earth surface for the same resolution, and soil properties and geology at the scale of 1: 50,000. Within the state of Baden-Wurttemberg, different regions were selected encompassing distinct environmental characteristics regarding climate, soil properties, land use, topography and geology. RoGeR was tested and validated by simulating 33 observed flood events in 13 mesoscale catchments without calibration and by modelling seven 60-m(2) artificial rainfall experiments on five different hillslopes in different regions of Switzerland. The results showed that the model was able to reproduce the temporal runoff dynamics as well as the peak discharge and the runoff volume in the mesoscale catchments as well as the 60-m(2) hillslope plots. The model could reproduce processes and hydrological response under different antecedent soil moisture and precipitation characteristics without any calibration, despite applying it to different regions and different scales. This suggests that RoGeR is predestinated to quantify runoff generation processes during heavy rainfall events at different scales without the typical model calibration procedure allowing to better quantify input and model uncertainty.