On The Added Value Of Radar Data In Hydrological Modelling And Flood Forecasting

Good quality rainfall data are essential in hydrological modelling and flood forecasting. Classically, rain gauge data are being used as rainfall input for hydrological modelling, but they only provide point information. Because rainfall can be highly variable in space, radar images can provide important additional spatial information, but the quantitative rainfall data quality of these images is often limited. Merging techniques between rain gauge and radar data can provide a solution to this problem. In this research, a simple kriging merging technique, making use of two C-band radars, is tested for the Demer catchment in Belgium. Three periods with different types of rainfall were selected: two winter periods with stratiform rainfall and one summer period with convective rainfall. First, it was tested whether the merging technique is able to correct the quantitative radar rainfall information, by comparing the rainfall volumes at rain gauge locations, which were not used during the merging with the observed values. It was found that the merging technique performed well under stratiform conditions, but this was not always the case for the convective conditions. Secondly, the added value of the radar information was tested, by comparing hydrological and hydraulic model outputs, generated by rain gauge and/or radar data, to flow and water level observations. It is found that the added value of the radar data is limited for the winter periods, but that for the summer periods a significant improvement is obtained