Real-time extremity assessment of rainfall observations and SINFONY forecasts for small hydrological catchments

Small-scale, convective heavy rainfall events present a major challenge in flood forecasting, primarily affecting smaller catchments. At such scales, flood forecasts are challenging due to short response times, a lack of stream gauges and limitations of operationally used hydrological models. These models are typically designed for larger catchments, therefore we explore alternative strategies to support the German flood forecasters.

The AREA product (Areal Rainfall Extremity Assessment) aims at complementing the flood forecasters’ workflow based on hydrological modeling by rapidly identifying catchments affected by strong rainfall. We intend to provide a novel post-processing product containing information about the extremity of catchment-specific areal rainfall. First, a nationwide catchment delineation is performed for each pixel of a 50 m x 50 m digital elevation model, selecting only catchments smaller with an area between 10 and 500 km². The catchments and stream network are subsequently upscaled to the operational radar grid with a resolution of 1 km. Finally, areal rainfall is computed for each pixel using the underlying catchment geometry from rain gauge-adjusted radar observations as well as seamless rainfall forecasts resulting from the SINFONY project with lead times of up to 12h.

In order to estimate the extremity of a catchment rainfall event in real-time, we derive return periods based on extreme value statistics. To that end, we consider various accumulation durations and perform a recalculation of areal rainfall for all catchments using a 20-year dataset of radar-derived rainfall. Given the short and limiting observation period of radar data, we attempt to combine the obtained extreme value distributions with existing, regionalized long-term rain gauge statistics (DWD-KOSTRA), in order to estimate longer return periods.

The resulting spatial distribution of areal rainfall with corresponding return periods based on an exhaustive collection of catchments appears to be a useful visualization technique to identify small catchments affected by heavy rainfall. The product will be illustrated based on the analysis of specific case studies.