Open Access

Appropriate precautions in the case of flood occurrence often require long lead times (several days) in hydrological forecasting. This in turn implies large uncertainties that are mainly inherited from the meteorological precipitation forecast. Here we present a case study of the extreme flood event of August 2005 in the Swiss part of the Rhine catchment (total area 34 550 km2). This event caused tremendous damage and was associated with precipitation amounts and flood peaks with return periods beyond 10 to 100 years. To deal with the underlying intrinsic predictability limitations, a probabilistic forecasting system is tested, which is based on a hydrological-meteorological ensemble prediction system. The meteorological component of the system is the operational limited-area COSMO-LEPS that downscales the ECMWF ensemble prediction system to a horizontal resolution of 10 km, while the hydrological component is based on the semi-distributed hydrological model PREVAH with a spatial resolution of 500 m. We document the setup of the coupled system and assess its performance for the flood event under consideration. We show that the probabilistic meteorological-hydrological ensemble prediction chain is quite effective and provides additional guidance for extreme event forecasting, in comparison to a purely deterministic forecasting system. For the case studied, it is also shown that most of the benefits of the probabilistic approach may be realized with a comparatively small ensemble size of 10 members.

Medium range hydrological forecasts in mesoscale catchments are only possible with the use of hydrological models driven by meteorological forecasts, which in particular contribute quantitative precipitation forecasts (QPF). QPFs are accompanied by large uncertainties, especially for longer lead times, which are propagated within the hydrometeorological model system. To deal with this limitation of predictability, a probabilistic forecasting system is tested, which is based on a hydrological-meteorological ensemble prediction system. The meteorological component of the system is the operational limited-area ensemble prediction system COSMO-LEPS that downscales the global ECMWF ensemble to a horizontal resolution of 10 km, while the hydrological component is based on the semi-distributed hydrological model PREVAH with a spatial resolution of 500 m. Earlier studies have mostly addressed the potential benefits of hydrometeorological ensemble systems in short case studies. Here we present an analysis of hydrological ensemble hindcasts for two years (2005 and 2006). It is shown that the ensemble covers the uncertainty during different weather situations with an appropriate spread-skill relationship. The ensemble also shows advantages over a corresponding deterministic forecast, even under consideration of an artificial spread.