Combination of different types of ensembles for the adaptive simulation of probabilistic flood forecasts: hindcasts for the Mulde 2002 extreme event

Abstract

Abstract. Flood forecasts are essential to issue reliable flood warnings and to initiate flood control measures on time. The accuracy and the lead time of the predictions for head waters primarily depend on the meteorological forecasts. Ensemble forecasts are a means of framing the uncertainty of the potential future development of the hydro-meteorological situation.This contribution presents a flood management strategy based on probabilistic hydrological forecasts driven by operational meteorological ensemble prediction systems. The meteorological ensemble forecasts are transformed into discharge ensemble forecasts by a rainfall-runoff model. Exceedance probabilities for critical discharge values and probabilistic maps of inundation areas can be computed and presented to decision makers. These results can support decision makers in issuing flood alerts. The flood management system integrates ensemble forecasts with different spatial resolution and different lead times. The hydrological models are controlled in an adaptive way, mainly depending on the lead time of the forecast, the expected magnitude of the flood event and the availability of measured data.The aforementioned flood forecast techniques have been applied to a case study. The Mulde River Basin (SouthEastern Germany, Czech Republic) has often been affected by severe flood events including local flash floods. Hindcasts for the large scale extreme flood in August 2002 have been computed using meteorological predictions from both the COSMO-LEPS ensemble prediction system and the deterministic COSMO-DE local model. The temporal evolution of a) the meteorological forecast uncertainty and b) the probability of exceeding flood alert levels is discussed. Results from the hindcast simulations demonstrate, that the sysCorrespondence to: J. Dietrich (joerg.dietrich@rub.de) tems would have predicted a high probability of an extreme flood event, if they would already have been operational in 2002. COSMO-LEPS showed a reasonably good performance within a lead time of 2 to 3 days. Some of the deterministic very short-range forecast initializations were able to predict the dynamics of the event, but others underpredicted rainfall. Thus a lagged average ensemble approach is suggested. The findings from the case study support the often proposed added value of ensemble forecasts and their probabilistic evaluation for flood management decisions.

An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios

“…It has a total area of 336 km 2 , which is considerably smaller than most catchments, and even sub-catchments, referred to in the current literature on ensemble streamflow forecasting (e.g. Dietrich et al, 2008;Jaun and Ahrens, 2009;Thielen et al, 2009b;Reggiani et al, 2009). Earlier studies have shown that forecast skill depends on temporal and spatial scales.…”

Use of past precipitation data for regionalisation of hourly rainfall in the low mountain ranges of Saxony, Germany

“…For the very small Wiltzsch sub-catchment, a contributing area of a reservoir, the model was only calibrated for the flood event evaluated within this case study. All hourly simulations started seven days before the chosen event for an optimal adjusting of initial model conditions, which had been computed by a continuous long time model run with daily time steps before (Dietrich et al, 2008). We calculated the following objective indicators of performance for the events four and five:…”

“…We used the conceptual hydrological model ArcEGMO (Becker et al, 2002), which is in wide use for its short computational time, its flexibility in spatial, temporal and structural resolution and the mainly GIS-based assignment of parameters. The model was calibrated for the Mulde catchment for flood events from 1954 to 2006 using precipitation data from a) recording stations with high temporal resolution and b) disaggregated time series from stations with daily records (Dietrich et al, 2008). The upper Mulde catchment is situated in the Ore Mountains, whereas several sub-catchments drain from South to North.…”

Ensemble flood forecasting based on operational forecasts of the regional Eta EPS in the Taquari-Antas basin

“…Ensemble flood forecasting based on operational forecasts of the regional Eta EPS in the Taquari-Antas basin To derive streamflow forecasts, the hydrological model was forced with observed rainfall up to the start of forecast, and then coupled to deterministic QPF and each one of the ensemble members (herein referred to the HEPS). In addition, a combination of current forecasts with earlier model runs, known as Lagged Averaged Forecasts -LAF (DIETRICH et al, 2008), was adopted in order to increase the number of hydrological ensemble members without extra computational cost. The procedure used to generate the lagged forecasts was similar to that presented by Machado et al (2010), but in this case considering the hydrological forecasts instead of the meteorological ones.…”

“…In this approach, a set of possible future states of the atmosphere can be provided through small perturbations in the initial conditions of a control forecast (BUIZZA, 1997), different physical representations and changes in parameterization schemes of atmospheric models (STENSRUD; BAO;WARNER, 2000;WANDISHIN et al, 2001), or combination of previous forecasts with the most recent ones (DIETRICH et al, 2008;MACHADO et al, 2010). These systems have achieved consistent recognition for the improvement of weather forecast skill, leading hydrological research towards the development of Hydrological Ensemble Prediction Systems -HEPS (e.g.…”