A probabilistic view on the August 2005 floods in the upper Rhine catchment

Abstract. 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.

[1]  M. Zappa,et al.  The hydrological modelling system PREVAH , 2007 .

[2]  S. Bergström,et al.  DEVELOPMENT OF A CONCEPTUAL DETERMINISTIC RAINFALL-RUNOFF MODEL , 1973 .

[3]  K. Beven,et al.  Cascading model uncertainty from medium range weather forecasts (10 days) through a rainfall-runoff model to flood inundation predictions within the European Flood Forecasting System (EFFS) , 2005 .

[4]  C. Diks,et al.  Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation , 2005 .

[5]  Massimiliano Zappa,et al.  Verification of a coupled hydrometeorological modelling approach for alpine tributaries in the Rhine basin , 2006 .

[6]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[7]  F. Molteni,et al.  The ECMWF Ensemble Prediction System: Methodology and validation , 1996 .

[8]  A. Baltensweiler,et al.  Spatially distributed hydrotope-based modelling of evapotranspiration and runoff in mountainous basins , 1999 .

[9]  B. Ahrens.  Evaluation of precipitation forecasting with the limited area model ALADIN in an alpine watershed , 2003 .

[10]  C. Schär,et al.  Cloud‐resolving ensemble simulations of the August 2005 Alpine flood , 2008 .

[11]  B. Haddad,et al.  River Flow Forecasting with ANN OMID , 2005 .

[12]  Massimiliano Zappa,et al.  Multiple-response verification of a distributed hydrologial model at different spatial scales , 2002 .

[13]  J. Steppeler,et al.  Meso-gamma scale forecasts using the nonhydrostatic model LM , 2003 .

[14]  F. Pappenberger,et al.  Ignorance is bliss: Or seven reasons not to use uncertainty analysis , 2006 .

[15]  Ezio Todini,et al.  Role and treatment of uncertainty in real‐time flood forecasting , 2004 .

[16]  Tiziana Paccagnella,et al.  The COSMO-LEPS mesoscale ensemble system: validation of the methodology and verification , 2005 .

[17]  Pertti Nurmi,et al.  Recommendations on the verification of local weather forecasts , 2003 .

[18]  E. Kalnay,et al.  Ensemble Forecasting at NCEP and the Breeding Method , 1997 .

[19]  Günter Blöschl,et al.  Ensemble prediction of floods – catchment non-linearity and forecast probabilities , 2007 .

[20]  Bodo Ahrens,et al.  Information-Based Skill Scores for Probabilistic Forecasts , 2008 .

[21]  Giorgio Boni,et al.  A hydrometeorological approach for probabilistic flood forecast , 2005 .

[22]  Christoph Schär,et al.  Probabilistic Flood Forecasting with a Limited-Area Ensemble Prediction System: Selected Case Studies , 2007 .

[23]  Tomas Vitvar,et al.  A comparative study in modelling runoff and its components in two mountainous catchments , 2003 .

[24]  Mark A. Liniger,et al.  The discrete brier and ranked probability skill scores , 2007 .

[25]  Göran Lindström,et al.  Development and test of the distributed HBV-96 hydrological model , 1997 .

[26]  F. Molteni,et al.  A strategy for high‐resolution ensemble prediction. I: Definition of representative members and global‐model experiments , 2001 .

[27]  D. Legates,et al.  Evaluating the use of “goodness‐of‐fit” Measures in hydrologic and hydroclimatic model validation , 1999 .

[28]  Emmanuel Roulin,et al.  Skill of Medium-Range Hydrological Ensemble Predictions , 2005 .

[29]  Mark A. Liniger,et al.  Generalization of the Discrete Brier and Ranked Probability Skill Scores for Weighted Multimodel Ensemble Forecasts , 2007 .

[30]  C. Collier.  Flash flood forecasting: What are the limits of predictability? , 2007 .

[31]  Wolfgang-Albert Flügel,et al.  Combining GIS with regional hydrological modelling using hydrological response units (HRUs): an application from Germany , 1997 .

[32]  Stefania Tamea,et al.  Verification tools for probabilistic forecasts of continuous hydrological variables , 2006 .

[33]  Roberto Buizza,et al.  The Singular-Vector Structure of the Atmospheric Global Circulation , 1995 .

[34]  Francisco J. Doblas-Reyes,et al.  A Debiased Ranked Probability Skill Score to Evaluate Probabilistic Ensemble Forecasts with Small Ensemble Sizes , 2005 .

[35]  W. Briggs.  Statistical Methods in the Atmospheric Sciences , 2007 .