Ensemble flood forecasting: a review.

Operational medium range flood forecasting systems are increasingly moving towards the adoption of ensembles of numerical weather predictions (NWP), known as ensemble prediction systems (EPS), to drive their predictions. We review the scientific drivers of this shift towards such ‘ensemble flood forecasting’ and discuss several of the questions surrounding best practice in using EPS in flood forecasting systems. We also review the literature evidence of the ‘added value’ of flood forecasts based on EPS and point to remaining key challenges in using EPS successfully.

[1]  Martin Göber,et al.  Fairplay in the verification of operational quantitative precipitation forecasts , 2004 .

[2]  Xixi Lu,et al.  River channel change during the last 50 years in the middle Yangtze River, the Jianli reach , 2007 .

[3]  Craig H. Bishop,et al.  Adaptive sampling with the ensemble transform Kalman filter , 2001 .

[4]  F. Atger.  Verification of intense precipitation forecasts from single models and ensemble prediction systems , 2001 .

[5]  Peter J. Webster,et al.  A 1–10-Day Ensemble Forecasting Scheme for the Major River Basins of Bangladesh: Forecasting Severe Floods of 2003–07* , 2010 .

[6]  Roman Krzysztofowicz,et al.  Integrator of uncertainties for probabilistic river stage forecasting: precipitation-dependent model , 2001 .

[7]  H. Hersbach.  Decomposition of the Continuous Ranked Probability Score for Ensemble Prediction Systems , 2000 .

[8]  K. Bogner,et al.  Error‐correction methods and evaluation of an ensemble based hydrological forecasting system for the Upper Danube catchment , 2008 .

[9]  B. Golding.  Quantitative precipitation forecasting in the UK , 2000 .

[10]  Florence Rabier,et al.  An update on THORPEX-related research in data assimilation and observing strategies , 2008 .

[11]  Uwe Grünewald,et al.  Flood Risk Reduction in Germany - Lessons Learned from the 2002 Disaster in the Elbe Region : Summary of the Study , 2004 .

[12]  Roman Krzysztofowicz,et al.  Bayesian theory of probabilistic forecasting via deterministic hydrologic model , 1999 .

[13]  Florian Pappenberger,et al.  Monthly‐, medium‐, and short‐range flood warning: testing the limits of predictability , 2009 .

[14]  Piotr K. Smolarkiewicz,et al.  Predicting weather, climate and extreme events , 2008, J. Comput. Phys..

[15]  I. Jolliffe,et al.  Forecast verification : a practitioner's guide in atmospheric science , 2011 .

[16]  Herbert Lang,et al.  Advanced flood forecasting in Alpine watersheds by coupling meteorological observations and forecasts with a distributed hydrological model , 2002 .

[17]  Ross N. Hoffman,et al.  Lagged average forecasting, an alternative to Monte Carlo forecasting , 1983 .

[18]  UNCERTAINTIES IN APPLICATION OF NWP-BASED QPF IN REAL-TIME FLOOD FORECASTING , 2005 .

[19]  Jonathan R. M. Hosking,et al.  MODELLING THE EFFECTS OF SPATIAL VARIABILITY IN RAINFALL ON CATCHMENT RESPONSE. : 1. FORMULATION AND CALIBRATION OF A STOCHASTIC RAINFALL FIELD MODEL , 1996 .

[20]  D. Lettenmaier,et al.  An ensemble approach for attribution of hydrologic prediction uncertainty , 2008 .

[21]  T. N. Krishnamurti,et al.  Improved Weather and Seasonal Climate Forecasts from Multimodel Superensemble. , 1999, Science.

[22]  C. Doswell,et al.  On Summary Measures of Skill in Rare Event Forecasting Based on Contingency Tables , 1990 .

[23]  Keith Beven,et al.  The sensitivity of hydrological models to spatial rainfall patterns: an evaluation using observed data , 1994 .

[24]  François Anctil,et al.  Impact of spatial aggregation of inputs and parameters on the efficiency of rainfall‐runoff models: A theoretical study using chimera watersheds , 2004 .

[25]  K. Beven,et al.  Development of a European flood forecasting system , 2003 .

[26]  C. Bishop,et al.  Ensemble Transform Kalman Filter-based ensemble perturbations in an operational global prediction system at NCEP , 2006 .

[27]  V. Fortin,et al.  Probabilistic forecasting from ensemble prediction systems: Improving upon the best‐member method by using a different weight and dressing kernel for each member , 2006 .

[28]  S. Bhowmik,et al.  Multi-model ensemble forecasting of rainfall over Indian monsoon region , 2008 .

[29]  Barbara G. Brown,et al.  Forecast verification: current status and future directions , 2008 .

[30]  F. Joseph Turk,et al.  Real-time multianalysis-multimodel superensemble forecasts of precipitation using TRMM and SSM/I products , 2001 .

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

[32]  Renate Hagedorn,et al.  The rationale behind the success of multi-model ensembles in seasonal forecasting-II , 2005 .

[33]  R. Buizza,et al.  The Hydrologic Ensemble Prediction EXperiment (HEPEX) , 2006 .

[34]  Peter C. Young,et al.  A data based mechanistic approach to nonlinear flood routing and adaptive flood level forecasting , 2008 .

[35]  Michael K. Tippett,et al.  Skill of Multimodel ENSO Probability Forecasts , 2008 .

[36]  Roman Krzysztofowicz,et al.  Hydrologic uncertainty processor for probabilistic river stage forecasting , 2000 .

[37]  A. H. Murphy.  The Finley Affair: A Signal Event in the History of Forecast Verification , 1996 .

[38]  Murugesu Sivapalan,et al.  Transformation of point rainfall to areal rainfall: Intensity-duration-frequency curves , 1998 .

[39]  Vijay P. Singh,et al.  Effect of spatial and temporal variability in rainfall and watershed characteristics on stream flow hydrograph , 1997 .

[40]  I. Rodríguez‐Iturbe,et al.  The design of rainfall networks in time and space , 1974 .

[41]  A. Georgakakos,et al.  Assessment of Folsom Lake response to historical and potential future climate scenarios: 2. Reservoir management , 2001 .

[42]  E. Roulin,et al.  Skill and relative economic value of medium-range hydrological ensemble predictions , 2006 .

[43]  T. Diomede,et al.  A meteo-hydrological prediction system based on a multi-model approach for precipitation forecasting , 2008 .

[44]  Ian Cluckie,et al.  Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction , 2006 .

[45]  Tempei Hashino,et al.  Evaluation of bias-correction methods for ensemble streamflow volume forecasts , 2006 .

[46]  T. N. Krishnamurti,et al.  A Perturbation Method for Hurricane Ensemble Predictions , 1999 .

[47]  Roman Krzysztofowicz.  Probabilistic flood forecast: bounds and approximations , 2002 .

[48]  Jutta Thielen,et al.  The european flood alert system EFAS - Part 2: statistical skill assessment of probabilistic and deterministic operational forecasts. , 2008 .

[49]  Florian Pappenberger,et al.  New dimensions in early flood warning across the globe using grand‐ensemble weather predictions , 2008 .

[50]  U. Germann,et al.  MAP D-PHASE: Real-Time Demonstration of Weather Forecast Quality in the Alpine region , 2009 .

[51]  Keith Beven,et al.  Uniqueness of place and process representations in hydrological modelling , 2000 .

[52]  Michael D. Kane,et al.  Nonparametric Framework for Long‐range Streamflow Forecasting , 1992 .

[53]  Roberto Buizza,et al.  The value of probabilistic prediction , 2008 .

[54]  Martyn P. Clark,et al.  The Hydrological Ensemble Prediction Experiment , 2007 .

[55]  David B. Stephenson,et al.  The extreme dependency score: a non‐vanishing measure for forecasts of rare events , 2008 .

[56]  Matthew D. Wilson,et al.  Tracking the uncertainty in flood alerts driven by grand ensemble weather predictions , 2009 .

[57]  Simon Jaun,et al.  A probabilistic view on the August 2005 floods in the upper Rhine catchment , 2008 .

[58]  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 .

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

[60]  Roman Krzysztofowicz,et al.  Bayesian system for probabilistic stage transition forecasting , 2004 .

[61]  Keith Beven,et al.  Environmental Modelling , 2007 .

[62]  Thielen Del Pozo Jutta,et al.  Evaluation of the Medium-Range European Flood Forecasts for the March-April 2006 Flood in the Morava River , 2008 .

[63]  Maria-Helena Ramos,et al.  Development of decision support products based on ensemble forecasts in the European flood alert system , 2007 .

[64]  J. Schaake,et al.  Correcting Errors in Streamflow Forecast Ensemble Mean and Spread , 2008 .

[65]  Edmund C. Penning-Rowsell,et al.  The Benefits of Flood Warnings: Real But Elusive, and Politically Significant , 2000 .

[66]  R. Buizza,et al.  Performance of the ECMWF and the BoM Ensemble Prediction Systems in the Southern Hemisphere , 2004 .

[67]  Zongjian Ke,et al.  Multimodel Ensemble Forecasts for Precipitations in China in 1998 , 2008 .

[68]  G. Lindström,et al.  Deterministic evaluation of ensemble streamflow predictions in Sweden , 2007 .

[69]  Gheorghe Stancalie,et al.  Transboundary Floods: Reducing Risks Through Flood Management , 2006 .

[70]  P. Webster,et al.  Extended-Range Probabilistic Forecasts of Ganges and Brahmaputra Floods in Bangladesh , 2010 .

[71]  R. Buizza,et al.  Flood forecasting using medium-range probabilistic weather prediction , 2005 .

[72]  Craig H. Bishop,et al.  The THORPEX Interactive Grand Global Ensemble , 2010 .

[73]  Thielen Del Pozo Jutta,et al.  Assessing Operational Forecasting Skill of EFAS , 2007 .

[74]  P. E. O'connell,et al.  IAHS Decade on Predictions in Ungauged Basins (PUB), 2003–2012: Shaping an exciting future for the hydrological sciences , 2003 .

[75]  Balázs Gauzer,et al.  APPLICATION OF METEOROLOGICAL ENSEMBLES FOR DANUBE FLOOD FORECASTING AND WARNING , 2006 .

[76]  E. Foufoula‐Georgiou,et al.  Fluvial processes and streamflow variability: Interplay in the scale‐frequency continuum and implications for scaling , 2005 .

[77]  Jutta Thielen,et al.  EFAS forecasts for the March–April 2006 flood in the Czech part of the Elbe River Basin—a case study , 2008 .

[78]  G. Thirel,et al.  On the Impact of Short-Range Meteorological Forecasts for Ensemble Streamflow Predictions , 2008 .

[79]  David S. Richardson,et al.  On the effect of ensemble size on the discrete and continuous ranked probability scores , 2008 .

[80]  G. Socher.  Conclusions References , 2000 .

[81]  K. Georgakakos,et al.  Assessment of Folsom lake response to historical and potential future climate scenarios: 1. Forecasting , 2001 .

[82]  P. Naden.  Spatial variability in flood estimation for large catchments: the exploitation of channel network structure , 1992 .

[83]  Thomas M. Hamill,et al.  Ensemble Reforecasting: Improving Medium-Range Forecast Skill Using Retrospective Forecasts , 2004 .

[84]  Martyn P. Clark,et al.  HEPEX: The Hydrological Ensemble Prediction Experiment , 2007 .

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

[86]  Y. Ben-Haim.  Information-gap decision theory : decisions under severe uncertainty , 2001 .

[87]  Alberto Montanari,et al.  Large sample behaviors of the generalized likelihood uncertainty estimation (GLUE) in assessing the uncertainty of rainfall‐runoff simulations , 2005 .

[88]  Roberto Buizza,et al.  A strategy for high‐resolution ensemble prediction. II: Limited‐area experiments in four Alpine flood events , 2001 .

[89]  Roman Krzysztofowicz,et al.  Hydrologic uncertainty processor for probabilistic stage transition forecasting , 2004 .

[90]  Dennis J. Parker,et al.  An evaluation of flood forecasting, warning and response systems in the European Union , 1996 .

[91]  T. Palmer,et al.  Stochastic representation of model uncertainties in the ECMWF ensemble prediction system , 2007 .

[92]  G. Shutts.  A kinetic energy backscatter algorithm for use in ensemble prediction systems , 2005 .

[93]  A. Montani,et al.  A spatial verification method applied to the evaluation of high‐resolution ensemble forecasts , 2008 .

[94]  D. Richardson.  Skill and relative economic value of the ECMWF ensemble prediction system , 2000 .

[95]  S. Jaun,et al.  Evaluation of a probabilistic hydrometeorological forecast system. , 2009 .

[96]  Renate Hagedorn,et al.  The rationale behind the success of multi-model ensembles in seasonal forecasting — I. Basic concept , 2005 .

[97]  E. Lorenz.  The predictability of a flow which possesses many scales of motion , 1969 .

[98]  David S. Richardson,et al.  Measures of skill and value of ensemble prediction systems, their interrelationship and the effect of ensemble size , 2001 .

[99]  Paul O'Connell,et al.  Modelling the effects of spatial variability in rainfall on catchment response. 2. Experiments with distributed and lumped models , 1996 .

[100]  Keith Beven,et al.  So just why would a modeller choose to be incoherent , 2008 .

[101]  Jan Seibert,et al.  On the need for benchmarks in hydrological modelling , 2001 .

[102]  Todini,et al.  Coupling meteorological and hydrological models for flood forecasting , 2005 .

[103]  Qingyun Duan,et al.  NOAA'S Advanced Hydrologic Prediction Service: Building Pathways for Better Science in Water Forecasting , 2005 .

[104]  Leonard A. Smith,et al.  Evaluating Probabilistic Forecasts Using Information Theory , 2002 .

[105]  Keith Beven,et al.  The future of distributed models: model calibration and uncertainty prediction. , 1992 .

[106]  Jason P. Antenucci,et al.  A three dimensional model of Cryptosporidium dynamics in lakes and reservoirs: A new tool for risk management , 2004 .

[107]  Albrecht H. Weerts,et al.  Probabilistic Quantitative Precipitation Forecast for Flood Prediction: An Application , 2008 .

[108]  S. Vogt,et al.  MAP D‐PHASE: real‐time demonstration of hydrological ensemble prediction systems , 2008 .

[109]  Renate Hagedorn,et al.  Probabilistic Forecast Calibration Using ECMWF and GFS Ensemble Reforecasts. Part I: Two-Meter Temperatures , 2008 .

[110]  Francisco J. Doblas-Reyes,et al.  How much does simplification of probability forecasts reduce forecast quality? , 2008 .

[111]  R. Buizza,et al.  A Comparison of the ECMWF, MSC, and NCEP Global Ensemble Prediction Systems , 2005 .

[112]  M. Huttunen,et al.  Hydrological Forecasting and Real Time Monitoring in Finland: The Watershed Simulation and Forecasting System (WSFS) , 2001 .

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

[114]  Roland K. Price,et al.  Rijnland case study: hindcast experiment for anticipatory water‐system control , 2008 .

[115]  M. Collins.  Ensembles and probabilities: a new era in the prediction of climate change , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

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

[117]  S. Kohnová,et al.  ROUTING OF NUMERICAL WEATHER PREDICTIONS THROUGH A RAINFALL-RUNOFF MODEL , 2006 .

[118]  Roman Krzysztofowicz,et al.  Bayesian system for probabilistic river stage forecasting , 2002 .

[119]  G. Lindström,et al.  Evaluation and calibration of operational hydrological ensemble forecasts in Sweden , 2008 .

[120]  Victor Koren,et al.  Runoff response to spatial variability in precipitation: an analysis of observed data , 2004 .

[121]  G. Roth,et al.  Applicability of a forecasting chain in a different morphological environment in Italy , 2005 .

[122]  Jutta Thielen,et al.  Ensemble predictions and perceptions of risk, uncertainty, and error in flood forecasting , 2007 .

[123]  Keith Beven,et al.  Informal likelihood measures in model assessment: Theoretic development and investigation , 2008 .

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

[125]  Roberto Buizza,et al.  TIGGE: Preliminary results on comparing and combining ensembles , 2008 .

[126]  J. Schaefer.  The critical success index as an indicator of Warning skill , 1990 .

[127]  Dennis P. Lettenmaier,et al.  Long range experimental hydrologic forecasting for the eastern U.S. , 2002 .

[128]  Arun Kumar,et al.  Long‐range experimental hydrologic forecasting for the eastern United States , 2002 .

[129]  P. L. Houtekamer,et al.  Using ensemble forecasts for model validation , 1997 .

[130]  Stochastic Modelling of Space-Time Rainfall: And the Significance of Spatial Data for Flood Runoff Generation , 2010 .

[131]  Gerald N. Day,et al.  Extended Streamflow Forecasting Using NWSRFS , 1985 .

[132]  A. Schumann,et al.  Combination of different types of ensembles for the adaptive simulation of probabilistic flood forecasts: hindcasts for the Mulde 2002 extreme event , 2008 .

[133]  Soroosh Sorooshian,et al.  Effect of rainfall‐sampling errors on simulations of desert flash floods , 1994 .

[134]  Hannah L. Cloke,et al.  Evaluating forecasts of extreme events for hydrological applications: an approach for screening unfamiliar performance measures , 2008 .

[135]  J. Seibert.  On TOPMODEL's ability to simulate groundwater dynamics , 1999 .

[136]  Keith Beven,et al.  Multi-period and multi-criteria model conditioning to reduce prediction uncertainty in an application of TOPMODEL within the GLUE framework , 2007 .

[137]  Harold E. Brooks,et al.  Societal and Economic Research and Applications For Weather Forecasts: Priorities for the North American THORPEX Program , 2008 .

[138]  J. Thielen,et al.  The European Flood Alert System – Part 1: Concept and development , 2008 .

[139]  S. Ray.  Evaluation and calibration , 2002 .

[140]  L. Mark Berliner,et al.  Bayesian Design and Analysis for Superensemble-Based Climate Forecasting , 2008 .

[141]  Murugesu Sivapalan,et al.  A synthesis of space‐time variability in storm response: Rainfall, runoff generation, and routing , 1999 .

[142]  Sandro Carniel,et al.  A note on the multimodel superensemble technique for reducing forecast errors , 2008 .

[143]  Keith Beven,et al.  Functional classification and evaluation of hydrographs based on Multicomponent Mapping (Mx) , 2004 .