A Bayesian approach for real-time flood forecasting

Abstract The paper describes a methodology based on the Bayesian Forecasting System (BFS), aimed at evaluating total uncertainty in real-time forecasting of flood events. The system was adapted for a small basin in the Calabria region (Southern Italy), assuming a stochastic model as rainfall predictor and a distributed rainfall–runoff model for simulating the hydrological response. Through two separate processors, the system evaluates the input uncertainty and the hydrological uncertainty, associated with all other possible sources of error. To discriminate adequately the effect of more intense rainfall in the hydrological response, the total uncertainty consists of a mixture of two components, conditioned on forecast rainfall, with respect to an assigned threshold, and on discharge observed at the forecast time. The results highlight the role of each BFS component in the real-time forecasting of a flood event.

[1]  Keith Beven,et al.  Estimation of flood inundation probabilities as conditioned on event inundation maps , 2003 .

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

[3]  Roger Alexander Falconer.  Water Quality Modelling , 1992 .

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

[5]  Keith Beven,et al.  Uncertainty and equifinality in calibrating distributed roughness coefficients in a flood propagation model with limited data , 1998 .

[6]  Christine A. Shoemaker,et al.  Introduction to special section on Uncertainty Assessment in Surface and Subsurface Hydrology: An overview of issues and challenges , 2009 .

[7]  Davide Luciano De Luca,et al.  Rainfall nowcasting by at site stochastic model P.R.A.I.S.E. , 2007 .

[8]  Yuqiong Liu,et al.  Uncertainty in hydrologic modeling: Toward an integrated data assimilation framework , 2007 .

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

[10]  George Kuczera,et al.  Bayesian analysis of input uncertainty in hydrological modeling: 1. Theory , 2006 .

[11]  Roman Krzysztofowicz,et al.  Identification of likelihood and prior dependence structures for hydrologic uncertainty processor , 2004 .

[12]  H. Gupta,et al.  Understanding uncertainty in distributed flash flood forecasting for semiarid regions , 2008 .

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

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

[15]  D. A. Woolhiser,et al.  Impact of small-scale spatial rainfall variability on runoff modeling , 1995 .

[16]  George Kuczera,et al.  Bayesian analysis of input uncertainty in hydrological modeling: 2. Application , 2006 .

[17]  G. Viviani,et al.  An urban drainage stormwater quality model model development and uncertainty quantification , 2010 .

[18]  Roman Krzysztofowicz,et al.  The case for probabilistic forecasting in hydrology , 2001 .

[19]  M. B. Beck,et al.  Water quality modeling: A review of the analysis of uncertainty , 1987 .

[20]  Gabriele Freni,et al.  Urban runoff modelling uncertainty: Comparison among Bayesian and pseudo-Bayesian methods , 2009, Environ. Model. Softw..

[21]  D. Kavetski,et al.  Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterising model error using storm-dependent parameters , 2006 .

[22]  Søren Liedtke Thorndahl,et al.  Event based uncertainty assessment in urban drainage modelling applying the GLUE methodology , 2008 .

[23]  Chong-Yu Xu,et al.  Statistical Analysis of Parameters and Residuals of a Conceptual Water Balance Model – Methodology and Case Study , 2001 .

[24]  George Kuczera,et al.  Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors , 2010 .

[25]  Pasquale Versace,et al.  Uncertainty assessment through a precipitation dependent hydrologic uncertainty processor: An application to a small catchment in southern Italy , 2010 .

[26]  David Huard,et al.  Calibration of hydrological model GR2M using Bayesian uncertainty analysis , 2008 .

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

[28]  M. Borga,et al.  Flash flood warning based on rainfall thresholds and soil moisture conditions: An assessment for gauged and ungauged basins , 2008 .

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

[30]  Roman Krzysztofowicz,et al.  Hydrologic uncertainty processor for probabilistic river stage forecasting: precipitation-dependent model , 2001 .