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Tuesday 13 Dec 2011: A Methodology for Probabilistic Real -Time Forecasting – An urban Case Study
Jeanne-Rose Renee - University of Exeter
HAR170 14:00-15:00
The phenomenon of urban flooding due to rainfall exceeding the design capacity of drainage systems is a global problem and can have significant economic and social consequences. The complex nature of quantitative precipitation forecasts (QPFs’) from Numerical weather prediction (NWP) models has facilitated a need to model and manage uncertainty. This paper presents a probabilistic approach for modelling uncertainty in QPF at different lead times. The uncertainty models in the form of probability distributions combined with a 1D sewer model is an important advancement in real-time flood forecasting at the urban scale. The methodological approach utilized in this paper involves a retrospective comparison between historical forecasted rainfall from a NWP model and observed rainfall from rain gauges. Two different sampling methods, respectively, quantile of rainfall and the Latin hypercube sampling based method were used to determine the uncertainty in forecasted variants (water level, volume) for a test urban area, the city of Aarhus. The results indicate the potential for applying uncertainty assessment in rainfall forecasts and its subsequent use in flood forecasting.
