Proceedings of 11th International Conference on Hydroinformatics (HIC 2014) pages:1-8
11th International Conference on Hydroinformatics edition:2014 location:New York, USA date:17-21 August 2014
Rainfall forecast errors are considered to be the key source of uncertainty in flood forecasting. To quantify the rainfall forecast uncertainty itself and its impact on the total flood forecast uncertainty, a Monte-Carlo based statistical method has been developed. This method takes into account the dependency of the rainfall forecast error with the lead time and the rainfall amount. The forecasted rainfall errors are described by truncated normal distributions, allowing to quantify the full uncertainty distribution of the deterministic rainfall forecast. By means of Monte-Carlo sampling and taking the forecast error autocorrelation into account, the impact of the rainfall forecast uncertainty on a flood forecast was quantified. This was done for the Rivierbeek river in Belgium. In addition, comparison was made between the total flood forecast uncertainty and the uncertainty due to the forecasted rainfall. The total flood forecast uncertainty was quantified by a non-parametric data-based approach. It was concluded that the forecasted rainfall uncertainty contributes for about 30 percent to the total flood forecast uncertainty.