Hydraulic modelling approaches to decrease uncertainty in flood frequency relations

River floods are a major global hazard causing extensive damage and loss of lives. To protect the hinterland from severe inundations, flood defences are commonly designed according to appropriate safety levels that are determined based on a statistical return period. To estimate discharges associated with different return periods, flood frequency analyses are used that fit a distribution to the data set of annual maximum discharges.

The data sets of measured annual maximum discharges are generally in the order of 100 years. Consequently, the predicted design discharges with a return period of e.g. 100,000 years are based on extrapolation and therefore highly uncertain. To decrease the uncertainty of flood frequency relations, historical flood information can be added to the data set of measured discharges.

We aimed to study the effect of extending the data set of measured discharges on the reduction of the 95% uncertainty interval of flood frequency relations. The data set was extended with reconstructed historic flood events using hydraulic modelling approaches. The Rhine delta was used as a case study, but the proposed methodologies can also be applied to other river basins and coastal areas provided that sufficient data is available.

The study shows various efficient modelling approaches in which computational times are low while model accuracy is sufficiently high. Furthermore, we present a method to normalize historic flood events for natural and anthropological changes in the river system. The study ends with a method to extend the data set of annual maximum discharges with 600 years resulting in a significant reduction of the 95% confidence interval.