Uncertainty and sensitivity of flood risk calculations for a dike ring in the south of the Netherlands

Abstract

A central tool in risk management is the exceedance-probability loss (EPL) curve, which denotes the probabilities of damages being exceeded or equalled. These curves are used for a number of purposes, including the calculation of the expected annual damage (EAD), a common indicator for risk. The model calculations that are used to create such a curve contain uncertainties that accumulate in the end result. As a result, EPL curves and EAD calculations are also surrounded by uncertainties. Knowledge of the magnitude and source of these uncertainties helps to improve assessments and leads to better informed decisions. This study, therefore, performs uncertainty and sensitivity analyses for a dike-ring area in the Netherlands, on the south bank of the river Meuse. In this study, a Monte Carlo framework is used that combines hydraulic boundary conditions, a breach growth model, an inundation model, and a damage model. It encompasses the modelling of thirteen potential breach locations and uncertainties related to probability, duration of the flood wave, height of the flood wave, erodibility of the embankment, damage curves, and the value of assets at risk. The assessment includes uncertainty and sensitivity of risk estimates for each individual location, as well as the dike-ring area as a whole. The results show that for the dike ring in question, EAD estimates exhibit a 90% percentile range from about 8 times lower than the median, up to 4.5 times higher than the median. This level of uncertainty can mainly be attributed to uncertainty in depth-damage curves, uncertainty in the probability of a flood event and the duration of the flood wave. There are considerable differences between breach locations, both in the magnitude of the uncertainty, and in its source. This indicates that local characteristics have a considerable impact on uncertainty and sensitivity of flood damage and risk calculations.

Keywords: Flood risk assessment; Meuse river; Monte Carlo; Sensitivity analysis; Uncertainty analysis.