Keywords
flood defence, uncertainty, climate change, adaptation, rhine, dike, risk analysis
Start Date
1-7-2008 12:00 AM
Abstract
Although river dikes still play a key role for flood protection in the Netherlands there is a growing interest for other measures to deal with larger peak discharges, such as lowering or widening the floodplains. Regardless of the strategy chosen the assessment of its effect on the flood risk depends on the peak discharge statistics. A problem here is that the statistical analysis of peak discharges relies on probability distributions based on the limited time series of extreme discharges. The extrapolation of these distributions are subject to considerable uncertainty, because there is a measuring record of only about 100 years and the natural variability can be expected to change as a result of climate change. This raises the question whether a more direct response to the effects of climate change is possible. The natural variability of the peak discharge changes, the changes in this variability due to e.g. climate change and the new statistical distribution can only be established after the actual change has happened. Even with regular updates of the statistical distributions it is inherent that the actions taken to reduce the flood risk are not anticipatory but delayed. As an alternative, this paper presents an adaptive or so-called self-learning approach to deal with the uncertainty in the peak discharge statistics. The difference with the probabilistic design of flood defense works, which depends on the analysis and prediction of uncertain peak discharges, is that the dike is adapted in direct response to peak water levels exceeding the dike height minus a certain safety margin. The results indicate that, on average, adaptive flood management based on observed peak water levels is at least as safe as a probabilistic approach, which necessarily relies on uncertain discharge statistics. Other advantages of the adaptive strategy are also obvious: the rule of response is simple and easy to communicate to the public, and peak water levels are less difficult to measure. In general the example demonstrates that flood management can be based on a direct response to the effects of climate change, without tedious statistical analysis of peak discharge records.
Living With Peak Discharge Uncertainty: The Self-learning Dike
Although river dikes still play a key role for flood protection in the Netherlands there is a growing interest for other measures to deal with larger peak discharges, such as lowering or widening the floodplains. Regardless of the strategy chosen the assessment of its effect on the flood risk depends on the peak discharge statistics. A problem here is that the statistical analysis of peak discharges relies on probability distributions based on the limited time series of extreme discharges. The extrapolation of these distributions are subject to considerable uncertainty, because there is a measuring record of only about 100 years and the natural variability can be expected to change as a result of climate change. This raises the question whether a more direct response to the effects of climate change is possible. The natural variability of the peak discharge changes, the changes in this variability due to e.g. climate change and the new statistical distribution can only be established after the actual change has happened. Even with regular updates of the statistical distributions it is inherent that the actions taken to reduce the flood risk are not anticipatory but delayed. As an alternative, this paper presents an adaptive or so-called self-learning approach to deal with the uncertainty in the peak discharge statistics. The difference with the probabilistic design of flood defense works, which depends on the analysis and prediction of uncertain peak discharges, is that the dike is adapted in direct response to peak water levels exceeding the dike height minus a certain safety margin. The results indicate that, on average, adaptive flood management based on observed peak water levels is at least as safe as a probabilistic approach, which necessarily relies on uncertain discharge statistics. Other advantages of the adaptive strategy are also obvious: the rule of response is simple and easy to communicate to the public, and peak water levels are less difficult to measure. In general the example demonstrates that flood management can be based on a direct response to the effects of climate change, without tedious statistical analysis of peak discharge records.
