Managing uncertainty in design flood magnitude: Flexible protection strategies versus safety factors

Abstract

When planning flood protection, agencies are confronted with uncertainty in the design flood magnitude. In particular, the required capacity may increase in the future and render the protection insufficient. This problem can be adressed by applying a safety factor to the design capacity. We propose a Bayesian quantitative sequential decision model that identifies a cost-optimal safety factor in the face of uncertainty. It takes into account the flexibility of the protection system, that is, how costly it is to adjust. We focus on the description of the decision model and on the concept of flexibility, investigating only the effect of uncertainty from the historic flood record. Extension to other types of uncertainty is possible. The model is implemented for a catchment in Germany. Various degrees of uncertainty are investigated by using different lengths of historic records. The optimal safety factor decreases with decreasing uncertainty and with increasing system flexibility. K E Y W O R D SBayesian decision analysis, decision support under uncertainty, flexible protection strategies, flood protection, natural hazards, safety factor, uncertainty quantification

Climate uncertainty in flood protection planning

“…Dependence between projections is accounted for by using the concept of effective projection number. We demonstrated the estimation of uncertainties and the application of the optimization framework of (Dittes et al, 2017) in a pre-alpine catchment. The results show that for a given sizable internal variability, the protection recommendation is robust to further uncertainty and moderate changes in trend.…”

“…The protection requirement corresponds to the maximal required protection during the time step in question. As in (Dittes et al, 2017), we used a square 30 root cost function for the construction/extension of the protection system and a discounting rate of 2 %. In (Dittes et al, 2017), we considered a measure of flexibility which describes how costly it is to adapt measures later in their life time.…”

“…A Bayesian Network approach doing so for decisions on adapting infrastructure to a changing climate has been presented by (Nishijima, 2015) and a POMDP approach applied to flood protection, using climate scenarios, has been described 5 by (Špačková and Straub, 2016). An alternative sampling-based approach, which takes the full joint parameter PDF into account, has been proposed by (Dittes et al, 2017). The planning horizon is divided into a number of time periods.…”

“…In Sect. 3, we show how to combine the different sources of uncertainty to use in the decision framework of (Dittes et al, 2017). The resulting recommendations are presented and discussed in Sect.…”

“…We have previously proposed a fully quantitative Bayesian decision making framework for flood protection which takes into account the uncertainty in the parameters of extreme discharge and probabilistically models realizations of future extreme discharges for sequential protection planning (Dittes et al, 2017). The framework recommends a cost-optimal capacity of flood protection measures given a fixed protection criterion (such as the 100-year flood), taking into account possible future 20 measure adjustments.…”