A comparison is made between the current flood risk management policy in the Netherlands, which is a resistance strategy aimed at the prevention of flooding along the lower Rhine River by raising the dikes, and two alternative resilience strategies that aim at minimising the consequences of these floods, but at the same time allow some flooding. The alternative strategies rely on detention in compartments and on discharge via “green rivers”. These strategies were evaluated on their financial impacts (costs and flood damage) and on their impacts on economy, ecology and landscape, as well as on flexibility. The tangible effects, such as costs and damage were calculated using mathematical models; experts awarded scores to the intangibles, such as landscape quality and ecology. It is concluded that the initial costs of the resilience strategies are high whereas the gains, a reduction of the flood risk, will only be perceivable in the long term. On the other hand, the resilience strategies are more flexible and offer more opportunities for nature and landscape development

This paper addresses the large differences that are found between damage estimates of different flood damage models. It explains how implicit assumptions in flood damage functions and maximum damages can have large effects on flood damage estimates. This explanation is then used to quantify the uncertainty in the damage estimates with a Monte Carlo analysis. The Monte Carlo analysis uses a damage function library with 272 functions from seven different flood damage models. The paper shows that the resulting uncertainties in estimated damages are in the order of magnitude of a factor of 2 to 5. The uncertainty is typically larger for flood events with small water depths and for smaller flood events. The implications of the uncertainty in damage estimates for flood risk management are illustrated by a case study in which the economic optimal investment strategy for a dike segment in the Netherlands is determined. The case study shows that the uncertainty in flood damage estimates can lead to significant over- or under-investments.

Since flood disasters still occur and even increase in frequency and severity, flood risk management must be reconsidered. This paper describes a new way of looking at flood risk management by applying a systems approach. This approach may result in flood risk management that is better suited to the socio-economic context in which this flood risk management occurs. The systems approach allows the definition of resilience and resistance strategies for flood risk management. Resistance strategies aim at flood prevention, while resilience strategies aim at minimising flood impacts and enhancing the recovery from those impacts. A resilience strategy is supposed to be able to better cope with uncertainties than a resistance strategy. To enable the evaluation of resilience and resistance strategies under different conditions the concepts of resilience and resistance must first be sufficiently understood. This paper discusses the meaning of resilience and resistance and applies the concepts to flood risk management systems. This discussion is exemplified by The Netherlands' flood risk management.

Resilience strategies for flood risk management focus on minimising flood impacts and enhancing recovery in contrast with resistance strategies which aim at preventing floods entirely. Since resilience strategies are expected to result in improved flood risk management, they deserve careful evaluation. For the evaluation and comparison of strategies for flood risk management it is necessary to be able to quantify the resilience of the resulting flood risk management systems. However, no adequate methods to quantify this resilience are available yet. Therefore, this paper aims at defining and testing indicators for the resilience of flood risk management systems. A set of indicators is proposed, which covers the three aspects of resilience: amplitude of the reaction, graduality of the increase of reaction with increasingly severe flood waves, and recovery rate. To evaluate the behaviour of these indicators, they have been applied on simple hypothetical systems. It was found that with the combination of the indicators an overview of the resilience of flood risk management systems can be obtained.