Initial damage, caused by previous wave loading or other events, might affect the hydraulic stability of pattern-placed revetments. Three common types of damage are considered in this study. The effect of this assumed initial damage on the hydraulic stability and failure probability of revetments is quantified using a FEM model. This model is developed using data from large-scale flume and field experiments. Using results from the FEM model, surrogate models are created to predict the effect of each type of initial damage on the hydraulic stability and failure probability. Through the use of these surrogate models, it is demonstrated that S-shaped deformation caused by filter migration around the wave impact zone has the largest effect on the hydraulic stability decreasing up to 30%, and failure probability per year increasing up to 10,000 times. When the granular filling between the joints of the columns is washed-out, the stability decreases up to 29% and the failure probability increases up to 700 times. A missing column has a limited effect on the hydraulic stability and failure probability when there is no other (structural) damage. However, if it originates from underlying damage, it might be an initial sign of total failure of the revetment. This study demonstrates the effectiveness of finite element modeling for studying (damaged) revetments, which can be used to complement flume experiments. The results can be used to prioritize maintenance efforts in risk-based maintenance of pattern-placed revetments.

EU Member States invest some €2.5 billion per year in flood protection, yet flood damages continue to increase. A new approach to the planning, design and management of flood protection assets is needed to ensure risks are better managed and asset management is aligned with broader socio-economic policies and supporting governance systems. This paper sets out a policy framework to enable this transition. The framework results from a collaboration of researchers and practitioners from around the North Sea. The findings highlight common challenges and identify four priority Policy Recommendations in response to these: ‘Break free of the silo’ by aligning planning processes; ‘Mind the gap’ between strategic and operational choices; ‘Prepare for change’ by developing multi-functional and flexible plans; and ‘Make space for innovation’ by seeking to manage risk rather than avoiding it.

Climate change and deterioration require a continuous effort to reinforce flood defences and meet reliability requirements. To efficiently upgrade flood defence systems, insight in costs and benefits of measures at a system level is required throughout the process of planning and design. Due to the size of flood defence systems the number of possible decisions is large, which hampers system optimization. We describe a greedy search algorithm that can find (near-)optimal combinations of reinforcement measures for dike segments. The algorithm has been validated by comparing results for 2800 different dike segments to an integer programming implementation. The difference in objective value (Total Cost) is only 0.04% on average, which is small compared to other uncertainties in assessment and design of dike segments. The algorithm is applied to a reinforcement project for a dike segment of 41 independent sections, and compared to the common design practice which uses reliability-based requirements on a section level. It is found that the resulting reinforced dike segment is 42% cheaper to construct than the one obtained from the common approach, based on the same input information. This illustrates the practical and societal value of the design approach using a greedy search algorithm in this context.

Prioritisation of flood defence maintenance is typically based on visual inspection. However, literature shows that the Probability of Detection (PoD) of visual inspection can vary significantly. Here we investigate the PoD for visual inspections of flood defence structures, the consistency of damage classification, and the influence of different variables on the PoD, such as past experience. Four flood defence sections were inspected by 22 different inspectors for a variety of damage types, such as animal burrowing and damage to block revetments. It is found that the PoD varies significantly both per damage type and inspector. Additionally, the estimated severity of damages varies significantly in comparison to the reference situation: over half of the registered damages is assigned a different severity compared to the reference, which potentially leads to incorrect maintenance measures. A likely explanation for the variation in results is the complexity of inspection guidelines and task definitions. Therefore it is advised to simplify inspection guidelines and use more focussed inspections for the most important types of damage. This likely leads to both a reduction of the number of false negatives associated with an increase in flood risk, and better risk-based asset management and maintenance prioritisation in general.

Uncertainties about climate change consequences, changing societal requirements and system complexity require flood protection asset managers to continuously evaluate their asset management policies and practice to manage risk and improve the resilience of their assets. However, there are many challenges in doing this, with asset operators often facing conflicting interests and major uncertainties about the future needs for asset performance. In the EU Interreg IV FAIR project, flood protection asset owners and operators, with scientific partners from the North Sea Region of Europe collaborated to develop practical guidance for adaptive asset management of flood protection infrastructure. The central component of this guidance is the FAIR framework, presented here. The framework combines insights and principles from ISO 55000 on asset management and ISO 14090 on climate adaptation with asset operator experiences to provide a practical guide for integration of asset management considerations within both strategic and operational contexts via a tactical handshake. This is a means to avoid the common lack of connection between strategic plans and operational practice. The applicability of the framework is illustrated with examples from Pilot Cases within the FAIR project, in which its value in terms of improved asset management and reduced costs has been demonstrated.

Spatial variability and limited measurements often result in low reliability estimates of geotechnical failure modes of dikes (i.e., earthen flood defences). Required dike reinforcements are usually not executed within a few years after inception, which enables efforts to improve reliability estimates by reducing uncertainty. Often decision makers are unclear on whether uncertainty reduction is worth investing, and which (combination of) methods yields the highest Value of Information (VoI). This paper presents a framework to assess the VoI of two uncertainty reduction methods (proof loading and pore pressure monitoring) for a case study of a typical river dike with an insufficiently stable inner slope, using a decision tree. In all cases, a positive VoI was found for at least one strategy consisting of a proof load test, monitoring or both. The optimal strategy of proof loading and monitoring has a VoI of 4.0 M€, being a reduction in total cost of 25% compared to a conventional dike reinforcement. It was also found that sometimes proof loading enhances the VoI of pore pressure monitoring, which demonstrates the benefits of jointly considering different methods in a single decision tree. The decision framework yields insight in total cost and VoI of risk reduction strategies, which enables decision makers to determine where proof loading and/or pore pressure monitoring are efficient, leading to more efficient flood defence asset management.