Infrastructure Asset Management (IAM) is the process by which decisions are made and resources allocated to ensure organisational or societal assets continue to deliver, as required. IAM is an evolving field. We discuss this evolution and present our perspectives on the future direction of IAM. IAM was born as a response to the poor state of maintenance of infrastructure, largely due to lack of resources, and emphasizes the need to prioritize maintenance and renewal using risk-based approaches. The demands on IAM have also continued to evolve as asset systems have become more complex, with multifunctionality, adaptative capacity and nature-based infrastructure, all issues that IAM must now consider. These challenges underpin the changing context of Water Infrastructure Asset Management (WIAM) and the opportunity for WIAM to harness new technical developments from other IAM domains. WIAM will need to continue to evolve, responding to these challenges and take advantage of these opportunities through research and application in collaboration with a relevant education and capacity development agenda.

One of the most rapidly emerging measures in infrastructure asset management is Structural Health Monitoring (SHM), which aims at reducing uncertainty in structural performance by using monitoring equipment. As earthen flood defence structures typically have large strength uncertainties, such techniques can be particularly promising. However, insight in the key characteristics for successful SHM for flood defences is lacking, which hampers the practical implementation. In this study, we explore the benefits of pore pressure monitoring, one of the most promising SHM techniques for earthen flood defences. The approach is based on a Bayesian pre-posterior analysis, and results are evaluated based on the Value of Information (VoI) obtained from different monitoring strategies. We specifically investigate the effect on long-term reinforcement decisions. The results show that, next to the relative magnitude of reducible uncertainty, the combination of the probability of having a useful observation and the duration of a SHM effort determine the VoI. As it is likely that increasing loads due to climate change will result in more frequent future reinforcements, the influence of scenarios of different rates of increase in future loads is also investigated. It was found that, in all considered possible scenarios, monitoring yields a positive Value of Information, hence it is an economically efficient measure for flood defence asset management both now and in the future.

Flood defences are in practice often multi‐used, multi‐managed and multi‐financed. Flood defence asset management contains technical, organizational and spatial complex issues involving multiple organizations. In the literature, little attention has been given to the conditions for successful cooperation between organizations in flood defence asset management. This paper elaborates on this aspect of mature asset management from a practical point of view. Although the importance of a fit‐for‐purpose cooperation seems trivial, practice shows that the shape of cooperation is often the coincidental result of implicit or ad‐hoc choices and is not deliberately designed. This paper reports on empirical data gathered in a case consisting of five different situations related to collaboration in flood defence management. The management context consists of three main tasks: performance assessment, reinforcement and daily management, and three decision levels: strategic, tactical and operational, resulting in nine different management environments and related interfaces. For effectively achieving desired outcomes, the shape of cooperation has to be explicitly chosen dependent on the complexity of content and organizational context, and relevant external circumstances: situational cooperation.

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.

North Sea Region countries depend heavily on flood protection infrastructure, such as dikes, dams, sluices and flood gates. Knowledge on where, when and how much to invest to ensure functioning is of crucial importance for asset owners and operators. This requires asset management approaches that are adaptable, respond to feedback and function within various contexts. The FAIR (Flood defense infrastructure Asset management & Investment in Renovation, adaptation, optimisation and maintenance) project has developed a unique framework to ensure that asset management processes are adaptive, comprehensive and make effective connections across strategic, tactical and operational contexts. The framework has for the first time informed an assessment of maturity of five flood protection asset management organisations in the North Sea Region, using a seven-factor maturity assessment model. This paper describes the self-assessment process and the self-reported maturity changes during the project. Maturity assessments were undertaken on two occasions, at the start of the project, and again toward the end. This has revealed how the baseline level of maturity for each organisation developed over the course of the three-year project. The observed maturity changes indicate that adopting the FAIR framework has added value in improving current approaches to asset management.