Climate change brings new challenges for traditional environmental risk management, particularly for major infrastructure projects, where the decisions made today can have long-term implications. A major challenge is that projections of future climate are deeply uncertain. If this uncertainty is not managed appropriately, long-lived infrastructure may need to be replaced or expensively retrofitted before the end of the design lifetime. The Thames Estuary 2100 Project (TE2100) was one of the first major infrastructure projects to explicitly recognise and address the issue of the deep uncertainty in climate projections throughout the planning process. In this paper, we discuss the innovations and techniques that were adopted in this case that enabled it to cope with this uncertainty. We classify the overall approach as 'dynamic robustness', which aims to build flexible strategies that can be changed over time as more is learnt or as conditions change. The project combined four key innovations: (1) the 'decision-centric' process; (2) the combination of numerical models and expert judgement to develop narrative sea level rise scenarios; (3) the adoption of an 'Adaptation Pathways' approach to identify the timing and sequencing of possible 'pathways' of adaptation measures over time under different scenarios; and (4) the development of a monitoring framework that triggers defined decision points. A secondary focus of this paper is an exploration of how climate information was used in TE2100. We suggest that the techniques employed in TE2100 imply different needs from climate science that may cause them to redefine their research priorities related to adaptation; namely a shift in emphasis away from probabilistic modelling, toward greater investment in observations and monitoring; improved understanding of historical climate variability; and improved understanding of physical Earth system processes and their representation in models to enhance 'best guess' models and to better bound future projections using narrative scenarios.

Worldwide, an increase in flood damage is observed. Governments are looking for effective ways to protect lives, buildings, and infrastructure. At the same time, a large investment gap seems to exist—a big difference between what should necessarily be done to curb the increase in damage and what is actually being done. Decision-makers involved in climate adaptation are facing fundamental (so-called deep) uncertainties. In the course of time, the scientific community has developed a wide range of different approaches for dealing with these uncertainties. One of these approaches, adaptation pathways, is gaining traction as a way of framing and informing climate adaptation. But research shows that “very little work has been done to evaluate the current use of adaptation pathways and its utility to practitioners and decision makers” (Lin et al. 2017, p. 387). With this paper, the authors, as action researchers and practitioners involved in two of the world’s largest real-life applications of this approach in flood risk management, aim to contribute to filling in that gap. Analysis of the experience in the United Kingdom and the Netherlands in long-term planning in flood risk management shows that the adaptation pathways approach is effective in keeping decision processes going forward, to the final approval of a long-term plan, and helps increase awareness about uncertainties. It contributes to political support for keeping long-term options open and motivates decision-makers to modify their plans to better accommodate future conditions. When it comes to implementing the plans, there are still some major challenges, yet to be addressed, amongst others: the timely detection of tipping points in situations with large natural variability, the inclusion of measures that prepare for a switch to transformational strategies, and the retention of commitment of regional and local authorities, non government organizations, and the private sector, to climate adaptation as national policies move from blueprint planning to adaptive plans. In delivering this feedback, the authors hope to motivate the scientific community to take on these challenges.

Deltas and coastal cities around the world face the need to adapt to uncertain future changes. We compared adaptation planning on flood risk management in four cases based on three main elements of adaptive planning: to prepare for a wide range of plausible future scenarios; to respond to change with robust and flexible actions; and to monitor critical changes to be able to reassess the plan accordingly. Differences can be observed in the implementation of these elements. Good practices could be distinguished: cases consider a wide range of future scenarios; short-term decisions are coupled with long-term options while envisioning these options and possibilities for switching between them through adaptation pathways; opportunities originating from other agendas to achieve multiple objective investments are seized; and the system's resilience is improved by a wide variety of measures. At the same time some barriers for using adaptive planning approaches were identified: the use of a wide range of scenarios is only accepted in an exploratory phase of planning. Structural flood protection measures taken in the past do constrain future choices. The potential for monitoring and reassessment of options is hampered by the fact that trends in some variables cannot be detected.

Journal of Flood Risk Management AbstractLong term planning for flood risk management in coastal and estuarine areas requires timely and reliable information on changes in land and sea levels. In this paper we describe how we have produced a detailed, high resolution map of current changes in land levels for the Thames region, and carried out a new assessment of the changes in sea level relative to the land along the Thames Estuary over the past few decades / past century. We conclude the paper by considering the potential benefits of extended monitoring for the long term planning of flood and coastal defences in that region.

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