Global mean sea-level rise (SLR) has accelerated since 1900 from less than 2 mm yr-1 during most of the century to more than 3 mm yr-1 since 1993. Decision-makers in coastal countries, however, require information on SLR at the regional scale, where detection of an acceleration in SLR is difficult, because the long-term sea-level signal is obscured by large inter-annual variations with multi-year trends that are easily one order of magnitude larger than global mean values. Here, we developed a time series approach to determine whether regional SLR is accelerating based on tide gauge data. We applied the approach to eight 100-year records in the southern North Sea and detected, for the first time, a common breakpoint in the early 1990s. The mean SLR rate at the eight stations increases from 1.7 ± 0.3 mm yr-1 before the breakpoint to 2.7 ± 0.4 mm yr-1 after the breakpoint (95% confidence interval), which is unprecedented in the regional instrumental record. These findings are robust provided that the record starts before 1970 and ends after 2015. Our method may be applied to any coastal region with tidal records spanning at least 40 years, which means that vulnerable coastal communities still have time to accumulate the required time series as a basis for adaptation decisions in the second half of this century.

To deal with large uncertainties about future climate and socio-economic developments, planners in deltas are adopting an integrative and adaptive planning approach referred to as Adaptive Delta Management (ADM). Bangladesh has used the ADM approach for the development of its adaptive plan; Bangladesh Delta Plan 2100 (BDP 2100). The success of policy strategies in an adaptive delta plan critically depends on a specific adaptation of livelihoods of local communities (Community Livelihood Adaptation; CLA), especially in an agriculture-oriented society like Bangladesh. For example, while triple rice cropping might be evaluated as a robust strategy in all futures considered, its success eventually depends on whether farmers’ will actually make that choice, which is deeply uncertain. In this paper, we use literature review, insights from interviews and field observations to examine how the uncertainty in CLA impacts (adaptive) delta management. We study two historical cases of livelihood adaptation of farmer communities confronted with salinization and waterlogging in the polders of southwest Bangladesh since the 1960s. We conclude that historically the uncertainty about CLA in polders has been ignored in the development of policy plans, leading to the failure of anticipated policy outcomes. We recommend planners in Bangladesh and other deltas worldwide to take account of CLA as uncertainty when developing long-term adaptive plans.

Coastal cities combine intensive socioeconomic activities and investments with high exposure to flood hazards. Developing effective strategies to manage flood risk in coastal cities is often a costly and complicated process. In designing strategies, engineers rely on computationally demanding flood simulation models, but they can only compare a limited number of strategies due to computational constraints. This limits the efficacy of standard flood simulation models in the crucial conceptual phase of flood risk management. This paper presents the Flood Risk Reduction Evaluation and Screening (FLORES) model, which provides useful risk information in this early conceptual phase. FLORES rapidly performs numerous simulations and compares the impact of many storms, strategies, and future scenarios. This article presents FLORES and demonstrates its merits in a case study for Beira, Mozambique. Our results demonstrate that expansion of the drainage capacity and strengthening of its coastal protection in the southwest are crucial components of any effective flood risk management strategy for Beira.

In designing and retrofitting infrastructure systems, engineers are increasingly confronted by uncertainties about the future operating conditions of these systems, stemming from climate change or rapid socio-economic development. Particularly for long-lived capital-intensive infrastructure components like pumping stations, current engineering practices need to be complemented by structured approaches for designing infrastructures whose performance is robust to a wide range of possible future operating conditions. This paper presents multi-objective robust simulation as a viable approach. We investigate its applicability in a case study of the re-design of a polder pumping-station in The Netherlands. The research demonstrates the added value of multi-objective robust simulation in establishing robust design alternatives. The approach generates additional decision relevant insights into the performance of the pumping-station under uncertain future conditions while supplying decision-makers with the information required to make informed trade-offs amongst key design choices.

The spatial manifestation of climate crisis rarely appeals to one’s imagination. Yet, when reviewing the range of sea level rise projections and their accelerated rate of change, it is clear that understanding when and why to navigate between mitigation, adaptation and transformation measures is essential for flourishing coastal communities globally.

The Netherlands is one of those and has been characterised by a long history of renowned flood risk and water management as well as spatial planning. Facing the potential extreme scenarios of sea level rise, the country now however struggles to include measures preparing for a shift from incremental to the required transformative strategies.

This research project identifies the criticalities by means of a risk matrix and stress maps as an initial act to introduce the Sea Level Impact Knowledge Collect and its transdisciplinary Research by Design approach to guide the discussion on transformative change and its implementation in living labs.

Adaptive policies have emerged as a valuable strategy for dealing with uncertainties by recognising the capacity of systems to adapt over time to new circumstances and surprises. The efficacy of adaptive policies hinges on detecting on-going change and ensuring that actions are indeed taken if and when necessary. This is operationalised by including a monitoring system composed of signposts and triggers in the design of the plan. A well-designed monitoring system is indispensable for the effective implementation of adaptive policies. Despite the importance of monitoring for adaptive policies, the present literature has not considered criteria enabling the a-priori evaluation of the efficacy of signposts. In this paper, we introduce criteria for the evaluation of individual signposts and the monitoring system as a whole. These criteria are relevance, observability, completeness, and parsimony. These criteria are intended to enhance the capacity to detect the need for adaptation in the presence of noisy and ambiguous observations of the real system. The criteria are identified from an analysis of the information chain, from system observations to policy success, focusing on how data becomes information. We illustrate how models, in particular, the combined use of stochastic and exploratory modelling can be used to assess individual signposts, and the whole monitoring system according to these criteria. This analysis provides significant insight into critical factors that may hinder learning from data. The proposed criteria are demonstrated using a hypothetical case, in which a monitoring system for a flood protection policy in the Niger River is designed and tested.

Climate change raises serious concerns for policymakers that want to ensure the success of long-term policies. To guarantee satisfactory decisions in the face of deep uncertainties, adaptive policy pathways might be used. Adaptive policy pathways are designed to take actions according to how the future will actually unfold. In adaptive pathways, a monitoring system collects the evidence required for activating the next adaptive action. This monitoring system is made of signposts and triggers. Signposts are indicators that track the performance of the pathway. When signposts reach pre-specified trigger values, the next action on the pathway is implemented. The effectiveness of the monitoring system is pivotal to the success of adaptive policy pathways, therefore the decision-makers would like to have sufficient confidence about the future capacity to adapt on time. "On time" means activating the next action on a pathway neither so early that it incurs unnecessary costs, nor so late that it incurs avoidable damages. In this paper, we show how mapping the relations between triggers and the probability of misclassification errors inform the level of confidence that a monitoring system for adaptive policy pathways can provide. Specifically, we present the "trigger-probability" mapping and the "trigger-consequences" mappings. The former mapping displays the interplay between trigger values for a given signpost and the level of confidence regarding whether change occurs and adaptation is needed. The latter mapping displays the interplay between trigger values for a given signpost and the consequences of misclassification errors for both adapting the policy or not. In a case study, we illustrate how these mappings can be used to test the effectiveness of a monitoring system, and how they can be integrated into the process of designing an adaptive policy.

Delta communities worldwide are facing a multitude of challenges in their life and livelihood. In many developing countries, improving the quality of life and livelihood is a key challenge. While development is a central goal of delta planning in such countries, the effectiveness of planning is challenged by uncertain changes in climate and socio-economy. Bangladesh (one of the countries) is moving towards the adaptive delta management approach to deal with such uncertainties. Historical examples illustrate that Community Livelihood Adaptation (CLA) can critically influence the effectiveness of a policy strategy. Therefore, there is a clear need to explore CLA under uncertainty. For that purpose, this paper develops and applies a conceptual model-based approach combining the mental model and scenarios techniques. Our approach starts by using a participatory process to elicit mental models a farmers’ community uses when considering adaptation decisions; we capture these in the form of a cognitive map, and this map can serve as a conceptual model for analyzing livelihood adaptation decision-making in a future-oriented scenario analysis. To illustrate the approach, a case study of cropping decision-making of farmers community at a polder location under the saline condition in the southwest of Bangladesh has been elaborated. Results show that the approach is useful in structuring the cognitive and qualitative nature of complex decision-making process, and helps in understanding the dynamic interactions of farmers’ adaptation decisions with other actors, their environmental attributes, and market traits. It can help policymakers anticipate the adaptation direction of policy strategies.

Despite all research efforts, climate change remains unpredictable in the long term. Climate change unpredictability  raises serious concerns for policymakers that prepare long-term policies. To guarantee that climate adaptation  policies perform satisfycingly despite the unavoidable uncertainty, adaptive policies might be used. Adaptive  policies are designed to be adapted over time in response to how the future is actually unfolding. Signposts are  used to track exogenous developments that critically affect the performance of a plan, and when pre-specified  triggers are reached the policy is adapted. This so-called monitoring system is used to gather evidence of change,  on the basis of which a policy is adapted. The ability of the monitoring system to effectively detect change is  pivotal to the success of the whole adaptive policy.  A decision-maker would like to have sufficient confidence about the future capacity to adapt the policy on  time. On time means adapting the policy not too early for that incurs unnecessary costs, nor too late which  incurs avoidable damages. The capacity to adapt the policy on time is to be tested before the adaptive policy is  implemented. Despite the substantial and growing attention by researchers for supporting the making of climate  adaptation decisions under uncertainty, the ex-ante evaluation of the degree to which the monitoring system  enables timely adaptation has been largely overlooked.  We present innovative graphical instruments to assess ex-ante the level of confidence that a monitoring system for  adaptive policies will offer at the moment at which adaptation is required: the Trigger-Power-Significance (T-PS)  plot and the Trigger-Consequences (T-C) plot. These instruments explore the interplay between the possible  trigger values of a given signpost and the level of confidence about the need for adapting the policy. We illustrate  how these instruments can be used to test the effectiveness of a monitoring system, and how they can be integrated  into the process of designing an adaptive policy.  The use of the proposed instruments and approach are demonstrated using a case study of designing an  adaptive policy for coastal flood protection in the Netherlands. This application shows the effectiveness of these  instruments in evaluating ex-ante the capacity of a monitoring system to provide the information required to adapt  on time with sufficient confidence, and redesign it if this is not the case.