Dynamic adaptive policy pathways: A method for crafting robust decisions for a deeply uncertain world

Coping with the Wickedness of Public Policy Problems: Approaches for Decision Making under Deep Uncertainty

The Dynamic Adaptive Policy Pathways (DAPP) approach has successfully been used to manage uncertainties in large infrastructure projects. However, the viability of the DAPP approach for spatial planning in smaller municipal settings is not clear. This paper examines opportunities and constraints of using adaptive pathways approaches to help small municipalities plan for future sea-level rise. The methodology was based on developing a simplified DAPP-approach, which was tested in a multiple experimental case study of spatial planning projects in three municipalities in Sweden. The results show that the approach promoted vulnerability-based thinking among the end-users and generated new ideas on how to manage the uncertain long-term impacts of future sea-level rise. However, the increased understanding of uncertainties was used to justify static, rather than adaptive, solutions. This somewhat surprising outcome can be explained by perceived legal constraints, lack of experience of adaptive pathways, and unwillingness to prescribe actions that could prove difficult to enforce in the future. More research is needed to further understand at what planning phases dynamic policy pathway approaches work best and how current barriers in legislation, practices, mind-set, organization, and resources can be overcome.

ABSTRACTFlood management in urban areas requires innovative and adaptive strategies to address the growing challenges posed by climate change, land use transformations, and socio‐economic developments. This study provides a comprehensive analysis of the complex interactions within an urban area using integrated modeling approaches, offering critical insights into potential future challenges. These approaches incorporate climate, land use, hydrological, hydraulic, and damage models, complemented by an adaptation pathways map and recommendations for the most effective strategies, conducted in a flood‐prone urban area. The analysis projects an increase by 2080 of 3.39°C in temperature, 46% in precipitation, and 29% in flood‐related damages. The study underscores the substantial impact of land use changes on flood damages, highlighting the need for integrating land use planning into flood mitigation strategies. A rigorous evaluation identified a combination of measures—including concrete dyke construction, dredging, afforestation, and forest conservation—as effective actions for mitigating flood risks in the region near the Caspian Sea. Forest conservation and afforestation reduce peak flood discharge by 12.2% and 23.1%, respectively, for a 100‐year return period. Economic evaluations were performed for all adaptation pathways to assess their feasibility and cost‐effectiveness. Using the Analytic Hierarchy Process (AHP), the study determined that the optimal strategy is the simultaneous implementation of concrete dyke construction, dredging, and forest conservation. Additionally, six adaptation pathways were defined through the Dynamic Adaptive Policy Pathways (DAPP) method to provide a structured roadmap for implementing and adjusting flood management measures over time. These pathways aim to reduce potential future flood damage to negligible levels. Overall, this research highlights the importance of adopting integrated and adaptive strategies to address the multi‐faceted challenges posed by environmental changes, ensuring effective flood management amidst growing deep uncertainties.

A variety of model-based approaches for supporting decision-making under deep uncertainty have been suggested, but they are rarely compared and contrasted. In this paper, we compare Robust Decision-Making with Dynamic Adaptive Policy Pathways. We apply both to a hypothetical case inspired by a river reach in the Rhine Delta of the Netherlands, and compare them with respect to the required tooling, the resulting decision relevant insights, and the resulting plans. The results indicate that the two approaches are complementary. Robust Decision-Making offers insights into conditions under which problems occur, and makes trade-offs transparent. The Dynamic Adaptive Policy Pathways approach emphasizes dynamic adaptation over time, and thus offers a natural way for handling the vulnerabilities identified through Robust Decision-Making. The application also makes clear that the analytical process of Robust Decision-Making is path-dependent and open ended: an analyst has to make many choices, for which Robust Decision-Making offers no direct guidance.

Adaptation requires planning strategies that consider the combined effect of climatic and non-climatic drivers, which are deeply uncertain. This uncertainty arises from many sources, cascades and accumulates in risk estimates. A prominent trend to incorporate this uncertainty in adaptation planning is through adaptive approaches such as the dynamic adaptive policy pathways (DAPP). We present a quantitative DAPP application for coastal erosion management to increase its utilisation in this field. We adopt an approach in which adaptation objectives and actions have continuous quantitative metrics that evolve over time as conditions change. The approach hinges on an adaptation information system that comprises hazard and impact modelling and systematic monitoring to assess changing risks and adaptation signals in the light of adaptation pathway choices. Using an elaborated case study, we force a shoreline evolution model with waves and storm surges generated by means of stochastic modelling from 2010 to 2100, considering uncertainty in extreme weather events, climate variability and mean sea-level rise. We produce a new type of adaptation pathways map showing a set of 90-year probabilistic trajectories that link changing objectives (e.g., no adaptation, limit risk increase, avoid risk increase) and nourishment placement over time. This DAPP approach could be applied to other domains of climate change adaptation bringing a new perspective in adaptive planning under deep uncertainty.

<p>Mediterranean agricultural systems often rely on irrigation, which can cause conflicts with domestic water demand due to limited water resources. Climate change could enhance these conflicts by bringing a drier climate, lowering water availability, while increasing irrigation demands, therefore creating a need for timely adaptation actions. However, the creation of adaptation plans requires the integration of local policy-makers and stakeholders, both to ensure that the plans are adjusted to local physical and social conditions, and to secure investment in the implementation phase. As many are not technical experts in water resources, this integration requires innovative methodologies to ensure that knowledge gained from advanced hydrological methods can be effectively transmitted for use.</p><p>These issues were addressed in the climate change adaptation plan for water resources in the Algarve region (southern Portugal), which was co-created between hydrologists and local stakeholders and policy-makers under project CLIMAAA, by using the Dynamic Adaptive Policy Pathways (DAAP) approach to synthetize the results from hydrological modelling of future scenarios.</p><p>Future scenarios were simulated from the present until 2100 using a hydrological model, with multiple realizations of climate scenarios RCP4.5and RCP8.5. The results show an increase in water stress conditions, mainly in the RCP8.5 scenario. Future scenarios and potential adaptation measures were discussed with the local policy-makers (regional and municipal water managers) and water users (water utilities, farmer associations). An agreed-upon set of measures was then simulated with the model to assess their effectiveness for adaptation. These results were used to design a DAAP specifically for the water sector in the Algarve.</p><p>Policy-makers were then presented with the DAPP, combined with a cost assessment, and selected the most suitable and politically reliable adaptation pathway until 2100. They did not consider socially desirable to decrease irrigation use, and showed a strong preference for measures such as promoting efficient water use and water retention landscapes, which are distributed and incremental, to measures such as wastewater recycling which require a large investment. However, they did consider desalination as a last resort despite the high investment, to be applied in case other measures fail to maintain water stress below an acceptable threshold. In the end, an adaptation plan for water resources was co-created between policy-makers and researchers which strongly reflected local desires and preferences, while ensuring that its effectiveness was assessed with the best available tools; this plan is now in in the review and implementation stage.</p>

Strategic adaptation pathway planning to manage sea-level rise and changing coastal flood risk

Integrated Assessment Models (IAMs) were initially developed to inform decision processes relating to climate change and then extended to other natural resource management decisions, including issues around integrated water resources management. Despite their intention to support long-term planning decisions, model uptake has generally been limited, partly due to their unfulfilled capability to manage deep uncertainty issues and consider multiple perspectives and trade-offs involved when solving problems of interest. In recent years, more emphasis has been put on the need for existing models to evolve to be used for exploratory modeling and analysis to capture and manage deep uncertainty. Building new models is a solution but may face challenges in terms of feasibility and the conservation of knowledge assets. Integration and augmentation of existing models is another solution, but little guidance exists on how to realize model augmentation that addresses deep uncertainty and how to use such models for exploratory modeling purposes. To provide guidance on how to augment existing models to support decisions under deep uncertainty we present an approach for identifying minimum information requirements (MIRs) that consists of three steps: (1) invoking a decision support framework [here, Dynamic Adaptive Policy Pathways (DAPP)] to synthesize information requirements, (2) characterizing misalignment with an existing integrated model, (3) designing adjustable solutions that align model output with immediate information needs. We employ the Basin Futures model to set up the approach and illustrate outcomes in terms of its effectiveness to augment models for exploratory purposes, as well as its potential for supporting the design of adaptative pathways. The results are illustrated in the context of the Brahmani River Basin (BRB) system and discussed in terms of generalization and transferability of the approach to identifying MIRs. Future work directions include the refinement and evaluation of the approach in a planning context and testing of the approach with other models.

Decision-making for flood adaptation in coastal cities is complicated by deep uncertainty about sea level rise, subsidence, and socioeconomic trends, which increases the possibility of under- or over-investment. Using the megacity of Shanghai as a case study, we apply the dynamic adaptive policy pathways (DAPP) framework to demonstrate robust and flexible decision-making under uncertainty. The framework integrates compound flood risk modeling of flood risk, economic evaluation, and dynamic adaptation pathways. Our results show that without adaptation, annual damages and annual casualties could increase by 86–167%, and 45–97 times, respectively, by the year 2100. ‘Hard adaptation strategies’ such as levees can reduce projected damages by 58–94%. In contrast, local scale ‘soft adaptation’ (flood-proofing buildings) is only effective and economically efficient in combination with hard adaptation (‘hybrid strategy’). The best economic performance is a hybrid strategy that starts implementing a large storage tank adding a mix of measures around 2050 (coastal wetlands, dry-floodproofing, and land elevation). Depending on how the future plays out, a hybrid strategy of a combination of a storm-surge barrier and coastal wetlands would yield high economic benefits after ~2070.

Integrating a hydrological model into regional water policies: Co-creation of climate change dynamic adaptive policy pathways for water resources in southern Portugal

Dynamic Adaptive Policy Pathways (DAPP) is a DMDU approach that explicitly includes decision making over time.The essence is proactive and dynamic planning in response to how the future actually unfolds.• DAPP explores alternative sequences of decisions (adaptation pathways) for multiple futures and illuminates the path dependency of alternative strategies.It opens the decision space and helps to overcome policy paralysis due to deep uncertainty.There are different routes that can achieve the objectives under changing conditions (like 'different roads leading to Rome').• Policy actions have an uncertain design life and might fail sooner or later to continue achieving objectives as the operating conditions change (i.e. they reach an adaptation tipping point (ATP)).Similarly, opportunity tipping points may occur.• Multiple pathways are typically visualized in a metro map or decision tree, with time or changing conditions on one of the axes.• DAPP supports the design of a dynamic adaptive strategy that includes initial actions, long-term options, and adaptation signals to identify when to implement the long-term options or revisit decisions.

Designing climate change dynamic adaptive policy pathways for agricultural water management using a socio-hydrological modeling approach

The majority of modern emergency management systems were created for event-driven hazards, which are abrupt shocks with distinct beginnings and ends. However, the climate issue is increasingly producing slow-onset, compound, and cascading threats that blur such lines. In order to enhance preparedness, response, recovery, and long-term resilience, this paper critically investigates how fundamental climate adaptation concepts—anticipation, flexibility, redundancy, equity, multi-level governance, and adaptive learning—can be effectively incorporated into emergency management frameworks. The study assesses integrative planning approaches, identifies institutional enablers and barriers, and suggests an operational roadmap for practitioners and policymakers based on an empirically grounded comparative framework and a structured theoretical synthesis (resilience and socio-ecological systems, adaptive governance, and decision-making under deep uncertainty). The argument is supported by international policy tools like the Sendai Framework and IPCC risk assessments, which emphasise the necessity of alignment between adaptation and disaster risk reduction, and it is demonstrated using tried-and-true techniques like Dynamic Adaptive Policy Pathways and Robust Decision Making. A typology of integrative processes (mainstreaming, parallel, and hybrid), an evaluation rubric for assessing the quality of adaptation–emergency integration, and useful suggestions for operationalising anticipatory and equitable action in emergency practice are all included in this work. The final section identifies research goals, such as institutional paths for transformative adaptation, culturally grounded techniques for equality, and metrics for attribution. Keywords: Climate Adaptation, Emergency Management, Resilience, Anticipatory Action, Dynamic Adaptive Policy Pathways, Sendai Framework.

Designing a monitoring system to detect signals to adapt to uncertain climate change

A transdisciplinary modeling framework for the participatory design of dynamic adaptive policy pathways