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To support equitable adaptation planning, quantitative assessments should consider the fairness of the distribution of outcomes to different people. What constitutes a fair distribution, however, is a normative question. In this study, we explore the use of different moral principles drawn from theories of distributive justice to evaluate fairness. We use adaptation planning in Vietnam Mekong Delta as a case study. We evaluate the preference ranking of six alternative policies for seven moral principles across an ensemble of scenarios. Under the baseline scenario, each principle yields distinctive preference rankings, though most principles identify the same policy as the most preferred one. Across the ensemble of scenarios, the commonly used utilitarian principle yields the most stable ranking, while rankings from other principles are more sensitive to uncertainty. The sufficientarian and the envy-free principles yield the most distinctive ranking of policies, with a median ranking correlation of only 0.07 across all scenarios. Finally, we identify scenarios under which using these two principles results in reversed policy preference rankings. Our study highlights the importance of considering multiple moral principles in evaluating the fairness of adaptation policies, as this would reduce the possibility of maladaptation.

Transport network criticality analysis aims at ranking transport infrastructure elements based on their contribution to the performance of the overall infrastructure network. Despite the wide variety of transport network criticality metrics, little guidance is available on selecting metrics that are fit for the specific purpose of a study. To address this gap, this study reviews, evaluates and compares seventeen criticality metrics. First, we conceptually evaluate these metrics in terms of the functionality of the transport system that the metrics try to represent (either maintaining connectivity, reducing travel cost, or improving accessibility), the underlying ethical principles (either utilitarianism or egalitarianism), and the spatial aggregation considered by the metrics (either network-wide or localised). Next, we empirically compare the metrics by calculating them for eight transport networks. We define the empirical similarity between two metrics as the degree to which they yield similar rankings of infrastructure elements. Pairs of metrics that have high empirical similarity highlight the same set of transport infrastructure elements as critical. We find that empirical similarity is partly dependent on the network’s topology. We also observe that metrics that are conceptually similar do not necessarily have high empirical similarity. Based on the insights from the conceptual and empirical comparison, we propose a five-step guideline for transport authorities and analysts to identify the set of criticality metrics to use which best aligns with the nature of their policy questions.

Models for supporting climate adaptation and mitigation planning, mostly in the form of Integrated Assessment Models, are poorly equipped for aiding questions related to fairness of adaptation and mitigation strategies, because they often disregard distributional outcomes. When evaluating policies using such models, the costs and benefits are typically aggregated across all actors in the system, and over the entire planning horizon. While a policy may be beneficial when considering the aggregate outcome, it can be harmful to some people, somewhere, at some point in time. The practice of aggregating over all actors and over time thus gives rise to problems of justice; it could also exacerbate existing injustices. While the literature discusses some of these injustices in ad-hoc and case specific manner, a systematic approach for considering distributive justice in model-based climate change planning is lacking. This study aims to fill this gap by proposing 11 requirements that an Integrated Assessment Model should meet in order to enable the assessment of distributive justice in climate mitigation and adaptation policies. We derive the requirements from various ethical imperatives stemming from the theory of distributive justice. More specifically, we consider both intra-generational (among people within one generation) and intergenerational (between generations) distributive justice. We investigate to what extent the 11 requirements are being met in recent model-based climate planning studies, and highlight several directions for future research to advance the accounting for distributive justice in model-based support for climate change planning. This article is categorized under: Climate, Nature, and Ethics g Climate Change and Global Justice.

The need for explicitly considering equity in climate change adaptation planning is increasingly being recognized. However, evaluations of adaptation often adopt an aggregated perspective, while disaggregation of results is important to learn about who benefits when and where. A typical example is adaptation of rice agriculture in the Vietnam Mekong Delta (VMD). Efforts focused on flood protection have mainly benefitted large‐scale farmers while harming small‐scale farmers. To investigate the distributional consequences of adaptation policies in the VMD, we assess both aggregate total output and equity indicators, as well as disaggregated impacts in terms of district‐level farming profitability. Doing so requires an adequate representation of the multisectoral dynamics between the human and biophysical systems which influence farming profitability. We develop a spatially explicit integrated assessment model that couples inundation, sedimentation, soil fertility and nutrient dynamics, and behavioral land‐use change and farming profitability calculation. We find that inter‐district inequality responds in a non‐linear way to climatic and socio‐economic changes and choices of adaptation policies. The patterns of who wins and who loses could change substantially when a different policy is implemented or if a slightly different uncertain future materializes. We also find that there is no simple ranking of alternative adaptation policies, so one should make trade‐offs based on agreed preferences. Accounting for equity implies exploring the distribution of outcomes over different groups over a range of uncertain futures. Only by accounting for multisectoral dynamics can planners anticipate the equity consequences of adaptation and prepare additional measures to aid the worse‐off actors.

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.

Water management involves optimizing the allocation of ‘enough’ water, a limited resource, to meet demands from competing actors and/or sectors such as agriculture, energy, ecosystems, and water supply. Although such demands are often associated only with current or existing generations, it’s understandable that future generations will have their own demands for these resources. There is, therefore, a moral dilemma and a question of justice regarding how much current generations must account for and be concerned with the generations to come with respect to managing resources in general and water resources in particular. Questions of intergenerational justice, i.e., the extent to which we should be concerned about future generations, are becoming increasingly common particularly due to a changing climate and growing population both of which require longer term planning and resources optimization. However, only limited suggestions are available in the literature for the practical implementation of intergenerational justice theories in the water resources literature to address such questions.Operationalization of justice principles in general, and intergenerational justice principles in particular is hard because different conceptualizations may exist concerning the same moral value. As a result, it’s often difficult to arrive at common understanding, schemes, and/or commitment levels for water resources management, particularly during negotiations in transboundary rivers involving multiple states, socio-political landscapes, and different possible ethical underpinnings.In this study, we present a novel scheme for operationalizing intergenerational justice which involves analysis and visualization of a range of commitment levels for future generations and trade-off analysis to existing generations. We implemented ranges of discount on current and potential utilization of water resources for various services. These discounts are then applied on water related services, which include water needs for hydropower generation, food production, and for various other human and ecological needs in water basins. By doing so, we present a mechanism for stakeholders in water resources management where they can assign different weights, depending on possibly different ethical underpinnings, to conserving water resources for future generation and evaluate the potential trade-off of such alternatives. We think that this is particularly important to tame negotiations in transboundary water resources management where multiple states, socio-political landscapes, and different ethical underpinnings often lead to escalated disputes. Here, we present our operationalization scheme for the Nile in light of existing disputes in this transboundary water basin. Although our scheme may not escape the challenge of, and hence did not attempt to, quantitative standardized values across the various stakeholders involved, it provides the opportunity for all stakeholders to put their own value for future generations in water resources management and weigh the implications of their considerations in terms of intergenerational trade-offs. We think this study adds value to the current literature on ethically-informed optimization in water resources management.

The importance of considering equity in climate change adaptation planning is increasingly being acknowledged. A preferred adaptation strategy is one that not only yields robust outcomes under multiple futures, but also has a fair distribution of benefits and harms across affected actors. In this study we propose two complementary approaches for assessing the equity of impacts of adaptation strategies. First, in the explorative approach, we explore what different multi-actor inequality patterns might emerge under different policy and uncertainty scenarios. Put differently, we identify who benefits and who loses under which kind of circumstances. Second, in the normative approach, we attempt to rank alternative strategies based on their performance across uncertain futures. Identifying which strategy is more preferable requires us to define what kind of distribution is considered to be ‘good’. We thus employ six alternative distributive moral principles that each has its own maxim in justifying the moral righteousness of a distribution: utilitarianism, prioritarianism, sufficientarianism, envy measures, weighted utilitarianism, and the Rawlsian difference principle.We apply both approaches to a case study on agricultural adaptation planning in An Giang and Dong Thap, two provinces in the upper Vietnam Mekong Delta. We develop an integrated assessment metamodel to assess the equity implications of six alternative adaptation strategies, including dikes (de)construction policies, fertilizer subsidy, and seeds upgrading. We evaluate the distributional impacts of the alternative strategies to 23 districts in the two provinces under a large number of strategic scenarios, i.e., combinations of policy scenarios and uncertain futures. From the explorative approach, we discover six distinctive inequality patterns and identify the strategic scenarios that give rise to each inequality pattern. We find a trade-off between districts located along the Mekong river and those located further away. In some strategic scenarios the former group of districts are substantially better-off than the latter, and vice versa.From the normative approach, we find a mixed result of preferred strategies depending on what moral principle is being adopted. The dikes deconstruction policy in Dong Thap, which performs best from a utilitarian point of view, ranks fifth from a prioritarian perspective. Upgrading seed is the most preferred strategy from the prioritarian view, but it performs the worst when looked at from a sufficientarian point of view. We further find that the results from each principle are strongly affected by uncertainties. For example, the fertilizer subsidy policy ranks last in approximately 70% of the uncertain futures according to the sufficientarian principle, but it becomes the most preferable in the other 20% of the uncertain futures. Our findings further emphasize the simultaneous consideration of both uncertainties and alternative distributive principles in adaptation planning. By using multiple moral principles, we expand the information base upon which adaptation decisions are made, and thus minimizing potential surprises and unintended consequences from our choice.

The importance of cooperation on transboundary waters is stated as a target in the United Nations 2030 Agenda for Sustainable Development Goals (SDG6: water). Cooperation on transboundary water management is critical, particularly because it concerns issues across multiple states, SDGs and targets regarding agriculture, energy, ecosystems, climate adaptation, health, and peace and security. The percentage of transboundary basin area within a country that has an “operational arrangement” for water cooperation is used as the main indicator of such cooperation in the SDGs for “equitable and reasonable use“ of water resources (SDG 6.5.2). However, no clear criteria and explanation are available for what exactly constitutes an “equitable and reasonable use” in any such “operational arrangements.” Furthermore, it is understandable that any such arrangements may be shaped by differences in historical, legal, and political contexts and hence may be inherently unjust. Here, we highlight the limitations of SDG indicators, particularly SDG 6.5.2, to monitor equity of resource sharing in transboundary river systems. Using Walzer’s theory of morality of the state and cosmopolitanism as a framework, we examine the Nile basin as a case study to demonstrate the shortcomings of current SDG criteria and indicators. Our article contributes ideas of “operationalizing” theoretical justice toward a more equitable water management in transboundary rivers.

Finding leverage points for sustainability transformation of industrial and infrastructure systems is challenging, given that transformation is emergent from the complex interactions among socio-technical system elements over time within a specific social, technical and geographical context. Participatory multi-modelling, in which modellers and stakeholders collaborate to develop multiple interacting models to support a shared understanding of systems, is a promising approach to support sustainability transformations. Theparticipatory processof modeling can serve as a leverage point by facilitating social learning amongst stakeholders, in which models can function as boundary objects that facilitate dialogue between stakeholders from different social worlds. We propose that participatory multi-modeling allows for the creation ofa boundary object ecology, which involves a set of interacting and co-evolving boundary objects emerging throughout the modeling process. To explore this, we analyse the participatory multi-modelling process in the Windmaster project in the Rotterdam Port industrial cluster to understand which design choices were key to the creation of boundary objects. Our analysis shows that two types of design choices were key: design choices that enabled translations between participants, and those between participants and their organisation. We conclude that conceptualising participatory multi-modelling as a process of an evolving boundary object ecology, creating and adaptingmultipleinteracting boundary objects provides a novel perspective that is useful for analysis and design of future participatory multi-modeling processes.

Coastal cities combine intensive socio-economic activity 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 the design of these strategies, engineers rely on computationally demanding flood simulation models and only compare a few 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 specifically aims to provide useful risk information early on in the planning process. FLORES performs numerous quick simulations and compares the impact of many storms, strategies, and future scenarios. This article presents the screening model 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.

Governing risks is not only a technical matter, but also a matter of ethical and societal considerations. In this article, we argue that in addition to scientific and technical uncertainties, we need to also address normative uncertainties of risk decisions. We define normative uncertainties as situations where there are different partially morally defensible -- but incompatible -- options or courses of action, or ones in which there is no fully morally defensible option. We conceptualize normative uncertainties, distinguishing between the four categories of evolutionary, theoretical, conceptual, and epistemic normative uncertainties. We will show different instances of normative uncertainties in climate adaptation strategies. We finally present two methods for identifying and dealing with normative uncertainties, namely, the Wide Reflective Equilibrium and adaptive planning. Situations of normative uncertainties have always been and will continue to be present in risk decisions and they have often been dealt with in an implicit manner. In this article, we make them explicit, which could lead to better morally informed and justified decisions about climate risks. This article is categorized under: Climate, Nature, and Ethics > Ethics and Climate Change., SCOPUS: re.j, info:eu-repo/semantics/published

Climate-related inequality can arise from the implementation of adaptation policies. As an example, the dike expansion policy for protecting rice farmers in the Vietnam Mekong Delta in the long run backfires to the small-scale farmers. The prevention of annual flooding reduces the supply of natural sediments, forcing farmers to apply more and more fertilizers to achieve the same yield. While large-scale farmers can afford this, small-scale farmers do not possess the required economics of scale and are thus harmed eventually. Together with climatic and socioeconomic uncertainties, the implementation of new policies can not only exacerbate existing inequalities, but also induce new inequalities. Hence, distributional impacts to affected stakeholders should be assessed in climate change adaptation planning.In this study, we propose a two-stage approach to assess the distributional impacts of policies in model-based support for adaptation planning. The first stage is intended to explore potential inequality patterns that may emerge due to combination of new policies and the realization of exogenous scenarios. This stage comprises four steps: (i) disaggregation of performance indicators in the model in order to observe distributional impacts, (ii) performance of large-scale simulation experimentation to account for deep uncertainties, (iii) clustering of simulation results to identify distinctive inequality patterns, and (iv) application of scenario discovery tools, in particular classification and regression trees, to identify combinations of policies and uncertainties that lead to a specific inequality pattern.In the second stage we attempt to asses which policies are morally preferable with respect to the inequality patterns they generate, rather than only descriptively explore the patterns which is the case in the previous stage. To perform a normative evaluation of the distributional impacts, we operationalize five alternative principles of justice: improvement of total welfare (utilitarianism), prioritization of worse-off actors (prioritarianism), reduction of welfare differences across actors (two derivations: absolute inequality and envy measure), and improvement of worst-off actor (Rawlsian difference). The different operationalization of each of these principles forms the so-called social welfare function with which the distributional impacts can be aggregated.To test this approach, we use an agricultural planning case study in the upper Vietnam Mekong Delta. Specifically, we assess the distributional impacts of alternative adaptation policies in the upper Vietnam Mekong Delta by using an integrated assessment model. We consider six alternative policies as well as uncertainties related to upstream discharge, sediment supply, and land-use change. Through the first stage, we identify six potential inequality patterns among the 23 districts in the study area, as well as the combinations of policies and uncertainties that result in these types of patterns. From applying the second stage we obtain complete rankings of alternative policies, based on their performance with respect to distributional impacts, under different realizations of scenarios. The explorative stage allows policy-makers to identify potential actions to compensate worse-off actors while the normative stage helps them to easily rank alternative policies based on a preferred moral principle.

Tide gauges are the main source of information about sea-level changes in the Industrial Age. When looking at global mean values, century-long reconstructions produce rates between 1-2 mm/yr, while estimates over the last three decades reveal a much faster rise of about 3 mm/yr, as also indicated by satellite altimetry observations. In spite of this evidence for a recent acceleration, its quantification remains a challenging and relevant task, because results are highly dependent on the length of the record and on the reconstruction technique, whereas decision makers require clear proof to legitimise action.While global mean results are very important to understand climate change, regional to local variations are more relevant for the purpose of planning mitigation and adaptation measures. However, mainly due to natural variability, looking at individual tide gauge stations hampers the accurate determination of linear and non-linear trends.We analyse tide gauge records along the Dutch coast by means of advanced statistical techniques, with the main objective of determining whether and under which conditions it is possible to detect departures from secular trends. We particularly focus on how to handle noise in the natural system, which for the Dutch coast is mainly represented by local atmospheric effects and by variability in ocean dynamics in the NE Atlantic.

Even though real options analysis (ROA) is often thought as the best tool available for evaluating flexible strategies, there are profound problems with the assumptions underpinning ROA rendering it unsuitable for use in supporting planning and decision-making on climate adaptation. In the face of dynamic and deep uncertainty about the future, flexible strategies which can be adapted in response to how the uncertainty is resolving are attractive. Traditional cost-benefit analysis cannot account for the value created through optionality. ROA sets out to amend this. There are however several profound problems with how ROA tries to do this. It is typically not clear what is the baseline plan, without options, against which value is to be estimated. Different baselines significantly change option value. Even if option value can unequivocally be established for a given scenario, ROA relies on expected values over a set of scenarios. First, this requires assigning weights, or probabilities, to scenarios. Given the long-time horizon involved in climate adaptation, these probabilities are meaningless. Second, the expected value over a set of scenarios need not obtain in any single scenario and is thus not a meaningful summary of option value. This article is categorized under:. Climate Economics > Iterative Risk-Management Policy Portfolios.

In recent years, a family of approaches has emerged for supporting decision-making on complex environmental problems characterized by deep uncertainties and competing priorities. Many-Objective Robust Decision Making (MORDM), Multi-scenario MORDM and. Many-Objective Robust Optimization (MORO) differ with respect to the degree to which robustness is considered during the search for promising candidate solutions. To assess the efficacy of these three methods, we compare them using three different policy formulations of the lake problem: inter-temporal, planned adaptive, and direct policy search. The more robustness is considered in the search phase, the more robust solutions are also after re-evaluation but also the lower the performance in individual reference scenarios. Adaptive policy formulations positively affect robustness, but do not reduce the price for robustness. Multi-scenario MORDM strikes a pragmatic balance between robustness considerations and optimality in individual scenarios, at reasonable computational costs.

Flood risk management decisions in many countries are based on decision‐support frameworks which rely on cost‐benefit analyses. Such frameworks are seldom informative about the geographical distribution of risk, raising questions on the fairness of the proposed policies. In the present work, we propose a new decision criterion that accounts for the distribution of risk reduction and apply it to support flood risk management decisions on a transboundary stretch of the Rhine River. Three types of interventions are considered: embankment heightening, making Room for the River, and changing the discharge distribution of the river branches. The analysis involves solving a flood risk management problem according to four alternative formulations, based on different ethical principles. Formulations based on cost optimization lead to very poor performances in some areas for the sake of reducing the overall aggregated costs. Formulations that also include equity criteria have different results depending on how these are defined. When risk reduction is distributed equally, very poor economic performance is achieved. When risk is distributed equally, results are in line with formulations based on cost optimization, while a fairer risk distribution is achieved. Risk reduction measures also differ, with the cost optimization approach strongly favoring the leverage of changing the discharge distribution and the alternative formulations spending more on embankment heightening and Room for the River, to rebalance inequalities in risk levels. The proposed method advances risk‐based decision‐making by allowing to consider risk distribution aspects and their impacts on the choice of risk reduction measures.

Scenario Discovery is a widely used method in model-based decision support for identifying common input space properties across ensembles of exploratory model runs. For model runs with behavior over time, these properties are identified by reducing each run to a single value, which obscures potentially decision-relevant dynamics. We address the problem of considering dynamics in Scenario Discovery by applying time series clustering to the ensemble of model runs, and then finding the common input properties for each cluster. This separates the input space into multiple scenarios, each corresponding to a distinct model dynamic. Policy interventions can be targeted at different scenarios by analyzing overlap of these subspaces. Our work expands Scenario Discovery by improving consideration of system behavior over time, which is highly relevant for the management of complex nonlinear systems such as ecosystems or technical infrastructure.

Multiple plausible future scenarios are being used increasingly in preference to a single deterministic or probabilistic prediction of the future in the long-term planning of water resources systems. These scenarios enable the determination of the robustness of a system—the consideration of performance across a range of plausible futures—and allow an assessment of which possible future system configurations result in a greater level of robustness. There are many approaches to selecting scenarios, and previous studies have observed that the choice of scenarios might affect the estimated robustness of the system. However, these observations have been anecdotal and qualitative. This paper develops a systematic, quantitative methodology for exploring the influence of scenario selection on the robustness and the ranking of decision alternatives. The methodology is illustrated on the Lake Problem. The quantitative results obtained confirm the qualitative observations of previous works, showing that the selection of scenarios is important, as it has a large influence on the robustness value calculated for each decision alternative. However, we show that it has a relatively small influence on how those decision alternatives are ranked. This implies that despite the difference in robustness values, similar decision outcomes will be reached in this case study, regardless of the basis on which the scenarios are obtained. It is also revealed that the impact of the scenarios on the robustness values is due to complex interactions with the system model and robustness metrics.

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.