Transportation plays a pivotal role in society in the accessibility of socio-economic functions, such as education and health services. At the same time these transport networks are put under pressure due to increasing demands and the often-increasing occurrence of climate-induced events. To increase resilience of the transportation network to disruptions, network criticality has been used to prioritise segments of the network for interventions. Here we present how equity principles can be applied in the context of decision making for resilient infrastructure. This is done for both a data-rich (The Hague, The Netherlands) and data-poor (Pontianak, Indonesia) environment. The results show that depending on the underlying equity principle different intervention locations are prioritized and changes the impact for different socio-economic groups and the general population.

Flooding is among the most prevalent natural hazards, with particularly disastrous impacts in low-income countries. This study presents global estimates of the number of people exposed to high flood risks in interaction with poverty. It finds that 1.81 billion people (23% of world population) are directly exposed to 1-in-100-year floods. Of these, 1.24 billion are located in South and East Asia, where China (395 million) and India (390 million) account for over one-third of global exposure. Low- and middle-income countries are home to 89% of the world’s flood-exposed people. Of the 170 million facing high flood risk and extreme poverty (living on under $1.90 per day), 44% are in Sub-Saharan Africa. Over 780 million of those living on under $5.50 per day face high flood risk. Using state-of-the-art poverty and flood data, our findings highlight the scale and priority regions for flood mitigation measures to support resilient development.

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.

Transport network criticality analyses aim at identifying important segments in a transport network. Such studies are often based on the utilitarian principle, where the criticality of a segment is assessed based on its contribution to the aggregate performance of the transport system. To allow for the use of alternative moral principles, I systematically operationalize concepts from the transport equity literature into an equity-based criticality analysis framework. There are two main ideas in this framework: calculation of equity-weighted transport demand based on distributive moral principles and adaptation of an equity-weighted user equilibrium assignment algorithm. Using the Bangladesh freight transport network as a case study, I show that different sets of transport segments emerge as being critical when different moral principles are used. The use of some pairs of moral principles, for example global equalization and proportionality, even produces a negative ranking correlation. This implies that links which are considered to be critical based on one principle are not at all critical based on the other one. Selection of a moral principle, either explicitly or implicitly, is an inevitable step in transport network criticality analysis. Hence, it is advised to use multiple moral principles or to make a deliberative selection of a moral principle, as considering alternative moral principles in a criticality analysis could expose previously overlooked transport segments.

As development and adaptation are closely intertwined, assessing the benefits of adaptation by focusing only on how it reduces climate impacts could lead to misleading policy advice. In some cases, trying to minimize climate impacts could lead to inferior outcomes. It is preferable to explore how policies influence the absolute level of metrics of interest in scenarios with climate change rather than to focus on how they influence incremental climate impacts.

As development and adaptation are closely intertwined, assessing the benefits of adaptation by focusing only on how it reduces climate impacts could lead to misleading policy advice. In some cases, trying to minimize climate impacts could lead to inferior outcomes. It is preferable to explore how policies influence the absolute level of metrics of interest in scenarios with climate change rather than to focus on how they influence incremental climate impacts.

Natural gas vehicles (NGV) face significant adoption barriers in Jakarta. Therefore, a successful transition requires measures from the government. Owing to the high cost of transition policies, the efficacy of these policies must be analyzed to identify the most effective policy. The implementation of transition policies, however, could dynamically influence people's perception and behavior, which then changes the landscape of adoption barriers. Furthermore, even a seemingly successful policy may fail when a certain pathway of uncertainties emerges in the future. To address these concerns, we integrated agent-based modeling, exploratory modeling, and diffusion of innovation theory into the exploratory model-based diffusion analysis approach. This approach evaluates the policy's performance, explores changes in the relative importance of different adoption barriers, and identifies policy vulnerabilities, i.e., scenarios leading to policy failures. We tested this approach on four NGV transition policies targeting three adoption barriers. We found that the importance of adoption barriers and the critical uncertainties upon the implemented policies. The social–behavioral barrier predominates under current conditions, whereas the economic factor becomes more relevant when all policies are executed. Understanding the changes in adoption barriers and policy vulnerabilities will help decision-makers to prepare additional measures that ensure a successful transition.

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.