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Urban adaptation to climate change is likely to emerge from the responses of residents, authorities, and infrastructure providers to the impact of flooding, water scarcity, and other climate-related hazards. These responses are, in part, modulated by political relationships under cultural norms that dominate the institutional and collective decisions of public and private actors. The legacy of these decisions, which are often associated with investment in hard and soft infrastructure, has lasting consequences that influence current and future vulnerabilities. Making those decisions visible, and tractable is, therefore, an urgent research and political challenge in vulnerability assessments. In this work, we present a modeling framework to explore scenarios of institutional decision-making and socio-political processes and the resultant effects on spatial patterns of vulnerability. The approach entails using multi-criteria decision analysis, agent-based models, and geographic information simulation. The approach allows for the exploration of uncertainties, spatial patterns, thresholds, and the sensitivities of vulnerability outcomes to different policy scenarios. Here, we present the operationalization of the framework through an intentionally simplified model example of the governance of water in Mexico City. We discuss results from this example as part of a larger effort to empirically implement the framework to explore sociohydrological risk patterns and trade-offs of vulnerability in real urban landscapes. • Urban politics is rarely considered in vulnerability analyses. • We present an approach to integrate socio-politics into environmental risk modeling. • A stylized example demonstrates the influence of socio-political forces on vulnerability. • Trade-offs, sensitivities, and spatial patterns outcomes from political forces are analyzed. [ABSTRACT FROM AUTHOR]

Abstract Residents of Mexico City experience major hydrological risks, including flooding events and insufficient potable water access for many households. A participatory modeling project, MEGADAPT, examines hydrological risk as co-constructed by both biophysical and social factors and aims to explore alternative scenarios of governance. Within the model, neighborhoods are represented as agents that take actions to reduce their sensitivity to exposure and risk. These risk management actions (to protect their households against flooding and scarcity) are based upon insights derived from focus group discussions within various neighborhoods. We developed a role-playing game based on the model's rules in order to validate the assumptions we made about residents' decision-making given that we had translated qualitative information from focus group sessions into a quantitative model algorithm. This enables us to qualitatively validate the perspective and experience of residents in an agent-based model mid-way through the modeling process. Within the context of described hydrological events and the causes of these events, residents took on the role of themselves in the game and were asked to make decisions about how to protect their households against scarcity and flooding. After the game, we facilitated a discussion with residents about whether or not the game was realistic and how it could be improved. The game helped to validate our assumptions, validate the model with community members, and reinforced our connection with the community. We then discuss the potential further development of the game as a learning and communication tool. Highlights • Role-play games can be used to re-engage stakeholders in participatory modeling projects. • Agent-Based Model assumptions were qualitatively validated using a role-play game. • Role-play games should be further explored as tools to promote stakeholder learning. [ABSTRACT FROM AUTHOR]

Formal models are commonly used in natural resource management (NRM) to study human-environment interactions and inform policy making. In the majority of applications, human behaviour is represented by the rational actor model despite growing empirical evidence of its shortcomings in NRM contexts. While the importance of accounting for the complexity of human behaviour is increasingly recognized, its integration into formal models remains a major challenge. The challenges are multiple: i) there exist many theories scattered across the social sciences, ii) most theories cover only a certain aspect of decision-making, iii) they vary in their degree of formalization, iv) causal mechanisms are often not specified. We provide a framework- MoHuB (Modelling Human Behavior) - to facilitate a broader inclusion of theories on human decision-making in formal NRM models. It serves as a tool and common language to describe, compare and communicate alternative theories. In doing so, we not only enhance understanding of commonalities and differences between theories, but take a first step towards tackling the challenges mentioned above. This approach may enable modellers to find and formalize relevant theories, and be more explicit and inclusive about theories of human decision making in the analysis of social-ecological systems. [ABSTRACT FROM AUTHOR]