Complexity is inherent to the policy processes and to more and more domains such as environment or social policy. Complexity produces unexpected and counterintuitive effects, in particular, the phenomenon of policy regimes falling short of expectations while made by refined policies. This paper addresses this phenomenon by investigating the process of policy integration and its nonlinearities in the long run. We consider that the increase in the number of policies unexpectedly impacts the policy coherence within a policy regime. We argue that, depending on the degree of policy interactions, this impact varies in direction and intensity over time, which explains nonlinearities in integration. The impact turns negative when the regime is made of numerous policies, which favors non-coordinated policy interactions. Finally, the negative impact prevents further integration as stated by the Institutional Complexity Trap hypothesis and explains the contemporary paradoxical phenomenon of ineffective policy regimes made of refined policies. Empirically, we draw on a relational analysis of policies in the Swiss flood risk policy regime from 1848 to 2017. We study the co-evolution of the number of policies and of their de facto interlinkages, i.e., the co-regulations of a common issue. Findings support that the Institutional Complexity Trap is a structural and long-term dynamic punctuated by periods of policy learning and policy selection. We identify three main phases in the evolution of the regime: the start (1848–1874), the development (1874–1991), and the Institutional Complexity Trap (since 1991).

The Social-Ecological Systems framework serves as a valuable framework to explore and understand social and ecological interactions, and pathways in water governance. However, it lacks a robust understanding of change. We argue an analytical and methodological approach to engaging global changes in SES is critical to strengthening the scope and relevance of the SES framework. Relying on SES and resilience thinking, we propose an institutional and cognitive model of change where institutions and natural resources systems co-evolve. Our model of change provides a dynamic understanding of SES that stands on three causal mechanisms: institutional complexity trap, rigidity trap, and learning processes. We illustrate how data cube technology could overcome current limitations and offer reliable avenues for testing hypotheses about the dynamics of Social-Ecological Systems and water security by offering to combine spatial and time data with no major technical requirements for users.