Ciardulli, Paolo2026-01-302026-01-302026-01-302026-01-17https://hdl.handle.net/10012/22916Flood risk remains a persistent societal challenge, as no existing measures can offer complete protection against its impacts. Despite advancements in forecasting technologies, infrastructure and policy, flood events continue to result in substantial economic, social and environmental consequences. The complexity of managing flood risk stems from the interaction of dynamic and interrelated factors such as land-use change, risk constructs, governance structures, stakeholder priorities and coordination mechanisms. Integrated Flood Risk Management (IFRM) offers a comprehensive approach, recognizing the need for coordination across governmental levels, sectors and stakeholders while adapting to changing conditions. Within these interconnected socio-ecological systems, continuous learning and adaptation are essential. Social learning, particularly Multi-Loop Social Learning (MLSL), is a key supportive element of IFRM, yet it remains underexplored in this context. This dissertation investigates the presence of theoretically grounded MLSL capacities and enabling conditions in the practices and collaborative processes of Ontario’s Conservation Authorities (CAs). Particular attention is given to their interactions with the broader Ontario flood management network. These MLSL factors are theorized to play a critical role in supporting the development and application of an IFRM strategy. The IFRM strategy used in this research is modeled after a multi-phased, bio-regionally based, iterative, real-world and documented example: the European Union’s Floods Directive. The study examines how MLSL capacities align with the demands of such an IFRM approach in the Ontario context. Therefore, it situates Ontario within a broader Canadian conversation about the intersection of river basin-based water resources management and MLSL. Ontario’s CAs, which are river basin–based organizations with legal mandates in flood risk reduction, served as embed units of analysis within the wider case study (i.e., the CA flood management network) for this research. A two-round Delphi survey was conducted with 20 flood risk management (FRM) experts. Survey questions were designed to reflect MLSL factors derived from a previously developed research framework which focused on said factors in the context of Québec’s watershed management organizations. The modified Delphi approach also made it possible to capture both consensus and divergence between academic and practitioner perspectives. Findings indicate that several enabling MLSL capacities are evident in Ontario’s IFRM setting. These include (1) collaborative partnerships and networks, (2) an intentional approach to learning regarding collaborative processes, (3) sustained participation with governmental stakeholders, (4) cross-sectoral collaboration, (5) internal technical expertise, and (6) learning related to project goals. Respondents attributed these capacities to the CAs’ pivotal roles in flood management networks, long-standing engagement with municipalities and the province, their ecosystem-based approach, and their ability to convene diverse stakeholders across watersheds. CAs were also recognized for their multidisciplinary teams, adaptive management practices, and facilitation skills. Conversely, the study identified several areas where MLSL capacities are lacking. These include (1) shared data access among governmental actors, (2) collaborative decision-making across governmental levels, (3) an enabling democratic environment, (4) in-depth project reflection using formalized assessments, and (5) access to external expertise. Respondents attributed these gaps to uncertainty about data access, staff and funding constraints, inconsistent capacity among CAs, governance limitations, and unclear roles of external experts. These gaps highlight both institutional and policy limitations that impact the potential to fully transition toward IFRM in Ontario. This research isolates and analyzes specific MLSL themes, thus, making it possible to assess specific conditions that enable capacity for MLSL. Two key dimensions emerged: (1) the extent to which MLSL capacities are present and (2) how they manifest across IFRM phases. Together, these insights reveal the degree to which MLSL supports IFRM strategy development and implementation. A cross-comparison with a seminal study found convergence on 9 of 11 MLSL themes. This degree of alignment suggests that MLSL capacity challenges are broadly consistent across Canadian river basin-based water resources management contexts; particularly between Ontario and Québec. This study contributes to scholarly discourse by advancing understanding of MLSL in IFRM settings and offering practical insights for flood management organizations seeking to transition toward more integrated and adaptive approaches. The broader problem this research addressed is the extent to which watershed management agencies, or similar institutions, can effectively transition from one management model to another, particularly when such a transition necessitates the development of specialized MLSL capacities required for implementing the new strategy or model. In parallel, the research highlights policy needs by showing where Ontario’s flood strategy can be reinforced: shared data systems, inclusive decision-making, reflexive evaluation, expanded expertise and sustained multi-sectoral collaboration.enintegrated flood risk managementmulti-loop social learningflood risk managementwatershed-based managementConservation Authorities (Ontario)Delphi methodFloods DirectiveDoctoral Thesis