San Francisco Bay, the largest estuary on the Pacific Coast of North America, is heavily encroached by a metropolitan region with over 7 million inhabitants. Urban development and infrastructure, much of which built over landfill and at the cost of former baylands, were placed at very low elevations. Sea level rise (SLR) poses a formidable challenge to these highly exposed urban areas and already stressed natural systems.
“Green”, or ecosystem-based, adaptation is already on the way around the Bay. Large scale wetland restoration projects have already been concluded, and further action now often requires articulation with the reinforcement of flood defense structures, given the level of urban encroachment. While levee setback, or removal, would provide greater environmental benefit, the need to protect urban areas and infrastructure has led to the trial of ingenious solutions for promoting wetland resilience while upgrading the level of protection provided by levees.
We analyzed the region’s environmental governance and planning structure, through direct observation, interviews with stakeholders, and study of planning documents and projects. We present two examples where actual implementation of SLR adaptation has led, or may lead to, the need to revise standards and practices or require uneasy choices between conflicting public interests.
Among the region’s stakeholders, there is an increasing awareness of the risks related to SLR, but the institutional arrangements are complex, and communication between the different public agencies/departments is not always as streamlined as it could be. Some agencies and departments need to adapt their procedures in order to remove institutional barriers to adaptation, but path dependence is an obstacle. There is evidence that more frank and regular communication between public actors is needed. It also emphasizes the benefits of a coordination of efforts and strategies, something that was eroded in the transition from central-government-led policies to a new paradigm of local-based adaptive governance.