While adapting to future sea-level rise (SLR) and its hazards and impacts is a multidisciplinary challenge, the interaction of scientists across different research fields, and with practitioners, is limited. To stimulate collaboration and develop a common research agenda, a workshop held in June 2024 gathered 22 scientists and policymakers working in the Netherlands. Participants discussed the interacting uncertainties across three different research fields: sea-level projections, hazards and impacts, and adaptation. Here, we present our view on the most important uncertainties within each field and the feasibility of managing and reducing those uncertainties. We find that enhanced collaboration is urgently needed to prioritize uncertainty reductions, manage expectations and increase the relevance of science to adaptation planning. Furthermore, we argue that in the coming decades, significant uncertainties will remain or newly arise in each research field and that rapidly accelerating SLR will remain a possibility. Therefore, we recommend investigating the extent to which early warning systems can help policymakers as a tool to make timely decisions under remaining uncertainties, in both the Netherlands and other coastal areas. Crucially, this will require viewing SLR, its hazards and impacts, and adaptation as a whole.

In this study, we present a novel modeling framework that provides a stylized representation of coastal adaptation and migration dynamics under sea level rise (SLR). We develop an agent-based model that simulates household and government agents adapting to shoreline change and increasing coastal flood risk. This model is coupled to a gravity-based model of migration to simulate coastward migration. Household characteristics are derived from local census data from 2015, and household decisions are calibrated based on empirical survey data on household adaptation in France. We integrate projections of shoreline retreat and flood inundation levels under two Representative Concentration Pathways (RCPs) and account for socioeconomic development under two Shared Socioeconomic Pathways (SSPs). The model is then applied to simulate coastal adaptation and migration between 2015 and 2080. Our results indicate that without coastal adaptation, SLR could drive the cumulative net outmigration of 13,100 up to as many as 21,700 coastal inhabitants between 2015 and 2080 under SSP2–RCP4.5 and SSP5–RCP8.5, respectively. This amounts to between 3.0 %–3.7 % of the coastal population residing in the 1/100-year flood zone in 2080 under a scenario of SLR. We find that SLR-induced migration is largely dependent on the adaptation strategies pursued by households and governments. Household implementation of floodproofing measures combined with beach renourishment reduces the projected SLR-induced migration by 31 %–36 % when compared to a migration under a scenario of no adaptation. A sensitivity analysis indicates that the effect of beach renourishment on SLR-induced migration largely depends on the level of coastal flood protection offered by sandy beaches. By explicitly modeling household behavior combined with governmental protection strategies under increasing coastal risks, the framework presented in this study allows for a comparison of climate change impacts on coastal communities under different adaptation strategies.