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Tierolf L, Haer T, Athanasiou P, Luijendijk AP, Botzen WJW, Aerts JCJH. Coastal adaptation and migration dynamics under future shoreline changes. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 917:170239. [PMID: 38278243 DOI: 10.1016/j.scitotenv.2024.170239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 01/09/2024] [Accepted: 01/15/2024] [Indexed: 01/28/2024]
Abstract
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.
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Affiliation(s)
- Lars Tierolf
- Institute for Environmental Studies, VU University Amsterdam, Amsterdam, the Netherlands.
| | - Toon Haer
- Institute for Environmental Studies, VU University Amsterdam, Amsterdam, the Netherlands
| | | | - Arjen P Luijendijk
- Deltares, Delft, the Netherlands; Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
| | - W J Wouter Botzen
- Institute for Environmental Studies, VU University Amsterdam, Amsterdam, the Netherlands; Utrecht University School of Economics, Utrecht University, Utrecht, the Netherlands
| | - Jeroen C J H Aerts
- Institute for Environmental Studies, VU University Amsterdam, Amsterdam, the Netherlands; Deltares, Delft, the Netherlands
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Vestby J, Schutte S, Tollefsen AF, Buhaug H. Societal determinants of flood-induced displacement. Proc Natl Acad Sci U S A 2024; 121:e2206188120. [PMID: 38190537 PMCID: PMC10801835 DOI: 10.1073/pnas.2206188120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 12/07/2022] [Indexed: 01/10/2024] Open
Abstract
What explains human consequences of weather-related disaster? Here, we explore how core socioeconomic, political, and security conditions shape flood-induced displacement worldwide since 2000. In-sample regression analysis shows that extreme displacement levels are more likely in contexts marked by low national income levels, nondemocratic political systems, high local economic activity, and prevalence of armed conflict. The analysis also reveals large residual differences across continents, where flood-induced displacement in the Global South often is much more widespread than direct human exposure measures would suggest. However, these factors have limited influence on our ability to accurately predict flood displacement on new data, pointing to important, hard-to-operationalize heterogeneity in flood impacts across contexts and critical data limitations. Although results are consistent with an interpretation that the sustainable development agenda is beneficial for disaster risk reduction, better data on societal consequences of natural hazards are critically needed to support evidence-based decision-making.
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Affiliation(s)
- Jonas Vestby
- Peace Research Institute OsloNO-0134Oslo, Norway
| | | | | | - Halvard Buhaug
- Peace Research Institute OsloNO-0134Oslo, Norway
- Department of Sociology and Political Science, Norwegian University of Science and Technology,NO-7491Trondheim, Norway
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Best K, He Q, Reilly AC, Niemeier DA, Anderson M, Logan T. Demographics and risk of isolation due to sea level rise in the United States. Nat Commun 2023; 14:7904. [PMID: 38036553 PMCID: PMC10689761 DOI: 10.1038/s41467-023-43835-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 11/21/2023] [Indexed: 12/02/2023] Open
Abstract
Within coastal communities, sea level rise (SLR) will result in widespread intermittent flooding and long-term inundation. Inundation effects will be evident, but isolation that arises from the loss of accessibility to critical services due to inundation of transportation networks may be less obvious. We examine who is most at risk of isolation due to SLR, which can inform community adaptation plans and help ensure that existing social vulnerabilities are not exacerbated. Combining socio-demographic data with an isolation metric, we identify social and economic disparities in risk of isolation under different SLR scenarios (1-10 ft) for the coastal U.S. We show that Black and Hispanic populations face a disproportionate risk of isolation at intermediate levels of SLR (4 ft and greater). Further, census tracts with higher rates of renters and older adults consistently face higher risk of isolation. These insights point to significant inequity in the burdens associated with SLR.
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Affiliation(s)
- Kelsea Best
- Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH, USA.
- Knowlton School of Architecture, City and Regional Planning, The Ohio State University, Columbus, OH, USA.
| | - Qian He
- Department of Geography, Planning, and Sustainability, Rowan University, Glassboro, NJ, USA
- Department of Civil and Environmental Engineering, University of Maryland, College Park, MD, USA
| | - Allison C Reilly
- Department of Civil and Environmental Engineering, University of Maryland, College Park, MD, USA
| | - Deb A Niemeier
- Department of Civil and Environmental Engineering, University of Maryland, College Park, MD, USA
| | - Mitchell Anderson
- Department of Civil and Natural Resources Engineering, University of Canterbury, Christchurch, New Zealand
| | - Tom Logan
- Department of Civil and Natural Resources Engineering, University of Canterbury, Christchurch, New Zealand
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Reimann L, Jones B, Bieker N, Wolff C, Aerts JCJH, Vafeidis AT. Exploring spatial feedbacks between adaptation policies and internal migration patterns due to sea-level rise. Nat Commun 2023; 14:2630. [PMID: 37149629 PMCID: PMC10164174 DOI: 10.1038/s41467-023-38278-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 04/21/2023] [Indexed: 05/08/2023] Open
Abstract
Climate change-induced sea-level rise will lead to an increase in internal migration, whose intensity and spatial patterns will depend on the amount of sea-level rise; future socioeconomic development; and adaptation strategies pursued to reduce exposure and vulnerability to sea-level rise. To explore spatial feedbacks between these drivers, we combine sea-level rise projections, socioeconomic projections, and assumptions on adaptation policies in a spatially-explicit model ('CONCLUDE'). Using the Mediterranean region as a case study, we find up to 20 million sea-level rise-related internal migrants by 2100 if no adaptation policies are implemented, with approximately three times higher migration in southern and eastern Mediterranean countries compared to northern Mediterranean countries. We show that adaptation policies can reduce the number of internal migrants by a factor of 1.4 to 9, depending on the type of strategies pursued; the implementation of hard protection measures may even lead to migration towards protected coastlines. Overall, spatial migration patterns are robust across all scenarios, with out-migration from a narrow coastal strip and in-migration widely spread across urban settings. However, the type of migration (e.g. proactive/reactive, managed/autonomous) depends on future socioeconomic developments that drive adaptive capacity, calling for decision-making that goes well beyond coastal issues.
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Affiliation(s)
- Lena Reimann
- Coastal Risks and Sea-level Rise Research Group, Department of Geography, Kiel University, Ludewig-Meyn-Straße 8, 24118, Kiel, Germany.
- CUNY Institute for Demographic Research (CIDR), City University of New York, 135 E 22nd St, New York City, NY, 10010, USA.
- Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, De Boelelaan 1111, 1081 HV, Amsterdam, The Netherlands.
| | - Bryan Jones
- CUNY Institute for Demographic Research (CIDR), City University of New York, 135 E 22nd St, New York City, NY, 10010, USA
| | - Nora Bieker
- Coastal Risks and Sea-level Rise Research Group, Department of Geography, Kiel University, Ludewig-Meyn-Straße 8, 24118, Kiel, Germany
| | - Claudia Wolff
- Coastal Risks and Sea-level Rise Research Group, Department of Geography, Kiel University, Ludewig-Meyn-Straße 8, 24118, Kiel, Germany
| | - Jeroen C J H Aerts
- Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, De Boelelaan 1111, 1081 HV, Amsterdam, The Netherlands
| | - Athanasios T Vafeidis
- Coastal Risks and Sea-level Rise Research Group, Department of Geography, Kiel University, Ludewig-Meyn-Straße 8, 24118, Kiel, Germany
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A coupled agent-based model for France for simulating adaptation and migration decisions under future coastal flood risk. Sci Rep 2023; 13:4176. [PMID: 36914726 PMCID: PMC10011601 DOI: 10.1038/s41598-023-31351-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 03/10/2023] [Indexed: 03/16/2023] Open
Abstract
In this study, we couple an integrated flood damage and agent-based model (ABM) with a gravity model of internal migration and a flood risk module (DYNAMO-M) to project household adaptation and migration decisions under increasing coastal flood risk in France. We ground the agent decision rules in a framework of subjective expected utility theory. This method addresses agent's bounded rationality related to risk perception and risk aversion and simulates the impact of push, pull, and mooring factors on migration and adaptation decisions. The agents are parameterized using subnational statistics, and the model is calibrated using a household survey on adaptation uptake. Subsequently, the model simulates household adaptation and migration based on increasing coastal flood damage from 2015 until 2080. A medium population growth scenario is used to simulate future population development, and sea level rise (SLR) is assessed for different climate scenarios. The results indicate that SLR can drive migration exceeding 8000 and 10,000 coastal inhabitants for 2080 under the Representative Concentration Pathways 4.5 and 8.5, respectively. Although household adaptation to flood risk strongly impacts projected annual flood damage, its impact on migration decisions is small and falls within the 90% confidence interval of model runs. Projections of coastal migration under SLR are most sensitive to migration costs and coastal flood protection standards, highlighting the need for better characterization of both in modeling exercises. The modeling framework demonstrated in this study can be upscaled to the global scale and function as a platform for a more integrated assessment of SLR-induced migration.
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