Modes of climate mobility under sea-level rise

被引:8
作者
Seeteram, Nadia A. [1 ,2 ,3 ]
Ash, Kevin [4 ]
Sanders, Brett F. [5 ,6 ]
Schubert, Jochen E. [5 ]
Mach, Katharine J. [7 ,8 ]
机构
[1] Florida Int Univ, Dept Earth & Environm, Miami, FL 33199 USA
[2] Florida Int Univ, Inst Environm, Miami, FL 33199 USA
[3] Columbia Univ, Columbia Climate Sch, New York, NY 10025 USA
[4] Univ Florida, Dept Geog, Gainesville, FL USA
[5] UC Irvine, Dept Civil & Environm Engn, Irvine, CA 92697 USA
[6] UC Irvine, Dept Urban Planning & Publ Policy, Irvine, CA 92697 USA
[7] Univ Miami, Rosenstiel Sch Marine Atmospher & Earth Sci, Dept Environm Sci & Policy, Miami, FL USA
[8] Univ Miami, Leonard & Jayne Abess Ctr Ecosyst Sci & Policy, Coral Gables, FL USA
基金
美国国家科学基金会;
关键词
climate mobility; climate migration; adaptation; sea-level rise; flood risk; social vulnerability; SOCIAL VULNERABILITY; COMMUNITY VULNERABILITY; NEW-ORLEANS; MIGRATION; HAZARDS; ADAPTATION; DISASTER; THRESHOLDS; NETWORKS; KATRINA;
D O I
10.1088/1748-9326/acfe22
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Exposure to sea-level rise (SLR) and flooding will make some areas uninhabitable, and the increased demand for housing in safer areas may cause displacement through economic pressures. Anticipating such direct and indirect impacts of SLR is important for equitable adaptation policies. Here we build upon recent advances in flood exposure modeling and social vulnerability assessment to demonstrate a framework for estimating the direct and indirect impacts of SLR on mobility. Using two spatially distributed indicators of vulnerability and exposure, four specific modes of climate mobility are characterized: (1) minimally exposed to SLR (Stable), (2) directly exposed to SLR with capacity to relocate (Migrating), (3) indirectly exposed to SLR through economic pressures (Displaced), and (4) directly exposed to SLR without capacity to relocate (Trapped). We explore these dynamics within Miami-Dade County, USA, a metropolitan region with substantial social inequality and SLR exposure. Social vulnerability is estimated by cluster analysis using 13 social indicators at the census tract scale. Exposure is estimated under increasing SLR using a 1.5 m resolution compound flood hazard model accounting for inundation from high tides and rising groundwater and flooding from extreme precipitation and storm surge. Social vulnerability and exposure are intersected at the scale of residential buildings where exposed population is estimated by dasymetric methods. Under 1 m SLR, 56% of residents in areas of low flood hazard may experience displacement, whereas 26% of the population risks being trapped (19%) in or migrating (7%) from areas of high flood hazard, and concerns of depopulation and fiscal stress increase within at least 9 municipalities where 50% or more of their total population is exposed to flooding. As SLR increases from 1 to 2 m, the dominant flood driver shifts from precipitation to inundation, with population exposed to inundation rising from 2.8% to 54.7%. Understanding shifting geographies of flood risks and the potential for different modes of climate mobility can enable adaptation planning across household-to-regional scales.
引用
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页数:16
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