Modeling migration patterns in the USA under sea level rise


Autoři: Caleb Robinson aff001;  Bistra Dilkina aff002;  Juan Moreno-Cruz aff003
Působiště autorů: School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America aff001;  Viterbi School of Engineering, University of Southern California, Los Angeles, California, United States of America aff002;  School of Environment, Enterprise and Development, University of Waterloo, Waterloo, Ontario, Canada aff003
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0227436

Souhrn

Sea level rise in the United States will lead to large scale migration in the future. We propose a framework to examine future climate migration patterns using models of human migration. Our framework requires that we distinguish between historical versus climate driven migration and recognizes how the impacts of climate change can extend beyond the affected area. We apply our framework to simulate how migration, driven by sea level rise, differs from baseline migration patterns. Specifically, we couple a sea level rise model with a data-driven model of human migration and future population projections, creating a generalized joint model of climate driven migration that can be used to simulate population distributions under potential future sea level rise scenarios. The results of our case study suggest that the effects of sea level rise are pervasive, expanding beyond coastal areas via increased migration, and disproportionately affecting some areas of the United States.

Klíčová slova:

Artificial neural networks – Climate change – Climate modeling – Flooding – Human mobility – Sea level rise – Solar radiation – Urban areas


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Článek vyšel v časopise

PLOS One


2020 Číslo 1