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Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk

Impacts of sea level rise will last for centuries; therefore, flood risk modeling must transition from identifying risky locations to assessing how populations can best cope. We present the first spatially interactive (i.e., what happens at one location affects another) land change model (FUTURES 3....

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Autores principales: Sanchez, Georgina M., Petrasova, Anna, Skrip, Megan M., Collins, Elyssa L., Lawrimore, Margaret A., Vogler, John B., Terando, Adam, Vukomanovic, Jelena, Mitasova, Helena, Meentemeyer, Ross K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10620417/
https://www.ncbi.nlm.nih.gov/pubmed/37914805
http://dx.doi.org/10.1038/s41598-023-46195-9
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author Sanchez, Georgina M.
Petrasova, Anna
Skrip, Megan M.
Collins, Elyssa L.
Lawrimore, Margaret A.
Vogler, John B.
Terando, Adam
Vukomanovic, Jelena
Mitasova, Helena
Meentemeyer, Ross K.
author_facet Sanchez, Georgina M.
Petrasova, Anna
Skrip, Megan M.
Collins, Elyssa L.
Lawrimore, Margaret A.
Vogler, John B.
Terando, Adam
Vukomanovic, Jelena
Mitasova, Helena
Meentemeyer, Ross K.
author_sort Sanchez, Georgina M.
collection PubMed
description Impacts of sea level rise will last for centuries; therefore, flood risk modeling must transition from identifying risky locations to assessing how populations can best cope. We present the first spatially interactive (i.e., what happens at one location affects another) land change model (FUTURES 3.0) that can probabilistically predict urban growth while simulating human migration and other responses to flooding, essentially depicting the geography of impact and response. Accounting for human migration reduced total amounts of projected developed land exposed to flooding by 2050 by 5%–24%, depending on flood hazard zone (50%–0.2% annual probability). We simulated various “what-if” scenarios and found managed retreat to be the only intervention with predicted exposure below baseline conditions. In the business-as-usual scenario, existing and future development must be either protected or abandoned to cope with future flooding. Our open framework can be applied to different regions and advances local to regional-scale efforts to evaluate potential risks and tradeoffs.
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spelling pubmed-106204172023-11-03 Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk Sanchez, Georgina M. Petrasova, Anna Skrip, Megan M. Collins, Elyssa L. Lawrimore, Margaret A. Vogler, John B. Terando, Adam Vukomanovic, Jelena Mitasova, Helena Meentemeyer, Ross K. Sci Rep Article Impacts of sea level rise will last for centuries; therefore, flood risk modeling must transition from identifying risky locations to assessing how populations can best cope. We present the first spatially interactive (i.e., what happens at one location affects another) land change model (FUTURES 3.0) that can probabilistically predict urban growth while simulating human migration and other responses to flooding, essentially depicting the geography of impact and response. Accounting for human migration reduced total amounts of projected developed land exposed to flooding by 2050 by 5%–24%, depending on flood hazard zone (50%–0.2% annual probability). We simulated various “what-if” scenarios and found managed retreat to be the only intervention with predicted exposure below baseline conditions. In the business-as-usual scenario, existing and future development must be either protected or abandoned to cope with future flooding. Our open framework can be applied to different regions and advances local to regional-scale efforts to evaluate potential risks and tradeoffs. Nature Publishing Group UK 2023-11-01 /pmc/articles/PMC10620417/ /pubmed/37914805 http://dx.doi.org/10.1038/s41598-023-46195-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Sanchez, Georgina M.
Petrasova, Anna
Skrip, Megan M.
Collins, Elyssa L.
Lawrimore, Margaret A.
Vogler, John B.
Terando, Adam
Vukomanovic, Jelena
Mitasova, Helena
Meentemeyer, Ross K.
Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk
title Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk
title_full Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk
title_fullStr Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk
title_full_unstemmed Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk
title_short Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk
title_sort spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10620417/
https://www.ncbi.nlm.nih.gov/pubmed/37914805
http://dx.doi.org/10.1038/s41598-023-46195-9
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