An Empirical Social Vulnerability Map for Flood Risk Assessment at Global Scale (“GlobE‐SoVI”)
Abstract Fatalities caused by natural hazards are driven not only by population exposure, but also by their vulnerability to these events, determined by intersecting characteristics such as education, age and income. Empirical evidence of the drivers of social vulnerability, however, is limited due...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-03-01
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| Series: | Earth's Future |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2023EF003895 |
| _version_ | 1797220391337328640 |
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| author | Lena Reimann Elco Koks Hans de Moel Marijn J. Ton Jeroen C. J. H. Aerts |
| author_facet | Lena Reimann Elco Koks Hans de Moel Marijn J. Ton Jeroen C. J. H. Aerts |
| author_sort | Lena Reimann |
| collection | DOAJ |
| description | Abstract Fatalities caused by natural hazards are driven not only by population exposure, but also by their vulnerability to these events, determined by intersecting characteristics such as education, age and income. Empirical evidence of the drivers of social vulnerability, however, is limited due to a lack of relevant data, in particular on a global scale. Consequently, existing global‐scale risk assessments rarely account for social vulnerability. To address this gap, we estimate regression models that predict fatalities caused by past flooding events (n = 913) based on potential social vulnerability drivers. Analyzing 47 variables calculated from publicly available spatial data sets, we establish five statistically significant vulnerability variables: mean years of schooling; share of elderly; gender income gap; rural settlements; and walking time to nearest healthcare facility. We use the regression coefficients as weights to calculate the “Global‐Empirical Social Vulnerability Index (GlobE‐SoVI)” at a spatial resolution of ∼1 km. We find distinct spatial patterns of vulnerability within and across countries, with low GlobE‐SoVI scores (i.e., 1–2) in for example, Northern America, northern Europe, and Australia; and high scores (i.e., 9–10) in for example, northern Africa, the Middle East, and southern Asia. Globally, education has the highest relative contribution to vulnerability (roughly 58%), acting as a driver that reduces vulnerability; all other drivers increase vulnerability, with the gender income gap contributing ∼24% and the elderly another 11%. Due to its empirical foundation, the GlobE‐SoVI advances our understanding of social vulnerability drivers at global scale and can be used for global (flood) risk assessments. |
| first_indexed | 2024-04-24T12:48:48Z |
| format | Article |
| id | doaj.art-3c485f8987ce44f1ba26627eede3aa8d |
| institution | Directory Open Access Journal |
| issn | 2328-4277 |
| language | English |
| last_indexed | 2024-04-24T12:48:48Z |
| publishDate | 2024-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Earth's Future |
| spelling | doaj.art-3c485f8987ce44f1ba26627eede3aa8d2024-04-06T12:00:35ZengWileyEarth's Future2328-42772024-03-01123n/an/a10.1029/2023EF003895An Empirical Social Vulnerability Map for Flood Risk Assessment at Global Scale (“GlobE‐SoVI”)Lena Reimann0Elco Koks1Hans de Moel2Marijn J. Ton3Jeroen C. J. H. Aerts4Institute for Environmental Studies (IVM) Vrije Universiteit Amsterdam Amsterdam The NetherlandsInstitute for Environmental Studies (IVM) Vrije Universiteit Amsterdam Amsterdam The NetherlandsInstitute for Environmental Studies (IVM) Vrije Universiteit Amsterdam Amsterdam The NetherlandsInstitute for Environmental Studies (IVM) Vrije Universiteit Amsterdam Amsterdam The NetherlandsInstitute for Environmental Studies (IVM) Vrije Universiteit Amsterdam Amsterdam The NetherlandsAbstract Fatalities caused by natural hazards are driven not only by population exposure, but also by their vulnerability to these events, determined by intersecting characteristics such as education, age and income. Empirical evidence of the drivers of social vulnerability, however, is limited due to a lack of relevant data, in particular on a global scale. Consequently, existing global‐scale risk assessments rarely account for social vulnerability. To address this gap, we estimate regression models that predict fatalities caused by past flooding events (n = 913) based on potential social vulnerability drivers. Analyzing 47 variables calculated from publicly available spatial data sets, we establish five statistically significant vulnerability variables: mean years of schooling; share of elderly; gender income gap; rural settlements; and walking time to nearest healthcare facility. We use the regression coefficients as weights to calculate the “Global‐Empirical Social Vulnerability Index (GlobE‐SoVI)” at a spatial resolution of ∼1 km. We find distinct spatial patterns of vulnerability within and across countries, with low GlobE‐SoVI scores (i.e., 1–2) in for example, Northern America, northern Europe, and Australia; and high scores (i.e., 9–10) in for example, northern Africa, the Middle East, and southern Asia. Globally, education has the highest relative contribution to vulnerability (roughly 58%), acting as a driver that reduces vulnerability; all other drivers increase vulnerability, with the gender income gap contributing ∼24% and the elderly another 11%. Due to its empirical foundation, the GlobE‐SoVI advances our understanding of social vulnerability drivers at global scale and can be used for global (flood) risk assessments.https://doi.org/10.1029/2023EF003895global‐Empirical Social Vulnerability index (GlobE‐SoVI)social vulnerability mapempirical validationflood risk assessmentmultiple linear regression modelflood fatalities |
| spellingShingle | Lena Reimann Elco Koks Hans de Moel Marijn J. Ton Jeroen C. J. H. Aerts An Empirical Social Vulnerability Map for Flood Risk Assessment at Global Scale (“GlobE‐SoVI”) Earth's Future global‐Empirical Social Vulnerability index (GlobE‐SoVI) social vulnerability map empirical validation flood risk assessment multiple linear regression model flood fatalities |
| title | An Empirical Social Vulnerability Map for Flood Risk Assessment at Global Scale (“GlobE‐SoVI”) |
| title_full | An Empirical Social Vulnerability Map for Flood Risk Assessment at Global Scale (“GlobE‐SoVI”) |
| title_fullStr | An Empirical Social Vulnerability Map for Flood Risk Assessment at Global Scale (“GlobE‐SoVI”) |
| title_full_unstemmed | An Empirical Social Vulnerability Map for Flood Risk Assessment at Global Scale (“GlobE‐SoVI”) |
| title_short | An Empirical Social Vulnerability Map for Flood Risk Assessment at Global Scale (“GlobE‐SoVI”) |
| title_sort | empirical social vulnerability map for flood risk assessment at global scale globe sovi |
| topic | global‐Empirical Social Vulnerability index (GlobE‐SoVI) social vulnerability map empirical validation flood risk assessment multiple linear regression model flood fatalities |
| url | https://doi.org/10.1029/2023EF003895 |
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