<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper constructs an assessment framework through theoretical research and literature study, determines the assessment indicators using the systematic review method, and forms a final assessment system of social resilience after flooding based on the correlation test. On this basis, the index weights were determined using the comprehensive assignment method, and the social resilience index was calculated using multi-criteria optimization and compromise solutions methods. The spatiotemporal evolution trend and spatial correlation characteristics of post-flood social resilience were explored by combining mathematical statistical methods, geographic information technology, and spatial measurement models. The temporal evolution characteristics of different dimensions of social resilience during the period 2012–2021 show that the social resilience index declined steeply in 2012, reached a maximum value of 0.316 in 2018, then gradually decreased to 0.305 in 2020, and recovered to 0.312 in 2021, with an overall increase of 5.05%. Assessing the social resilience of 17 cities under the jurisdiction of Henan Province, overall, the ability of the social system to cope with heavy rainfall and flooding disasters in 10 cities showed an increasing trend, and 7 towns showed a decreasing trend.The social resilience of Zhengzhou City under heavy rainfall and flooding disasters in 2017–2021 showed a trend of decreasing and increasing, with a composite index fit of 0.885, 0.893, 0.806, 0.893, 0.806, 0.824, 0.861.This paper constructs a social resilience assessment system after flooding to provide some reference for central cities to cope with extreme weather.</p>
</abstract>

This paper constructs an assessment framework through theoretical research and literature study, determines the assessment indicators using the systematic review method, and forms a final assessment system of social resilience after flooding based on the correlation test. On this basis, the index weights were determined using the comprehensive assignment method, and the social resilience index was calculated using multi-criteria optimization and compromise solutions methods. The spatiotemporal evolution trend and spatial correlation characteristics of post-flood social resilience were explored by combining mathematical statistical methods, geographic information technology, and spatial measurement models. The temporal evolution characteristics of different dimensions of social resilience during the period 2012–2021 show that the social resilience index declined steeply in 2012, reached a maximum value of 0.316 in 2018, then gradually decreased to 0.305 in 2020, and recovered to 0.312 in 2021, with an overall increase of 5.05%. Assessing the social resilience of 17 cities under the jurisdiction of Henan Province, overall, the ability of the social system to cope with heavy rainfall and flooding disasters in 10 cities showed an increasing trend, and 7 towns showed a decreasing trend.The social resilience of Zhengzhou City under heavy rainfall and flooding disasters in 2017–2021 showed a trend of decreasing and increasing, with a composite index fit of 0.885, 0.893, 0.806, 0.893, 0.806, 0.824, 0.861.This paper constructs a social resilience assessment system after flooding to provide some reference for central cities to cope with extreme weather.

Construction of Social Resilience Assessment System after Floods in the New Era

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Construction of Social Resilience Assessment System after Floods in the New Era"}

This paper constructs an assessment framework through theoretical research and literature study, determines the assessment indicators using the systematic...

Construction of Social Resilience Assessment System after Floods in the New Era

Publicado en línea: 03 may 2024

Páginas: -

Recibido: 07 abr 2024

Aceptado: 13 abr 2024

DOI: https://doi.org/10.2478/amns-2024-0896

Palabras clave
Multi-criteria optimization, Comprehensive assignment method, Compromise solution method, Geographic information technology, Spatial measurement, Social resilience assessment

© 2024 Junyi Yin, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Construction of Social Resilience Assessment System after Floods in the New Era

Publicado en línea: 03 may 2024

Páginas: -

Recibido: 07 abr 2024

Aceptado: 13 abr 2024

DOI: https://doi.org/10.2478/amns-2024-0896

Palabras claveMulti-criteria optimization, Comprehensive assignment method, Compromise solution method, Geographic information technology, Spatial measurement, Social resilience assessment

© 2024 Junyi Yin, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
Multi-criteria optimization, Comprehensive assignment method, Compromise solution method, Geographic information technology, Spatial measurement, Social resilience assessment