Assessing Urban Flood Resilience in Langfang City: A Multi-Criteria Evaluation and Spatiotemporal Evolution Analysis Under PSR-VIKOR Framework

Flood disasters are among the most frequent, widespread and devastating natural disasters worldwide, and accelerating urbanization together with more frequent extreme rainfall events continues to increase urban flood risk. This study develops a flood resilience evaluation framework for Langfang City (Hebei Province, China), a core node of the Beijing–Tianjin–Hebei region, based on the Pressure–State–Response (PSR) model. Indicators were screened through literature word-frequency analysis and Pearson correlation analysis, yielding an index system of three dimensions and seventeen indicators adapted to local conditions. The FAHP–CRITIC combined weighting method and the VIKOR multi-criteria evaluation method were applied to calculate flood resilience indices for ten districts in 2014, 2019 and 2024, complemented by sensitivity analyses of the compromise coefficient λ and of the weighting scheme; spatial autocorrelation and LISA cluster analyses were conducted to examine spatiotemporal patterns. The results show that the yearly means of the resilience index follow a descriptive inverted-U shape pattern (0.4918 → 0.5138 → 0.4516), remaining at a medium-to-low level throughout the study period, with a statistically significant post-2019 decline (Wilcoxon signed-rank test, p < 0.01). Resilience exhibits a pronounced “higher in the north, lower in the south, core–periphery” spatial pattern: Guangyang District and Bazhou City consistently rank highest, whereas Yongqing and Dacheng counties remain lowest. Global Moran’s I values are negative but statistically non-significant in all three years, and the LISA analysis identifies only isolated local contrasts (H–L in Gu’an and Bazhou in 2014–2019; L–H in Yongqing in 2019–2024). Urban flood control design standards, the proportion of low-lying terrain and maximum 24-h rainfall carry the highest combined weights and thus contribute most to the measured variation of the resilience index among districts; this reflects the weight structure of the evaluation system rather than verified causal influence. Based on these findings, differentiated resilience-enhancement strategies are proposed for four groups of districts, including compensation mechanisms for the counties hosting flood storage and detention areas.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2026-10-30
DOI
https://doi.org/10.3390/su182111080
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing Urban Flood Resilience in Langfang City: A Multi-Criteria Evaluation and Spatiotemporal Evolution Analysis Under PSR-VIKOR Framework

Lingzhi Ouyang, Yuhai Zhang, Huaqing Tang, Tianwei Zhang
4 links
Sustainability
Flood Risk Assessment and Management
article

Assessing Urban Flood Resilience in Langfang City: A Multi-Criteria Evaluation and Spatiotemporal Evolution Analysis Under PSR-VIKOR Framework

Lingzhi Ouyang, Yuhai Zhang, Huaqing Tang, Tianwei Zhang
article en

Abstract

Flood disasters are among the most frequent, widespread and devastating natural disasters worldwide, and accelerating urbanization together with more frequent extreme rainfall events continues to increase urban flood risk. This study develops a flood resilience evaluation framework for Langfang City (Hebei Province, China), a core node of the Beijing–Tianjin–Hebei region, based on the Pressure–State–Response (PSR) model. Indicators were screened through literature word-frequency analysis and Pearson correlation analysis, yielding an index system of three dimensions and seventeen indicators adapted to local conditions. The FAHP–CRITIC combined weighting method and the VIKOR multi-criteria evaluation method were applied to calculate flood resilience indices for ten districts in 2014, 2019 and 2024, complemented by sensitivity analyses of the compromise coefficient λ and of the weighting scheme; spatial autocorrelation and LISA cluster analyses were conducted to examine spatiotemporal patterns. The results show that the yearly means of the resilience index follow a descriptive inverted-U shape pattern (0.4918 → 0.5138 → 0.4516), remaining at a medium-to-low level throughout the study period, with a statistically significant post-2019 decline (Wilcoxon signed-rank test, p < 0.01). Resilience exhibits a pronounced “higher in the north, lower in the south, core–periphery” spatial pattern: Guangyang District and Bazhou City consistently rank highest, whereas Yongqing and Dacheng counties remain lowest. Global Moran’s I values are negative but statistically non-significant in all three years, and the LISA analysis identifies only isolated local contrasts (H–L in Gu’an and Bazhou in 2014–2019; L–H in Yongqing in 2019–2024). Urban flood control design standards, the proportion of low-lying terrain and maximum 24-h rainfall carry the highest combined weights and thus contribute most to the measured variation of the resilience index among districts; this reflects the weight structure of the evaluation system rather than verified causal influence. Based on these findings, differentiated resilience-enhancement strategies are proposed for four groups of districts, including compensation mechanisms for the counties hosting flood storage and detention areas.

SustainabilityVol. 18(21)
China People's Police University (CN)
Sustainable cities and communities, Clean water and sanitation
Openalex Percentile: Top 17%
Flood Risk Assessment and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon