Comparison of Flood Resilience Between Low-Carbon and Traditional Communities: A Case Study of Kunming, China

Under China’s dual carbon strategy, low-carbon city construction is expected to help reduce urban flood risks. However, the flood resilience of low-carbon communities remains unclear, limiting effective disaster prevention. This study examines traditional and newly built low-carbon communities in Kunming, establishing indices for community flood resilience and low-carbon development according to current national and local standards. Flood resilience (UFR) and low-carbon development level (ULC) were measured using the critic–entropy weight and TOPSIS methods, and a coupling coordination analysis model was used to analyze their correlation and coordination. The results are as follows: (1) The two communities exhibit marked spatial heterogeneity in both UFR and ULC. On average, the UFR in traditional communities is 21.53% higher than in low-carbon communities, while the ULCs are 4.33% higher in low-carbon communities compared to traditional ones. (2) UFR and ULC showed a high coupling level in both communities (over 98%), indicating a strong correlation. (3) The Moran’s I index of 0.664 for coupling coordination indicates notable spatial dependence. These results suggest that, initially, low-carbon communities in Kunming may not exhibit stronger flood resilience, but low-carbon development can significantly improve flood resilience over time. This paper also provides recommendations for enhancing flood resilience in urban low-carbon communities.

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Publication Details

Journal
Land
Published
2025-06-28
DOI
https://doi.org/10.3390/land14071368
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Comparison of Flood Resilience Between Low-Carbon and Traditional Communities: A Case Study of Kunming, China

Yifei Liu, Zhiqiang Xie, Wei Cheng, Sidong Zhao et al.
Land
Flood Risk Assessment and Management
article

Comparison of Flood Resilience Between Low-Carbon and Traditional Communities: A Case Study of Kunming, China

Yifei Liu, Zhiqiang Xie, Wei Cheng, Sidong Zhao, Yang Li, Zheng Zhang, Zhiyong Yuan, Junxiao Wang, Dan Zhou, Ping Wen, Ling Zhu, Shihan Bai, Q. Yang
article en

Abstract

Under China’s dual carbon strategy, low-carbon city construction is expected to help reduce urban flood risks. However, the flood resilience of low-carbon communities remains unclear, limiting effective disaster prevention. This study examines traditional and newly built low-carbon communities in Kunming, establishing indices for community flood resilience and low-carbon development according to current national and local standards. Flood resilience (UFR) and low-carbon development level (ULC) were measured using the critic–entropy weight and TOPSIS methods, and a coupling coordination analysis model was used to analyze their correlation and coordination. The results are as follows: (1) The two communities exhibit marked spatial heterogeneity in both UFR and ULC. On average, the UFR in traditional communities is 21.53% higher than in low-carbon communities, while the ULCs are 4.33% higher in low-carbon communities compared to traditional ones. (2) UFR and ULC showed a high coupling level in both communities (over 98%), indicating a strong correlation. (3) The Moran’s I index of 0.664 for coupling coordination indicates notable spatial dependence. These results suggest that, initially, low-carbon communities in Kunming may not exhibit stronger flood resilience, but low-carbon development can significantly improve flood resilience over time. This paper also provides recommendations for enhancing flood resilience in urban low-carbon communities.

LandVol. 14(7)
Kunming University (CN), Yunnan University (CN), Yunnan Water Conservancy and Hydropower Survey and Design Institute (CN), Nanjing Surveying and Mapping Research Institute (China) (CN), Beijing Drainage Group (China) (CN)
National Natural Science Foundation of China, Yunnan University
Openalex Percentile: Top 85%
Flood Risk Assessment and Management
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