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Analyzing spatial variance of urban waterlogging disaster at multiple scales based on a hydrological and hydrodynamic model

Author

Listed:
  • Luoyang Wang

    (Hangzhou Normal University
    Hangzhou Normal University)

  • Yao Li

    (University of Twente)

  • Hao Hou

    (Hangzhou Normal University
    Hangzhou Normal University
    Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change)

  • Yan Chen

    (Hangzhou Normal University
    Hangzhou Normal University)

  • Jinjin Fan

    (Hangzhou Normal University
    Hangzhou Normal University)

  • Pin Wang

    (Hangzhou Normal University
    Hangzhou Normal University
    Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change)

  • Tangao Hu

    (Hangzhou Normal University
    Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change)

Abstract

The frequency of urban waterlogging is increasing significantly under the combined influence of natural factors (precipitation and terrain) and anthropogenic factors (drainage system and urbanization). Previous studies had explored the effect of landscape pattern and topography on waterlogging based on historical waterlogging events records. However, the research on current waterlogging issues based on historical records had limitations since the impact factors of waterlogging are inconsistent due to the changes of surface and meteorological conditions. This paper applied a hydrological and hydrodynamic model named InfoWorks ICM, to simulate the urban waterlogging depth (UWD). Under the consistent surface and meteorological conditions, UWD were selected as the dependent variable to analyze the influence of landscape pattern and topography on waterlogging at multiple scales. Pearson correlation analysis and stepwise regression models were used to discover the relationship between these indices. According to the results, in terms of landscape composition, the percentages of built-up area and urban green space have the most significant influence on waterlogging. In addition, organizing average built-up area patch sizes and integrating green spaces with complex shape and high connectivity can improve the state of urban waterlogging. Besides, the rational allocation of topographic gradient is an effective measure at small scale. The adjusted R2 of regression model were 0.723 at 400 m analysis scale, 0.323 at 600 m analysis scale, and 0.193 at 800 m analysis scale, indicating that attention should be paid to scale effect in similar research. This research can provide a reference for mitigating urban waterlogging disasters.

Suggested Citation

  • Luoyang Wang & Yao Li & Hao Hou & Yan Chen & Jinjin Fan & Pin Wang & Tangao Hu, 2022. "Analyzing spatial variance of urban waterlogging disaster at multiple scales based on a hydrological and hydrodynamic model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(2), pages 1915-1938, November.
    • Handle: RePEc:spr:nathaz:v:114:y:2022:i:2:d:10.1007_s11069-022-05453-1
    DOI: 10.1007/s11069-022-05453-1
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    1. Lariyah Mohd Sidek & Aminah Shakirah Jaafar & Wan Hazdy Azad Wan Abdul Majid & Hidayah Basri & Mohammad Marufuzzaman & Muzad Mohd Fared & Wei Chek Moon, 2021. "High-Resolution Hydrological-Hydraulic Modeling of Urban Floods Using InfoWorks ICM," Sustainability, MDPI, vol. 13(18), pages 1-20, September.
    2. Deepak Singh Bisht & Chandranath Chatterjee & Shivani Kalakoti & Pawan Upadhyay & Manaswinee Sahoo & Ambarnil Panda, 2016. "Modeling urban floods and drainage using SWMM and MIKE URBAN: a case study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(2), pages 749-776, November.
    3. Rui-Song Quan, 2014. "Rainstorm waterlogging risk assessment in central urban area of Shanghai based on multiple scenario simulation," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(3), pages 1569-1585, September.
    4. Boni Su & Hong Huang & Yuntao Li, 2016. "Integrated simulation method for waterlogging and traffic congestion under urban rainstorms," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(1), pages 23-40, March.
    5. Yijun Shi & Guofang Zhai & Shutian Zhou & Yuwen Lu & Wei Chen & Jinyang Deng, 2019. "How Can Cities Respond to Flood Disaster Risks under Multi-Scenario Simulation? A Case Study of Xiamen, China," IJERPH, MDPI, vol. 16(4), pages 1-18, February.
    6. Shiqiang Du & Anton Van Rompaey & Peijun Shi & Jing’ai Wang, 2015. "A dual effect of urban expansion on flood risk in the Pearl River Delta (China) revealed by land-use scenarios and direct runoff simulation," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(1), pages 111-128, May.
    7. Huafei Yu & Yaolong Zhao & Yingchun Fu & Le Li, 2018. "Spatiotemporal Variance Assessment of Urban Rainstorm Waterlogging Affected by Impervious Surface Expansion: A Case Study of Guangzhou, China," Sustainability, MDPI, vol. 10(10), pages 1-22, October.
    8. Song Liu & Mengnan Lin & Chunlin Li, 2019. "Analysis of the Effects of the River Network Structure and Urbanization on Waterlogging in High-Density Urban Areas—A Case Study of the Pudong New Area in Shanghai," IJERPH, MDPI, vol. 16(18), pages 1-13, September.
    9. Boni Su & Hong Huang & Yuntao Li, 2016. "Integrated simulation method for waterlogging and traffic congestion under urban rainstorms," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(1), pages 23-40, March.
    10. Yu Song & Xiaodong Song & Guofan Shao, 2020. "Effects of Green Space Patterns on Urban Thermal Environment at Multiple Spatial–Temporal Scales," Sustainability, MDPI, vol. 12(17), pages 1-18, August.
    11. Yan-Fang Sang & Moyuan Yang, 2017. "Urban waterlogs control in China: more effective strategies and actions are needed," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(2), pages 1291-1294, January.
    12. Lei Yao & Liding Chen & Wei Wei, 2017. "Exploring the Linkage between Urban Flood Risk and Spatial Patterns in Small Urbanized Catchments of Beijing, China," IJERPH, MDPI, vol. 14(3), pages 1-16, February.
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