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An ensemble risk assessment model for urban rainstorm disasters based on random forest and deep belief nets: a case study of Nanjing, China

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  • Junfei Chen

    (Hohai University
    Hohai University
    Jiangsu Research Base of Yangtze Institute for Conservation and High-Quality Development)

  • Liming Liu

    (Hohai University)

  • Jinpeng Pei

    (Hohai University)

  • Menghua Deng

    (Hohai University
    Jiangsu Research Base of Yangtze Institute for Conservation and High-Quality Development)

Abstract

Effective management of rainstorm risk is essential for reducing regional rainstorm disaster risks and losses. In this paper, we discussed the influencing factors of urban rainstorm disaster (URSD) risk from four aspects and then constructed the index system of URSD risk assessment which includes 16 influencing factors. Furtherly, important indexes were extracted as the input of deep belief nets (DBN) model after analyzing the types and risk characteristics of URSD. As well as a coupling risk assessment model of URSD based on random forest and deep belief nets (RF–DBN) was established due to the capacity of high-dimensional data processing of RF and robustness of DBN. To test the validity of this risk assessment model, it was applied to evaluate the rainstorm disaster risk in 11 districts of Nanjing, China, from May to September during 2009 and 2017. Finally, the risk grade map of rainstorm disaster in Nanjing was drawn and the corresponding countermeasures for the regulation and control of URSD were put forward. The results show that the rainstorm risk in Nanjing is generally high during the period of rainy season and the risk of rainstorm disaster has egional features during the flood season.

Suggested Citation

  • Junfei Chen & Liming Liu & Jinpeng Pei & Menghua Deng, 2021. "An ensemble risk assessment model for urban rainstorm disasters based on random forest and deep belief nets: a case study of Nanjing, China," 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. 107(3), pages 2671-2692, July.
    • Handle: RePEc:spr:nathaz:v:107:y:2021:i:3:d:10.1007_s11069-021-04630-y
    DOI: 10.1007/s11069-021-04630-y
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    References listed on IDEAS

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    Cited by:

    1. Menghua Deng & Zhiqi Li & Feifei Tao, 2022. "Rainstorm Disaster Risk Assessment and Influence Factors Analysis in the Yangtze River Delta, China," IJERPH, MDPI, vol. 19(15), pages 1-16, August.
    2. Jingyi Gao & Osamu Murao & Xuanda Pei & Yitong Dong, 2022. "Identifying Evacuation Needs and Resources Based on Volunteered Geographic Information: A Case of the Rainstorm in July 2021, Zhengzhou, China," IJERPH, MDPI, vol. 19(23), pages 1-21, November.
    3. Ping Zhang & Zhuo Chen & Gang Ding & Jiaqi Fang & Jinglong Fan & Shengyu Li, 2024. "Spatial Analysis and Risk Assessment of Meteorological Disasters Affecting Cotton Cultivation in Xinjiang: A Comprehensive Model Approach," Sustainability, MDPI, vol. 16(12), pages 1-17, June.
    4. Yi Chen & Zhicong Ye & Hui Liu & Ruishan Chen & Zhenhuan Liu & Hui Liu, 2021. "A GIS-Based Approach for Flood Risk Zoning by Combining Social Vulnerability and Flood Susceptibility: A Case Study of Nanjing, China," IJERPH, MDPI, vol. 18(21), pages 1-17, November.

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