IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v10y2021i2p210-d502389.html
   My bibliography  Save this article

Key Disaster-Causing Factors Chains on Urban Flood Risk Based on Bayesian Network

Author

Listed:
  • Shanqing Huang

    (Institute of Management Science, Business School, Hohai University, Nanjing 211100, China
    State Key Laboratory of Hydrology Water Resources and Hydraulic Engineering, Nanjing 210098, China)

  • Huimin Wang

    (Institute of Management Science, Business School, Hohai University, Nanjing 211100, China
    State Key Laboratory of Hydrology Water Resources and Hydraulic Engineering, Nanjing 210098, China)

  • Yejun Xu

    (Institute of Management Science, Business School, Hohai University, Nanjing 211100, China)

  • Jingwen She

    (Institute of Management Science, Business School, Hohai University, Nanjing 211100, China)

  • Jing Huang

    (Institute of Management Science, Business School, Hohai University, Nanjing 211100, China)

Abstract

Drivers of urban flood disaster risk may be related to many factors from nature and society. However, it is unclear how these factors affect each other and how they ultimately affect the risk. From the perspective of risk uncertainty, flood inundation risk is considered to be the probability of inundation consequences under the influence of various factors. In this paper, urban flood inundation risk assessment model is established based on Bayesian network, and then key disaster-causing factors chains are explored through influence strength analysis. Jingdezhen City is selected as study area, where the flood inundation probability is calculated, and the paths of these influential factors are found. The results show that the probability of inundation in most areas is low. Risk greater than 0.8 account for about 9%, and most of these areas are located in the middle and southern section of the city. The influencing factors interact with each other in the form of factor chain and, finally, affect the flood inundation. Rainfall directly affects inundation, while river is the key factor on inundation which is influenced by elevation and slope. In addition, in the chain of socio-economic factors, the population will determine the pipe density through affecting gross domestic product (GDP), and lead to the inundation. The approach proposed in this study can be used to find key disaster-causing factors chains, which not only quantitatively reveal the formation of risks but also provide reference for early warning.

Suggested Citation

  • Shanqing Huang & Huimin Wang & Yejun Xu & Jingwen She & Jing Huang, 2021. "Key Disaster-Causing Factors Chains on Urban Flood Risk Based on Bayesian Network," Land, MDPI, vol. 10(2), pages 1-21, February.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:2:p:210-:d:502389
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/10/2/210/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/10/2/210/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zening Wu & Yanxia Shen & Huiliang Wang, 2019. "Assessing Urban Areas’ Vulnerability to Flood Disaster Based on Text Data: A Case Study in Zhengzhou City," Sustainability, MDPI, vol. 11(17), pages 1-15, August.
    2. Rui Liu & Yun Chen & Jianping Wu & Lei Gao & Damian Barrett & Tingbao Xu & Xiaojuan Li & Linyi Li & Chang Huang & Jia Yu, 2017. "Integrating Entropy‐Based Naïve Bayes and GIS for Spatial Evaluation of Flood Hazard," Risk Analysis, John Wiley & Sons, vol. 37(4), pages 756-773, April.
    3. Hongjun Joo & Changhyun Choi & Jungwook Kim & Deokhwan Kim & Soojun Kim & Hung Soo Kim, 2019. "A Bayesian Network-Based Integrated for Flood Risk Assessment (InFRA)," Sustainability, MDPI, vol. 11(13), pages 1-15, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jozef Kubás & Katarína Bugánová & Mária Polorecká & Katarína Petrlová & Adéla Stolínová, 2022. "Citizens’ Preparedness to Deal with Emergencies as an Important Component of Civil Protection," IJERPH, MDPI, vol. 19(2), pages 1-18, January.
    2. Mo Wang & Xiaoping Fu & Dongqing Zhang & Furong Chen & Jin Su & Shiqi Zhou & Jianjun Li & Yongming Zhong & Soon Keat Tan, 2023. "Urban Flooding Risk Assessment in the Rural-Urban Fringe Based on a Bayesian Classifier," Sustainability, MDPI, vol. 15(7), pages 1-16, March.
    3. Chao Ma & Wenchao Qi & Hongshi Xu & Kai Zhao, 2022. "An integrated quantitative framework to assess the impacts of disaster-inducing factors on causing urban flood," 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. 113(3), pages 1903-1924, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Meiling Zhou & Xiuli Feng & Kaikai Liu & Chi Zhang & Lijian Xie & Xiaohe Wu, 2021. "An Alternative Risk Assessment Model of Urban Waterlogging: A Case Study of Ningbo City," Sustainability, MDPI, vol. 13(2), pages 1-20, January.
    2. Hariklia D. Skilodimou & George D. Bathrellos, 2021. "Natural and Technological Hazards in Urban Areas: Assessment, Planning and Solutions," Sustainability, MDPI, vol. 13(15), pages 1-5, July.
    3. Jifei Zhang & Shuai Zhang, 2022. "Assessing Integrated Effectiveness of Rural Socio-Economic Development and Environmental Protection of Wenchuan County in Southwestern China: An Approach Using Game Theory and VIKOR," Land, MDPI, vol. 11(11), pages 1-17, October.
    4. Aldo Mascareño & Pablo A. Henríquez & Marco Billi & Gonzalo A. Ruz, 2020. "A Twitter-Lived Red Tide Crisis on Chiloé Island, Chile: What Can Be Obtained for Social-Ecological Research through Social Media Analysis?," Sustainability, MDPI, vol. 12(20), pages 1-38, October.
    5. Stefano Morelli & Veronica Pazzi & Olga Nardini & Sara Bonati, 2022. "Framing Disaster Risk Perception and Vulnerability in Social Media Communication: A Literature Review," Sustainability, MDPI, vol. 14(15), pages 1-28, July.
    6. Bikram Manandhar & Shenghui Cui & Lihong Wang & Sabita Shrestha, 2023. "Urban Flood Hazard Assessment and Management Practices in South Asia: A Review," Land, MDPI, vol. 12(3), pages 1-29, March.
    7. Wen-Cheng Liu & Tien-Hsiang Hsieh & Hong-Ming Liu, 2021. "Flood Risk Assessment in Urban Areas of Southern Taiwan," Sustainability, MDPI, vol. 13(6), pages 1-22, March.
    8. Xun Liu & Peng Zhou & Yichen Lin & Siwei Sun & Hailu Zhang & Wanqing Xu & Sangdi Yang, 2022. "Influencing Factors and Risk Assessment of Precipitation-Induced Flooding in Zhengzhou, China, Based on Random Forest and XGBoost Algorithms," IJERPH, MDPI, vol. 19(24), pages 1-20, December.
    9. Sina Mallah & Manouchehr Gorji & Mohammad Reza Balali & Hossein Asadi & Naser Davatgar & Hojjat Varmazyari & Anna Maria Stellacci & Mirko Castellini, 2023. "Deep Insight on Land Use/Land Cover Geospatial Assessment through Internet-Based Validation Tool in Upper Karkheh River Basin (KRB), South-West Iran," Land, MDPI, vol. 12(5), pages 1-22, April.
    10. Angeliki Mentzafou & Momčilo Blagojević & Elias Dimitriou, 2021. "A GIS-MCDA-Based Suitability Analysis for Meeting Targets 6.3 and 6.5 of the Sustainable Development Goals," Sustainability, MDPI, vol. 13(8), pages 1-23, April.
    11. Bao Meng & Jifei Zhang & Xiaohui Zhang, 2023. "Detecting the Spatial Network Structure of the Guanzhong Plain Urban Agglomeration, China: A Multi-Dimensional Element Flow Perspective," Land, MDPI, vol. 12(3), pages 1-18, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:10:y:2021:i:2:p:210-:d:502389. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.