IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i5p4640-d1088840.html
   My bibliography  Save this article

Urban Flood Modeling and Risk Assessment with Limited Observation Data: The Beijing Future Science City of China

Author

Listed:
  • Huan Xu

    (College of Water Conservancy and Hydropower, Hebei University of Engineering, Handan 056021, China)

  • Ying Wang

    (North China Municipal Engineering Design and Research Institute Co., Ltd., Tianjin 300074, China)

  • Xiaoran Fu

    (College of Water Conservancy and Hydropower, Hebei University of Engineering, Handan 056021, China
    National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China)

  • Dong Wang

    (Hebei Provincial Research Center of Water Ecological Civilization & Social Governance, Handan 056021, China)

  • Qinghua Luan

    (Key Laboratory of Flood Disaster Prevention and Control of the Ministry of Emergency Management in China, Hohai University, Nanjing 210024, China)

Abstract

The frequency of urban storms has increased, influenced by the climate changing and urbanization, and the process of urban rainfall runoff has also changed, leading to severe urban waterlogging problems. Against this background, the risk of urban waterlogging was analyzed and assessed accurately, using an urban stormwater model as necessary. Most studies have used urban hydrological models to assess flood risk; however, due to limited flow pipeline data, the calibration and the validation of the models are difficult. This study applied the MIKE URBAN model to build a drainage system model in the Beijing Future Science City of China, where the discharge of pipelines was absent. Three methods, of empirical calibration, formula validation, and validation based on field investigation, were used to calibrate and validate the parameters of the model. After the empirical calibration, the relative error range between the simulated value and the measured value was verified by the formula as within 25%. The simulated runoff depth was consistent with a field survey verified by the method of validation based on field investigation, showing the model has good applicability in the study area. Then, the rainfall scenarios of different return periods were designed and simulated. Simulation results showed that, for the 10-year return period, there are overflow pipe sections in northern and southern regions, and the number of overflow pipe sections in the northern region is more than that in the southern region. For the 20-year return period and 50-year return period, the number of overflow pipe sections and nodes in the northern region increased, while for the 100-year return period, the number of overflow nodes both increased. With the increase in the rainfall return period, the pipe network load increased, the points and sections prone to accumulation and waterlogging increased, and the regional waterlogging risk increased. The southern region is prone to waterlogging because the pipeline network density is higher than that in the northern region and the terrain is low-lying. This study provides a reference for the establishment of rainwater drainage models in regions with similar database limitations and provides a technical reference for the calibration and validation of stormwater models that lack rainfall runoff data.

Suggested Citation

  • Huan Xu & Ying Wang & Xiaoran Fu & Dong Wang & Qinghua Luan, 2023. "Urban Flood Modeling and Risk Assessment with Limited Observation Data: The Beijing Future Science City of China," IJERPH, MDPI, vol. 20(5), pages 1-23, March.
  • Handle: RePEc:gam:jijerp:v:20:y:2023:i:5:p:4640-:d:1088840
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/5/4640/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/20/5/4640/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhongping Zeng & Yujia Li & Jinyu Lan & Abdur Rahim Hamidi, 2021. "Utilizing User-Generated Content and GIS for Flood Susceptibility Modeling in Mountainous Areas: A Case Study of Jian City in China," Sustainability, MDPI, vol. 13(12), pages 1-18, June.
    2. Zhenbao Shi & Qingran Shen & Qiong Tan & Tian Li, 2021. "Development of Integrated Flooding Early Warning and Rainfall Runoff Management Platform for Downtown Area of Shanghai," Sustainability, MDPI, vol. 13(20), pages 1-15, October.
    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. Mariusz Starzec & Sabina Kordana-Obuch, 2024. "Evaluating the Utility of Selected Machine Learning Models for Predicting Stormwater Levels in Small Streams," Sustainability, MDPI, vol. 16(2), pages 1-29, January.

    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. Joško Trošelj & Han Soo Lee & Lena Hobohm, 2023. "Enhancing a Real-Time Flash Flood Predictive Accuracy Approach for the Development of Early Warning Systems: Hydrological Ensemble Hindcasts and Parameterizations," Sustainability, MDPI, vol. 15(18), pages 1-33, September.

    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:jijerp:v:20:y:2023:i:5:p:4640-:d:1088840. 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.