IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i19p3613-d271119.html
   My bibliography  Save this article

Optimization of Impervious Surface Space Layout for Prevention of Urban Rainstorm Waterlogging: A Case Study of Guangzhou, China

Author

Listed:
  • Huafei Yu

    (School of Geography, South China Normal University, Guangzhou 510631, China
    School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China)

  • Yaolong Zhao

    (School of Geography, South China Normal University, Guangzhou 510631, China)

  • Yingchun Fu

    (School of Geography, South China Normal University, Guangzhou 510631, China)

Abstract

With the rapid expansion of impervious surfaces, urban waterlogging has become a typical “urban disease” in China, seriously hindering the sustainable development of cities. Therefore, reducing the impact of impervious surfaces on surface runoff is an effective approach to alleviate urban waterlogging. Presently, the development mode of many cities in China has shifted from an increase in urban scale to the improvement of urban quality through urban renewal, which is the current and future development path for most cities. Optimizing the design of impervious surfaces in urban renewal planning to reduce its impact on surface runoff is an important way to prevent and control urban waterlogging. The aim of this research is to construct an optimization model of impervious surface space layout under the framework of a geographic simulation technology-integrated ant colony optimization (ACO) and Soil Conservation Service curve number (SCS-CN) model (ACO-SCS) in a case study of Guangzhou in China. Urban runoff plots in the study area are divided according to the area of the urban planning unit. With the goal of minimizing the runoff coefficient, the optimal space layout of the impervious surfaces is obtained, which provides a technical method and reference for urban waterlogging prevention and control through urban renewal planning. The results reveal that the optimization of impervious surface space layout through ACO-SCS achieves a satisfactory effect with an average optimization rate of 9.52%, and a maximum optimization rate of 33.16%. The research also shows that the initial impervious surface layout is the key influencing factor in ACO-SCS. In the urban renewal planning stage, the space layout of the impervious surfaces with a high–low–high density discontinuous connection can be constructed by transforming medium-density impervious surfaces into low-density impervious surfaces to achieve the flat and long-type agglomeration of the low-density and high-density impervious surfaces, which can effectively reduce the influence of urban development on surface runoff. There is spatial heterogeneity of the optimal results in different urban runoff plots. Therefore, the policy of urban renewal planning for urban waterlogging prevention and control should be different. The optimized results of impervious surface space layout provide useful reference information for urban renewal planning.

Suggested Citation

  • Huafei Yu & Yaolong Zhao & Yingchun Fu, 2019. "Optimization of Impervious Surface Space Layout for Prevention of Urban Rainstorm Waterlogging: A Case Study of Guangzhou, China," IJERPH, MDPI, vol. 16(19), pages 1-28, September.
  • Handle: RePEc:gam:jijerp:v:16:y:2019:i:19:p:3613-:d:271119
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/19/3613/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/16/19/3613/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Yuan, Kuang-Yu & Lin, Ying-Chen & Chiueh, Pei-Te & Lo, Shang-Lien, 2018. "Spatial optimization of the food, energy, and water nexus: A life cycle assessment-based approach," Energy Policy, Elsevier, vol. 119(C), pages 502-514.
    3. Wang, Dan & Gong, Zhiguang & Yang, Zhongzhen, 2018. "Design of industrial clusters and optimization of land use in an airport economic zone," Land Use Policy, Elsevier, vol. 77(C), pages 288-297.
    4. Mao, Xuhui & Jia, Haifeng & Yu, Shaw L., 2017. "Assessing the ecological benefits of aggregate LID-BMPs through modelling," Ecological Modelling, Elsevier, vol. 353(C), pages 139-149.
    5. Xingqi Zhang & Xinya Guo & Maochuan Hu, 2016. "Hydrological effect of typical low impact development approaches in a residential district," 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. 80(1), pages 389-400, January.
    6. Peng Chen & Jiquan Zhang & Lifeng Zhang & Yingyue Sun, 2014. "Evaluation of Resident Evacuations in Urban Rainstorm Waterlogging Disasters Based on Scenario Simulation: Daoli District (Harbin, China) as an Example," IJERPH, MDPI, vol. 11(10), pages 1-17, September.
    7. Weizhong Su & Gaobin Ye & Shimou Yao & Guishan Yang, 2014. "Urban Land Pattern Impacts on Floods in a New District of China," Sustainability, MDPI, vol. 6(10), pages 1-21, September.
    8. Xu QuanLi & Yang Kun & Wang GuiLin & Yang YuLian, 2015. "Agent-based modeling and simulations of land-use and land-cover change according to ant colony optimization: a case study of the Erhai Lake Basin, 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. 75(1), pages 95-118, January.
    9. Xingqi Zhang & Maochuan Hu & Gang Chen & Youpeng Xu, 2012. "Urban Rainwater Utilization and its Role in Mitigating Urban Waterlogging Problems—A Case Study in Nanjing, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(13), pages 3757-3766, October.
    10. Xiaodan Wu & Dapeng Yu & Zhongyuan Chen & Robert Wilby, 2012. "An evaluation of the impacts of land surface modification, storm sewer development, and rainfall variation on waterlogging risk in Shanghai," 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. 63(2), pages 305-323, September.
    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.
    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. Sheng Cheng & Liqun Liu & Ke Li, 2020. "Explaining the Factors Influencing the Individuals’ Continuance Intention to Seek Information on Weibo during Rainstorm Disasters," IJERPH, MDPI, vol. 17(17), pages 1-16, August.
    2. 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.
    3. Mo Wang & Xiaoping Fu & Dongqing Zhang & Siwei Lou & Jianjun Li & Furong Chen & Shan Li & Soon Keat Tan, 2023. "Urban agglomeration waterlogging hazard exposure assessment based on an integrated Naive Bayes classifier and complex network analysis," 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. 118(3), pages 2173-2197, 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. 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.
    2. 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.
    3. Weike Chen & Jing Dong & Chaohua Yan & Hui Dong & Ping Liu, 2021. "What Causes Waterlogging?—Explore the Urban Waterlogging Control Scheme through System Dynamics Simulation," Sustainability, MDPI, vol. 13(15), pages 1-21, July.
    4. Qingyu Huang & Jun Wang & Mengya Li & Moli Fei & Jungang Dong, 2017. "Modeling the influence of urbanization on urban pluvial flooding: a scenario-based case study in Shanghai, 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. 87(2), pages 1035-1055, June.
    5. Chunlin Li & Miao Liu & Yuanman Hu & Rongqing Han & Tuo Shi & Xiuqi Qu & Yilin Wu, 2018. "Evaluating the Hydrologic Performance of Low Impact Development Scenarios in a Micro Urban Catchment," IJERPH, MDPI, vol. 15(2), pages 1-14, February.
    6. Xingqi Zhang & Xinya Guo & Maochuan Hu, 2016. "Hydrological effect of typical low impact development approaches in a residential district," 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. 80(1), pages 389-400, January.
    7. Lu Liu & Jian Sun & Binliang Lin, 2022. "A large-scale waterlogging investigation in a megacity," 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 1505-1524, November.
    8. Chang Zhai & Zhonghui Zhang & Guangdao Bao & Dan Zhang & Ting Liu & Jiaqi Chen & Mingming Ding & Ruoxuan Geng & Ning Fang, 2022. "Comparing the Urban Floods Resistance of Common Tree Species in Winter City Parks," Land, MDPI, vol. 11(12), pages 1-14, December.
    9. Yinhong Hu & Weiwei Yu & Bowen Cui & Yuanyuan Chen & Hua Zheng & Xiaoke Wang, 2021. "Pavement Overrides the Effects of Tree Species on Soil Bacterial Communities," IJERPH, MDPI, vol. 18(4), pages 1-11, February.
    10. Thomas D. Pol & Ekko C. Ierland & Silke Gabbert, 2017. "Economic analysis of adaptive strategies for flood risk management under climate change," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 22(2), pages 267-285, February.
    11. Mohsen Goodarzi & Nafiseh Haghtalab & Iman Saeedi & Nathan J. Moore, 2020. "Structural and functional improvement of urban fringe areas: toward achieving sustainable built–natural environment interactions," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(7), pages 6727-6754, October.
    12. Xu-Wei Wang & Ye-Shuang Xu, 2022. "Investigation on the phenomena and influence factors of urban ground collapse in 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. 113(1), pages 1-33, August.
    13. Iman Saeedi & Mohsen Goodarzi, 2020. "Rainwater harvesting system: a sustainable method for landscape development in semiarid regions, the case of Malayer University campus in Iran," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(2), pages 1579-1598, February.
    14. Tong Xu & Zhiqiang Xie & Fei Zhao & Yimin Li & Shouquan Yang & Yangbin Zhang & Siqiao Yin & Shi Chen & Xuan Li & Sidong Zhao & Zhiqun Hou, 2022. "Permeability control and flood risk assessment of urban underlying surface: a case study of Runcheng south area, Kunming," 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. 111(1), pages 661-686, March.
    15. Junfei Chen & Juan Ji & Huimin Wang & Menghua Deng & Cong Yu, 2020. "Risk Assessment of Urban Rainstorm Disaster Based on Multi-Layer Weighted Principal Component Analysis: A Case Study of Nanjing, China," IJERPH, MDPI, vol. 17(15), pages 1-19, July.
    16. Xiao Liang & Yuqing Liang & Chong Chen & Meine Pieter van Dijk, 2020. "Implementing Water Policies in China: A Policy Cycle Analysis of the Sponge City Program Using Two Case Studies," Sustainability, MDPI, vol. 12(13), pages 1-11, June.
    17. Chad W. Higgins & Majdi Abou Najm, 2020. "An Organizing Principle for the Water-Energy-Food Nexus," Sustainability, MDPI, vol. 12(19), pages 1-15, October.
    18. Wenfeng Chi & Jing Jia & Tao Pan & Liang Jin & Xiulian Bai, 2020. "Multi-Scale Analysis of Green Space for Human Settlement Sustainability in Urban Areas of the Inner Mongolia Plateau, China," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
    19. 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.
    20. Bhanage Vinayak & Han Soo Lee & Shirishkumar Gedem, 2021. "Prediction of Land Use and Land Cover Changes in Mumbai City, India, Using Remote Sensing Data and a Multilayer Perceptron Neural Network-Based Markov Chain Model," Sustainability, MDPI, vol. 13(2), pages 1-22, January.

    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:16:y:2019:i:19:p:3613-:d:271119. 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.