IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i7p2232-d155137.html
   My bibliography  Save this article

Copula-Based Joint Probability Analysis of Compound Floods from Rainstorm and Typhoon Surge: A Case Study of Jiangsu Coastal Areas, China

Author

Listed:
  • Ping Ai

    (College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
    College of Computer and Information, Hohai University, Nanjing 211100, China)

  • Dingbo Yuan

    (College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China)

  • Chuansheng Xiong

    (College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China)

Abstract

Coastal areas are vulnerable to floods caused by rainstorms and typhoons. It is necessary to ascertain the risk of floods caused by both of these extreme weather events. A conceptual risk model is proposed to evaluate the rainstorm risk, typhoon surge risk, and the compound risk in the coastal areas of Jiangsu Province during the period of 1960–2012. The results of the model show that the typhoon surge risk in the study region is greater than the rainstorm risk. Three Archimedean copulas were used to fit the joint probability distributions of the compound events. The Frank copula and the Gumbel copula proved to be the best-fitting joint distribution function for the Huaibei plain district and the Lixiahe district, respectively. The probability of the extreme compound events not happening is less than 90% in the study region. This means that the flood risk is mainly subject to the encounter of a low-level rainstorm and a low-level typhoon surge. The study shows that the northern region of Jiangsu Province is more vulnerable to the compound risk, and that we should pay more attention to the floods caused by the compound events of rainstorm and typhoon surge.

Suggested Citation

  • Ping Ai & Dingbo Yuan & Chuansheng Xiong, 2018. "Copula-Based Joint Probability Analysis of Compound Floods from Rainstorm and Typhoon Surge: A Case Study of Jiangsu Coastal Areas, China," Sustainability, MDPI, vol. 10(7), pages 1-18, June.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:7:p:2232-:d:155137
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/7/2232/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/10/7/2232/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jean-David Fermanian, 2003. "Goodness of Fit Tests for Copulas," Working Papers 2003-34, Center for Research in Economics and Statistics.
    2. Shanshan Tao & Sheng Dong & Nannan Wang & C. Guedes Soares, 2013. "Estimating storm surge intensity with Poisson bivariate maximum entropy distributions based on copulas," 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. 68(2), pages 791-807, September.
    3. Stephane Hallegatte & Colin Green & Robert J. Nicholls & Jan Corfee-Morlot, 2013. "Future flood losses in major coastal cities," Nature Climate Change, Nature, vol. 3(9), pages 802-806, September.
    4. Yenan Wu & Ping-an Zhong & Yu Zhang & Bin Xu & Biao Ma & Kun Yan, 2015. "Integrated flood risk assessment and zonation method: a case study in Huaihe River 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. 78(1), pages 635-651, August.
    5. Jonathan D. Woodruff & Jennifer L. Irish & Suzana J. Camargo, 2013. "Coastal flooding by tropical cyclones and sea-level rise," Nature, Nature, vol. 504(7478), pages 44-52, December.
    6. Christian M. Hafner & Hans Manner, 2012. "Dynamic stochastic copula models: estimation, inference and applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(2), pages 269-295, March.
    7. Jun Wang & Wei Gao & Shiyuan Xu & Lizhong Yu, 2012. "Evaluation of the combined risk of sea level rise, land subsidence, and storm surges on the coastal areas of Shanghai, China," Climatic Change, Springer, vol. 115(3), pages 537-558, December.
    8. Sheng Dong & Chun-Shuo Jiao & Shan-Shan Tao, 2017. "Joint return probability analysis of wind speed and rainfall intensity in typhoon-affected sea area," 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. 86(3), pages 1193-1205, April.
    9. Fermanian, Jean-David, 2005. "Goodness-of-fit tests for copulas," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 119-152, 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. Kui Xu & Chenyue Wang & Lingling Bin, 2023. "Compound flood models in coastal areas: a review of methods and uncertainty 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. 116(1), pages 469-496, March.
    2. Poornima Unnikrishnan & Kumaraswamy Ponnambalam & Nirupama Agrawal & Fakhri Karray, 2023. "Joint Flood Risks in the Grand River Watershed," Sustainability, MDPI, vol. 15(12), pages 1-14, June.
    3. Amjad, Muhammad & Akbar, Muhammad & Ullah, Hamd, 2022. "A copula-based approach for creating an index of micronutrient intakes at household level in Pakistan," Economics & Human Biology, Elsevier, vol. 46(C).

    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. Zhang, Shulin & Okhrin, Ostap & Zhou, Qian M. & Song, Peter X.-K., 2016. "Goodness-of-fit test for specification of semiparametric copula dependence models," Journal of Econometrics, Elsevier, vol. 193(1), pages 215-233.
    2. repec:hum:wpaper:sfb649dp2013-041 is not listed on IDEAS
    3. Jie Huang & Haiming Zhou & Nader Ebrahimi, 2022. "Bayesian Bivariate Cure Rate Models Using Copula Functions," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 11(3), pages 1-9, May.
    4. Gaißer, Sandra & Schmid, Friedrich, 2010. "On testing equality of pairwise rank correlations in a multivariate random vector," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2598-2615, November.
    5. Scaillet, Olivier, 2007. "Kernel-based goodness-of-fit tests for copulas with fixed smoothing parameters," Journal of Multivariate Analysis, Elsevier, vol. 98(3), pages 533-543, March.
    6. Wanling Huang & Artem Prokhorov, 2014. "A Goodness-of-fit Test for Copulas," Econometric Reviews, Taylor & Francis Journals, vol. 33(7), pages 751-771, October.
    7. Ke Wang & Yongsheng Yang & Genserik Reniers & Quanyi Huang, 2021. "A study into the spatiotemporal distribution of typhoon storm surge disasters 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. 108(1), pages 1237-1256, August.
    8. Xun Lu & Kin Lai & Liang Liang, 2014. "Portfolio value-at-risk estimation in energy futures markets with time-varying copula-GARCH model," Annals of Operations Research, Springer, vol. 219(1), pages 333-357, August.
    9. Weijiang Li & Jiahong Wen & Bo Xu & Xiande Li & Shiqiang Du, 2018. "Integrated Assessment of Economic Losses in Manufacturing Industry in Shanghai Metropolitan Area Under an Extreme Storm Flood Scenario," Sustainability, MDPI, vol. 11(1), pages 1-19, December.
    10. Beatriz Mendes & Mariângela Semeraro & Ricardo Leal, 2010. "Pair-copulas modeling in finance," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 24(2), pages 193-213, June.
    11. Aloui, Riadh & Aïssa, Mohamed Safouane Ben & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Dependence and extreme dependence of crude oil and natural gas prices with applications to risk management," Energy Economics, Elsevier, vol. 42(C), pages 332-342.
    12. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation of copula-based semiparametric time series models," Journal of Econometrics, Elsevier, vol. 130(2), pages 307-335, February.
    13. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "Rejoinder on: An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 442-447, September.
    14. Reguero, Borja G. & Beck, Michael W. & Schmid, David & Stadtmüller, Daniel & Raepple, Justus & Schüssele, Stefan & Pfliegner, Kerstin, 2020. "Financing coastal resilience by combining nature-based risk reduction with insurance," Ecological Economics, Elsevier, vol. 169(C).
    15. Can, S.U. & Einmahl, John & Laeven, R.J.A., 2020. "Goodness-of-fit testing for copulas: A distribution-free approach," Other publications TiSEM 211b2be9-b46e-41e2-9b95-1, Tilburg University, School of Economics and Management.
    16. Faugeras, Olivier P., 2009. "A quantile-copula approach to conditional density estimation," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 2083-2099, October.
    17. Derumigny Alexis & Fermanian Jean-David, 2017. "About tests of the “simplifying” assumption for conditional copulas," Dependence Modeling, De Gruyter, vol. 5(1), pages 154-197, August.
    18. Bouezmarni, Taoufik & Rombouts, Jeroen V.K. & Taamouti, Abderrahim, 2010. "Asymptotic properties of the Bernstein density copula estimator for [alpha]-mixing data," Journal of Multivariate Analysis, Elsevier, vol. 101(1), pages 1-10, January.
    19. Jonas Meier, 2020. "Multivariate Distribution Regression," Diskussionsschriften dp2023, Universitaet Bern, Departement Volkswirtschaft.
    20. Kajal Lahiri & Liu Yang, 2023. "Predicting binary outcomes based on the pair-copula construction," Empirical Economics, Springer, vol. 64(6), pages 3089-3119, June.
    21. Bhatti, M. Ishaq & Nguyen, Cuong C., 2012. "Diversification evidence from international equity markets using extreme values and stochastic copulas," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(3), pages 622-646.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jsusta:v:10:y:2018:i:7:p:2232-:d:155137. 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.