Technical Papers
Jun 15, 2012

Flood Coincidence Risk Analysis Using Multivariate Copula Functions

Publication: Journal of Hydrologic Engineering
Volume 17, Issue 6

Abstract

The coincidence of flood flows of the mainstream and its tributaries may determine flood peaks. This study analyzed the risk of flooding as a result of such flood coincidences by considering flood magnitudes and time (dates) of occurrence. The Pearson Type III (P3) and log-Pearson Type III (LP3) distributions were selected as the marginal distribution of flood magnitude for annual maximum flood series; the mixed von Mises distribution was selected as the marginal distribution of flood occurrence dates. Two four-dimensional (4D) copula functions were developed for the joint distribution of flood magnitudes and occurrence dates. The upper Yangtze River in China and the Colorado River in the United States were selected to evaluate the method of computing risk. The coincidence probabilities of flood magnitudes and dates were calculated, and the conditional probabilities for the Three Gorges Reservoir (TGR) were analyzed. Results show that the von Mises distribution can fit the observed flood dates data well. The X-Gumbel copula was selected for risk analysis. On the basis of the proposed model, the coincidence and conditional probabilities for any return period were obtained.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

The study is financially supported by the Ministry of Science and Technology (2009BAC56B01; 2009BAC56B02; 2010CB428405) of China.

References

AghaKouchak, A., Bárdossy, A., and Habib, E. (2010a). “Conditional simulation of remotely sensed rainfall data using a non-Gaussian v-transformed copula.” Adv. Water Resour.AWREDI, 33(6), 624–634.
AghaKouchak, A., Bárdossy, A., and Habib, E. (2010b). “Copula-based uncertainty modelling: Application to multisensor precipitation estimates.” Hydrol. ProcessesHYPRE3, 24(15), 2111–2124.
Black, A. R., and Werritty, A. (1997). “Seasonality of flooding: A case study of north Britain.” J. Hydrol. (Amsterdam)JHYDA7, 195(1–4), 1–25.
Carta, J. A., and Ramírez, P. (2007). “Analysis of two-component mixture Weibull statistics for estimation of wind speeds distribution.” Renewable EnergyRNENE3, 32(3), 518–531.
Chen, L., Guo, S. L., Yan, B. W., Liu, P., and Fang, B. (2010). “A new seasonal design flood method based on bivariate joint distribution of flood magnitude and date of occurrence.” Hydrol. Sci. J.HSJODN, 55(8), 1264–1280.
De Michele, C., and Salvadori, G. (2003). “A generalized Pareto intensity duration model of storm rainfall exploiting 2-copulas.” J. Geophys. Res.JGREA2, 108(D2), 1–11.
De Michele, C., Salvadori, G., Passni, G., and Vezzoli, R. (2007). “A multivariate model of sea storms using copulas.” Coastal Eng.COENDE, 54(10), 734–751.
de Waal, D. J., van Gelder, P. H. A. J. M., and Nel, A. (2007). “Estimating joint tail probabilities of river discharges through the logistic copula.” EnvironmetricsENVCEE, 18(6), 621–631.
Dupuis, D. J. (2007). “Using copulas in hydrology: Benefits, cautions, and issues.” J. Hydrol. Eng.JHYEFF, 12(4), 381–393.
Environmental Agency (EA). (2003). Strategy for flood risk management (2003/4-2007/8), London.
Favre, A-C., Adlouni, S., Perreault, L., Thiémonge, N., and Bobée, B. (2004). “Multivariate hydrological frequency analysis using copulas.” Water Resour. Res.WRERAQ, 40(1), W01101.
Fisher, N. I. (1993). Statistical analysis of circular data, Cambridge University Press, Cambridge, UK.
Genest, C., and Segers, J. (2009). “Rank-based inference for bivariate extreme-value copulas.” Ann. Stat.ASTSC7, 37(5B), 2990–3022.
Grimaldi, S., and Serinaldi, F. (2006a). “Design hyetographs analysis with 3-copula function.” Hydrol. Sci. J.HSJODN, 51(2), 223–238.
Grimaldi, S., and Serinaldi, F. (2006b). “Asymmetric copula in multivariate flood frequency analysis.” Adv. Water Resour.AWREDI, 29(8), 1155–1167.
Interagency Advisory Committee on Water Data (IACWD). (1982). “Guidelines for determining flood flow frequency: Bulletin 17b of the hydrology subcommittee.” Office of Water Data Coordination, U.S. Geological Survey, Reston, VA.
Kao, S. C., and Govindaraju, R. S. (2007). “A bivariate frequency analysis of extreme rainfall with implications for design.” J. Geophys. Res.JGREA2, 112(D1), 13119.
Kao, S. C., and Govindaraju, R. S. (2008). “Trivariate statistical analysis of extreme rainfall events via the Plackett family of copulas.” Water Resour. Res.WRERAQ, 44(2), W02415.
Kao, S., and Govindaraju, R. S. (2010). “A copula-based joint deficit index for droughts.” J. Hydrol. (Amsterdam)JHYDA7, 380(1–2), 121–134.
Karmakar, S., and Simonovic, S. P. (2009). “Bivariate flood frequency analysis. Part 2: A copula-based approach with mixed marginal distributions.” J. Flood Risk Manage., 2(1), 32–44.
Keef, C., Svensson, C., and Tawn, J. A. (2009). “Spatial dependence in extreme river flows and precipitation for Great Britain.” J. Hydrol. (Amsterdam)JHYDA7, 378(3–4), 240–252.
Kuhn, G., Khan, S., Ganguly, A. R., and Branstetter, M. L. (2007). “Geospatial temporal dependence among weekly precipitation extremes with applications to observations and climate model simulations in South America.” Adv. Water Resour.AWREDI, 30(12), 2401–2423.
Mardia, K. V. (1972). Statistics of directional data, Academic Press, London.
Ministry of Water Resources (MWR). (1993). Regulation for calculating design flood of water resources and hydropower projects, Chinese Shuili Shuidian Press, Beijing (in Chinese).
Munro, P. (1992). A Mojave dictionary, UCLA, Los Angeles.
Nazemi, A., and Elshorbagy, A. (2011). “Application of copula modeling to the performance assessment of reconstructured watersheds.” Stoch. Environ. Res. Risk Assess., 26(2), 189–205.
Nelsen, R. B. (2006). An introduction to copulas, 2nd Ed., Springer-Verlag, New York.
Otieno, B. S., and Anderson-Cook, C. M. (2006). “Measures of preferred direction for circular data for experimental and ecological data.” J. Environ. Ecol. Sci.EESTFM, 13(3), 311–324.
Poulin, A., Huard, D., Favre, A.-C., and Pugin, S. (2007). “Importance of tail dependence in bivariate frequency analysis.” J. Hydrol. Eng.JHYEFF, 12(4), 394–403.
Prohaska, S., Ilic, A., and Majkic, B. (2008). “Multiple-coincidence of flood waves on the main river and its tributaries.” IOP Conf. Series: Earth and Environmental Science, IOP Publishing, Bristol, UK.
Reed, D. (1999). The flood estimation handbook-1: Overview, Institute of Hydrology, Wallingford, UK.
Renard, B., and Lang, M. (2007). “Use of a Gaussian copula for multivariate extreme value analysis: Some case studies in hydrology.” Adv. Water Resour.AWREDI, 30(4), 897–912.
Robson, A., and Reed, D. (1999). “Flood estimation handbook.” Statistical procedure for flood frequency estimation, Institute of Hydrology, 3, Wallingford, UK.
Salvadori, G. (2004). “Bivariate return periods via 2-copulas.” Stat. Methodol., 1(1–2), 129–144.
Salvadori, G., and De Michele, C. (2004). “Frequency analysis via copulas: Theoretical aspects and applications to hydrological events.” Water Resour. Res.WRERAQ, 40(12), W12511.
Salvadori, G., and De Michele, C. (2010). “Multivariate multiparameter extreme value models and return periods: A copula approach.” Water Resour. Res.WRERAQ, 46(10), W10501.
Salvadori, G., and De Michele, C. (2011). “Estimating strategies for multiparameter multivariate extreme value copulas.” Hydrol. Earth Syst. Sci.HESSCF, 15(1), 141–150.
Salvadori, G., De Michele, C., Kottegoda, N. T., and Rosso, R. (2007). Extremes in nature: An approach using copulas, Springer, New York.
Serinaldi, F., Bonaccorso, B., Cancelliere, A., and Grimaldi, S. (2009). “Probabilistic characterization of drought properties through copulas.” Phys. Chem. EarthPCEAAV, 34(10–12), 596–605.
Serinaldi, F., and Grimaldi, S. (2007). “Fully nested 3-copula: Procedure and application on hydrological data.” J. Hydrol. Eng.JHYEFF, 12(4), 420–430.
Shiau, J. T. (2006). “Fitting drought duration and severity with two-dimensional copulas.” Water Resour. Manage.WRMAEJ, 20(5), 795–815.
Shiau, J. T., Wang, H. Y., and Chang, T. T. (2006). “Bivariate frequency analysis of floods using copulas.” J. Am. Water Resour. Assoc.JWRAF5, 42(6), 1549–1564.
Singh, V. P., Rajagopal, A. K., and Singh, K. (1986). “Derivation of some frequency distributions using the principle of maximum entropy (POME).” Adv. Water Resour.AWREDI, 9(2), 91–106.
Singh, V. P., and Zhang, L. (2007). “IDF curves using the frank Archimedean copula.” J. Hydrol. Eng., 12(6), 651–662.
Sklar, A. (1959). Fonctions de répartition à n dimensions et leursmarges, Publications del’Institut de Statistique de l’Université de, Paris, 8, 229–231 (in French).
Song, S., and Singh, V. P. (2010a). “Meta-elliptical copulas for drought frequency analysis of periodic hydrologic data.” Stoch. Environ. Res. Risk Assess., 24(3), 425–444.
Song, S., and Singh, V. P. (2010b). “Frequency analysis of droughts using the plackett copula and parameter estimation by genetic algorithm.” Stoch. Environ. Res. Risk Assess., 24(5), 783–805.
U.S. Geological Survey (USGS). (2011). “National hydrography dataset high-resolution flowline data.” The National Map, Denver, CO.
Wang, C., Chang, N. B., and Yeh, G. T. (2009). “Copula-based flood frequency (COFF) analysis at the confluences of river systems.” Hydrol. ProcessesHYPRE3, E23(10), 1471–1486.
Xiao, Y., Guo, S. L., Liu, P., and Fang, B. (2008). “A new design flood hydrograph method based on bivariate joint distribution.” IAHS-AISH Publications, (319), 75–82.
Xiao, Y., Guo, S. L., Liu, P., Yan, B. W., and Chen, L. (2009). “Design flood hydrograph based on multicharacteristic synthesis index method.” J. Hydrol. Eng.JHYEFF, 14(12), 1359–1364.
Yin, H. F., and Li, C. A. (2001). “Human impact on floods and flood disasters on the Yangtze River.” GeomorphologyGEMPEZ, 41(2–3), 105–109.
Zhang, L., and Singh, V. P. (2006). “Bivariate flood frequency analysis using the copula method.” J. Hydrol. Eng.JHYEFF, 11(2), 150–164.
Zhang, L., and Singh, V. P. (2007a). “Gumbel Hougaard copula for trivariate rainfall frequency analysis.” J. Hydrol. Eng.JHYEFF, 12(4), 409–419.
Zhang, L., and Singh, V. P. (2007b). “Bivariate rainfall frequency distributions using Archimedean copulas.” J. Hydrol. (Amsterdam)JHYDA7, 332(1–2), 93–109.
Zhang, L., and Singh, V. P. (2007c). “Trivariate flood frequency analysis using the Gumbel–Hougaard copula.” J. Hydrol. Eng.JHYEFF, 12(4), 431–439.

Information & Authors

Information

Published In

Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 17Issue 6June 2012
Pages: 742 - 755

History

Received: May 13, 2011
Accepted: Sep 13, 2011
Published online: Sep 15, 2011
Published in print: Jun 1, 2012
Published ahead of production: Jun 15, 2012

Permissions

Request permissions for this article.

Authors

Affiliations

Lu Chen, S.M.ASCE [email protected]
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan Univ., Wuhan, 430072, China, Dept. of Biological & Agricultural Eng., Texas A & M Univ., College Station, TX 77843-2117 (corresponding author). E-mail: [email protected]
Vijay P. Singh, F.ASCE [email protected]
Caroline & William N. Lehrer Distinguished Chair in Water Engineering and Professor, Dept. of Biological. & Agricultural Eng. and Professor, Dept. of Civil & Environmental Eng., Texas A & M Univ., College Station, TX 77843-2117. E-mail: [email protected]
Guo Shenglian [email protected]
Professor, State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan Univ., Wuhan 430072, China. E-mail: [email protected]
Zenchao Hao
Dept. of Biological & Agricultural Eng., Texas A & M Univ., College Station, TX 77843-2117.
Tianyuan Li [email protected]
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan Univ., Wuhan, 430072, China. E-mail: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share