Improving Flood-Risk Analysis for Confluence Flooding Control Downstream Using Copula Monte Carlo Method
Publication: Journal of Hydrologic Engineering
Volume 22, Issue 8
Abstract
In this study, a Copula Monte Carlo (CMC) method was proposed to improve flood risk for confluence flooding control downstream of a reservoir. The effects of reservoir operation and joint relationships between two rivers’ streamflow were both considered in the method. The Copula function modeled the dependence between the main stream and tributary; whereas the Monte Carlo (MC) method estimated the flood risk after the reservoir routing of main-stream flood and the simulated tributary flood from the Copula function. This proposed method was applied to a case study in the confluence flooding control downstream (Jinsha and Min Rivers) of Xiluodu-Xiangjiaba reservoirs, southwest China. After the simulation, the results were compared with the current MC method. Our results indicated that with the CMC method, the downstream flood risk caused by the Min River flood was 4.32, 2.35, and 1.08% for the 0.5, 1, and 2% design floods of the Jinsha River, respectively; whereas the MC method underestimated the flood risk. The CMC method is more robust than the MC method because it can consider both the flood spatial correlations and the inside flood domain stochastic characteristics. Further, this method can provide decision support for joint operation of Xiluodu and Xiangjiaba cascaded reservoirs and flood risk planning and management.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This research was funded by the CRSRI Open Research Program (CKWV2015201/KY) and the National Natural Science Foundation of China (51679088 and 51179069).
References
AghaKouchak, A., Cheng, L., Mazdiyasni, O., and Farahmand, A. (2014). “Global warming and changes in risk of concurrent climate extremes: Insights from the 2014 California drought.” Geophys. Res. Lett., 41(24), 8847–8852.
Chebana, F., Dabo-Niang, S., and Ouarda, T. B. M. J. (2012). “Exploratory functional flood frequency analysis and outlier detection.” Water Resour. Res., 48(4), W04514.
Chen, L., Singh, V., Shenglian, G., Hao, Z., and Li, T. (2012). “Flood coincidence risk analysis using multivariate copula functions.” J. Hydrol. Eng., 742–755.
De Michele, C., and Salvadori, G. (2003). “A generalized Pareto intensity duration model of storm rainfall exploiting 2-copulas.” J. Geophys. Res., 108(D2), 1–11.
EA (Environmental Agency). (2003). “Strategy for flood risk management.” London.
Fan, Y., Huang, W., Huang, G., Li, Y., Huang, K., and Li, Z. (2016). “Hydrologic risk analysis in the Yangtze River basin through coupling Gaussian mixtures into copulas.” Adv. Water Resour., 88, 170–185.
Fan, Y. R., Huang, W. W., Huang, G. H., Huang, K., Li, Y. P., and Kong, X. M. (2015). “Bivariate hydrologic risk analysis based on a coupled entropy-copula method for the Xiangxi River in the Three Gorges Reservoir area, China.” Theor. Appl. Climatol., 125(1), 381–397.
Favre, A. C., Adlouni, S., Perreault, L., Thiémonge, N., and Bobée, B. (2004). “Multivariate hydrological frequency analysis using copulas.” Water Resour. Res., 40(1), W01101.
Frees, E. W., and Valdez, E. A. (1998). “Understanding relationships using copulas.” North Am. Actuarial J., 2(1), 1–25.
Fu, X., Wang, L. P., and Ji, C. M. (1999). “Estimating flood hazard risk rate of flood control region under flood encountering combination.” Water Resour. Power, 17(4), 23–26 (in Chinese).
Ganguli, P., and Reddy, M. J. (2013). “Probabilistic assessment of flood risks using trivariate copulas.” Theor. Appl. Climatol., 111(1–2), 341–360.
Genest, C., Rémillard, B., and Beaudoin, D. (2009). “Goodness-of-fit tests for copulas: A review and a power study.” Insur Math Econ., 44(2), 199–213.
Gringorten, I. I. (1963). “A plotting rule for extreme probability paper.” J. Geophys. Res., 68(3), 813–814.
Gumbel, E. J. (1961). “Bivariate logistic distributions.” J. Amer. Stat. Assoc., 56(294), 335–349.
Hosking, J. R. M. (1998). L-moments, Wiley, New York.
Li, Y. P., Huang, G. H., and Nie, S. L. (2008). “Inexact multistage stochastic integer programming for water resources management under uncertainty.” J. Environ. Manage., 88(1), 93–107.
Madadgar, S., and Moradkhani, H. (2011). “Drought analysis under climate change using copula.” J. Hydrol. Eng., 746–759.
Madadgar, S., and Moradkhani, H. (2013). “A Bayesian framework for probabilistic seasonal drought forecasting.” J. Hydrometeorol., 14(6), 1685–1705.
Madadgar, S., and Moradkhani, H. (2014a). “Improved Bayesian multimodeling: Integration of copulas and Bayesian model averaging.” Water Resour. Res., 50(12), 9586–9603.
Madadgar, S., and Moradkhani, H. (2014b). “Spatio-temporal drought forecasting within Bayesian networks.” J. Hydrol., 512, 134–146.
Madadgar, S., Moradkhani, H., and Garen, D. (2014). “Towards improved post-processing of hydrologic forecast ensembles.” Hydrol. Process., 28(1), 104–122.
Ming, X. D., Xu, W., Li, Y., Du, J., Liu, B. Y., and Shi, P. J. (2015). “Quantitative multi-hazard risk assessment with vulnerability surface and hazard joint return period.” Stochastics Environ. Res. Risk A, 29(1), 35–44.
MWR (Ministry of Water Resources). (1993). Regulation for calculating design flood of water resources and hydropower projects, Chinese Shuili Shuidian Press, Beijing (in Chinese).
Najafi, M. R., and Moradkhani, H. (2013). “Analysis of runoff extremes using spatial hierarchical Bayesian modeling.” Water Resour. Res., 49(10), 6656–6670.
Najafi, M. R., and Moradkhani, H. (2014). “A hierarchical Bayesian approach for the analysis of climate change impact on runoff extremes.” Hydrol. Process., 28(26), 6292–6308.
NCHRP. (2010). “Estimating joint probabilities of design coincidence flows at stream confluence.”, Washington, DC.
Nelsen, R. B. (2006). An introduction to copulas, 2nd Ed., Springer, New York.
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, U.K.
Qin, Y. Y., Ji, C. M., Zhang, Y. K., and Shi, J. (2013). “Research on the multivariate risk assessment model for the flood control area downstream.” China Rural Water and Hydropower, (10), 147–150 (in Chinese).
Raynal, J. A., and Salas, J. D. (1987). “A probabilistic model for flooding downstream of the junction of two rivers.” Hydrologic frequency modeling, V. P. Singh, ed., D. Reidel Publishing Company, Dordrecht, Netherlands, 595–602.
Salvadori, G., De Michele, C., Kottegoda, N. T., and Rosso, R. (2007). Extremes in nature: An approach using copula, Springer Science & Business Media, Berlin.
Serinaldi, F. (2015). “Dismissing return periods.” Stochastic Environ. Res. Risk Assess., 29(4), 1179–1189.
Singh, V. P., Jain, S. K., and Tyagi, A. K. (2007). Risk and reliability analysis: A handbook for civil and environmental engineers, ASCE, New York.
Sraj, M., Bezak, N., and Brilly, M. (2014). “Bivariate flood frequency analysis using the copula function: A case study of the Litija station on the Sava River.” Hydrol. Processes, 29(2), 225–238.
Stedinger, J., and Griffis, V. (2008). “Flood frequency analysis in the United States: Time to update.” J. Hydrol. Eng., 199–204.
Tan, W. Y., and Huang, S. X. (1983). “Estimate of urban flood risk of reservoir downstream.” ShuiLi Xuebao, (7), 37–40 (in Chinese).
Wang, C., Chang, N. B., and Yeh, G. T. (2009). “Copula-based flood frequency (COFF) analysis at the confluences of river systems.” Hydrol. Process., 23(10), 1471–1486.
Wang, Y. F. (1999). “Overview of the Jinsha River’s historical floods features.” Sichuan Water Conservancy, 20(3), 46–48 (in Chinese).
Xiao, T. G., and Zhao, T. Y. (2002). “Floods in the Min River.” Express water resources and hydropower information, 23(2), 29–30 (in Chinese).
Xu, H., Taylor, R. G., Kinston, D. G., Jiang, T., Thompson, J. R., and Todd, M. C. (2010). “Hydrological modeling of River Xiangxi using SWAT2005: A comparison of model parameterizations using station and gridded meteorological observations.” Quat. Int., 226(1–2), 54–59.
Yan, H. (2012). “Magnitude and frequency of floods for rural, unregulated streams of Tennessee by L-moments method.” Univ. of Arkansas, Fayetteville, AR.
Yan, H., DeChant, C. M., and Moradkhani, H. (2015). “Improving soil moisture profile prediction with the particle filter-Markov chain Monte Carlo method.” IEEE Trans. Geosci. Remote Sens., 53(11), 6134–6147.
Yan, H., and Edwards, F. (2013). “Effects of land use change on hydrologic response at a watershed scale, Arkansas.” J. Hydrol. Eng., 1779–1785.
Yan, H., and Moradkhani, H. (2014). “Bayesian model averaging for flood frequency analysis.” World Environmental and Water Resources Congress, 1886–1895.
Yan, H., and Moradkhani, H. (2015). “A regional Bayesian hierarchical model for flood frequency analysis.” Stochastics Environ. Res. Risk Assess., 29(3), 1019–1036.
Yan, H., and Moradkhani, H. (2016a). “Combined assimilation of streamflow and satellite soil moisture with the particle filter and geostatistical modeling.” Adv. Water Resour., 94, 364–378.
Yan, H., and Moradkhani, H. (2016b). “Toward more robust extreme flood prediction by Bayesian hierarchical and multimodeling.” Nat. Hazards, 81(1), 203–225.
Zhang, L., and Singh, V. (2006). “Bivariate flood frequency analysis using the copula method.” J. Hydrol. Eng., 150–164.
Zhang, Q., Xiao, M. Z., Singh, V. P., and Chen, X. H. (2013). “Copula-based risk evaluation of hydrological droughts in the East River basin, China.” Stochastics Environ. Res. Risk A, 27(6), 1397–1406.
Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 22 • Issue 8 • August 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Mar 29, 2016
Accepted: Jan 20, 2017
Published online: Apr 12, 2017
Published in print: Aug 1, 2017
Discussion open until: Sep 12, 2017
Authors
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.