Case Studies
Feb 27, 2021

Copula-Based Frequency and Coincidence Risk Analysis of Floods in Tropical-Seasonal Rivers

Publication: Journal of Hydrologic Engineering
Volume 26, Issue 5

Abstract

The conventional method of univariate flood frequency analysis based solely on peak flow (Q) overlooks the influence of other characteristic flood variables, such as the accumulated volume (V) of the flood and the duration (D) of flood events. A copula-based multivariate model that represents the joint behavior of these dependent flood variables could aid in computing joint return periods of flood events in tropical, seasonal rivers of India. In connection with the potential locations of high flood risk among west-flowing rivers, multivariate flood frequency analysis was performed on the Bharatapuzha, Periyar, and Chaliyar Rivers of the state of Kerala, India. A comparison of univariate return periods with multivariate return periods reveals that the intersection of flood variables corresponding to a 20-year univariate return period yields a trivariate return period of 91  years at Bharatapuzha and 144  years at Periyar and Chaliyar. The return period by the union of such flood variables is 10  years. The choice of flood variables and their combination depend on the problem at hand. Additionally, basinwise confluence flood frequency models are built with the peak flow at each stream as the random variables show their spatial interdependencies using conditional probabilities and return periods. The copula-based flood coincidence risk model captures the temporal aspect of the co-occurrence of flood peaks in a basin’s streams. The co-occurrence of annual flood peaks between the stream pairs of the Bharatapuzha, Periyar, and Muvathapuzha basins is the highest toward the end of July with probabilities of approximately 2.2×104 (at the Kumbidi and Mankara stations), 3×104, and 1×103, respectively. A trio of copula-based multivariate flood frequency, confluence flood frequency, and flood coincidence risk models could be used to design safe and economic hydrologic infrastructure.

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Data Availability Statement

Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This work was supported by the Indian National Committee on Climate Change (INCCC), Ministry of Water Resources, Government of India, Grant No. 28/8/2016-R&D/308-336, dated February 9, 2018. The authors are grateful to the reviewers and the editor for their constructive comments, suggestions, and valuable time to improve this work.

References

Acreman, M., and J. Holden. 2013. “How wetlands affect floods.” Wetlands 33 (5): 773–786. https://doi.org/10.1007/s13157-013-0473-2.
Ayantobo, O. O., Y. Li, and S. Song. 2019. “Multivariate drought frequency analysis using four-variate symmetric and asymmetric archimedean copula functions.” Water Resour. Manage. 33 (1): 103–127. https://doi.org/10.1007/s11269-018-2090-6.
Bezak, N., M. Mikoš, and M. Šraj. 2014. “Trivariate frequency analyses of peak discharge, hydrograph volume, and suspended sediment concentration data using copulas.” Water Resour. Manage. 28 (8): 2195–2212. https://doi.org/10.1007/s11269-014-0606-2.
Bhatti, M. I., and H. Q. Do. 2019. “Recent development in copula and its applications to the energy, forestry and environmental sciences.” Int. J. Hydrogen Energy 44 (36): 19453–19473. https://doi.org/10.1016/j.ijhydene.2019.06.015.
Brunner, M. I., J. Seibert, and A.-C. Favre. 2016. “Bivariate return periods and their importance for flood peak and volume estimation.” Wiley Interdiscip. Rev.: Water 3 (6): 819–833. https://doi.org/10.1002/wat2.1173.
Chen, L., V. P. Singh, G. Shenglian, Z. Hao, and T. Li. 2012. “Flood coincidence risk analysis using multivariate copula functions.” J. Hydrol. Eng. 17 (6): 742–755. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000504.
De Michele, C., and G. Salvadori. 2007. “On the use of copulas in hydrology: Theory and practice.” J. Hydrol. Eng. 12 (4): 369–380. https://doi.org/10.1061/(ASCE)1084-0699(2007)12:4(369).
Dong, N. D., V. Agilan, and K. V. Jayakumar. 2019. “Bivariate flood frequency analysis of nonstationary flood characteristics.” J. Hydrol. Eng. 24 (4): 04019007. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001770.
Drissia, T. K., V. Jothiprakash, and A. B. Anitha. 2019. “Flood frequency analysis using L moments: A comparison between at-site and regional approach.” Water Resour. Manage. 33 (3): 1013–1037. https://doi.org/10.1007/s11269-018-2162-7.
Fang, W., S. Huang, Q. Huang, G. Huang, H. Wang, G. Leng, L. Wang, P. Li, and L. Ma. 2019. “Bivariate probabilistic quantification of drought impacts on terrestrial vegetation dynamics in mainland China.” J. Hydrol. 577 (Jun): 123980. https://doi.org/10.1016/j.jhydrol.2019.123980.
Favre, A. C., S. El Adlouni, L. Perreault, N. Thiémonge, and B. Bobée. 2004. “Multivariate hydrological frequency analysis using copulas.” Water Resour. Res. 40 (1): 1–12. https://doi.org/10.1029/2003WR002456.
Feng, Y., P. Shi, S. Qu, S. Mou, C. Chen, and F. Dong. 2020. “Nonstationary flood coincidence risk analysis using time-varying copula functions.” Sci. Rep. 10 (1): 1–12. https://doi.org/10.1038/s41598-020-60264-3.
GADM (Global Administrative Areas). 2020. “GADM maps and data.” Accessed July 1, 2020. https://gadm.org/data.html.
Ganguli, P., and M. J. Reddy. 2013. “Probabilistic assessment of flood risks using trivariate copulas.” Theor. Appl. Climatol. 111 (1–2): 341–360. https://doi.org/10.1007/s00704-012-0664-4.
Grimaldi, S., and F. Serinaldi. 2006. “Asymmetric copula in multivariate flood frequency analysis.” Adv. Water Resour. 29 (8): 1155–1167. https://doi.org/10.1016/j.advwatres.2005.09.005.
Huang, K., L. Chen, J. Zhou, J. Zhang, and V. P. Singh. 2018. “Flood hydrograph coincidence analysis for mainstream and its tributaries.” J. Hydrol. 565 (Oct): 341–353. https://doi.org/10.1016/j.jhydrol.2018.08.007.
Jarvis, A., H. I. Reuter, A. Nelson, and E. Guevara. 2008. “Hole-filled SRTM for the globe version 4.” Accessed July 1, 2020. https://cgiarcsi.community/data/srtm-90m-digital-elevation-database-v4-1/.
Jyothi, P. V., and S. Sureshkumar. 2018. “Patterns of vegetation dynamics across mild disturbance gradient in a freshwater wetland system in Southern India.” Wetlands 38 (4): 807–817. https://doi.org/10.1007/s13157-018-1031-8.
Karmakar, S., and S. P. Simonovic. 2008. “Bivariate flood frequency analysis. Part 1: Determination of marginals by parametric and nonparametric techniques.” J. Flood Risk Manage. 1 (4): 190–200. https://doi.org/10.1111/j.1753-318X.2008.00022.x.
Karmakar, S., and S. P. Simonovic. 2009. “Bivariate flood frequency analysis. Part 2: A copula-based approach with mixed marginal distributions.” J. Flood Risk Manage. 2 (1): 32–44. https://doi.org/10.1111/j.1753-318X.2009.01020.x.
Kelly, K. S., and R. Krzysztofowicz. 1997. “A bivariate meta-Gaussian density for use in hydrology.” Stochastic Hydrol. Hydraulics 11 (1): 17–31. https://doi.org/10.1007/BF02428423.
Liu, D.-F., B.-T. Xie, and H.-J. Li. 2011. “Design flood volume of the Three Gorges Dam project.” J. Hydrol. Eng. 16 (1): 71–80. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000287.
Ma, M., S. Song, L. Ren, S. Jiang, and J. Song. 2013. “Multivariate drought characteristics using trivariate Gaussian and Student t copulas.” Hydrol. Process. 27 (8): 1175–1190. https://doi.org/10.1002/hyp.8432.
Nabaei, S., A. Sharafati, Z. M. Yaseen, and S. Shahid. 2019. “Copula based assessment of meteorological drought characteristics: Regional investigation of Iran.” Agric. For. Meteorol. 276–277 (June): 107611. https://doi.org/10.1016/j.agrformet.2019.06.010.
Nelsen, R. B. 2006. An introduction to copulas. 2nd ed. New York: Springer.
Nikhil Raj, P. P., and P. A. Azeez. 2012. “Trend analysis of rainfall in Bharathapuzha River basin, Kerala, India.” Int. J. Climatol. 32 (4): 533–539. https://doi.org/10.1002/joc.2283.
Peng, Y., Y. Shi, H. Yan, K. Chen, and J. Zhang. 2019. “Coincidence risk analysis of floods using multivariate copulas: A case study of Jinsha River and Min River, China.” J. Hydrol. Eng. 24 (2): 05018030. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001744.
Rajsekhar, D., V. P. Singh, and A. K. Mishra. 2014. “Hydrologic drought Atlas for Texas.” J. Hydrol. Eng. 20 (7): 05014023. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001074.
Reddy, M. J., and P. Ganguli. 2012. “Bivariate flood frequency analysis of upper Godavari River flows using Archimedean copulas.” Water Resour. Manage. 26 (14): 3995–4018. https://doi.org/10.1007/s11269-012-0124-z.
Reddy, M. J., and P. Ganguli. 2013. “Spatio-temporal analysis and derivation of copula-based intensity-area-frequency curves for droughts in western Rajasthan (India).” Stochastic Environ. Res. Risk Assess. 27 (8): 1975–1989. https://doi.org/10.1007/s00477-013-0732-z.
Savu, C., and M. Trede. 2010. “Hierarchies of Archimedean copulas.” Quant. Finance 10 (3): 295–304. https://doi.org/10.1080/14697680902821733.
Schumann, A. H. 2011. Flood risk assessment and management: How to specify hydrological loads, their consequences and uncertainties. New York: Springer.
Schweizer, B., and A. Sklar. 1983. Probabilistic metric spaces. New York: Elsevier Science.
Serinaldi, F., and S. Grimaldi. 2007. “Fully nested 3-copula: Procedure and application on hydrological data.” J. Hydrol. Eng. 12 (4): 420–430. https://doi.org/10.1061/(ASCE)1084-0699(2007)12:4(420).
Sinclair, C. D., and M. I. Ahmad. 1988. “Location-Invariant plotting positions for PWM estimation of the parameters of the GEV distribution.” J. Hydrol. 99 (3–4): 271–279. https://doi.org/10.1016/0022-1694(88)90053-4.
Singh, O., and M. Kumar. 2013. “Flood events, fatalities and damages in India from 1978 to 2006.” Nat. Hazards 69 (3): 1815–1834. https://doi.org/10.1007/s11069-013-0781-0.
Singh, P., C. Gnanaseelan, and J. S. Chowdary. 2017. “North-east monsoon rainfall extremes over southern peninsular India and their association with El Niño.” Dyn. Atmos. Oceans 80 (Dec): 1–11. https://doi.org/10.1016/j.dynatmoce.2017.08.002.
Siraj, M., N. Bezak, and M. Brilly. 2015. “Bivariate flood frequency analysis using the copula function: A case study of the Litija station on the Sava River.” Hydrol. Process. 29 (2): 225–238. https://doi.org/10.1002/hyp.10145.
Sruthy, S., and E. V. Ramasamy. 2017. “Microplastic pollution in Vembanad Lake, Kerala, India: The first report of microplastics in the lake and estuarine sediments in India.” Environ. Pollut. 222: 315–322. https://doi.org/10.1016/j.envpol.2016.12.038.
Sudheer, K. P., S. Murty Bhallamudi, B. Narasimhan, J. Thomas, V. M. Bindhu, V. Vema, and C. Kurian. 2019. “Role of dams on the floods of August 2018 in Periyar River Basin, Kerala.” Curr. Sci. 116 (5): 780–794. https://doi.org/10.18520/cs/v116/i5/780-794.
Thomas, J., and V. Prasannakumar. 2016. “Temporal analysis of rainfall (1871-2012) and drought characteristics over a tropical monsoon-dominated State (Kerala) of India.” J. Hydrol. 534 (Mar): 266–280. https://doi.org/10.1016/j.jhydrol.2016.01.013.
Tosunoglu, F., and V. P. Singh. 2018. “Multivariate modeling of annual instantaneous maximum flows using copulas.” J. Hydrol. Eng. 23 (3): 04018003. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001644.
Uttarwar, S. B., S. D. Barma, and A. Mahesha. 2020. “Bivariate modeling of hydroclimatic variables in humid tropical coastal region using archimedean copulas.” J. Hydrol. Eng. 25 (2011): 1–18. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001981.
Vazifehkhah, S., F. Tosunoglu, and E. Kahya. 2019. “Bivariate risk analysis of droughts using a nonparametric multivariate standardized drought index and copulas.” J. Hydrol. Eng. 24 (5): 05019006. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001775.
WRIS (Water Resources Information System of India). 2020. “Web enabled Water Resources Information System.” Accessed July 1, 2020. https://indiawris.gov.in/wris/#/RiverMonitoring.
Yue, S. 1999. “Applying bivariate normal distribution to flood frequency analysis.” Water Int. 24 (3): 248–254. https://doi.org/10.1080/02508069908692168.
Yue, S. 2000. “The bivariate lognormal distribution to model a multivariate flood episode.” Hydrol. Process. 14 (14): 2575–2588. https://doi.org/10.1002/1099-1085(20001015)14:14%3C2575::AID-HYP115%3E3.0.CO;2-L.
Yue, S. 2001. “A bivariate gamma distribution for use in multivariate flood frequency analysis.” Hydrol. Process. 15 (6): 1033–1045. https://doi.org/10.1002/hyp.259.
Yue, S., T. B. M. J. Ouarda, B. Bobée, P. Legendre, and P. Bruneau. 1999. “The Gumbel mixed model for flood frequency analysis.” J. Hydrol. 226 (1–2): 88–100. https://doi.org/10.1016/S0022-1694(99)00168-7.
Zhang, J., X. Lin, and B. Guo. 2016. “Multivariate copula-based joint probability distribution of water supply and demand in irrigation district.” Water Resour. Manage. 30 (7): 2361–2375. https://doi.org/10.1007/s11269-016-1293-y.
Zhang, L., and V. P. Singh. 2006. “Bivariate flood frequency analysis using the copula method.” J. Hydrol. Eng. 11 (2): 150–164. https://doi.org/10.1061/(ASCE)1084-0699(2006)11:2(150).
Zhang, L., and V. P. Singh. 2007. “Trivariate flood frequency analysis using the Gumbel–Hougaard copula.” J. Hydrol. Eng. 12 (4): 431–439. https://doi.org/10.1061/(ASCE)1084-0699(2007)12:4(431).
Zscheischler, J., et al. 2018. “Future climate risk from compound events.” Nat. Clim. Change 8 (6): 469–477. https://doi.org/10.1038/s41558-018-0156-3.

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 26Issue 5May 2021

History

Received: Jul 15, 2020
Accepted: Nov 20, 2020
Published online: Feb 27, 2021
Published in print: May 1, 2021
Discussion open until: Jul 27, 2021

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Research Scholar, Dept. of Water Resources and Ocean Engineering, National Institute of Technology Karnataka Surathkal, Mangaluru, Karnataka 575025, India (corresponding author). ORCID: https://orcid.org/0000-0003-3344-0195. Email: [email protected]
Professor, Dept. of Water Resources and Ocean Engineering, National Institute of Technology Karnataka Surathkal, Mangaluru, Karnataka 575025, India. ORCID: https://orcid.org/0000-0002-5903-7276

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