Simulation of Flood Characteristics of Ajichay RiverUsing a Multivariate Structure

Document Type : Original Article

Authors

1 Ph. D Candidate in Water Resources Engineering, Department of Water Engineering, Tabriz University., Tabriz., Iran.

2 Professor, Department of Water Engineering, Tabriz University, Tabriz, Iran

3 Associate Professor, Department of Water Engineering, Tabriz University, Tabriz, Iran

4 Assistant Professor. Department of Water Engineering, Shahre-kord University, Shahre-kord, Iran

Abstract

In this study, the first flood time series of vanyar station on Ajichay rivr was separated from base flow using local minimum method, 34 flood events were distinguished and flood event characteristics were extracted and then dependence structure between the characteristics of the flood event (peak flow, peak time, the total volume and base time of flood) diagnosed using the D-vine structure and then mentioned characteristics were simulated using the most accurate D-vine structure. To get the best D-Vine structure first structures were constructed through permuting the features of flood and then different Elliptical and Archimedean copula families were fitted on each pair-copula and the most accurate copulas were selected according to Akaike and Bayesian information criteria for each of pair-copula. In this way, the best combination of copulas was obtained for each of D-vine structures and the best structure was selected to simulate feature of flood and ultimately to evaluate the effectiveness of selected structure in the simulating of flood characteristics, the main statistics of simulated flood features were calculated and results showed that the mean and standard deviation of all simulated properties of flood were maintained well. However, the minimum, maximum and skewness of simulated features of flood in some features had been maintained well and also were preserved relatively well in some other features. Finally, the results showed that for obtaining the best D-vine structure should be performed all permuting of variables and also mentioned structure is capable in accurate simulation of flood characteristics even in short time series.

Keywords

References

شفائی،م.، فاخری­فرد،ا.، دین­پژوه،ی.، میرعباسی،ر. 1395. مدل­سازی تابع توزیع توام چهار بعدی ویژگی­های مهم سیل با استفاده از ساختار سی-واین. نشریه آبیاری و زهکشی ایران. 3.10: 327-337
Aas,K., Czado,C.,. Frigessi,A and Bakken,B. 2009. Pair-copula constructions of multiple dependence, Insurance: Mathematics and Economics 44182-198.
Bedford,T., Cooke,R. 2001. Probability density decomposition for conditionally dependent random variables modeled by vines, Ann. Math. Artif. Intel 32 245-268.
Bedford,T., Cooke,R. 2002, Vines. A new graphical model for dependent random variables, Annals of  Statistics. 30 1031-1068.
Brechmann,E.C. 2010. Truncated and simplified regular vines and their applications. Diploma thesis, Technische Universitaet Muenchen.
De Michele, C., Salvadori, G. 2003, A generalized Pareto intensity-duration model of storm rainfall exploiting 2-copulas, Journal of Geophysical Research. 108 (D2):4067:1-15.
De Michele, C., Salvadori, G., Canossi,M., Petaccia,A., Rosso,R. 2005. Bivariate statistical approach to check adequacy of dam spillway, Journal of Hydrologic Engineering. 10: 50-57.
Favre, A., Adlouni, S.E., Perreault,L., Thiemonge,N., Bobee B. 2004. Multivariate hydrological frequency analysis using copulas, Water Resources Research. 40:1-12.
 
Genest, C., Favre, A., Beliveau, J.and Jacques, J. 2007. Metaelliptical copulas and their use in frequency analysis of multivariate hydrological data, Water Resources Research. 43:1-12.
Gräler, B. 2014. Modelling skewed spatial random fields through the spatial vine copula. Spatial Statistics. 10: 87-102.
Grimaldi, S., Serinaldi, F., 2006. Design hyetograph analysis with 3-copula function. Hydrological Sciences Journal. 51.2: 223-238.
Gyasi-Agyei, Y., Melching, C. 2012. Modelling the dependence and internal structure of storm evens for continuous rainfall simulation. Journal of Hydrology. 464: 249-261.
Kao, S., Govindaraju, R. 2008. Trivariate statistical analysis of extreme rainfall events via the Plackett family of copulas. Water Resources Research. 44:1-19.
Kurowicka, D., Cooke, R. 2007. Sampling algorithms for generating joint uniform distributions using the vine-copula method. Computational Statistics and Data Analysis. 51.6: 2889-2906.
Mirabbasi,R., Fakheri-Fard,A., Dinpashoh,Y. 2012, Bivariate drought frequency analysis using the copula method, Theor Appl Climatol 108:191-206.
Mirabbasi,R., Anagnostou,EN., Fakheri-Fard,A., Dinpashoh,Y., Eslamian,S. 2013. Analysis of meteorological drought in Northwest Iran using the joint deficit index. Journal of  Hydrology. 4.92:35-48.
Salvadori,G and De Michele,C. 2004. Analytical calculation of storm volume statistics involving Pareto-like intensityduration marginal, Geophysical Research Letters, 31:1-4.
Salvadori,G., De Michele,C. 2006. Statistical characterization of temporal structure of storms, Advnces in Water Resources. 29:827-842.
Serinaldi, F and Grimaldi S. 2007. Fully nested 3-copula: procedure and application on hydrological data. Journal of Hydrologic Engineering. 12:420-430.
Shafaei,M., Fakheri-Fard,A., Dinpashoh,Y., Mirabbasi,R and De Michele,C. 2016. Modeling flood event characteristics using D-vine structures. Theoretical and Applied Climatology.1-12.
Sklar,A. 1959. Fonction de re’partition a’ n dimensions et leurs marges, vol. 8. Publications de L’Institute de Statistique, Universite’ de Paris: Paris: 229-231.
Sloto,R., Crouse,A. 1996. HYSEP: A computer program for streamflow hydrograph separation and analysis. U.S. Geological Survey, Water-Resources Investigations, Report 96-4040. Pennsylvania. 46.
Song,S., Singh,V. 2010. Meta-elliptical copulas for drought frequency analysis of periodic hydrologic data, Stochastic Environmental Research and Risk Assessment. 24: 425-444.
Vernieuwe,H., Vandenberghe,S., De Baets,B., Verhoest,N.E.C. 2015. A continuous rainfall model based on vine copulas, Hydrology and Earth System Sciences. 19.6:2685-2699.
Iranian Journal of Irrigation & Drainage
Volume 11, Issue 3
September and October 2017
Pages 471-483

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