Water Harvesting Research

Current Issue

By Issue

By Author

By Subject

Author Index

Keyword Index

About Journal

Aims and Scope

Editorial Board

Indexing and Abstracting

Related Links

FAQ

Peer Review Process

Journal Metrics

News

Publication Ethics

Self-Archiving Policy

Terms and conditions for submitting an article

Instructions for Authors

Forms and Templates

Frequency Analysis and Joint Simulation of Qualitative Variables of River Flow Using Copula Functions

Document Type : Research Paper

Authors

1 Department of Civil Engineering, Saba Institute of Higher Education, Urmia, Iran

2 Urmia university

3 Department of Water Engineering, Shahrekord University, Shahrekord, Iran

Abstract

In this study, in order to analyze the frequency of surface water quality variables (EC-Cl and EC-SO4) and to simulate the dependent variables, the applicability of copula-based functions was addressed. Since meteorological and hydrological variables are dependent on other variables in their surroundings, their analysis using single variable models is not able to estimate the desired results. In this regard, EC, Cl and SO4 data were used in the period of 1971-2017 at Bitas, Gardeyagoub and Kotar stations in the Mahabadchai sub-basin in the south of Lake Urmia. By choosing log logistic, generalized extreme values and also log normal marginal functions, the superior copulas regarding the mentioned pair-variables were investigated. While confirming the accepted correlation between the investigated pair-variables in Bitas stations (EC-Cl=0.39 and EC-SO4=0.38), Gardeyagoub (EC-Cl=0.81 and EC-SO4=0.78) and Kotar (EC-Cl= 0.54 and EC-SO4=0.51) and also based on RMSE, MAE and NSE criteria, Galambos copula was chosen as the best copula in all stations. The joint analysis of the mentioned pair-variables using the Galambos copula led to the presentation of typical curves regarding the estimation of Cl and SO4 values corresponding to the specific EC unit with different probabilities in the studied stations. Given that the presented curves are based on the statistical distribution of data, they are specific to the studied station.

Keywords

Main Subjects

References
Abdi, A., Hassanzadeh, Y., Talatahari, S., Fakheri-Fard, A., & Mirabbasi, R. (2017). Regional bivariate modeling of droughts using L-comoments and copulas. Stochastic Environmental Research and Risk Assessment, 31(5), 1199-1210.
Bárdossy, A. (2006). Copula‐based geostatistical models for groundwater quality parameters. Water Resources Research, 42(11).
Chen, L., Singh, V. P., Shenglian, G., Hao, Z., & Li, T. (2011). Flood coincidence risk analysis using multivariate copula functions. Journal of Hydrologic Engineering, 17(6), 742-755.
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(1), 50-57.
De Michele, C., Salvadori, G., Passoni, G., & Vezzoli, R. (2007). A multivariate model of sea storms using copulas. Coastal Engineering, 54(10), 734-751.
Favre, A. C., El Adlouni, S., Perreault, L., Thiémonge, N., & Bobée, B. (2004). Multivariate hydrological frequency analysis using copulas. Water resources research, 40(1).
Genest, C., Favre, A. C., Béliveau, J., & Jacques, C. (2007). Metaelliptical copulas and their use in frequency analysis of multivariate hydrological data. Water Resources Research, 43(9).
Kao, S. C., & Govindaraju, R. S. (2008). Trivariate statistical analysis of extreme rainfall events via the Plackett family of copulas. Water Resources Research, 44(2).
Mirabbasi, R., Anagnostou, E. N., Fakheri-Fard, A., Dinpashoh, Y., & Eslamian, S. (2013). Analysis of meteorological drought in northwest Iran using the Joint Deficit Index. Journal of Hydrology, 492, 35-48.
Mirakbari, M., Ganji, A., & Fallah, S. R. (2010). Regional bivariate frequency analysis of meteorological droughts. Journal of Hydrologic Engineering, 15(12), 985-1000.
Nash, J. E., & Sutcliffe, J. V. (1970). River flow forecasting through conceptual models part I—A discussion of principles. Journal of hydrology, 10(3), 282-290.
Nazeri Tahroudi, M., Khashei Siuki, A., & Ramezani, Y. (2019). Redesigning and monitoring groundwater quality and quantity networks by using the entropy theory. Environmental monitoring and assessment, 191(4), 1-17.
Nazeri Tahroudi, M., Ramezani, Y., De Michele, C., & Mirabbasi, R. (2022). Multivariate analysis of rainfall and its deficiency signatures using vine copulas. International Journal of Climatology, 42(4), 2005-2018.
Nelsen, R. B. (2006). Archimedean Copulas. An Introduction to Copulas, 109-155.
Pronoos Sedighi, M., Ramezani, Y., Nazeri Tahroudi, M. and Taghian, M., 2022. Joint frequency analysis of river flow rate and suspended sediment load using conditional density of copula functions. Acta Geophysica, pp.1-13.
Salvadori, G., & De Michele, C. (2004). Frequency analysis via copulas: Theoretical aspects and applications to hydrological events. Water resources research, 40(12).
Khashei, A., Shahidi, A., Nazeri-Tahroudi, M., & Ramezani, Y. (2022). Bivariate simulation and joint analysis of reference evapotranspiration using copula functions. Iranian Journal of Irrigation & Drainage, 16(3), 639-656.
Salvadori, G., & De Michele, C. (2006). Statistical characterization of temporal structure of storms. Advances in Water Resources, 29(6), 827-842.
Salvadori, G., & De Michele, C. (2010). Multivariate multiparameter extreme value models and return periods: A copula approach. Water resources research, 46(10).
Sklar, M. (1959). Fonctions de repartition an dimensions et leurs marges. Publ. inst. statist. univ. Paris, 8, 229-231.
Tahroudi, M. N., Ramezani, Y., De Michele, C., & Mirabbasi, R. (2020). Analyzing the conditional behavior of rainfall deficiency and groundwater level deficiency signatures by using copula functions. Hydrology Research, 51(6), 1332-1348.
Water Harvesting Research
Volume 5, Issue 1 - Serial Number 7
January 2022
Pages 131-143
Files
Share
How to cite
Statistics