Document Type : Research Paper

Authors

Department of Water Engineering, Shahrekord University, Shahrekord, Iran

Abstract

The purpose of this research is to joint frequency analyze of precipitation anomaly percentage as a meteorological drought index and flow rate at Chalekhmaz station located in the Zarinerood basin at south of Lake Urmia in the period of 1995-2016, which is based on the duration of the mentioned indicators. The results of the analysis of investigated copula functions in Zarinerood basin showed that, based on evaluation criteria, Frank's copula function describes well the dependence between two variables of the duration of anomaly percentage and the duration of hydrological drought. In Chalekhmaz station, the expectation of drought duration of 4 to 7 months for the hydrological variable and 9 to 12 months for the meteorological variable in the coming years is not far from reality. The results of the study of the return period of drought characteristics showed that in the case of the frequency of the stream flow drought index, the return period also increases with the increase in the severity of the drought. The joint frequency analysis of drought characteristics shows how meteorological and hydrological drought characteristics can be determined simultaneously in one station by using joint probabilities. This can provide users and researchers with very useful information related to the probable behavior of drought characteristics in order to optimally use of surface water. For the duration of a certain meteorological drought in a station, the duration of the hydrological drought in the hydrometric station can be determined based on the conditional probability of occurrence and also certain return periods.

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Main Subjects

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 Assessment31, 1199-1210.
Ahangi, G., Khalili, K., & Nazeri Tahroudi, M. (2023). Frequency analysis and joint simulation of qualitative variables of river flow using copula functions. Water Harvesting Research, 5(1): 131-143.
Chebana, F., & Ouarda, T. B. (2009). Index flood–based multivariate regional frequency analysis. Water Resources Research45(10).
Chen, L., Singh, V. P., Shenglian, G., Hao, Z., & Li, T. (2012). Flood coincidence risk analysis using multivariate copula functions. Journal of Hydrologic Engineering17(6), 742-755.
Dastourani, M., & Nazeri Tahroudi, M. (2022). Toward coupling of groundwater drawdown and pumping time in a constant discharge. Applied Water Science12(4), 74.
De Michele, C., Salvadori, G., Canossi, M., Petaccia, A., & Rosso, R. (2005). Bivariate statistical approach to check adequacy of dam spillway. Journal of Hydrologic Engineering10(1), 50-57.
Favre, A. C., El Adlouni, S., Perreault, L., Thiémonge, N., & Bobée, B. (2004). Multivariate hydrological frequency analysis using copulas. Water resources research40(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 Research43(9).
Joe, H. (1997). Multivariate models and multivariate dependence concepts. CRC Press
Kao, S. C., & Govindaraju, R. S. (2008). Trivariate statistical analysis of extreme rainfall events via the Plackett family of copulas. Water Resources Research44(2).
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 & Drainage16(3), 639-656.
Khashei‐Siuki, A., Shahidi, A., Ramezani, Y., & Nazeri Tahroudi, M. (2021). Simulation of potential evapotranspiration values based on vine copula. Meteorological Applications28(5), e2027.
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 Hydrology492, 35-48.
Mirabbasi, R., Fakheri-Fard, A., & Dinpashoh, Y. (2012). Bivariate drought frequency analysis using the copula method. Theoretical and Applied Climatology, 108(1-2), 191-206.
Mirakbari, M., Ganji, A., & Fallah, S. R. (2010). Regional bivariate frequency analysis of meteorological droughts. Journal of Hydrologic Engineering15(12), 985-1000.
Nalbantis, I., & Tsakiris, G. (2009). Assessment of hydrological drought revisited. Water resources management23, 881-897.
Nazeri Tahroudi, M., Ramezani, Y., De Michele, C., & Mirabbasi, R. (2022). Application of copula‐based approach as a new data‐driven model for downscaling the mean daily temperature. International Journal of Climatology.
Nazeri Tahroudi, M., Ramezani, Y., De Michele, C., & Mirabbasi, R. (2021). Flood routing via a copula-based approach. Hydrology Research52(6), 1294-1308.
Nazeri Tahroudi, M., Ramezani, Y., De Michele, C., & Mirabbasi, R. (2020). A new method for joint frequency analysis of modified precipitation anomaly percentage and streamflow drought index based on the conditional density of copula functions. Water Resources Management34, 4217-4231.
Pronoos Sedighi, M., Ramezani, Y., Nazeri Tahroudi, M., & Taghian, M. (2022). Joint frequency analysis of river flow rate and suspended sediment load using conditional density of copula functions. Acta Geophysica, 1-13.
Ramezani, Y., Nazeri Tahroudi, M., De Michele, C., & Mirabbasi, R. (2023). Application of copula-based and ARCH-based models in storm prediction. Theoretical and Applied Climatology, 1-17.
Salvadori, G., & De Michele, C. (2007). On the use of copulas in hydrology: theory and practice. Journal of Hydrologic Engineering12(4), 369-380.
Shiau, J. T., Wang, H. Y., & Tsai, C. T. (2006). Bivariate frequency analysis of floods using copulas1. JAWRA Journal of the American Water Resources Association42(6), 1549-1564.
Sklar, M. (1959). Fonctions de repartition an dimensions et leurs marges. Publ. inst. statist. univ. Paris8, 229-231.
Sung, J. H., Ryu, Y., & Chung, E. S. (2022). Multivariate Frequency Analysis for Streamflow Drought Having Different Time Resolution Using Archimedean Copula Functions. KSCE Journal of Civil Engineering26(4), 2013-2021.
Tabatabaei, S. M., Dastourani, M., Eslamian, S., & Nazeri Tahroudi, M. (2022). Ranking and optimizing the rain-gauge networks using the entropy–copula approach (Case study of the Siminehrood Basin, Iran). Applied Water Science12(9), 214.
Xu, P., Wang, D., Wang, Y., & Singh, V. P. (2022). A Stepwise and Dynamic C-Vine Copula–Based Approach for Nonstationary Monthly Streamflow Forecasts. Journal of Hydrologic Engineering27(1), 04021043.
Yang, X., Chen, Z., & Qin, M. (2023). Joint probability analysis of streamflow and sediment load based on hybrid copula. Environmental Science and Pollution Research, 1-14.
Zhang, D. D., Yan, D. H., Lu, F., Wang, Y. C., & Feng, J. (2015). Copula-based risk assessment of drought in Yunnan province, China. Natural Hazards75, 2199-2220.
Zhang, Q., Li, J., Singh, V. P., & Xu, C. Y. (2013). Copula‐based spatio‐temporal patterns of precipitation extremes in China. international Journal of Climatology33(5), 1140-1152.
Zhang, Q., Singh, V. P., Li, J., & Chen, X. (2011). Analysis of the periods of maximum consecutive wet days in China. Journal of Geophysical Research: Atmospheres116(D23).