Aas, K., Czado, C., Frigessi, A., & Bakken, H. (2009). Pair-copula constructions of multiple dependence. Insurance: Mathematics and economics, 44(2), 182-198.
Bedford, T., & Cooke, R. (2001). Probabilistic risk analysis: foundations and methods. Cambridge University Press.
Bevacqua, E., Maraun, D., HobækHaff, I., Widmann, M., Vrac, M. (2017). Multivariate statistical modelling of compound events via pair-copula constructions: analysis of floods in Ravenna (Italy). Sciences, 21(6), 2701-2723.
Bezak, N., Rusjan, S., KramarFijavž, M., Mikoš, M., &Šraj, M. J. W. (2017). Estimation of suspended sediment loads using copula functions. Water, 9(8), 628.
Brunner, M. I., Furrer, R., & Favre, A. C. (2019). Modeling the spatial dependence of floods using the Fisher copula. Hydrology and Earth System Sciences, 23(1), 107-124.
Cooke, R. M., Kurowicka, D., & Wilson, K. (2015). Sampling, conditionalizing, counting, merging, searching regular vines. Journal of Multivariate Analysis, 138, 4-18.
Czado, C. (2019). Analyzing dependent data with vine copulas. Lecture Notes in Statistics, Springer, 222.
Dastourani, M., & Nazeri Tahroudi, M. (2022). Toward coupling of groundwater drawdown and pumping time in a constant discharge. Applied Water Science, 12(4), 1-13.
Favre, A. C., El Adlouni, S., Perreault, L., Thiémonge, N., & Bobée, B. (2004). Multivariate hydrological frequency analysis using copulas. Water Resources Research, 40(1).
Favre, A. C., Musy, A., &Morgenthaler, S. (2002). Two‐site modeling of rainfall based on the Neyman‐Scott process. Water Resources Research, 38(12), 43-1.
Gräler, B., van den Berg, M., Vandenberghe, S., Petroselli, A., Grimaldi, S., De Baets, B., & Verhoest, N. (2013). Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation. Hydrology and Earth System Sciences, 17(4), 1281-1296.
Joe, H. (1997). Multivariate models and multivariate dependence concepts: Chapman and Hall/CRC.
Kao, S. C., &Govindaraju, R. S. (2007). A bivariate frequency analysis of extreme rainfall with implications for design. Journal of Geophysical Research: Atmospheres, 112(D13).
Khalili, K., Tahoudi, M. N., Mirabbasi, R., & Ahmadi, F. (2016). Investigation of spatial and temporal variability of precipitation in Iran over the last half century. Stochastic Environmental Research and Risk Assessment, 30(4), 1205-1221.
Khan, F., Spöck, G., & Pilz, J. (2020). A novel approach for modelling pattern and spatial dependence structures between climate variables by combining mixture models with copula models. International Journal of Climatology, 40(2), 1049-1066.
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.
Kurowicka, D., & Cooke, R. M. (2007). Sampling algorithms for generating joint uniform distributions using the vine-copula method. Computational statistics & data analysis, 51(6), 2889-2906.
Li, F., & Zheng, Q. (2016). Probabilistic modelling of flood events using the entropy copula. Advances in Water Resources, 97, 233-240.
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., Ramezani, Y., De Michele, C., & Mirabbasi, R. (2022). Application of Copula Functions for Bivariate Analysis of Rainfall and River Flow Deficiencies in the Siminehrood River Basin, Iran. Journal of Hydrologic Engineering, 27(11), 05022015.
Pham, M. T., Vernieuwe, H., De Baets, B., & Verhoest, N. (2018). A coupled stochastic rainfall-evapotranspiration model for hydrological impact analysis. Hydrology and Earth System Sciences, 22(2), 1263-1283.
PronoosSedighi, 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., & Ahmadi, F. (2019). Analyzing the droughts in Iran and its eastern neighboring countries using copula functions. IDŐJÁRÁS/QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE, 123(4), 435-453.
Salvadori, G., & De Michele, C. (2007). On the use of copulas in hydrology: theory and practice. Journal of Hydrologic Engineering, 12(4), 369-380.
Sklar, M. (1959). Fonctions de repartition an dimensions et leurs marges. Publ. inst. statist. univ. Paris, 8, 229-231.
Wang, R., Zhao, C., Zhang, J., Guo, E., Li, D., Alu, S., & Dong, Z. (2019). Bivariate copula function-based spatial–temporal characteristics analysis of drought in Anhui Province, China. Meteorology and Atmospheric Physics, 131(5), 1341-1355.
Xiao, Y., Guo, S., Liu, P., & Fang, B. (2008). A new design flood hydrograph method based on bivariate joint distribution. IAHS Publications-Series of Proceedings and Reports, 319, 75-82.
Yue, S., Ouarda, T. B. M. J., & Bobée, B. (2001). A review of bivariate gamma distributions for hydrological application. Journal of Hydrology, 246(1-4), 1-18.
Zhang, D., Yan, M., & Tsopanakis, A. (2018). Financial stress relationships among Euro area countries: an R-vine copula approach. The European Journal of Finance, 24(17), 1587-1608.
Zhang, L., & Singh, V. (2006). Bivariate flood frequency analysis using the copula method. Journal of Hydrologic Engineering, 11(2), 150-164.