مدل‌بندی داده‌های بارش و سطح آب زیرزمینی با استفاده از توابع مفصل زمان-متغیر

[1] C. Almeida, C. Czado and H. Manner, Modeling high‐dimensional time‐varying dependence using dynamic D‐vine models, Appl. Stoch. Models Bus. Ind., 32 no. 5 (2016) 621–638.
[2] S. Amini, R. Z. Bidaki, R. Mirabbasi and M. Shafaei, Flood risk analysis based on nested copula structure in Armand Basin, Iran, Acta Geophys., 70 (2022) 1385–1399.
[3] Z. Azhdari, O. Bazrafshan, H. Zamani, M. Shekari and V. P. Singh, Hydro-meteorological drought risk assessment using linear and nonlinear multivariate methods, Physics and Chemistry of the Earth, Parts A/B/C, 123 (2021).
[4] B. L. Bowerman, R. T. O’Connell and A. B. Koehler Forecasting, time series, and regression: an applied approach, Thomson Brooks/Cole, Business & Economics, 2005, 686 pp.
[5] G. Casella and R. L. Berger, Statistical inference, Wadsworth & Brooks/Cole Advanced Books & Software, Pacific Grove, CA, 1990.
[6] H. Chowdhary, L. A. Escobar and V. P. Singh, Identification of suitable copulas for bivariate frequency analysis of flood peak and flood volume data, Hydrology Research, 1 (2011) 193–216.
[7] D. J. Dupuis, Using copulas in hydrology: Benefits, cautions, and issues, J. Hydrol. Eng., 12 no. 4 (2007) 381–393.
[8] P. Jaworski, F. Durante, W. K. Hardle and T. Rychlik, Copula theory and its applications, Berlin, Springer, 2010.
[9] C. Jiang, L. Xiong, C. Y. Xu and S. Guo, Bivariate frequency analysis of nonstationary low‐flow series based on the time‐varying copula, Hydrological Processes, 15 no. 29 (2015) 1521–1534.
[10] C. M. Hafner and H. Manner, Dynamic stochastic copula models: Estimation, inference and applications, J. Appl. Econometrics, 27 no. 2 (2012) 269–295.
[11] S. Hesarkazzazi, R. Arabzadeh, M. Hajibabaei, W. Rauch, T. R. Kjeldsen, I. Prosdocimi, A. Castellarin and R. Sitzenfrei, Stationary vs non-stationary modelling of flood frequency distribution across northwest England, Hydrological Sciences Journal, 66 no. 4 (2021) 729–474.
[12] S. C. Kao and R. S. Govindaraju, A copula-based joint deficit index for droughts, Journal of Hydrology, 380 no. 1-2 (2010) 121–134.
[13] M. J. Machado, B. A. Botero, J. López, F. Francés, A. Díez-Herrero and G. Benito, Flood frequency analysis of historical flood data under stationary and non-stationary modelling, Hydrol. Earth Syst. Sci., 19 no. 6 (2015) 2561–2576.
[14] H. Manner and O. Reznikova, A survey on time-varying copulas: specification, simulations, and application, Econometric Rev., 31 no. 6 (2012) 654-687.
[15] A. A. Pathak and B. M. Dodamani, Connection between meteorological and groundwater drought with copula-based bivariate frequency analysis, J. Hydrol. Eng., 26 no. 7 (2021) 05021015.
[16] A. J. Patton, Modelling asymmetric exchange rate dependence, Internat. Econom. Rev., 47 no. 2 (2006) 527–556.
[17] M. Rodell, I. Velicogna and J. S. Famiglietti, Satellite-based estimates of groundwater depletion in India, Nature, 460 (2009) 999–1002.

[18] A. Sklar, Random variables, joint distribution functions, and copulas, Kybernetika (Prague), 9 (1973) 449–460.
[19] D. M. Stasinopoulos and R. A. Rigby, Generalized additive models for location scale and shape (GAMLSS) in R, Journal of Statistical Software, 23 (2008) 1-46.
[20] M. Xing, D. Xu and J. He, Modeling method of failure dependent system based on time varying copula function, Vibroengineering Procedia, 21 (2017) 76-81.