Entropy-copula method for single-site monthly streamflow simulation

Water Resources Research

Volumn 48, Issue 6, 2012, Pages

  Hao, Z ^a   Singh, V P ^a,b  

^a Texas A and M University   (United States)

^b TEXAS A AND M UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COLORADO RIVER; CONDITIONAL DISTRIBUTION; ENTROPY METHODS; ENTROPY-BASED; INTERANNUAL; JOINT DISTRIBUTIONS; MARGINAL DISTRIBUTION; STANDARD DEVIATION; STREAMFLOW SIMULATIONS;

ENTROPY;

STREAM FLOW;

ENTROPY; HYDROLOGICAL MODELING; RIVER DISCHARGE; STREAMFLOW;

COLORADO RIVER [NORTH AMERICA];

EID: 84862564232     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/2011WR011419     Document Type: Article

References (31)

1. Bardossy, A., and J. Li (2008), Geostatistical interpolation using copulas, Water Resour. Res., 44, W07412, doi:10.1029/2007WR006115.
2. Chebana, F., and T. B. M. J. Ouarda (2009), Index flood-basedmultivariate regional frequency analysis, Water Resour. Res., 45, W10435, doi:10.1029/2008WR007490.
3. Chowdhary, H., and V. P. Singh (2010), Reducing uncertainty in estimates of frequency distribution parameters using composite likelihood approach and copula-based bivariate distributions, Water Resour. Res., 46, W11516, doi:10.1029/2009WR008490.
4. Favre, A. C., S. El Adlouni, L. Perreault, N. Thiémonge, and B. Bobée (2004), Multivariate hydrological frequency analysis using copulas, Water Resour. Res., 40, W01101, doi:10.1029/2003WR002456.
5. Genest, C., and A. C. Favre (2007), Everything you always wanted to know about copula modeling but were afraid to ask, J. Hydrol. Eng., 12(4), 347-368.
6. Genest, C., J. F. Quessy, and B. Rémillard (2006), Goodness of fit procedures for Copula models based on the probability integral transformation, Scand. J. Stat., 33(2), 337-366.
7. Genest, C., A. C. Favre, J. Béliveau, and C. Jacques (2007), Metaelliptical copulas and their use in frequency analysis of multivariate hydrological data, Water Resour. Res., 43, W09401, doi:10.1029/2006WR005275.
8. Gotovac, H., V. Cvetkovic, and R. Andricevic (2010), Significance of higher moments for complete characterization of the travel time probability density function in heterogeneous porous media using the maximum entropy principle, Water Resour. Res., 46, W05502, doi:10.1029/2009WR008220.
9. Gyasi-Agyei, Y. (2011), Copula-based daily rainfall disaggregation model, Water Resour. Res., 47, W07535, doi:10.1029/2011WR010519.
10. Hao, Z., and V. Singh (2011), Single-site monthly streamflow simulation using entropy theory, Water Resour. Res., 47, W09528, doi:10.1029/2010WR010208.
11. Jaynes, E. (1957), Information theory and statistical mechanics, Physical Review, 106(4), 620-630.
12. Joe, H. (1997), Multivariate Models and Dependence Concepts, Chapman and Hall, London.
13. Kao, S. C., and R. S. Govindaraju (2008), Trivariate statistical analysis of extreme rainfall events via the Plackett family of copulas, Water Resour. Res., 44, W02415, doi:10.1029/2007WR006261.
14. Kapur, J. (1989), Maximum-entropy Models in Science and Engineering, John Wiley and Sons, New York.
15. Kesavan, H., and J. Kapur (1992), Entropy Optimization Principles with Applications, Academic Press, New York.
16. Lee, T., and J. D. Salas (2011), Copula-based stochastic simulation of hydrological data applied to Nile River flows, Hydrol. Res., 42(4), 318-330.
17. Loucks, D., J. Stedinger, and D. Haith (1981), Water Resource Systems Planning and Analysis, Prentice-Hall, Englewood Cliffs, N.J.
18. Matz, A. (1978), Maximum likelihood parameter estimation for the quartic exponential distribution, Technometrics, 20(4), 475-484.
19. Mead, L., and N. Papanicolaou (1984), Maximum entropy in the problem of moments, J. Math. Phys, 25(8), 2404-2417.
20. Nelsen, R. B. (2006), An Introduction to Copulas, Springer, New York.
21. Prairie, J., B. Rajagopalan, T. Fulp, and E. Zagona (2006), Modified K-NN model for stochastic streamflow simulation, J. Hydrol. Eng., 11(4), 371-378.
22. Renard, B. (2011), A Bayesian hierarchical approach to regional frequency analysis, Water Resour. Res., 47, W11513, doi :10.1029/2010WR010089.
23. Salvadori, G., and C. De Michele (2004), Frequency analysis via copulas: Theoretical aspects and applications to hydrological events, Water Resour. Res., 40, W12511, doi:10.1029/2004WR003133.
24. Salvadori, G., and C. De Michele (2010), Multivariate multiparameter extreme value models and return periods: A copula approach, Water Resour. Res., 46, W10501, doi:10.1029/2009WR009040.
25. Serinaldi, F. (2009), A multisite daily rainfall generator driven by bivariate copula-based mixed distributions, J. Geophys. Res., 114, D10103, doi:10.1029/2008JD011258.
26. Shannon, C. E. (1948), A mathematical theory of communications, Bell Syst. Tech. J., 27(7), 379-423.
27. Sharma, A., and R. O'Neill (2002), A nonparametric approach for representing interannual dependence in monthly streamflow sequences, Water Resour. Res., 38(7), 1100, doi:10.1029/2001WR000953.
28. Sivakumar, B., and R. Berndtsson (2010), Advances in Data-Based Approaches for Hydrologic Modeling and Forecasting, World Sci., Hackensack, N.J.
29. Smith, J. (1993), Moment methods for decision analysis, Manage. Sci., 39(3), 340-358.
30. Trivedi, P. K., and D. M. Zimmer (2005), Copula modeling: An introduction for practitioners, Found. Trends Econometrics, 1(1), 1-111.
31. Vandenberghe, S., N. E. C. Verhoest, C. Onof, and B. De Baets (2011), A comparative copula-based bivariate frequency analysis of observed and simulated storm events: A case study on Bartlett-Lewis modeled rainfall, Water Resour. Res., 47, W07529, doi:10.1029/2009WR008388.