Abstract
Univariate and bivariate Gamma distributions are among the most widely used distributions in hydrological statistical modeling and applications. This article presents the construction of a new bivariate Gamma distribution which is generated from the functional scale parameter. The utilization of the proposed bivariate Gamma distribution for drought modeling is described by deriving the exact distribution of the inter-arrival time and the proportion of drought along with their moments, assuming that both the lengths of drought duration (X) and non-drought duration (Y) follow this bivariate Gamma distribution. The model parameters of this distribution are estimated by maximum likelihood method and an objective Bayesian analysis using Jeffreys prior and Markov Chain Monte Carlo method. These methods are applied to a real drought dataset from the State of Colorado, USA.
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References
Alley WM (1984) The Palmer Drought Severity Index: limitations and assumptions. J Clim Appl Meteorol 23:1100–1109
Blom G (1958) Statistical estimates and transformed beta-variables. Wiley, New York
Bonaccorso B, Cancelliere A, Rossi G (2003) An analytical formulation of return period of drought severity. Stoch Environ Res Risk Assess 17:157–174
Bras RL (1990) Hydrology: an introduction to hydrologic science. Addison-Wesley, Reading
Chambers J, Cleveland W, Kleiner B, Tukey P (1983) Graphical methods for data analysis. Chapman and Hall, London
Cheng KS, Hou JC, Liou JJ, Wu YC, Chiang JL (2010) Stochastic simulation of bivariate Gamma distribution: a frequency-factor based approach. Stoch Environ Res Risk Assess 25(2):107–122
Clarke RT (1980) Bivariate gamma distribution for extending annual stream flow records from precipitation: some large sample results. Water Resour Res 16:863–870
Douglas EM, Vogel RM, Kroll CN (2002) Impact of streamflow persistence on hydrologic design. J Hydrol Eng 7(3):220–227
Dupuis DJ (2010) Statistical modeling of the monthly Palmer drought severity index. J Hydrol Eng 15(10):796–808
Guerrero-Salazar P, Yevjevich V (1975) Analysis of drought characteristics by the theory of runs. Hydrology Paper Nr. 80, Colorado State University, Fort Collins
Haan CT (1977) Statistical methods in hydrology. Iowa State University Press, Ames
Hallack-Alegria M, Watkins DW Jr (2007) Annual and warm season drought Intensity–Duration–Frequency analysis for Sonora, Mexico. J Clim 20(9):1897–1909
Hao Z, Singh VP (2011) Bivariate drought analysis using entropy theory. 2011 Symposium on Data-Driven Approaches to Droughts, Paper 43. http://docs.lib.purdue.edu/ddad2011/43
Henningsen A, Toomet O (2011) maxLik: a package for maximum likelihood estimation in R. J Comput Stat 26:443–458
Hu Q, Willson GD (2000) Effects of temperature anomalies on the Palmer Drought Severity Index in the central United States. Int J Climatol 20:1899–1911
Husak JG, Michaelsen J, Funk C (2007) Use of the gamma distribution to represent monthly rainfall in Africa for drought monitoring applications. Int J Climatol 27:935–944
Johnson NL, Kotz S, Balakrishnan N (1994) Continuous univariate distributions, vol 1. Wiley, New York
Kim TW, Valdes JB, Yoo C (2006) Nonparametric approach for bivariate drought characterization using Palmer Drought Index. J Hydrol Eng 11(2):134–143
Kogan FN (1995) Droughts of the late 1980s in the United States as derived from NOAA polar-orbiting satellite data. Bull Am Meteor Soc 76:655–668
Lloyd EH (1970) Return period in the presence of persistence. J Hydrol 10(3):202–215
Loaiciga HA, Leipnik RB (2005) Correlated gamma variables in the analysis of microbial densities in water. Adv Water Resour 28:329–335
Loaicigica M, Mariño MA (1991) Recurrence interval of geophysical events. J Water Resour Plan Manag 117(3):367–382
Martin AD, Quinn KM, Park JH (2011) MCMCpack: Markov Chain Monte Carlo in R. J Stat Softw 42(9):1–21
Mishra AK, Singh VP (2010) A review of drought concepts. J Hydrol 391:202–216
Mishra AK, Singh VP (2011) Drought modeling: a review. J Hydrol 403:157–175
Nadarajah S (2007) A bivariate gamma model for drought. Water Resour Res 43:W08501. doi:10.1029/2006WR005641
Nadarajah S (2008) The bivariate F distribution with application to drought data. Statistics 42(6):535–546
Nadarajah S (2009a) A bivariate Pareto model for drought. Stoch Environ Res Risk Assess 23:811–822
Nadarajah S (2009b) A bivariate distribution with gamma and beta marginals with application to drought data. J Appl Stat 36(3):277–301
Nadarajah S, Gupta AK (2006a) Cherian’s bivariate gamma distribution as a model for drought data. Agrociencia 40:483–490
Nadarajah S, Gupta AK (2006b) Intensity-duration models based on bivariate gamma distribution. Hiroshima Math J 36:387–395
Nadarajah S, Kotz S (2006) A note on the correlated gamma distribution of Loaiciga and Leipnik. Adv Water Resour 30:1053–1055
Porporato A, Laio F, Ridolfi L, Rodriguez-Iturbe I (2001) Plants in water-controlled ecosystem: active role in hydrologic processes and response to water stress: III. Vegetation water stress. Adv Water Resour 24:725–744
Prekopa A, Szantai T (1978) New multivariate gamma distribution and its fitting to empirical stream flow data. Water Resour Res 14:19–24
Prudnikov AP, Brychkov YA, Marichev OI (1986) Integrals and series, vols 1–3. Gordon and Breach Science Publishers, Amsterdam
Shiau JT (2003) Return period of bivariate distributed hydrological events. Stoch Environ Res Risk Assess 17:42–57
Shiau J, Shen HW (2001) Recurrence analysis of hydrologic droughts of differing severity. J Water Res Plan Manag 127(1):30–40
Song SB, Singh VP (2010) Frequency analysis of droughts using the Plackett copula and parameter estimation by genetic algorithm. Stoch Environ Res Risk Assess 24:783–805
Vogel RM (1987) Reliability indices for water supply systems. J Water Resour Plan Manag 113(4):645–654
Willeke G, Hosking JRM, Wallis JR, Guttman NB (1994) The National Drought Atlas. Institute for Water Resources Rep. 94-NDS-4. U.S. Army Corps of Engineers, Fort Belvoir, VA, 587 pp
Yevjevich V (1967) An objective approach to definitions and investigations of continental hydrologic drought. Hydrol. Pap., 23, Colorado State University, Fort Collins
Yue S (2001) A bivariate gamma distribution for use in multivariate flood frequency analysis. Hydrol Process 15:1033–1045
Yue S, Ouarda TBMJ, Bobee B (2001) A review of bivariate Gamma distribution for hydrological application. J Hydrol 246:1–18
Acknowledgments
The authors are thankful to the Associate editor and the two referees for their valuable comments and suggestions which significantly helped to improve the paper. The first author is also thankful to the Higher Education Commission of Pakistan for their financial support for this project.
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Appendix
Appendix
The Fisher information matrix \( Q\left( {\hat{g}} \right) \) is given by:
Here \( \,\psi^{\prime}\left( . \right) \) is the first derivative of the Psi function (also called trigamma function).
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Mohsin, M., Gebhardt, A., Pilz, J. et al. A new bivariate Gamma distribution generated from functional scale parameter with application to drought data. Stoch Environ Res Risk Assess 27, 1039–1054 (2013). https://doi.org/10.1007/s00477-012-0641-6
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DOI: https://doi.org/10.1007/s00477-012-0641-6