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Bivariate drought frequency curves and confidence intervals: a case study using monthly rainfall generation

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Abstract

Although water resources management practices recently use bivariate distribution functions to assess drought severity and its frequency, the lack of systematic measurements is the major hindrance in achieving quantitative results. This study aims to suggest a statistical scheme for the bivariate drought frequency analysis to provide comprehensive and consistent drought severities using observed rainfalls and their uncertainty using synthesized rainfalls. First, this study developed a multi-variate regression model to generate synthetic monthly rainfalls using climate variables as causative variables. The causative variables were generated to preserve their correlations using copula functions. This study then focused on constructing bivariate drought frequency curves using bivariate kernel functions and estimating their confidence intervals from 1,000 likely replica sets of drought frequency curves. The confidence intervals achieved in this study may be useful for making a comprehensive drought management plan through providing feasible ranges of drought severity.

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References

  • Adamowski K (1985) Nonparametric kernel estimation of flood frequencies. Water Resour Res 21(11):1585–1590

    Article  Google Scholar 

  • Bonaccorso B, Cancelliere A, Rossi G (2003) An analytical formulation of return period of drought severity. Stoch Env Res Risk Assess 17(3):157–174

    Article  Google Scholar 

  • Cancelliere A, Salas JD (2004) Drought length properties for periodic-stochastic hydrologic data. Water Resour Res 40(2):W02503

    Article  Google Scholar 

  • Chen L, Singh VP, Gui S (2011) Drought analysis based on copulas. 2011 Symposium on data-driven approaches to droughts. Purdue University, West Lafayette

    Google Scholar 

  • Chung C, Salas JD (2000) Drought occurrence probabilities and risks of dependent hydrologic processes. J Hydrol Eng 5(3):259–268

    Article  Google Scholar 

  • Delleur JW, Kavva ML (1978) Stochastic models for monthly rainfall forecasting and synthetic generation. J Appl Meteorol 17(10):1528–1536

    Article  Google Scholar 

  • Dracup JA, Lee KS, Paulson EG Jr (1980) On the definition of droughts. Water Resour Res 16(2):297–302

    Article  Google Scholar 

  • Fernandez B, Salas JD (1999) Return period and risk of hydrologic events. I: mathematical formulation. J Hydrol Eng 4(4):297–307

    Article  Google Scholar 

  • Genest C, Favre AC (2007) Everything you always wanted to know about copula modeling but were afraid to ask. J Hydrol Eng 12(4):347–368

    Article  Google Scholar 

  • Gonzalez J, Valdes JB (2003) Bivariate drought recurrence analysis using tree ring reconstructions. J Hydrol Eng 8(5):247–258

    Article  Google Scholar 

  • Kao SC, Govindaraju RS (2010) A copula-based joint deficit index for droughts. J Hydrol 380(1–2):121–134

    Article  Google Scholar 

  • Kim T-W, Valdes JB, Yoo C (2003) Nonparametric approach for estimating return periods of droughts in arid regions. J Hydrol Eng 8(5):237–246

    Article  Google Scholar 

  • Kim T-W, Valdes JB, Yoo C (2006) Nonparametric approach for bivariate drought characterization using Palmer drought index. J Hydrol Eng 11(2):134–143

    Article  CAS  Google Scholar 

  • Loaiciga H, Leipnik R (1996) Stochastic renewal model of low-flow streamflow sequences. Stochastic Hydrology and Hydraulics 10(1):65–85

    Article  Google Scholar 

  • Mirakbari M, Ganji A, Fallah S (2010) Regional bivariate frequency analysis of meteorological droughts. J Hydrol Eng 15(12):985–1000

    Article  Google Scholar 

  • Moon YI, Lall U (1994) Kernel quantile function estimator for flood frequency analysis. Water Resource Research 30(11):3095–3103

    Article  Google Scholar 

  • O’Brien RM (2007) A caution regarding rules of thumb for variance inflation factors. Qual Quant 41:673–690

    Article  Google Scholar 

  • Oliveria JDT (1975) Bivariate extremes: extensions. Bull Int Stat Inst 46(2):241–251

    Google Scholar 

  • Salas JD, Fu C, Cancelliere A, Dustin D, Bode D, Pineda A, Vincent E (2005) Characterizing the severity and risk of drought in the Poudre River, Colorado. J Water Resour Plan Manag 131(5):383–393

    Article  Google Scholar 

  • Scott DW (1992) Multivariate density estimation: theory, practice and visualization. Wiley, New York

    Book  Google Scholar 

  • Sharma A, O’Neill R (2002) A nonparametric approach for representing interannual dependence in monthly streamflow sequences. Water Resour Res 38(7): 5–1:5-10

    Google Scholar 

  • Shiau JT (2006) Fitting drought duration and severity with two-dimensional copulas. Water Resour Manage 20(5):795–815

    Article  Google Scholar 

  • Shiau JT, Shen HW (2001) Recurrence analysis of hydrologic droughts of differing severity. J Water Resour Plan Manag 127(1):30–40

    Article  Google Scholar 

  • Silverman BW (1986) Density estimation for statistics and data analysis. Chapman & Hall/CRC, London

    Google Scholar 

  • Sklar A (1959) Fonctions de repartition a n dimensions et leurs marges. Publ Inst Statist Univ Paris 8(1):11

    Google Scholar 

  • Smakhtin VU (2001) Low flow hydrology: a review. J Hydrol 240(3–4):147–186

    Article  Google Scholar 

  • Ünal N, Aksoy H, Akar T (2004) Annual and monthly rainfall data generation schemes. Stoch Env Res Risk Assess 18(4):245–257

    Article  Google Scholar 

  • Wilhite DA (2000) Drought as a natural hazard: concepts and definitions. Drought A Global Assess 1:3–18

    Google Scholar 

  • Yevjevich V (1967) Objective approach to definitions and investigations of continental hydrologic droughts. Hydrology Paper 23, Colorado State U, Fort Collins

  • Yue S, Ouarda TBMJ, Bobee B, Legendre P, Bruneau P (1999) The Gumbel mixed model for flood frequency analysis. J Hydrol 226(1–2):88–100

    Article  Google Scholar 

  • Zhang L, Singh VP (2006) Bivariate flood frequency analysis using the copula method. J Hydrol Eng 11(2):150–164

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by Grants from Korean National Research Foundation (No. 2010-0016717) and Korean National Emergency Management Agency (NEMA-11-NH-40). The authors also thank the anonymous reviewers for their constructive comments and corrections.

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Correspondence to Tae-Woong Kim.

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Yoo, J., Kim, U. & Kim, TW. Bivariate drought frequency curves and confidence intervals: a case study using monthly rainfall generation. Stoch Environ Res Risk Assess 27, 285–295 (2013). https://doi.org/10.1007/s00477-012-0588-7

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  • DOI: https://doi.org/10.1007/s00477-012-0588-7

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