Nonparametric Approach for Bivariate Drought Characterization Using Palmer Drought Index

Kim, Tae‐Woong; Valdés, Juan B.; Yoo, Chulsang

doi:10.1061/(asce)1084-0699(2006)11:2(134)

Cited by 76 publications

(50 citation statements)

References 19 publications

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“…Multiple attributes of droughts have been evaluated in these studies, but significant correlation relationships are not revealed by separate consideration of correlated characteristics. Some researchers including Shiau and Shen (2001), Bonaccorso et al (2003), González and Valdés (2003), Loáiciga (2005) and Kim et al (2006aKim et al ( , 2006b, further extended the univariate analysis to explore bivariate frequency of droughts.…”

Section: Introductionmentioning

confidence: 99%

Copula‐based drought severity‐duration‐frequency analysis in Iran

Shiau

Modarres

2009

Meteorological Applications

241

133

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Drought is a complex and multi-attribute natural hazard that has worldwide effects. Defined by a commonly used standardized precipitation index (SPI), each drought event is characterized by three correlated attributes: severity, duration and frequency. A probabilistic approach is developed to establish a drought severity-duration-frequency (SDF) relationship. Copulas are employed to construct the joint distribution function of drought severity and duration. Drought frequency, in terms of recurrence interval of drought events, is then related to the copula-based distribution function via a conditional distribution function. The derived analytic drought SDF thus becomes a function of univariate distribution functions of drought severity and duration, a copula function which links the fitted univariate models, and the arrival rate of drought events. In this study, rainfall data for the period of 1954-2003 from two gauge stations in Iran, Abadan in the southwestern semi-arid region and Anzali in the north humid region, are employed as an example to illustrate the proposed approach. From the derived drought SDF, drought severity in Anzali station is greater than those in Abadan station for given drought duration and recurrence interval. The results imply that the drought severity in humid region might be more severe if high rainfall fluctuations exist in that region.

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Section: Introductionmentioning

confidence: 99%

Copula‐based drought severity‐duration‐frequency analysis in Iran

Shiau

Modarres

2009

Meteorological Applications

241

133

View full text Add to dashboard Cite

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“…González and Valdés (2003) Consider the recurrence of droughts as an alternating renewal process, presented a methodology to evaluate the bivariate drought (duration and severity) frequency and risk of the occurrence of droughts. Kim et al (2006) proposed a nonparametric kernel density estimator for bivariate return period and joint distribution of droughts based on the Palmer Drought Severity Index. Nadarajah (2007) modeled drought duration (X) and non-drought duration (Y) using a bivariate gamma distribution, and derived the exact distribution of the sum of X ?…”

Section: Introductionmentioning

confidence: 99%

Meta-elliptical copulas for drought frequency analysis of periodic hydrologic data

Song

Singh

2009

Stoch Environ Res Risk Assess

201

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This study aims to model the joint probability distribution of periodic hydrologic data using meta-elliptical copulas. Monthly precipitation data from a gauging station (410120) in Texas, US, was used to illustrate parameter estimation and goodness-of-fit for univariate drought distributions using chi-square test, Kolmogorov-Smirnov test, Cramer-von Mises statistic, Anderson-Darling statistic, modified weighted Watson statistic, and Liao and Shimokawa statistic. Pearson's classical correlation coefficient r n , Spearman's q n , Kendall's s, Chi-Plots, and K-Plots were employed to assess the dependence of drought variables. Several meta-elliptical copulas and Gumbel-Hougaard, Ali-Mikhail-Haq, Frank and Clayton copulas were tested to determine the best-fit copula. Based on the root mean square error and the Akaike information criterion, meta-Gaussian and t copulas gave a better fit. A bootstrap version based on Rosenblatt's transformation was employed to test the goodness-of-fit for meta-Gaussian and t copulas. It was found that none of meta-Gaussian and t copulas considered could be rejected at the given significance level. The metaGaussian copula was employed to model the dependence, and these results were found satisfactory.

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“…Shiau and Shen (2001) derived the joint probability density function (JPDF) of drought considering stream flow as a drought index. Gonzalez and Valdes (2003) and Kim et al (2006) investigated bivariate drought characterization using the Palmer drought severity index (PDSI).…”

Section: Introductionmentioning

confidence: 99%

Drought characterization: a probabilistic approach

Mishra

Singh

Desai

2007

Stoch Environ Res Risk Assess

192

109

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Using the alternative renewable process and run theory, this study investigates the distribution of drought interval time, mean drought interarrival time, joint probability density function and transition probabilities of drought events in the Kansabati River basin in India. The standardized precipitation index series is employed in the investigation. The time interval of SPI is found to have a significant effect of the probabilistic characteristics of drought.

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Nonparametric Approach for Bivariate Drought Characterization Using Palmer Drought Index

Cited by 76 publications

References 19 publications

Copula‐based drought severity‐duration‐frequency analysis in Iran

Copula‐based drought severity‐duration‐frequency analysis in Iran

Meta-elliptical copulas for drought frequency analysis of periodic hydrologic data

Drought characterization: a probabilistic approach

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