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

Shiau, Jenq Tzong; Modarres, Reza

doi:10.1002/met.145

Cited by 241 publications

(149 citation statements)

References 38 publications

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“…We used copulas to link the univariate probability distributions of D and S to construct a bivariate joint distribution of D and S (Shiau and Modarres, 2009;Sklar, 1959) (step 3 in Fig. 2).…”

Section: Step 3: Estimate Copula Parametermentioning

confidence: 99%

“…Eastern Australia makes a very good case study for this kind of research as there are a wide range of climates in which data has been gathered using a consistent method by one agency. While other studies assessed the SDF characteristics at locations with the same climate in Iran (Shiau and Modarres, 2009;Shiau et al, 2012), no such investigations are known for any climatic region in Australia, for the same climate or different climates.…”

Section: Introductionmentioning

confidence: 99%

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Drought severity–duration–frequency curves: a foundation for risk assessment and planning tool for ecosystem establishment in post-mining landscapes

Halwatura

Lechner

Arnold

2015

Hydrol. Earth Syst. Sci.

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Abstract. Eastern Australia has considerable mineral and energy resources, with areas of high biodiversity value co-occurring over a broad range of agro-climatic environments. Lack of water is the primary abiotic stressor for (agro)ecosystems in many parts of eastern Australia. In the context of mined land rehabilitation quantifying the severityduration-frequency (SDF) of droughts is crucial for successful ecosystem rehabilitation to overcome challenges of early vegetation establishment and long-term ecosystem resilience.The objective of this study was to quantify the SDF of short-term and long-term drought events of 11 selected locations across a broad range of agro-climatic environments in eastern Australia by using three drought indices at different timescales: the Standardized Precipitation Index (SPI), the Reconnaissance Drought Index (RDI), and the Standardized Precipitation-Evapotranspiration Index (SPEI). Based on the indices we derived bivariate distribution functions of drought severity and duration, and estimated the recurrence intervals of drought events at different timescales. The correlation between the simple SPI and the more complex SPEI or RDI was stronger for the tropical and temperate locations than for the arid locations, indicating that SPEI or RDI can be replaced by SPI if evaporation plays a minor role for plant available water (tropics). Both short-term and long-term droughts were most severe and prolonged, and recurred most frequently in arid regions, but were relatively rare in tropical and temperate regions.Our approach is similar to intensity-duration-frequency (IDF) analyses of rainfall, which are crucial for the design of hydraulic infrastructure. In this regard, we propose to apply SDF analyses of droughts to design ecosystem components in post-mining landscapes. Together with design rainfalls, design droughts should be used to assess rehabilitation strategies and ecological management using drought recurrence intervals, thereby minimising the risk of failure of initial ecosystem establishment due to ignorance of fundamental abiotic and site-specific environmental barriers, such as flood and drought events.

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Section: Step 3: Estimate Copula Parametermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Drought severity–duration–frequency curves: a foundation for risk assessment and planning tool for ecosystem establishment in post-mining landscapes

Halwatura

Lechner

Arnold

2015

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…multivariate frequency analysis of droughts can be explored using copulas (Shiau and Shen, 2001;Shiau, 2003Shiau, , 2006Kim et al, 2006a,b;Shiau and Modarres, 2009;Wong et al, 2010). Copulas, proposed by Sklar (1959), are multivariate distribution functions that allow for the description of the dependence structure between random variables independent of their marginal behaviours (Genest and Favre, 2007;Salvadori and De Michele, 2010).…”

Section: T Pham Et Al: Assessing Drought Statistics Of Bartlett-mentioning

confidence: 99%

“…Copulas, proposed by Sklar (1959), are multivariate distribution functions that allow for the description of the dependence structure between random variables independent of their marginal behaviours (Genest and Favre, 2007;Salvadori and De Michele, 2010). These functions have already been widely used to investigate dependence structures between hydrological variables, albeit mostly in the field of rainfall and flood problems (Shiau and Modarres, 2009). …”

Section: T Pham Et Al: Assessing Drought Statistics Of Bartlett-mentioning

confidence: 99%

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An assessment of the ability of Bartlett–Lewis type of rainfall models to reproduce drought statistics

Pham

Vanhaute

Vandenberghe

et al. 2013

Hydrol. Earth Syst. Sci.

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Abstract. Of all natural disasters, the economic and environmental consequences of droughts are among the highest because of their longevity and widespread spatial extent. Because of their extreme behaviour, studying droughts generally requires long time series of historical climate data. Rainfall is a very important variable for calculating drought statistics, for quantifying historical droughts or for assessing the impact on other hydrological (e.g. water stage in rivers) or agricultural (e.g. irrigation requirements) variables. Unfortunately, time series of historical observations are often too short for such assessments. To circumvent this, one may rely on the synthetic rainfall time series from stochastic point process rainfall models, such as Bartlett-Lewis models. The present study investigates whether drought statistics are preserved when simulating rainfall with Bartlett-Lewis models. Therefore, a 105 yr 10 min rainfall time series obtained at Uccle, Belgium is used as a test case. First, drought events were identified on the basis of the Effective Drought Index (EDI), and each event was characterized by two variables, i.e. drought duration (D) and drought severity (S). As both parameters are interdependent, a multivariate distribution function, which makes use of a copula, was fitted. Based on the copula, four types of drought return periods are calculated for observed as well as simulated droughts and are used to evaluate the ability of the rainfall models to simulate drought events with the appropriate characteristics. Overall, all Bartlett-Lewis model types studied fail to preserve extreme drought statistics, which is attributed to the model structure and to the model stationarity caused by maintaining the same parameter set during the whole simulation period.

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Modeling the relationship between climate oscillations and drought by a multivariate GARCH model

Modarres¹,

Ouarda²

2014

Water Resour. Res.

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[1] Typical multivariate time series models may exhibit comovement in mean but not in variance of hydrologic and climatic variables. This paper introduces multivariate generalized autoregressive conditional heteroscedasticity (GARCH) models to capture the comovement of the variance or the conditional covariance between two hydroclimatic time series. The diagonal vectorized and Baba-Engle-Kroft-Kroner models are developed to evaluate the covariance between drought and two atmospheric circulations, Southern Oscillation Index (SOI) and North Atlantic Oscillation (NAO) time series during 1954-2000. The univariate generalized autoregressive conditional heteroscedasticity model indicates a strong persistency level in conditional variance for NAO and a moderate persistency level for SOI. The conditional variance of short-term drought index indicates low level of persistency, while the long-term index drought indicates high level of persistency in conditional variance. The estimated conditional covariance between drought and atmospheric indices is shown to be weak and negative. It is also observed that the covariance between drought and atmospheric indices is largely dependent on short-run variance of atmospheric indices rather than their long-run variance. The nonlinearity and stationarity tests show that the conditional covariances are nonlinear but stationary. However, the degree of nonlinearity is higher for the covariance between long-term drought and atmospheric indices. It is also observed that the nonlinearity of NAO is higher than that for SOI, in contrast to the stationarity which is stronger for SOI time series.

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

Cited by 241 publications

References 38 publications

Drought severity–duration–frequency curves: a foundation for risk assessment and planning tool for ecosystem establishment in post-mining landscapes

Drought severity–duration–frequency curves: a foundation for risk assessment and planning tool for ecosystem establishment in post-mining landscapes

An assessment of the ability of Bartlett–Lewis type of rainfall models to reproduce drought statistics

Modeling the relationship between climate oscillations and drought by a multivariate GARCH model

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