Nonparametric Approach for Estimating Return Periods of Droughts in Arid Regions

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

doi:10.1061/(asce)1084-0699(2003)8:5(237)

Cited by 133 publications

(93 citation statements)

References 29 publications

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“…A familiar approach to describing the relationships between drought characteristics is to use the multivariate joint distribution of these characteristics. Most such studies have focused on the relationship between drought duration and severity for meteorological and hydrological droughts separately (Shiau and Shen 2001, Kim et al 2003, Salas et al 2005, Mishra et al 2009, Serinaldi et al 2009, Cancelliere and Salas 2010, Song and Singh 2010a, 2010b. For example, Shiau and Shen (2001) formulated a methodology for frequency and risk analysis of hydrological droughts using streamflow, and obtained a theoretical derivation of the recurrence interval of hydrological droughts above a certain severity.…”

Section: Introductionmentioning

confidence: 99%

“…For example, Shiau and Shen (2001) formulated a methodology for frequency and risk analysis of hydrological droughts using streamflow, and obtained a theoretical derivation of the recurrence interval of hydrological droughts above a certain severity. Other statistical relationships, such as the nonparametric kernel estimator used by Kim et al (2003) and the alternative renewal process by Mishra et al (2009), have also been reported.…”

Section: Introductionmentioning

confidence: 99%

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Probabilistic analysis of hydrological drought characteristics using meteorological drought

Wong

Lanen

Torfs

2013

Hydrological Sciences Journal

109

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Droughts are an inevitable consequence of climate variability and are pervasive across many regions. Their effects can vary on an extensive scale, depending on the type of drought and people's vulnerability. Crucial characteristics of both hydrological (groundwater, streamflow) and meteorological (precipitation) droughts are related to their durations and severities, and these characteristics are typically correlated. While many studies have addressed the dependencies between these characteristics for either the meteorological or hydrological drought, the cross-dependence between meteorological and hydrological drought characteristics is barely investigated. The development of meteorological drought characteristics to hydrological drought characteristics is often hard to model and their connection is not definitively established. In order to better understand and explain this relationship, this study seeks to apply statistical tools and models. Drought characteristics data from areas in Europe with different climates are analysed. Two approaches of identifying related meteorological and hydrological drought are explored and compared. Classical linear correlation techniques do not provide promising results, indicating that any statistic of a hydrological drought is not a straightforward function of a preceding meteorological drought. Subsequently, the application of the concept of copulas to explore this dependence between meteorological and hydrological drought characteristics is investigated. The more comprehensive approach of copulas shows that the meteorological drought contains probability information of the successive hydrological drought.Key words hydrological drought; meteorological drought; cross-dependence; copula; correlation; bivariate distribution; forecasting Analyse probabiliste des caractéristiques de la sécheresse hydrologique utilisant la sécheresse météorologique Résumé Les sécheresses sont une conséquence inévitable de la variabilité du climat et sont omniprésentes dans de nombreuses régions. Leurs effets peuvent énormément varier, en fonction du type de la sécheresse et de la vulnérabilité des populations. Les caractéristiques essentielles des sécheresses hydrologiques (eaux souterraines, débits) et météorologiques (précipitations) sont liées à leur durée et à leur sévérité, et ces caractéristiques sont généralement corrélées. Alors que de nombreuses études ont porté sur les dépendances entre ces caractéristiques soit pour les sécheresses météorologiques soit pour les sécheresses hydrologiques, la dépendance croisée entre les caractéristiques des sécheresses météorologiques et hydrologiques a à peine été abordée. Le passage des caractéris-tiques des sécheresses météorologiques à celles des sécheresses hydrologiques est souvent difficile à modéliser et leur relation n'est pas définitivement établie. Afin de mieux comprendre et expliquer cette relation, cette étude vise à appliquer des outils statistiques et des modèles. Des données des caractéristiques de sécheresses provenant de régi...

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Probabilistic analysis of hydrological drought characteristics using meteorological drought

Wong

Lanen

Torfs

2013

Hydrological Sciences Journal

109

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“…'Magnitude' has been referred to as 'intensity' (e.g. Kim et al, 2003) or 'severity' (e.g. Dracup et al, 1980;Shiau and Shen, 2001).…”

Section: Introductionmentioning

confidence: 99%

“…Yue et al (1999) and Correira (1987) mention that flood analysis has, so far, concentrated on studying flood peaks, whereas the solution of many hydrological problems also requires knowledge of the magnitude and duration. Yevjevich (1967) and Kim et al (2003) emphasize that drought is a multivariate event characterized by its duration, magnitude, and intensity: separate analysis of such drought characteristics cannot uncover relationships among them. Various models have been proposed for the joint distribution of duration and magnitude (Krstanovic and Singh, 1987;Sackl and Bergmann, 1987;Goel et al, 1998;Yue et al, 1999;Yue, 2001;Kim et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

“…Yevjevich (1967) and Kim et al (2003) emphasize that drought is a multivariate event characterized by its duration, magnitude, and intensity: separate analysis of such drought characteristics cannot uncover relationships among them. Various models have been proposed for the joint distribution of duration and magnitude (Krstanovic and Singh, 1987;Sackl and Bergmann, 1987;Goel et al, 1998;Yue et al, 1999;Yue, 2001;Kim et al, 2003). These models use a continuous distribution for duration, but time is often considered a discrete variable (see Acreman, 1990); hence, one should use a discrete marginal for duration and a continuous marginal for magnitude.…”

Section: Introductionmentioning

confidence: 99%

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A new model for quantifying climate episodes

2005

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When long records of climate (precipitation, temperature, stream runoff, etc.) are available, either from instrumental observations or from proxy records, the objective evaluation and comparison of climatic episodes becomes necessary. Such episodes can be quantified in terms of duration (the number of time intervals, e.g. years, the process remains continuously above or below a reference level) and magnitude (the sum of all series values for a given duration). The joint distribution of duration and magnitude is represented here by a stochastic model called BEG, for 'bivariate distribution with exponential and geometric marginals'. The model is based on the theory of random sums, and its mathematical derivation confirms and extends previous empirical findings. Probability statements that can be obtained from the model are illustrated by applying it to a 2300-year dendroclimatic reconstruction of water-year precipitation for the eastern Sierra Nevada-western Great Basin. Using the Dust Bowl drought period as an example, the chance of a longer or greater drought is 8%. Conditional probabilities are much higher, i.e. a drought of that magnitude has a 62% chance of lasting for 11 years or longer, and a drought that lasts 11 years has a 46% chance of having an equal or greater magnitude. In addition, because of the bivariate model, we can estimate a 6% chance of witnessing a drought that is both longer and greater. Additional examples of model application are also provided. This type of information provides a way to place any climatic episode in a temporal perspective, and such numerical statements help with reaching science-based management and policy decisions.

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How climate seasonality modifies drought duration and deficit

et al. 2014

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Drought propagation through the terrestrial hydrological cycle is associated with a change in drought characteristics (duration and deficit), moving from precipitation via soil moisture to discharge. Here we investigate climate controls on drought propagation with a modeling experiment in 1271 virtual catchments that differ only in climate type. For these virtual catchments we studied the bivariate distribution of drought duration and standardized deficit for the variables precipitation, soil moisture, and discharge. We found that for meteorological drought (below‐normal precipitation), the bivariate distributions of drought characteristics have a linear shape in all climates and are thus not affected by seasonality in climate. Despite the linear shape of meteorological drought, soil moisture drought (below‐normal storage in the unsaturated zone) and hydrological drought (below‐normal water availability in aquifers, lakes, and/or streams) show strongly nonlinear shapes in drought characteristics in climates with a pronounced seasonal cycle in precipitation and/or temperature. These seasonality effects on drought propagation are found in monsoonal, savannah, and Mediterranean climate zones. In these regions, both soil moisture and discharge show deviating shapes in drought characteristics. The effect of seasonality on drought propagation is even stronger in cold seasonal climates (i.e., at high latitudes and altitudes), where snow accumulation during winter prevents recovery from summer hydrological drought, and deficit increases strongly with duration. This has important implications for water resources management in seasonal climates, which cannot solely rely on meteorology‐based indices as proxies for hydrological drought duration and deficit and need to include seasonal variation in both precipitation and temperature in hydrological drought forecasting.

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Nonparametric Approach for Estimating Return Periods of Droughts in Arid Regions

Cited by 133 publications

References 29 publications

Probabilistic analysis of hydrological drought characteristics using meteorological drought

Probabilistic analysis of hydrological drought characteristics using meteorological drought

A new model for quantifying climate episodes

How climate seasonality modifies drought duration and deficit

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