New approach in bivariate drought duration and severity analysis

Montaseri, Majid; Amirataee, Babak; Rezaie, Hossein

doi:10.1016/j.jhydrol.2018.02.018

Cited by 50 publications

(31 citation statements)

References 49 publications

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“…His main contribution was the use of copula functions to model the complex dependence of drought characteristics. Copulas are functions capable of modeling the dependency structure flexibly by not restricting the use of the same distribution for its marginals [25][26][27][28], and many applications were applied all over the world [29][30][31][32][33][34], primarily on a punctual approach.The limitation of the punctual approach is its focus on a local region, but the occurrence of drought may cover large areas. Thus, regional analysis has proven to be more efficient for drought management than the punctual approach [35,36].…”

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confidence: 99%

Copula-Based Multivariate Frequency Analysis of the 2012–2018 Drought in Northeast Brazil

Filho

Martins

et al. 2020

Water

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The 2012–2018 drought was such an extreme event in the drought-prone area of Northeast Brazil that it triggered a discussion about proactive drought management. This paper aims at understanding the causes and consequences of this event and analyzes its frequency. A consecutive sequence of sea surface temperature anomalies in the Pacific and Atlantic Oceans, at both the decadal and interannual scales, led to this severe and persistent drought. Drought duration and severity were analyzed using run theory at the hydrographic region scale as decision-makers understand impact analysis better at this scale. Copula functions were used to properly model drought joint characteristics as they presented different marginal distributions and an asymmetric behavior. The 2012–2018 drought in Ceará State had the highest mean bivariate return period ever recorded, estimated at 240 years. Considering drought duration and severity simultaneously at the level of the hydrographic regions improves risk assessment. This result advances our understanding of exceptional events. In this sense, the present work proposes the use of this analysis as a tool for proactive drought planning.

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confidence: 99%

Copula-Based Multivariate Frequency Analysis of the 2012–2018 Drought in Northeast Brazil

Filho

Martins

et al. 2020

Water

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“…Subsequently, Genest et.al, [62] established the definition of Archimedean copula functions, which often are used in hydrological variable analysis [32,63−65]. Among the several existing Archimedean copula families, these work-tested copula functions of three families are frequently used in drought analyses (Table 1) [32,66,67]. Given that the series of S and D have a correlation (linear or nonlinear) to each other expressed by the Kendall correlation ) (τ , it is possible to estimate the parameter θ of the copula functions by the relationships shown in the third column of Table 1.…”

Section: 3bivariate Copulamentioning

confidence: 99%

Bivariate Assessment of Drought Return Periods and Frequency in Brazilian Northeast Using Joint Distribution by Copula Method

et al. 2020

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The Northeast region of Brazil (NRB) is the most populous semiarid area in the world and is extremely susceptible to droughts. The severity and duration of these droughts depend on several factors, and they do not necessarily follow the same behavior. The aim of this work is to evaluate the frequency of droughts in the NRB and calculate the return period of each drought event using the copula technique, which integrates the duration and severity of the drought in the NRB in a joint bivariate distribution. Monthly precipitation data from 96 meteorological stations spatially distributed in the NRB, ranging from 1961 to 2017, are used. The copula technique is applied to the Standardized Precipitation Index (SPI) on the three-month time scale, testing three families of Archimedean copula functions (Gumbel–Hougaard, Clayton and Frank) to reveal which model is best suited for the data. Averagely, the most frequent droughts observed in the NRB are concentrated in the northern sector of the region, with an observed duration varying from three and a half to five and a half months. However, the eastern NRB experiences the most severe droughts, lasting for 14 to 24 months. The probability distributions that perform better in modeling the series of severity and duration of droughts are exponential, normal and lognormal. The observed severity and duration values show that, for average values, the return period across the region is approximately 24 months. Still in this regard, the southernmost tip of the NRB stands out for having a return period of over 35 months. Regarding maximum observed values of severity and duration, the NRB eastern strip has the longest return period (>60 months), mainly in the southeastern portion where a return period above 90 months was observed. The northern NRB shows the shortest return period (~45 months), indicating that it is the NRB sector with the highest frequency of intense droughts. These results provide useful information for drought risk management in the NRB.

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“…The conditional probability theory associated with copulas is highly used in hydrological applications to analyze multivariate dependence [17,21,22] and can be expressed by Equation 4. Let two random variables X and Y with U 1 = F x (x), U 2 = F y (y) and u 1 and u 2 being specific values.…”

Section: Conditional Probabilitymentioning

confidence: 99%

A Continuous Drought Probability Monitoring System, CDPMS, Based on Copulas

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Portela

Studart

et al. 2019

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The standardized precipitation index (SPI), is one of the most used drought indices. However, it is difficult to use to monitor the ongoing drought characteristics because it cannot be expeditiously related to precipitation deficits. It also does not provide information regarding the drought probability nor the temporal evolution of the droughts. By assigning the SPI to drought-triggering precipitation thresholds, a copula-based continuous drought probability monitoring system (CDPMS), was developed aiming to monitor the probability of having a drought as the rainy season advances. In fact, in climates with very pronounced rainy seasonality, the absence of precipitation during the rainy season is the fundamental cause of droughts. After presenting the CDPMS, we describe its application to Mainland Portugal and demonstrate that the system has an increased capability of anticipating drought probability by the end of the rainy season as new precipitation records are collected. The good performance of the system results from the ability of the copula to model complex dependence structures as those existing between precipitations at different time intervals. CDPMS is an innovative and user-friendly tool to monitor precipitation and, consequently, the drought probability, allowing the user to anticipate mitigation and adaptation measures, or even to issue alerts.

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New approach in bivariate drought duration and severity analysis

Cited by 50 publications

References 49 publications

Copula-Based Multivariate Frequency Analysis of the 2012–2018 Drought in Northeast Brazil

Copula-Based Multivariate Frequency Analysis of the 2012–2018 Drought in Northeast Brazil

Bivariate Assessment of Drought Return Periods and Frequency in Brazilian Northeast Using Joint Distribution by Copula Method

A Continuous Drought Probability Monitoring System, CDPMS, Based on Copulas

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