A copula-based drought assessment framework considering global simulation models
Study region: São Paulo state – Brazil. Study focus: Compound events, such as droughts and heat waves, may have severe impacts on human activities. Traditionally, they are characterized considering a univariate perspective. However, this approach may not be the most adequate to characterize such haz...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/631baabf08004ce8a31d623942131d57 |
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| Sumario: | Study region: São Paulo state – Brazil. Study focus: Compound events, such as droughts and heat waves, may have severe impacts on human activities. Traditionally, they are characterized considering a univariate perspective. However, this approach may not be the most adequate to characterize such hazards as they often result from a combination of variables interacting in space and time. Alternatively, several studies adopt the multivariate frequency analysis as it allows the consideration of concurrent drivers and their dependencies. Nevertheless, few of them evaluated this methodology in a climate change context. In view of this, this study aims to compare the uni and multivariate approaches to characterize extreme drought events considering both historical and future scenarios, using the severe water crisis experienced in the southeast region of Brazil in 2014–2015 as a study case. New hydrological insights for the region: The univariate approach can substantially underestimate the risk associated with extreme events. For future scenarios, differences between the two methodologies reached 90% of the estimated return period. Significant increasing trends were found only for temperature. Both approaches indicated that drought events will be more common and intense in the future. However, the univariate framework may misspecificate the associated risks, as it not account for the expected warming condition that may trigger or exacerbate extreme drought events. |
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