ABSTRACT The state of Paraná (Brazil) possesses an extensive hydrographic network comprising 11 basins, housing over 100 hydroelectric power plants of varying capacities that supply energy to different Brazilian states. Southeastern South America (SESA), where Paraná is located, represents one of the world's regions with the highest frequency of extreme precipitation events that challenge the absorption capacity of watersheds with distinct geographic, geological and hydrological characteristics. Understanding the connection between precipitation variability linked to the complexity of regional and global climate forcing mechanisms can contribute to the improvement of climate forecasting and the management of risks associated with extreme rainfall events. The primary objective of this study was to analyse precipitation variability, trends in extreme precipitation indices, and identify key oceanic regions for monitoring, thereby contributing to the incorporation of new elements in climate forecasting and regional planning, which is essential for water security. The study results indicated the absence of a homogeneous trend pattern in extreme precipitation indices across all analysed basins. The extreme indices that exhibited statistically significant trends throughout the time series were: Annual Total Precipitation (PRCPTOT) with positive trends in the Paraná I and Paraná II basins; Heavy Precipitation Days (R20) with positive trends only in the Paraná II basin; Maximum 1‐day Precipitation Accumulation (RX1day) with positive trends in the Iguaçu, Ivaí, Paraná I and III, Piquiri, Tibagi and Paranapanema/Pirapó basins. A significant finding for hydroclimatology was the identification that climate variability modulation in basins of Paraná is possibly influenced by conditions in the eastern Tropical Pacific and Tropical Atlantic, and that the Indian Ocean influence is more prominent in basins of direct and indirect tributaries of the Paraná River in the south‐central portion of the state. These constitute essential regional monitoring elements for water resource management and obtaining more reliable risk estimates aimed at mitigation strategies.
Ely et al. (Sun,) studied this question.
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