Analysis of the Spatiotemporal Trends of Standardized Drought Indices in Sicily Using ERA5-Land Reanalysis Data (1950–2023)

In this study, a spatiotemporal analysis of drought occurrence and trends across Sicily using ERA50-Land continuous gridded data is carried out. We first use the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) to evaluate drought conditions at various time scales from 1950 to 2023. Then, the Modified Mann–Kendall test was employed to detect trends and Sen’s slope estimator was used to quantify their magnitude. An analysis of the historical series confirms that 2002 was the most severe drought year, impacting all time scales from short-term to long-term. The spatial analysis revealed that the western regions of Sicily experienced the highest severity and frequency of drought events. In contrast, the northeastern regions were less severely affected compared with the other parts of the island. The analysis detects significant increasing trends in SPI values in the eastern coastal areas of the island, which are related to a possible historical increase in precipitation. On the other hand, the analysis of the SPEI indicates significant decreasing trends in the western part of the island, which are mainly related to increased evapotranspiration rates. These results are partially consistent with previous analyses of future climate change scenarios, where changes in the SPEI values in the island are projected to be way clearer than changes in SPI values.

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Publication Details

Journal
Water
Published
2024-09-13
DOI
https://doi.org/10.3390/w16182593
Citations
9
Primary Topic
Hydrology and Drought Analysis
Type
article
Field-Weighted Citation Impact
2.54

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article

Analysis of the Spatiotemporal Trends of Standardized Drought Indices in Sicily Using ERA5-Land Reanalysis Data (1950–2023)

David J. Peres, Antonino Cancelliere, Tagele Mossie Aschale, Nunziarita Palazzolo et al.
9 citations
Water
Hydrology and Drought Analysis
2.54
article

Analysis of the Spatiotemporal Trends of Standardized Drought Indices in Sicily Using ERA5-Land Reanalysis Data (1950–2023)

David J. Peres, Antonino Cancelliere, Tagele Mossie Aschale, Nunziarita Palazzolo, Gaetano Buonacera
article en
9 citations

Abstract

In this study, a spatiotemporal analysis of drought occurrence and trends across Sicily using ERA50-Land continuous gridded data is carried out. We first use the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) to evaluate drought conditions at various time scales from 1950 to 2023. Then, the Modified Mann–Kendall test was employed to detect trends and Sen’s slope estimator was used to quantify their magnitude. An analysis of the historical series confirms that 2002 was the most severe drought year, impacting all time scales from short-term to long-term. The spatial analysis revealed that the western regions of Sicily experienced the highest severity and frequency of drought events. In contrast, the northeastern regions were less severely affected compared with the other parts of the island. The analysis detects significant increasing trends in SPI values in the eastern coastal areas of the island, which are related to a possible historical increase in precipitation. On the other hand, the analysis of the SPEI indicates significant decreasing trends in the western part of the island, which are mainly related to increased evapotranspiration rates. These results are partially consistent with previous analyses of future climate change scenarios, where changes in the SPEI values in the island are projected to be way clearer than changes in SPI values.

WaterVol. 16(18)
University of Catania (IT), Debre Markos University (ET)
Università di Catania
Climate action
Openalex Percentile: Top 11%
Hydrology and Drought Analysis
2.54
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Analysis of the Spatiotemporal Trends of Standardized Drought Indices in Sicily Using ERA5-Land Reanalysis Data (1950–2023) — David J. Peres, Antonino Cancelliere, et al. · Water (2024) | TGRS Research Map | TGRS