Rain pattern analysis using the Standardized Precipitation Index for long-term drought characterization in Lebanon
Drought may cause losses to natural ecosystems, agriculture, and other sectors. Reliable monitoring of drought is essential for planning future mitigation measures and reducing potential impacts on different environmental and socio-economic sectors. Indicators such as the Standardized Precipitation...
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Published in: | Arabian journal of geosciences Vol. 14; no. 1 |
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Main Authors: | , , |
Format: | Journal Article |
Language: | English |
Published: |
Cham
Springer International Publishing
2021
Springer Nature B.V |
Subjects: | |
Online Access: | Get full text |
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Summary: | Drought may cause losses to natural ecosystems, agriculture, and other sectors. Reliable monitoring of drought is essential for planning future mitigation measures and reducing potential impacts on different environmental and socio-economic sectors. Indicators such as the Standardized Precipitation Index (SPI) have become essential tools for drought monitoring and analysis. In this context, monthly precipitation data for Lebanon during the period from 1926 through 2015 was analyzed using SPI at different time scales of 1, 3, 6, 9, and 12 months. When plotted over the whole study period (1926–2015), SPI-3 fall (October through December) showed neither an increase nor a decrease, while SPI-6 fall–winter (October through March) showed a sharp decrease. However, SPI-9 fall–winter–spring (October through June) showed slightly increasing trends. In addition, a slight decrease in SPI-12 values (fall–winter–spring–summer) was observed. Analyzing SPI-1, the months of December and January (i.e., months of highest precipitation) displayed decreasing trends across time, while the month of May displayed an increasing trend. These results indicated a decrease in fall and winter rain and an increase in late-in-the-season spring rain. In addition, SPI (3, 6, 9, and 12 months) experienced negative peak intensities in the range between − 1 and − 2, falling into a “very dry” classification. On the other hand, drought magnitude (DM) was negatively correlated with drought relative frequency (DRF). This indicated the association of lower DM with higher DRF. |
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ISSN: | 1866-7511 1866-7538 |
DOI: | 10.1007/s12517-020-06387-3 |