2022
DOI: 10.3390/w14223668
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SPI-Based Drought Classification in Italy: Influence of Different Probability Distribution Functions

Abstract: Drought is ranked second in type of natural phenomena associated with billion dollars weather disaster during the past years. It is estimated that in EU countries the number of people affected by drought was increased by 20% over the last decades. It is widely recognized that the Standardized Precipitation Index (SPI) can effectively provide drought characteristics in time and space. The paper questions the standard approach to estimate the SPI based on the Gamma probability distribution function, assessing th… Show more

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Cited by 21 publications
(8 citation statements)
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“…In contrast, SPI stands out from PDSI and SPEI due to its simple calculation, flexibility in terms of timescales, and low data requirements (only precipitation) [12,13], which led to its recommendation by the World Meteorological Organization (WMO) as a preferred meteorological drought index [14]. The superiority of SPI indices in the evaluation of drought has been proved in different areas across the world, including South Africa, Finland, Turkey, Iran, and Italy [3,[15][16][17][18].…”
Section: Introductionmentioning
confidence: 99%
“…In contrast, SPI stands out from PDSI and SPEI due to its simple calculation, flexibility in terms of timescales, and low data requirements (only precipitation) [12,13], which led to its recommendation by the World Meteorological Organization (WMO) as a preferred meteorological drought index [14]. The superiority of SPI indices in the evaluation of drought has been proved in different areas across the world, including South Africa, Finland, Turkey, Iran, and Italy [3,[15][16][17][18].…”
Section: Introductionmentioning
confidence: 99%
“…Finally, we found the best-fitted probability distributions for annual total precipitation, streamflow and annual mean soil moisture content follow a mixture of gamma, lognormal, normal and Weibull distributions across Australia. Globally the existence of a range of distributions has also been reported by authors including for the USA and Canada (Guttman, 1999;Markovic, 1965); Europe (Lloyd-Hughes & Saunders, 2002); Japan (Yue & Hashino, 2007); Brazil (Blain, 2011); Sudan (Mohamed & Ibrahim, 2015); China (Li et al, 2020b;Wu et al, 2021) and Italy (Moccia et al, 2022) questioning the usual approach of estimating the standardised indices based on gamma distribution. Furthermore, Laimighofer & Laaha, (2022) found that choice of distribution was one of the main sources of uncertainty in estimating SPI leading to substantial errors in drought detection and classification.…”
Section: Discussionmentioning
confidence: 97%
“…Meanwhile, n represents the count of opposing rainfall occurrences during the same month within the rainy season on any given time scale. As a result, the calculated SPIs for each month within the statistical period are denoted as Z, and they are subsequently normalized [65][66][67]. Once the index is computed, the drought intensity in the SPI index is determined based on the values presented in Table 3.…”
Section: The Standardized Precipitation Index (Spi)mentioning
confidence: 99%