Revisiting the probabilistic definition of drought: strengths, limitations and an agrometeorological adaptation

By Gabriel Constantino Blain. 2012

47 citations recorded by the source corpus.

Drought is a slow-moving hazard that occurs in virtually all countries of the world. In the light of this, several indices have been developed to improve the detection of drought’s onset, as well as quantifying other features of this phenomenon. The Standardized Precipitation Index (SPI) is often used in order to characterize meteorological droughts. In addition, this index is largely used by Brazilian’s agricultural institutions. In order to add important information to the drought literature, this review article described a general definition of drought, evaluated it from a statistical point of view, and also described the SPI strengths and limitations. An adaptation of the SPI that aims to develop a probability-based agricultural drought index was also presented. The results obtained herein, associated with several studies carried out throughout the world, demonstrated that the SPI is not an agricultural index. It is just a mathematical approach developed to transforming skewed distributions into the Gaussian form. If this standardization cannot be achieved, the use of this index becomes meaningless. Therefore, a normality test should be used in establishing a temporal lower limit for the SPI computations. It was also verified that for periods in which the probability associated with the zero precipitation value is close to 0.5, the SPI may erroneously indicate the end of an existing drought (or a decrease in its severity) in the presence of a decrease in the actual evapotranspiration values.

Subfields: Global and Planetary Change, Soil Science

View Paper: https://www.semanticscholar.org/paper/10513895af61359b488956021635e355d6517a1e

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Citations in the corpus

Comparison between Parametric and Nonparametric Approaches for the Calculation of Two Drought Indices: SPI and SSI (2014, methodology): “Note that the precipitation is characterized by a probability mass in zero, P0; thus, its cumulative distribution function is a mixed distribution: FðxÞ ¼ P0 þ ð1 − P0ÞFðxjx > 0Þ, where Fðxjx > 0Þ is the distribution of for strictly positive values of the variable (Blain 2012).”