On the use of Standardized Precipitation Index (SPI) for drought intensity assessment
By Mallenahalli Naresh Kumar, C. S. Murthy, M. S. Sai, P. Roy. Meteorological Applications, 2009
373 citations recorded by the source corpus.
Monthly rainfall data from June to October for 39 years were used to compute Standardized Precipitation Index (SPI) values based on two parameter gamma distribution for a low rainfall and a high rainfall districts of Andhra Pradesh state, India. Comparison of SPI with actual rainfall and rainfall deviation from the mean indicated that SPI values under‐estimate the intensity of dryness/wetness when the rainfall is very low/very high, respectively. As a result, the SPI in the worst drought years of 2002 and 2006 in the low rainfall district indicated only moderate dryness instead of extreme dryness. SPI values of the high rainfall district showed slightly better stretching in both positive and negative directions, compared to that of the low rainfall district. Further, the SPI values of longer time scales (2, 3 and 4 months) showed an extended range compared to that of 1 month, but the sensitivity in drought years has not improved significantly.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/ae935e424081d18d701caf1d449d43092230d714
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Citations in the corpus
- Revisiting the probabilistic definition of drought: strengths, limitations and an agrometeorological adaptation (2012, background): “Kumar et al. (2009) also suggested that the PE3 distribution may be a better choice than the Gam distribution, on SPI calculations.”
- Temporal-Spatial Variation of Drought Indicated by SPI and SPEI in Ningxia Hui Autonomous Region, China (2015, methodology): “The SPEI follows the same classification criteria as SPI, because of the similarity in the calculation principles of SPEI and SPI [5,70–74] listed in Table 1.”
- A universal Standardized Precipitation Index candidate distribution function for observations and simulations (2020, methodology): “Nevertheless, the Lilliefors and Anderson–Darling tests are inferior to the Shapiro–Wilk test (Blain et al., 2018; Stagge et al., 2015), which in turn is unreliable to evaluate SPI normality (Naresh Kumar et al., 2009).”
- A generalized framework for deriving nonparametric standardized drought indicators (2015, background): “Analyzing Texas droughts, [43] concluded that the SPI values are quite sensitive to the choice of parametric distribution function, especially in the tail of the distribution – see also [38].”