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TRANSFORMING THE PALMER DROUGHT SEVERITY INDEX INTO A STANDARDIZED MULTI-SCALAR INDEX: ASSESSING THE NORMALITY ASSUMPTION UNDER SOUTH AMERICA TROPICAL-SUBTROPICAL CONDITIONS
Published online by Cambridge University Press: 17 August 2018
Summary
Two of the most common criticisms over the widely used Palmer Drought Severity Index (PDSI) is that it cannot be calculated at different time scales and it is not as spatially comparable as other Standardized Drought Indices (SDI), such as the Standardized Precipitation Index (SPI). Therefore, the hypothesis that the PDSI may be transformed into a multi-scalar index sharing the same normalized nature of others SDI has been proposed in the scientific literature. This hypothesis was extensively evaluated in this study by statistical methods largely used to assess and improve the performance of others standardized drought indices (e.g. SPI). In general terms, these methods evaluated the ability of the transformed/probability-based Palmer's Index to approach the standard normal distribution. The strategy of basing the selection of a distribution for calculating such an index on its performance within the range of typical drought and flood events was adopted. The testing region was the State of São Paulo, a tropical-subtropical region of Brazil. Time scales ranging from 1- to 12-month and Available Water Capacity equal to 50, 100 and 150 mm were also considered. A computational algorithm for calculating the new version of the Palmer's index is also provided. The Generalized Logistic distribution with parameters estimated by the maximum likelihood method is recommended to calculate the new index. The results of the normality tests are consistent with the above-mentioned strategy. From a scientific standpoint, the results support the hypothesis of this study. Therefore, we conclude that the new Standardized Palmer Drought Index (SPDI) is capable of meeting the normally assumption under tropical-subtropical climatic conditions of Brazil. In other words, the new SPDI has shown to be capable of representing floods and drought events in a similar probabilistic/normalized way. This conclusion holds true for time scales ranging from 1- to 12-month and Available Water Capacity equal to 50, 100 and 150 mm.
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- Copyright © Cambridge University Press 2018
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