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Due to the lack of information concerning maximum rainfall equations for most locations in Mato Grosso do Sul State, the alternative for carrying out hydraulic work projects has been information from meteorological stations closest to the location in which the project is carried out. Alternative methods, such as 24 hours rain disaggregation method from rainfall data due to greater availability of stations and longer observations can work. Based on this approach, the objective of this study was to estimate maximum rainfall equations for Mato Grosso do Sul State by adjusting the 24 hours rain disaggregation method, depending on data obtained from rain gauge stations from Dourado and Campo Grande. For this purpose, data consisting of 105 rainfall stations were used, which are available in the ANA (Water Resources Management National Agency) database. Based on the results we concluded: the intense rainfall equations obtained by pluviogram analysis showed determination coefficient above 99%; and the performance of 24 hours rain disaggregation method was classified as excellent, based on relative average error WILMOTT concordance index (1982).

How to cite: LIMA rPC, SILVA DD, PereIrA SB, MOreIrA MC, PASSOS JBMC, COeLHO CD AND eLeSBON AAA. 2019. Development of an annual drought classification system based on drought severity indexes. An Acad Bras Cienc 91:e20180188.Abstract: In order to characterize the occurrence and intensity of droughts in the Doce river Basin, as well as to develop a system for its classification, four different drought indexes were evaluated: Percent of Normal Precipitation (PNP), Deciles Method (DM), rainfall Anomaly Index (rAI) and Standardized Precipitation Index (SPI). The indices were calculated annually, based on precipitation data from 89 rainfall stations of the Brazilian National Water Agency (ANA). Nine analysis units (AUs) were determined in the basin and the Thiessen Polygons method was used to obtain the average precipitation in the respective drainage areas. The indices were calculated for each AU and then related to the drought intensity classes. An overall classification of the indices was proposed for the drought classification system for a 30-year base period, from 1985 to 2015. The most critical hydrological years of the Doce river Basin in relation to the drought were the latter being the most critical of the last 30 years. The results show that the annual drought classification system proved to be efficient in the identification of events, allowing to verify that the Doce River Basin presents a severe climatic drought condition, on average, every seven years.

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