Aplicação dos índices de Palmer e Bhalme & Mooley na avaliação da seca no Estado do Ceará.

Abstract

Data of rainfall, air temperature, potential evapotranspiration and soil water capacity (SWC) of 67 locations for the period from 1973 to 2002 were used for characterizing the spatial and temporal of the droughts for the environmental conditions of the seven mesorregions of the Ceará state, Brazil (Northwestern, North, Metropolitan, Hinterlands, Jaguaribe, Central South and South). The potential evapotranspiration, obtained by the Hargreaves & Samani (1985) method, was used for determining the water balance and the Parmer drought severity index (PDSI) and the modified Bhalme & Mooley drought index (MBMDI) for each of the 67 locations spatially distributed in the mesorregions. For analyzing the results, the average drought index for each mesorregion was applied to the first order auto-regressive model for forecasting the monthly Palmer drought severity index (PDSI) and the Modified Bhalme & Mooley drought index (MBMDI) and also for validating and comparing these indexes thought the r, d, and c coefficients. The results showed that the PDSI, independently of the mesorregion analyzed, underestimated the frequency and intensity of droughts in Ceará state. However, it was observed that the PDSI established better the periods of extreme humidity in the state and that this drought index may also be used for monitoring the rainy events (Sansigolo, 2004). Extreme drought events were better identified by the MBMDI index which showed to be more sensible to the soil humidity changes and its good performance for identifying drought and humid periods. The PDSI identified extreme humidity events in the North mesorregion and humidity conditions approximately normal for all other except Metropolitan where the higher frequency of this index was for extreme humidity events. Also, on the average, the events of dry periods predicted by the PDSI occur with a lag of about three months in relation to those of MBMDI. During years of occurrence of El Niño the PDSI showed an higher degree of agreement in the dry events classification, particularly for the Ceará hinterlands mesorregion. Similar results were obtained with the MBMDI for state South mesorregion. Finally, the monthly values of the PDSI showed a first order autocorrelation highly significant (r2 > 0.95).