Estimating drought indexes from three satellite-based retrieval algorithms over the São Francisco River basin

Resumo

The prediction of droughts in the São Francisco River Basin (SFRB) plays an imperative role for
environmental and socioeconomic studies as it can provide estimates of short-, mid- and long-term water supply
in the basin. However, in smaller and more remote areas, the availability of a network of rain gauges is
compromised. Thus, satellite-based rainfall products become the only source of estimates of rainfall for much of
the regions in the SFRB, especially the more remote and underdeveloped ones. This study presents drought
indexes as calculated from estimates of rainfall from three satellite-based retrieval algorithms: TRMM,
PERSIANN and CHIRPS. Drought indexes are averaged for the whole SFRB and presented as time series for as
long as the estimates of rainfall from each algorithm spans. For this work, droughts were measured as a function
of the SPI (Standardized Precipitation Index). Estimates of SPI values indicated that 22, 18, 10 out of 252
months were from moderate to extreme droughts from TRMM, PERSIANN and CHIRPS, respectively.