Drought assessment using a TRMM-derived standardized precipitation index for the upper São Francisco River basin, Brazil

• Published in: Environmental monitoring and assessment 2017-06, Vol.189 (6), p.250-250, Article 250
• Main Authors: Santos, Celso Augusto Guimarães, Brasil Neto, Reginaldo Moura, Passos, Jacqueline Sobral de Araújo, da Silva, Richarde Marques
• Format: Article
• Language: English
• Subjects: Analysis; Atmospheric precipitations; Atmospheric Protection/Air Quality Control/Air Pollution; Brazil; Classification; Drought; Droughts; Earth and Environmental Science; Ecology; Ecotoxicology; Environment; Environmental Management; Environmental Monitoring; Hydrologic data; Monitoring/Environmental Analysis; Precipitation; Rain; Rainfall; Rainfall data; Rainy season; Regions; River basins; Rivers; Rivers - chemistry; Seasons; Spatial distribution; Standardized precipitation index; Tropical climate; Tropical rainfall; Tropical Rainfall Measuring Mission (TRMM); Wet season
• ISSN: 0167-6369; 1573-2959
• DOI: 10.1007/s10661-017-5948-9

In this work, the use of Tropical Rainfall Measuring Mission (TRMM) rainfall data and the Standardized Precipitation Index (SPI) for monitoring spatial and temporal drought variabilities in the Upper São Francisco River basin is investigated. Thus, the spatiotemporal behavior of droughts and cluster regions with similar behaviors is identified. As a result, the joint analysis of clusters, dendrograms, and the spatial distribution of SPI values proved to be a powerful tool in identifying homogeneous regions. The results showed that the northeast region of the basin has the lowest rainfall indices and the southwest region has the highest rainfall depths, and that the region has well-defined dry and rainy seasons from June to August and November to January, respectively. An analysis of the drought and rain conditions showed that the studied region was homogeneous and well-distributed; however, the quantity of extreme and severe drought events in short-, medium- and long-term analysis was higher than that expected in regions with high rainfall depths, particularly in the south/southwest and southeast areas. Thus, an alternative classification is proposed to characterize the drought, which spatially categorizes the drought type (short-, medium-, and long-term) according to the analyzed drought event type (extreme, severe, moderate, and mild).