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

Abstract

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).

Spatio-temporal analysis of the droughts in Cali, Colombia and their primary relationships with the El Niño-Southern Oscillation (ENSO) between 1971 and 2011

“…The station locations are illustrated in Figure 1. Among the most used drought indices during recent decades, the SPI, considered the most robust and effective index (Mckee et al, 1993;Vicente-Serrano and López-Moreno, 2005;Livada and Assimakopoulos, 2007;Vicente-Serrano et al, 2011;Guenang et al, 2014;Ionita et al, 2016;Santos et al, 2017), allows to determine the duration, magnitude and intensity of the droughts (Hayes et al, 1999), and can be calculated in different time scales to quantify various types of droughts (Wilhite et al, 2000;Ji and Peters, 2003).…”

Drought Monitoring Utility using Satellite-Based Precipitation Products over the Xiang River Basin in China

“…There are now many distinct satellite-based precipitation products available, with some of them being widely used and having large-scale coverage with high spatial and temporal resolutions, such as the National Aeronautics and Space Administration (NASA) tropical rainfall measuring mission (TRMM) multi-satellite precipitation analysis (TMPA) [15], the climate prediction center morphing (CMORPH) technique [16] and integrated multi-satellite retrievals for global precipitation measurement (IMERG) [17]. The TRMM precipitation datasets have been available since November 1997 and many researchers have proved its ability for drought monitoring [18][19][20][21][22][23][24]. For example, Zeng et al [18] evaluated the TRMM multi-satellite precipitation analysis (TMPA) in drought monitoring in Lancang River Basin.…”

Run-off–erosion modelling and water balance in the Epitácio Pessoa Dam river basin, Paraíba State in Brazil

“…In Brazil, water scarcity and sediment yield problems occur in several parts of the country, and in recent years there has been a decrease in water availability in regions that are not affected by water crises, such as the Metropolitan Region of São Paulo (Rao et al 2016). Several Brazilian municipalities have faced a decrease in rainfall since 2012, creating a complex scenario of water scarcity that has caused serious impacts on the public water supply and other water uses, such as irrigation and electric power generation (Santos et al 2017a). However, Silva et al (2013) notes that the scarcity in Brazil occurs mainly in the north-east, more precisely in the semi-arid region, which periodically faces the occurrence of annual or multi-annual droughts.…”