Innovative approach for geospatial drought severity classification: a case study of Paraiba state, Brazil

摘要

Trend analysis of droughts and their geospatial and temporal variability assists decision-making about water resources management around the world and decreases the harmful effects of drought that affect the entire population. This work aimed to analyze short-, medium- and long-term droughts and their trends in the Brazilian state of Paraiba from 1998 to 2015 using Tropical Rainfall Measuring Mission (TRMM) data and applying the Mann-Kendall test and Sen's slope estimator method, based on the standardized precipitation index (SPI). TRMM data were validated by comparison with data from 267 rain gauges in the region, which showed the consistency of the satellite data. Therefore, 187 monthly TRMM rainfall time series were used, each with 216months. The series were equally distributed over the entire study area. At the significance level of 0.01, a new geospatial classification of drought severity is proposed, through which it is possible to determine exactly which types of drought events affected or did not affect a given region based on the SPI and the trend of the analyzed SPI time series, which shows the situation of drought risk analysis. The results of the comparison between long- and short-term droughts indicate that the wettest regions of the state of Paraiba are strongly affected by extreme drought events and show trends with increasingly negative slopes. In this way, the proposed geospatial classification is proved to be a useful tool because it provides information about the current drought situation of a given region, simultaneously showing the trend slope with respect to short-, medium- and long-term droughts.