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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 Paraíba 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 216 months. 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 Paraíba 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.

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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).

This study evaluates erosivity, surface runoff generation, and soil erosion rates for Mamuaba catchment, sub-catchment of Gramame River basin (Brazil) by using the ArcView Soil and Water Assessment Tool (AvSWAT) model. Calibration and validation of the model was performed on monthly basis, and it could simulate surface runoff and soil erosion to a good level of accuracy. Daily rainfall data between 1969 and 1989 from six rain gauges were used, and the monthly rainfall erosivity of each station was computed for all the studied years. In order to evaluate the calibration and validation of the model, monthly runoff data between January 1978 and April 1982 from one runoff gauge were used as well. The estimated soil loss rates were also realistic when compared to what can be observed in the field and to results from previous studies around of catchment. The long-term average soil loss was estimated at 9.4 t ha(-1) year(-1); most of the area of the catchment (60%) was predicted to suffer from a low- to moderate-erosion risk (<6 t ha(-1) year(-1)) and, in 20% of the catchment, the soil erosion was estimated to exceed > 12 t ha(-1) year(-1). Expectedly, estimated soil loss was significantly correlated with measured rainfall and simulated surface runoff. Based on the estimated soil loss rates, the catchment was divided into four priority categories (low, moderate, high and very high) for conservation intervention. The study demonstrates that the AvSWAT model provides a useful tool for soil erosion assessment from catchments and facilitates the planning for a sustainable land management in northeastern Brazil.