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Eco-environmental change prediction models are important decision tools for policy makers, as they help to quantify environmental sensitivity and to understand the relationship between human activities and environmental quality. Thus, this paper aims to analyze eco-environmental changes in Monteiro County, a semi-arid zone within northeastern Brazil between 1987 and 2010, by means of satellite images, geographic information system and global positioning system techniques, topographic map, climatic data and soil maps, as well as field survey. The resulting outputs were evaluated for their ability to accurately predict the most sensitive and least sensitive areas. The results showed that land cover changes have modified the environment in general and the land degradation and low soil loss processes were identified. The mean soil loss decreased from 9.67 t ha-1 yr-1 in 1987 to 2.67 t ha-1 yr-1 in 2010, as an effect of vegetation gain and particularly the conversion of thousands of square kilometers of Tropophile caatinga middle slope and barren land into Tropophile caatinga plain and Tropophile caatinga high strand. Thus, this study provides insight on territorial ordering and management of environmental services with a regional perspective. [ABSTRACT FROM AUTHOR]

A Soil and Water Assessment Tool (SWAT) model was used to model streamflow in a tropical humid basin in the Cerrado biome, southeastern Brazil. This study was undertaken in the Upper São Francisco River basin, because this basin requires effective management of water resources in drought and high-flow periods. The SWAT model was calibrated for the period of 1978-1998 and validated for 1999-2007. To assess the model calibration and uncertainty, four indices were used: (a) coefficient of determination (R2); (b) Nash-Sutcliffe efficiency (NS); (c) p-factor, the percentage of data bracketed by the 95% prediction uncertainty (95PPU); and (d) r-factor, the ratio of average thickness of the 95PPU band to the standard deviation of the corresponding measured variable. In this paper, average monthly streamflow from three gauges (Porto das Andorinhas, Pari and Ponte da Taquara) were used. The results indicated that the R2 values were 0.73, 0.80 and 0.76 and that the NS values were 0.68, 0.79 and 0.73, respectively, during the calibration. The validation also indicated an acceptable performance with R2 = 0.80, 0.76, 0.60 and NS= 0.61, 0.64 and 0.58, respectively. This study demonstrates that the SWAT model provides a satisfactory tool to assess basin streamflow and management in Brazil. [ABSTRACT FROM AUTHOR]

Given the increasing occurrence of landslides on the East Coast Northeast of Brazil (ECNEB), it is essential to understand its conditions and triggering factors because meteorological anomalies triggered by a landslide will threaten life and property in the region. In this sense, this research aimed to diagnose the meteorological conditions that triggered landslides in the ECNEB in May 2017, evaluate the terrain's intrinsic conditions using elevation, slope, and susceptibility parameters and determine critical precipitation thresholds for the city with the highest number of landslide risk areas in the region. A dynamic downscaling experiment was carried out using the Regional Climate Model (RegCM) to verify the ability of this model to represent rainfall over the ECNEB. The results from the intrinsic factors showed that the ECNEB is highly susceptible to landslides with various high-risk sectors for landslides to the population. The extreme rainfall event was associated with the convergence of humidity at low levels over the ocean, which contributed to landslides in the ECNEB, mainly in the State of Pernambuco, where 67 landslides were registered. The RegCM numerical simulation underestimated the high daily rainfall signal seen on the Tropical Rainfall Measuring Mission satellite. It is suggested that sensitivity tests can be performed using other physical parameters to find the best model configuration for the ECNEB. This work recommends that exploring the relationship between precipitation and landslides will provide objective criteria for assessing risk areas by contributing to the predictability of disasters in this region. [ABSTRACT FROM AUTHOR]