Erosion process occurs naturally, shaping the Earth’s surface. Soil loss can cause harmful effects to the environment when intensive anthropic activities occur. Mathematical models have been used as effective and less costly alternatives for identifying sites highly prone to soil loss, especially at the watershed scale. In Brazil, the Revised Universal Soil Loss Equation (RUSLE) is one of the most commonly used soil loss prediction models. The RUSLE requires information on soil erodibility, rainfall erosivity, topography, land use and [...] ABSTRACT Erosion process occurs naturally, shaping the Earth’s surface. Soil loss can cause harmful effects to the environment when intensive anthropic activities occur. Mathematical models have been used as effective and less costly alternatives for identifying sites highly prone to soil loss, especially at the watershed scale. In Brazil, the Revised Universal Soil Loss Equation (RUSLE) is one of the most commonly used soil loss prediction models. The RUSLE requires information on soil erodibility, rainfall erosivity, topography, land use and

This paper describes the assessment of the SWAT hydrological model to reproduce continuous daily streamflow and simulate scenarios of forest management for a small catchment under tropical climate in Aracruz, Brazil. The main land use of the catchment consisted of eucalyptus cultivation. The SWAT parameters were calibrated and validated using daily hydrologic and meteorological data from 1997 to 2004. The statistical indices of SWAT validation (NS = 0.74, PBIAS = -14.34%, RSR = 0.51) show that SWAT performance was satisfactory in this application. Different land use and forest management scenarios were simulated with the aim of assessing their influence over the streamflow. The scenarios were: catchment under eucalyptus cultivation with three different forest managements and catchment under the native forest (Atlantic Rainforest). The scenarios simulations did not show significant changes in the long-term average streamflow. Minimum, maximum, and average annual streamflows were higher for eucalyptus scenarios compared to the native forest scenario. These results should be carefully applied to other watersheds as they reflect soil, landscape, and climate characteristics, as well as the geographic location, size, and use of water of the plantings and other vegetation.

For effective management practices and decision-making, the uncertainties associated with regional climate models (RCMs) and their scenarios need to be assessed in the context of climate change. This study analyzes long-term trends in precipitation and temperature data sets (maximum and minimum values) from the NASA, Earth Exchange Global Daily Downscaled Prediction (NEX-GDDP), under the São Francisco River Basin Representative Concentration Path (RCP) 4.5 and 8.5, using the REA (Reliable Ensemble Average) method. In each grid, the built multi-model was bias-corrected using the CMhyd software for annual, dry, wet, and pre-season periods – for historical (1961-2005) and future (2006-2100) periods. The multi-model and four different methods, namely: The Mann-Kendall, Mann-Kendall pre-brightening test, bias-corrected pre-brightening, and Spearman correlation, were used to detect trends in precipitation, and minimum and maximum temperature. In the analysis of precipitation and temperature metrics, the results for the NRMSD showed that, in general, the CSIRO model presented more satisfactory results in all physiographic regions. Person's correlation coefficient showed a better adjustment of precipitation for the MIROC5, EC.EARTH and NORESMI1 models, in areas of sub-medium and upper São Francisco. For the minimum temperature, the CSIRO and NORESMI1 models showed the best fit, in general. At maximum temperature, the EC.EARTH and CSIRO models showed more satisfactory results. With regard to trend analysis, the results indicated an increasing trend in mean annual temperature and precipitation across the basin. When analyzed by subregion, the results show an increasing trend in monthly average minimum and maximum temperatures in the middle and lower SFRB, while average monthly rainfall increases during the rainy season and preseason in Upper São Francisco. The results of this research can be used by government entities, such as Civil Defense, to subsidize decision-making that requires actions/measures to relocate people/communities to less risky locations to minimize risk or vulnerability situations for the population living nearby to the river.

The change of natural landscapes by anthropic activities is the main reason for the erosion deepening. Thus, it is necessary to know the processes that determine the hydrological balance to avoid erosion in this context. Due to the complexity of a basin and the need of making predictions, the development of mathematical models is essential for decision making. Among the existing models, the Soil and Water Assessment Tool (SWAT) is one of the most utilized models worldwide. Thus, the present study aims to compare the land use between different periods and quantify the soil loss in a basin (Feijão River, in the Brazilian southeast), using the SWAT + model, as also to provide guidance to decision making by determining priority areas to improve water quality. The simulation was performed by dividing the basin into sub-basins and assigning multiple HRUs. The metrics used to analyze the model's efficiency indicate that the results were satisfactory, Nash-Sutcliffe (NSE) of 0.53 and 0.54 for calibration and validation of streamflow, respectively. The model represented in this study can help guide future planning for land use and occupation of the basin, enabling the forecast of different scenarios and their possible impacts on water production.