Abstract
ABSTRACT Erosion prediction models are a useful tool for soil use planning and soil conservation. This study aimed to apply the Universal Soil Loss Equation (USLE) in an experimental sub-basin located in the municipality of Teixeira de Freitas, in the southern end of the state of Bahia, Brazil. The following variables were calculated: rainfall erosivity factor, using the precipitation data; soil erodibility factor, by the correlation between erosivity and soil losses obtained from a standard plot installed in the field; topographic factor; vegetation cover and management factor; and conservation practices factor. The product of these factors corresponded to the soil losses in the sub-basin. Data from erosion plots were used to validate the model. The USLE predicted higher soil losses than that observed in the plots, and the eucalyptus proved to be efficient at reducing soil losses by erosion.
Highlights
Changes in the soil use without proper management may cause soil susceptibility to erosive agents
The Universal Soil Loss Equation (USLE) predicted higher soil losses than that observed in the plots, and the eucalyptus proved to be efficient at reducing soil losses by erosion
This study considered the soil loss data collected from October 2012 to March 2014, from plots installed in the sub-basin in an area under native forest, eucalyptus, and uncovered soil, based on the methodology proposed by Cogo (1978)
Summary
Changes in the soil use without proper management may cause soil susceptibility to erosive agents. Water erosion is the most active form of soil degradation, and soil loss rate may exceed soil replacement rate (Eduardo et al, 2013; Ribeiro et al, 2016). Measures to prevent environmental and economic damage due to erosion must be adequately developed to ensure their efficiency. In this sense, the planning of conservation practices to be adopted in plant production systems must aim at expanding the productive capacity and rationality regarding soil use and conservation (Rampim et al, 2012). Water erosion prediction models are key tools to identify areas affected or subject to erosive processes, besides favoring the understanding of these processes and evaluating possible causes and effects (Santos et al, 2006)
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