Abstract
Water erosion is one of the main problems faced by the Furnas Lake Surrounding Watershed, located in southeast Brazil. The erosive process is intensified by inadequate land occupation of the lake margins where should be riparian forests, or permanent preservation areas (APP), in order to protect water resources. In this context, our work aimed to estimate the soil losses of this watershed using the Revised Universal Soil Loss Equation (RUSLE) in two different scenarios: I - considering the actual occupation of the area, and II - building an alternative scenario where permanent preservation areas were present. Therefore, we considered physical, edaphoclimatic, and land use and management factors. To simulate the presence of preservation areas, we based it on the Brazilian Forest Code (Bill no. 12.651/2012). In the real scenario (I), the total soil loss estimated was 31,580,907.47 Mg.year-1 (32% over the Soil Loss Tolerance) with an average loss of 19.00 Mg.ha-1.year-1, while in the conservationist scenario (II), there was 10% decrease, which means the mitigation of the erosion process as well as of the negative environmental impacts that can be generated by soil degradation.
Highlights
Water erosion is one of the most important forms of soil degradation in Brazilian agriculture, and this problem can be aggravated by inadequate landuse and occupation, and by the lack of environmental management practices to soil conservation (Dechen et al, 2015; Cunha et al, 2017)
Furnas Hydroelectric Plant is located in the GD3 (Figure 1), which presents an area of 16,643.00 km2 and covers 48 municipalities with an estimated population of 842,260.00 inhabitants (IBGE, 2011)
Gross water erosion in the watershed was estimated at 31,580,907.47 Mg year-1
Summary
Water erosion is one of the most important forms of soil degradation in Brazilian agriculture, and this problem can be aggravated by inadequate landuse and occupation, and by the lack of environmental management practices to soil conservation (Dechen et al, 2015; Cunha et al, 2017). Empirical models of prediction are useful tools to evaluate erosion rates and establish plans to reduce soil losses (Cunha et al, 2017). These models require obtainable and low-cost information, large scale water erosion evaluate is only possible with modeling techniques (Alewell et al, 2019). Associating the RUSLE with Geographic Information Systems (SIG), it is possible to produce maps to identify areas with an elevated risk of erosion and estimate the impacts of the different scenarios of land occupation, as well as the conservation practices effects on agricultural lands (Galdino et al, 2016)
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