Transformações na paisagem decorrentes da construção da Usina Hidrelétrica do Funil - UHE-Funil e o impacto no município de Ijaci, MG

Abstract

The building of a hydroelectric power station causes transformations in the regional landscape, in a process contrary to the long-standing movement of its formation, with negative impacts to both the fauna and flora. The establishment is defined by pre-requirements as water availability, topography and geological factors, without an integral landscape study which points out alternatives to the preservation of natural resources. The Funil Hydroelectric Power Station, UHE FUNI, with a power installed of 180 MW, was built on the upper part of the Rio Grande (Grande River), between the towns of Lavras and Perdões, in the State of Minas Gerais, Brazil, Ijaci being the most affected town. The lake´s formation and the beginning of the hydroelectric power´s operation established a new landscape and new socioeconomic profile in the region. Both plans and projects were designed with the objective of mitigating the environmental impacts. In the case of the UHE FUNIL, the conservation plan and use of the surroundings was based on the reading so the landscape and environmental fragilities from the large structures existent there. The objectives of this research work were: to investigate the EIA-RIMA documents to realize how the landscape was considered in the process; to identify environmental interferences and losses at Ijaci-Mg due to its directive plan and to evaluate visually the landscape in the surroundings of the UHE-Funil lake in that town, to detect landscape scenarios and environmental impacts. The results led to a temporary analysis of the landscape transformation in the area, identifying, however, a lack of timing between study stages and phases of hydroelectric power building; there are some misunderstandings in the interpretation of environmental laws in the directive plan, making it more permissive than the State Legislation and the methodology used for the landscape visual analysis was efficient to detect both landscape scenarios and environmental impacts and not detected by georeferenced images.