Aplicação do algoritmo SEBAL na estimativa da evapotranspiração e da biomassa acumulada da cana-de-açúcar

• Autor(a) principal: Andrade, Ricardo Guimarães
• Data de Publicação: 2008
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: LOCUS Repositório Institucional da UFV
• Texto Completo: http://locus.ufv.br/handle/123456789/1488
• topic: Evapotranspiração; Biomassa; SEBAL; Sensoriamento remoto; Cana-de-açúcar; Evapotranspiration; Biomass; SEBAL; Remote sensing; Sugarcane; CNPQ::CIENCIAS EXATAS E DA TERRA::GEOCIENCIAS::METEOROLOGIA::CLIMATOLOGIA

The growing demand for water resources requires the knowledge of where, when and how water is being utilized. It is, therefore, fundamental to understand and determine the regional water evapotranspirometric demand, since evapotranspiration (ET) accounts for, approximately, 75% of the total rainfall occurring on the continental surfaces. ET is highly dependent on and variable in time and space. Such information generally reveals important aspects for water resources planning and management, mainly in places where irrigated agricultural production accounts for a large percentage of the regional economy. Thus, methodologies using remote sensing stand out for their capabilities to cover extensive areas. This study utilized orbital images of MODIS-Terra and TM-Landsat 5 sensors to apply the Surface Energy Balance Algorithm for Land (SEBAL) for obtaining the energy fluxes on the surface and consequently to determine the ET rates and sugarcane biomass production at Boa Fé Farm, located at the Triângulo Mineiro municipality of Conquista, Minas Gerais. The results obtained showed that SEBAL has shown a good performance at regional scale in estimating the energy fluxes and biomass production of sugarcane plantation, with potential to be applied in areas with limiting availability of meteorological data.