Relação da variabilidade espaço-temporal da cobertura do solo e da evapotranspiração utilizando o algoritmo Sebal automatizado na bacia do rio Ipanema

• Ano de defesa: 2017
• Autor(a) principal: Silva , Alexandro Medeiros
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal da Paraíba; Brasil; Geografia; Programa de Pós-Graduação em Geografia; UFPB
• Palavras-chave em Português: SEBAL; Caatinga; Semiárido; Automatização; Evapotranspiração; Semiarid; region; Automatization; Evapotranspiration; CIENCIAS EXATAS E DA TERRA::GEOCIENCIAS
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/tede/9853

Environmental degradation is one of the results of the excessive pressure of anthropic actions through different forms of land use, as well as the influence of climatic factors, which is even more active in the Caatinga. The Caatinga is a Brazilian biome very susceptible to modifications of the climate and land uses. Then, to study the changes in the landscape occurred in this biome, it becomes necessary to understand the impacts of these modifications on the behavior of evapotranspiration in the different land uses. Thus, this work, using remote sensing, intends to analyze the influence of different types of land use on evapotranspiration estimates using the automated SEBAL algorithm for a portion of the Caatinga biome, the Ipanema River basin (BHRI), which is located between the states of Pernambuco and Alagoas. In order to analyze the changes in land cover, four Landsat images were used. In the mapping of land use four classes were identified, i.e. dense canopy, grassland, agriculture/pasture, and bare land. As result of the land use and land cover mapping, it was verified that for the analyzed period, areas of bare land were those that presented a greater variation, with 115% between 2005 and 2015. For the estimates of evapotranspiration, 282 images of the MODIS sensor were used between 2005 and 2015. Since the application of SEBAL requires a long process, automating the application of this algorithm may be an alternative to optimize the estimation of evapotranspiration for a long series of images. In this sense, the application of the SEBAL algorithm for the present work was totally automated, using a computational routine developed in MATLAB® software. Besides the estimates of evapotranspiration, the NDVI, surface temperature and net radiation were analyzed for the same period. For the NDVI, it was observed that from June to August the highest values were estimated, which average is around 0.6 for the whole BHRI. For the surface temperature, the values were estimated between 21 and 50°C, the month that presented the highest temperatures was November, when much of the basin had temperatures above 40°C. Estimates of the average daily net radiation showed values between 85 and 203 W/m². The highest averages of the net radiation were identified from November to December. For the monthly evapotranspiration, it was observed that from March, when the rainfall volume over the BHRI starts to rise, the average values of monthly ET begin to decrease in a relatively similar proportion among the different types of soil use. However, increase of the monthly ET values in the areas of dense canopy and grassland happens faster, whereas in the areas of agriculture/pasture and bare land this increase occurs more gradually. The results showed a 31% decrease in the mean annual evapotranspiration for the BHRI between 2005 (1211.42 mm/year) and 2015 (831.22 mm/year). According to the obtained results, the estimates obtained from the algorithm of SEBAL automation were very close when compared to those obtained by a specialist. Finally, the results obtained in the present work were satisfactory and provide important information about the biophysical characteristics of BHRI, which were until now very scarce.