Detalhes bibliográficos
Ano de defesa: |
2018 |
Autor(a) principal: |
Santos, Anderson de Almeida |
Orientador(a): |
Almeida, André Quintão de |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Dissertação
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Tipo de acesso: |
Acesso aberto |
Idioma: |
por |
Instituição de defesa: |
Não Informado pela instituição
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Programa de Pós-Graduação: |
Pós-Graduação em Recursos Hídricos
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Departamento: |
Não Informado pela instituição
|
País: |
Não Informado pela instituição
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Palavras-chave em Português: |
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Palavras-chave em Inglês: |
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Área do conhecimento CNPq: |
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Link de acesso: |
https://ri.ufs.br/jspui/handle/riufs/14260
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Resumo: |
The dynamics of the process of interception of rainfall by the forest canopy depends mainly on the characteristics of the rainfall and the vegetal structure, representing a process that is constantly changing due to the mutually interactive factors. This is the first process by which rainwater passes through the river basin. The monitoring and modeling of this process are important, although often neglected, to quantify which portion of the rain actually reaches the ground. For this, there are models that predict the direct interception, that is, through equipment, such as rain gauges, and indirectly, this being done through physical and analytical models such as Ruther models and Gash. With this, the objective of this work was to model the interception of rainfall in a fragment of Atlantic Forest in the Timbó river basin, Sergipe, using the Rutter model. In this study, three 30 x 30 meter plots were demarcated along a forest fragment of the Timbó river basin, SE. The internal precipitation (PI), in millimeters, was quantified from the installation of 75 rain gauges, 25 in each experimental plot. The external precipitation (P), also in millimeters, was obtained by means of a rain gauge in an open area, at a distance of 300 m from the experimental plots. Interception (I) was estimated by the difference between P and effective precipitation (PE). All parameters were monitored in the period from 05/22/2017 to 03/24/2018, resulting in 42 events. In order to relate the measured data to the estimates, the calibration and validation of the Rutter model was performed using the data obtained during the period characterized as the highest amount of rainfall in the region studied, from May 2017 to September 2017, totaling 21 precipitation events, which were then submitted to a simple linear regression analysis to adjust the coefficient of determination (R²). The parameters used by the Rutter model were, for example, Latitude; Longitude; Albedo; Altitude; Anemometer height; Height of Culture; Foliar Area Index; percentage free fall; percentage of Trunk Run; Maximum Storage of Canopy Storage; Solar Incident Radiation (W / m2); Relative humidity (%); Air Temperature (° C); Wind Speed (m / s); Gross rainfall (mm), obtained by a weather station. During this period the total precipitation measured was 658.4 mm. A wide range of open precipitation (PA) was obtained, with a minimum of 2.67 mm and a maximum of 190.98 mm. The internal precipitation (IP) reached a total volume of 518.5 mm, representing 78.75% of the total precipitation incident above the canopy. The interception totaled 139.3 mm, equivalent to 21.1% of the precipitation in the open. The BP measured when correlated with BP estimated by the Rutter model, presented a high coefficient of determination R² = 0.9464, considered satisfactory. The same occurred when the linear regression between the interception (I) measured by the rain gauges and the one estimated by the Rutter model (I Rutter) was performed, presenting a high coefficient of determination R² = 0.9999. Intercept values were then estimated for the period from October 2017 to March 2018. The modeled intercept represented 19.21% of the AP. From the results obtained by this study, it is proved that it is possible to simulate losses by interception of precipitation by the Atlantic Forest vegetation (I), with good level of efficiency using the Rutter model, besides serving as a tool for parameter monitoring water balance of similar river basins. |