Detalhes bibliográficos
| Ano de defesa: |
2017 |
| Autor(a) principal: |
OLIVEIRA, José Diorgenes Alves
 |
| Orientador(a): |
MOURA, Geber Barbosa de Albuquerque |
| Banca de defesa: |
MONTENEGRO, Abelardo Antônio de Assunção,
NASCIMENTO, Cristina Rodrigues,
NÓBREGA, Ranyére Silva |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal Rural de Pernambuco
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Engenharia Agrícola
|
| Departamento: |
Departamento de Engenharia Agrícola
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/7644
|
Resumo: |
The Alto Ipanema watershed, it is located in a semi-arid region, becomes more vulnerable and susceptible to the effects of environmental changes and the degradation process, it has serious economic and socio-environmental implications. Thus, the present dissertation had the objective to identify and evaluate the different degrees of environmental susceptibility of the Alto Ipanema watershed to climatic variability and the degradation / desertification process. In order to meet this objective, the following specific objectives were established: to evaluate the temporal variability of the precipitation in the watershed, using the Rainfall Anomaly Index (IAC), to evaluate the degree of aridity with the Aridity Index (IA) and to identify and analyze the spatial-temporal dynamics of biophysical parameters in the detection of environmental changes in the watershed with application of some components of the algorithm Surface Energy Balance Algorithm for Land (SEBAL). The data of monthly precipitation of the historical series (1962 to 2015) were used for the calculation of the IAC, considering the temporal means of the local precipitations, for the determination of dry and humid periods. The AI calculation was also performed to identify the trend towards watershed desertification through precipitation and potential evapotranspiration data. Biophysical parameters were estimated for the detection of environmental changes in the watershed, applying components of the SEBAL algorithm through the use of Landsat 5-TM and 8-OLI / TIRS images. The results showed a predominance of negative IACs for interannual variability with more extreme inflection points in the rainy years, which shows the whole watershed with an anomaly index between dry and rainy. It is also noticed the existence of strong evidence of the influence of the occurrence of the El Niño and La Niña phenomena on the events of droughts and rains in the watershed. Through the Index of Aridity it was found that the watershed is susceptible to the process of environmental degradation / desertification in a moderate way. With the biophysical parameters analyzed, it was found that the northwestern portion of the basin presents a considerable area of exposed soils with indication of a high degree of susceptibility to degradation and that the biophysical parameters evaluated by the SEBAL algorithm are effective and efficient in understanding the dynamics of spatial and temporal of semi-arid environments. |
