Detalhes bibliográficos
| Ano de defesa: |
2019 |
| Autor(a) principal: |
CRUZ, David Venancio da
 |
| Orientador(a): |
CUNHA FILHO, Moacyr |
| Banca de defesa: |
MOREIRA, Guilherme Rocha,
STOSIC, Tatijana,
PISCOYA, Victor Casimiro,
OLIVEIRA, Manoel Rivelino Gomes de |
| Tipo de documento: |
Tese
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal Rural de Pernambuco
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Biometria e Estatística Aplicada
|
| Departamento: |
Departamento de Estatística e Informática
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/8159
|
Resumo: |
The availability of water and hydrological risks are becoming more evident, attributed to the impacts of climate change, in this context the Upper São Francisco (ASF) region, which presents high climatic variability, both at the spatial and temporal levels. Does- precipitation behavior and temperature, in order to detect climate change. The objective of this study was to obtain a spatio-temporal daily behavior of maximum temperature, minimum temperature and precipitation in the ASF and monitor the water quality around the mouth of the Pará River, also located in ASF. As a metonym the Pettit test was calculated to identify (changes in means) significant changes in the climate and its intensities. To evaluate the water quality was used statistical process control. The results showed with respect to precipitation in the period between 1975 and 2016, at the stations analyzed it was verified that the points located in the cities of Aimores, Aracuai, Caparão-MG and Capinopolis, did not present any type of tendency, that is, increase or decrease in volume rainfall, according to the tests performed monthly in the historical precipitation series. O higher and persistent trends of the minimum temperature between January and March, the increase of this meteorological variable, during the studied period, a average 0.9715 C during the study period. In monitoring the variables related to water quality did not meet the independence assumptions of the samples. To treat autocorrelation, a geostatistical methodology was applied, besides being a more viable due to its ease and speed, does not need to model the data and later control charts to model waste. The methodology also allowed us to define important considerations, such as a proposal to monitor pH of the water, through the Statistical Process Control. |
