Study of trend analysis and sample entropy of precipitation in Paraíba, Brazil

• Ano de defesa: 2016
• Autor(a) principal: XAVIER JÚNIOR, Sílvio Fernando Alves
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal Rural de Pernambuco; Departamento de Estatística e Informática; Brasil; UFRPE; Programa de Pós-Graduação em Biometria e Estatística Aplicada
• Palavras-chave em Português: Precipitação (Meteorologia); Chuva; Entropia; CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA
• Link de acesso: http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/4505

The objective of this work was to present two different methodologies in order to obtain a better comprehension of rainfall phenomena and its consequences over a particular region which suffers from water scarcity. Firstly, semivariogram models were selected to estimate trends in monthly precipitation in Paraíba State-Brazil using ordinary kriging. The methodology involves the application of geostatistical interpolation of precipitation records of 51 years from 69 rainfall stations across the state. Analysis of semivariograms showed that anisotropy for specific months had a strong spatial dependence (Index of Spatial Dependence - IDE <25%). The trends were subjected to the following models: circular, spherical, pentaspherical, exponential, Gaussian, rational quadratic, K-Bessel and tetraspherical. The models with the best fit were selected by cross-validation and Error Comparison Index (ECI). Each data set month had a particular spatial dependence structure, which made it necessary to define specific models of semivariograms in order to enhance the adjustment of the experimental semivariogram. Besides, the standardized error prediction map and hot spot analysis were obtained with the aim of justifying the chosen models. Furthermore, one can see that a climate system is a complex nonlinear system. To describe the complexity characteristics of precipitation series in Paraíba, we propose the use of sample entropy, a kind of entropy-based algorithm, to measure the complexity of precipitation series. The Paraíba’s four macro-regions: Mata, Agreste, Borborema, and Sertão were analyzed. Results of analysis show that complexities of monthly average precipitation have differences in the macro-regions. Sample entropy can reflect the dynamic change of precipitation series providing a new way to investigate the complexity of hydrological series. The complexity exhibits an areal variation of local water resources system which can influence the basis for utilizing and developing resources in dry areas.