Avaliação das estimativas de chuva do satélite TRMM no estado da Paraíba

Detalhes bibliográficos
Autor(a) principal: Soares, Alexleide Santana Diniz
Data de Publicação: 2014
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações da UFPB
Texto Completo: https://repositorio.ufpb.br/jspui/handle/tede/5530
Resumo: The spatial and temporal variability is a precipitation feature and constitutes a factor of complexity for developing rainfall studies. Moreover, the low density of rain gauge stations and errors in data collection in the field increase the difficulties in implementing studies in this research area. However, such researches are essential considering that it is from them that we can carry out flood and drought forecasts, understand the hydrological regime of rivers, soil moisture, temperature changes, among others. Thus, the spatial rainfall estimates obtained through satellites data are important because, although present uncertainties, when compared with punctual data measured in the field can provide good indicators of the spatial distribution of rainfall for a given area. In this research, we evaluate the potential of rainfall estimates from TRMM (Tropical Rainfall Measuring Mission) sensor to represent the spatio-temporal variability of precipitation in the State of Paraíba, in the Northeast of Brazil. In this study we considered daily time series of 14 years length of rainfall data collected by AESA (Agência Executiva de Gestão das Águas do Estado da Paraíba) in 269 rainfall gauges and rainfall data estimated from TRMM satellite for a spatial mesh of 198 grid points covering the Paraíba State and which have been interpolated to the rain gauge locations using the inverse squared distance method. Comparisons were made considering the accumulated rainfall in different periods of time: daily, three days, seven days and monthly. With respect to spatial factors, the comparisons were developed based on punctual values in rain gauges stations, areal averages over sub-basins and mesoregions, and topographic profile. The statistical analyzes of comparison between the observed and estimated rainfall were developed based on the average rainfall, the linear correlations, the mean absolute error and root mean square error considering each accumulated period. Regarding the daily precipitation, the majority of the rain gauges (91%) showed correlation coefficients ranging from 0.5 to 0.7. This correlation increases for considering 3 days-rainfall, with values ranging from 0.5 to 0.7 in 56% of rain gauges, and of 0.7-0.8 for 42% of rain gauges. For the 7 days-rainfall, 58% of the rain gauges presented correlations ranging from 0.7 to 0.8, while for the monthly rainfall 95% of the rain gauges obtained correlations higher than 0.8. Therefore, the results indicate that the TRMM satellite provides better estimates when data are accumulated in larger time intervals. The monthly analysis showed that March and April are the months with higher correlation between observed and estimated precipitation, and that in the first months of the year the estimated and observed values have better approximations for all types of analyzes. It was also verified a good estimation potential in the analysis of seasonal variability of precipitation. Moreover, it was observed that the satellite presents the largest errors in the areas with the largest amount of rainfall. In the sub-basins and in the mesoregions of the state the rainfall regime was estimated quite closely. We concluded that the TRMM satellite presents very good skill in reproducing the observed rainfall measured in the gauge stations over the Paraíba state, becoming an important data source for helping the water resources planning and decision making
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spelling Avaliação das estimativas de chuva do satélite TRMM no estado da ParaíbaSensoriamento remotoEstimativas de chuva -ParaíbaRemote sensingTropical Rainfall Measuring Mission - TRMMENGENHARIAS::ENGENHARIA CIVILThe spatial and temporal variability is a precipitation feature and constitutes a factor of complexity for developing rainfall studies. Moreover, the low density of rain gauge stations and errors in data collection in the field increase the difficulties in implementing studies in this research area. However, such researches are essential considering that it is from them that we can carry out flood and drought forecasts, understand the hydrological regime of rivers, soil moisture, temperature changes, among others. Thus, the spatial rainfall estimates obtained through satellites data are important because, although present uncertainties, when compared with punctual data measured in the field can provide good indicators of the spatial distribution of rainfall for a given area. In this research, we evaluate the potential of rainfall estimates from TRMM (Tropical Rainfall Measuring Mission) sensor to represent the spatio-temporal variability of precipitation in the State of Paraíba, in the Northeast of Brazil. In this study we considered daily time series of 14 years length of rainfall data collected by AESA (Agência Executiva de Gestão das Águas do Estado da Paraíba) in 269 rainfall gauges and rainfall data estimated from TRMM satellite for a spatial mesh of 198 grid points covering the Paraíba State and which have been interpolated to the rain gauge locations using the inverse squared distance method. Comparisons were made considering the accumulated rainfall in different periods of time: daily, three days, seven days and monthly. With respect to spatial factors, the comparisons were developed based on punctual values in rain gauges stations, areal averages over sub-basins and mesoregions, and topographic profile. The statistical analyzes of comparison between the observed and estimated rainfall were developed based on the average rainfall, the linear correlations, the mean absolute error and root mean square error considering each accumulated period. Regarding the daily precipitation, the majority of the rain gauges (91%) showed correlation coefficients ranging from 0.5 to 0.7. This correlation increases for considering 3 days-rainfall, with values ranging from 0.5 to 0.7 in 56% of rain gauges, and of 0.7-0.8 for 42% of rain gauges. For the 7 days-rainfall, 58% of the rain gauges presented correlations ranging from 0.7 to 0.8, while for the monthly rainfall 95% of the rain gauges obtained correlations higher than 0.8. Therefore, the results indicate that the TRMM satellite provides better estimates when data are accumulated in larger time intervals. The monthly analysis showed that March and April are the months with higher correlation between observed and estimated precipitation, and that in the first months of the year the estimated and observed values have better approximations for all types of analyzes. It was also verified a good estimation potential in the analysis of seasonal variability of precipitation. Moreover, it was observed that the satellite presents the largest errors in the areas with the largest amount of rainfall. In the sub-basins and in the mesoregions of the state the rainfall regime was estimated quite closely. We concluded that the TRMM satellite presents very good skill in reproducing the observed rainfall measured in the gauge stations over the Paraíba state, becoming an important data source for helping the water resources planning and decision makingConselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPqA variabilidade temporal e espacial, que é um elemento característico da precipitação pluvial se configura como um fator de complexidade para as pesquisas sobre chuvas. Além disso, a baixa densidade de postos pluviométricos e os equívocos nos processos de coleta em campo aumentam as dificuldades na execução de estudos nessa área de pesquisa. No entanto, tais pesquisas são essenciais tendo em vista que é a partir delas que se pode fazer previsão de enchentes e estiagens, compreender o regime hidrológico dos rios, a umidade do solo, as mudanças de temperatura, dentre outras. Assim, as estimativas espaciais de precipitação realizadas por satélites são técnicas importantes, pois, embora contenham incertezas, quando comparadas com valores pontuais medidos em solo podem fornecer bons indicativos da distribuição espacial das chuvas para uma determinada área. Nesta pesquisa, avalia-se o potencial das estimativas de chuva do satélite TRMM, versão 7 e 3B42 (Tropical Rainfall Measuring Mission) para representar a variabilidade espaço-temporal da precipitação no Estado da Paraíba, no Nordeste do Brasil. No estudo considerou-se séries temporais de dados diários para um período de 14 anos (1998-2011) fornecidas pela AESA (Agência Executiva de Gestão das Águas do Estado da Paraíba) referentes a 269 postos pluviométricos e dados estimados pelo satélite TRMM numa malha espacial de 198 pontos que cobrem o Estado da Paraíba e que foram interpolados para os locais de observação de campo pelo método do inverso do quadrado da distância. As comparações foram realizadas considerando a chuva acumulada em diferentes períodos: diário, três dias, sete dias e mensal. Com relação aos fatores espaciais, os comparativos foram desenvolvidos com base em valores pontuais nos locais de observação, médias espaciais considerando sub-bacias, mesorregiões, e perfil topográfico. As análises estatísticas de comparação entre a chuva observada e a estimada foram desenvolvidas a partir das médias de chuva, das correlações lineares, do erro médio absoluto e da raiz do erro médio quadrático considerando cada período acumulado. Nas análises da chuva diária a maioria dos postos (91%) apresentou índices de correlação variando de 0,5 a 0,7. Esta correlação aumenta para os acumulados de 3 dias, com valores que variam de 0,5 a 0,7 em 56% dos postos pluviométricos e de 0,7 a 0,8 em 42% dos postos. Nos acumulados de 7 dias, 58% dos pluviômetros apresentaram correlações que variam de 0,7 a 0,8 e nos acumulados mensais 95% dos postos apresentam correlações superiores a 0,8. Portanto, os resultados indicam que o satélite TRMM apresenta melhores estimativas quando os dados estão acumulados em intervalos maiores de tempo. Na análise mensal verificou-se que março e abril são os meses mais significativos de estimação e que nos primeiros meses do ano os valores estimados e observados apresentam melhores aproximações para todos os tipos de análises. Identificou-se também bom potencial de estimação na análise da variabilidade sazonal de precipitação. Além disso, observou-se que o satélite apresenta os maiores erros para as áreas onde ocorrem os maiores volumes de chuva. Nas sub-bacias e nas mesorregiões do Estado, o regime de chuvas foi estimado com bastante fidelidade em todas as formas analisadas. Conclui-se que o satélite TRMM apresenta bom desempenho para reproduzir as chuvas observadas em pluviômetros no Estado da Paraíba, configurando-se como uma importante fonte de dados para o auxílio no planejamento e na tomada de decisões relativas aos recursos hídricosUniversidade Federal da Paraí­baBREngenharia Cívil e AmbientalPrograma de Pós-Graduação em Engenharia Urbana e AmbientalUFPBPaz, Adriano Rolim daPAZ, Adriano Rolim da.Soares, Alexleide Santana Diniz2015-05-14T12:09:33Z2018-07-21T00:05:31Z2015-01-212018-07-21T00:05:31Z2014-05-15info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfSOARES, Alexleide Santana Diniz. Avaliação das estimativas de chuva do satélite TRMM no estado da Paraíba. 2014. 114 f. Dissertação (Mestrado em Engenharia Urbana) - Universidade Federal da Paraí­ba, João Pessoa, 2014.https://repositorio.ufpb.br/jspui/handle/tede/5530porinfo:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UFPBinstname:Universidade Federal da Paraíba (UFPB)instacron:UFPB2018-09-06T00:41:29Zoai:repositorio.ufpb.br:tede/5530Biblioteca Digital de Teses e Dissertaçõeshttps://repositorio.ufpb.br/PUBhttp://tede.biblioteca.ufpb.br:8080/oai/requestdiretoria@ufpb.br|| diretoria@ufpb.bropendoar:2018-09-06T00:41:29Biblioteca Digital de Teses e Dissertações da UFPB - Universidade Federal da Paraíba (UFPB)false
dc.title.none.fl_str_mv Avaliação das estimativas de chuva do satélite TRMM no estado da Paraíba
title Avaliação das estimativas de chuva do satélite TRMM no estado da Paraíba
spellingShingle Avaliação das estimativas de chuva do satélite TRMM no estado da Paraíba
Soares, Alexleide Santana Diniz
Sensoriamento remoto
Estimativas de chuva -Paraíba
Remote sensing
Tropical Rainfall Measuring Mission - TRMM
ENGENHARIAS::ENGENHARIA CIVIL
title_short Avaliação das estimativas de chuva do satélite TRMM no estado da Paraíba
title_full Avaliação das estimativas de chuva do satélite TRMM no estado da Paraíba
title_fullStr Avaliação das estimativas de chuva do satélite TRMM no estado da Paraíba
title_full_unstemmed Avaliação das estimativas de chuva do satélite TRMM no estado da Paraíba
title_sort Avaliação das estimativas de chuva do satélite TRMM no estado da Paraíba
author Soares, Alexleide Santana Diniz
author_facet Soares, Alexleide Santana Diniz
author_role author
dc.contributor.none.fl_str_mv Paz, Adriano Rolim da
PAZ, Adriano Rolim da.
dc.contributor.author.fl_str_mv Soares, Alexleide Santana Diniz
dc.subject.por.fl_str_mv Sensoriamento remoto
Estimativas de chuva -Paraíba
Remote sensing
Tropical Rainfall Measuring Mission - TRMM
ENGENHARIAS::ENGENHARIA CIVIL
topic Sensoriamento remoto
Estimativas de chuva -Paraíba
Remote sensing
Tropical Rainfall Measuring Mission - TRMM
ENGENHARIAS::ENGENHARIA CIVIL
description The spatial and temporal variability is a precipitation feature and constitutes a factor of complexity for developing rainfall studies. Moreover, the low density of rain gauge stations and errors in data collection in the field increase the difficulties in implementing studies in this research area. However, such researches are essential considering that it is from them that we can carry out flood and drought forecasts, understand the hydrological regime of rivers, soil moisture, temperature changes, among others. Thus, the spatial rainfall estimates obtained through satellites data are important because, although present uncertainties, when compared with punctual data measured in the field can provide good indicators of the spatial distribution of rainfall for a given area. In this research, we evaluate the potential of rainfall estimates from TRMM (Tropical Rainfall Measuring Mission) sensor to represent the spatio-temporal variability of precipitation in the State of Paraíba, in the Northeast of Brazil. In this study we considered daily time series of 14 years length of rainfall data collected by AESA (Agência Executiva de Gestão das Águas do Estado da Paraíba) in 269 rainfall gauges and rainfall data estimated from TRMM satellite for a spatial mesh of 198 grid points covering the Paraíba State and which have been interpolated to the rain gauge locations using the inverse squared distance method. Comparisons were made considering the accumulated rainfall in different periods of time: daily, three days, seven days and monthly. With respect to spatial factors, the comparisons were developed based on punctual values in rain gauges stations, areal averages over sub-basins and mesoregions, and topographic profile. The statistical analyzes of comparison between the observed and estimated rainfall were developed based on the average rainfall, the linear correlations, the mean absolute error and root mean square error considering each accumulated period. Regarding the daily precipitation, the majority of the rain gauges (91%) showed correlation coefficients ranging from 0.5 to 0.7. This correlation increases for considering 3 days-rainfall, with values ranging from 0.5 to 0.7 in 56% of rain gauges, and of 0.7-0.8 for 42% of rain gauges. For the 7 days-rainfall, 58% of the rain gauges presented correlations ranging from 0.7 to 0.8, while for the monthly rainfall 95% of the rain gauges obtained correlations higher than 0.8. Therefore, the results indicate that the TRMM satellite provides better estimates when data are accumulated in larger time intervals. The monthly analysis showed that March and April are the months with higher correlation between observed and estimated precipitation, and that in the first months of the year the estimated and observed values have better approximations for all types of analyzes. It was also verified a good estimation potential in the analysis of seasonal variability of precipitation. Moreover, it was observed that the satellite presents the largest errors in the areas with the largest amount of rainfall. In the sub-basins and in the mesoregions of the state the rainfall regime was estimated quite closely. We concluded that the TRMM satellite presents very good skill in reproducing the observed rainfall measured in the gauge stations over the Paraíba state, becoming an important data source for helping the water resources planning and decision making
publishDate 2014
dc.date.none.fl_str_mv 2014-05-15
2015-05-14T12:09:33Z
2015-01-21
2018-07-21T00:05:31Z
2018-07-21T00:05:31Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv SOARES, Alexleide Santana Diniz. Avaliação das estimativas de chuva do satélite TRMM no estado da Paraíba. 2014. 114 f. Dissertação (Mestrado em Engenharia Urbana) - Universidade Federal da Paraí­ba, João Pessoa, 2014.
https://repositorio.ufpb.br/jspui/handle/tede/5530
identifier_str_mv SOARES, Alexleide Santana Diniz. Avaliação das estimativas de chuva do satélite TRMM no estado da Paraíba. 2014. 114 f. Dissertação (Mestrado em Engenharia Urbana) - Universidade Federal da Paraí­ba, João Pessoa, 2014.
url https://repositorio.ufpb.br/jspui/handle/tede/5530
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eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal da Paraí­ba
BR
Engenharia Cívil e Ambiental
Programa de Pós-Graduação em Engenharia Urbana e Ambiental
UFPB
publisher.none.fl_str_mv Universidade Federal da Paraí­ba
BR
Engenharia Cívil e Ambiental
Programa de Pós-Graduação em Engenharia Urbana e Ambiental
UFPB
dc.source.none.fl_str_mv reponame:Biblioteca Digital de Teses e Dissertações da UFPB
instname:Universidade Federal da Paraíba (UFPB)
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repository.name.fl_str_mv Biblioteca Digital de Teses e Dissertações da UFPB - Universidade Federal da Paraíba (UFPB)
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