Análise da distribuição espaço temporal de variáveis hidrológicas e biofísicas no semiárido de Pernambuco
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da UFRPE |
Texto Completo: | http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9100 |
Resumo: | The Brazilian semi-arid region has limited availability of water resources. In addition, profound changes in land use and occupation have occurred in watersheds of Pernambuco State, such as the implementation of the São Francisco River Integration Project (PISF). This dissertation aims to analyze the spatial distribution of hydrological variables in the semi-arid region of Pernambuco in two basins of this region, one that already has the PISF water supply and while the other does not, but there are future projects for its implementation through branch, are the basins of the Terra Nova and Brígida rivers, respectively. In the Terra Nova river basin, the objective was to evaluate the real evapotranspiration and map cultivated areas through remote sensing in a perennial stretch. Landsat-8 satellite images from 2015 to 2020 were selected. The images were processed in Google Earth Engine (GEE) and edited in QGIS 3.16 software. It was noticed by the NDVI, an increase in the vegetation cover index spatially. Regions with higher values of real evapotranspiration are linked to those with lower temperatures. A smaller amount of cultivated areas was observed in the Terra Nova River stretch in the 2015 images and the expansion of agriculture in the region on the banks of this river, in its perennial stretch. In addition to the pluviometric regime, the release of water from the PISF contributed to the increase in irrigated areas in the region. And in the Brígida river basin, the objective was to evaluate the distribution of precipitation in years under different rainfall regimes and its impacts on the dynamics of vegetation cover, addressing the water-vegetation nexus for the region, where water supply is strongly dependent on the occurrence of rains. Rainfall data from the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) was used in conjunction with observed data from 40 weather stations with an annual time series of 55 years (1962 to 2017). The Standardized Precipitation Index (SPI) was applied to assess the annual variability of precipitation (SPI-12). The data were submitted to classical statistics and geostatistical analysis, using ordinary kriging (KO) and Sequential Gaussian Simulation (SGS) methods to map the spatial distribution of rainfall. A comprehensive set of fifteen remote sensing images for years with different rainfall regimes was analyzed, allowing the calculation of the Normalized Difference Vegetation Index (NDVI) and the Modified Normalized Difference Water Index (MNDWI). There was a high correlation between observed and estimated data. The geostatistical analyzes showed models with strong spatial dependence for all the years adopted. Through kriging maps, it was found that the rainfall in the basin increases strongly with altitude. When the number of SGS realizations increases, SPI maps tend to be stable and capture inherent variability not represented by the kriging procedure. Among the established and validated semivariograms, the spherical model was the one that best fitted the data set used. Through the SGS technique, it was verified the low uncertainty of the CHIRPS data and also that 100 realizations are enough to generate SGS maps suitable for the SPI in the basin. Even in normal years, the number of water bodies is low, which can compromise water security in the region. |
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MONTENEGRO, Abelardo Antônio de AssunçãoSILVA, Thieres George Freire daGIONGO, Pedro RogérioCARVALHO, Ailton Alves dehttp://lattes.cnpq.br/9251782672090033SOUSA, Lizandra de Barros de2023-06-20T20:11:53Z2022-02-23SOUSA, Lizandra de Barros de. Análise da distribuição espaço temporal de variáveis hidrológicas e biofísicas no semiárido de Pernambuco. 2022. 110 f. Dissertação (Programa de Pós-Graduação em Engenharia Agrícola) - Universidade Federal Rural de Pernambuco, Recife.http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9100The Brazilian semi-arid region has limited availability of water resources. In addition, profound changes in land use and occupation have occurred in watersheds of Pernambuco State, such as the implementation of the São Francisco River Integration Project (PISF). This dissertation aims to analyze the spatial distribution of hydrological variables in the semi-arid region of Pernambuco in two basins of this region, one that already has the PISF water supply and while the other does not, but there are future projects for its implementation through branch, are the basins of the Terra Nova and Brígida rivers, respectively. In the Terra Nova river basin, the objective was to evaluate the real evapotranspiration and map cultivated areas through remote sensing in a perennial stretch. Landsat-8 satellite images from 2015 to 2020 were selected. The images were processed in Google Earth Engine (GEE) and edited in QGIS 3.16 software. It was noticed by the NDVI, an increase in the vegetation cover index spatially. Regions with higher values of real evapotranspiration are linked to those with lower temperatures. A smaller amount of cultivated areas was observed in the Terra Nova River stretch in the 2015 images and the expansion of agriculture in the region on the banks of this river, in its perennial stretch. In addition to the pluviometric regime, the release of water from the PISF contributed to the increase in irrigated areas in the region. And in the Brígida river basin, the objective was to evaluate the distribution of precipitation in years under different rainfall regimes and its impacts on the dynamics of vegetation cover, addressing the water-vegetation nexus for the region, where water supply is strongly dependent on the occurrence of rains. Rainfall data from the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) was used in conjunction with observed data from 40 weather stations with an annual time series of 55 years (1962 to 2017). The Standardized Precipitation Index (SPI) was applied to assess the annual variability of precipitation (SPI-12). The data were submitted to classical statistics and geostatistical analysis, using ordinary kriging (KO) and Sequential Gaussian Simulation (SGS) methods to map the spatial distribution of rainfall. A comprehensive set of fifteen remote sensing images for years with different rainfall regimes was analyzed, allowing the calculation of the Normalized Difference Vegetation Index (NDVI) and the Modified Normalized Difference Water Index (MNDWI). There was a high correlation between observed and estimated data. The geostatistical analyzes showed models with strong spatial dependence for all the years adopted. Through kriging maps, it was found that the rainfall in the basin increases strongly with altitude. When the number of SGS realizations increases, SPI maps tend to be stable and capture inherent variability not represented by the kriging procedure. Among the established and validated semivariograms, the spherical model was the one that best fitted the data set used. Through the SGS technique, it was verified the low uncertainty of the CHIRPS data and also that 100 realizations are enough to generate SGS maps suitable for the SPI in the basin. Even in normal years, the number of water bodies is low, which can compromise water security in the region.A região semiárida brasileira apresenta limitada disponibilidade de recursos hídricos. Além disso, profundas alterações no uso e ocupação do solo têm ocorrido nas bacias hidrográficas de Pernambuco, como a implementação do Projeto de Integração do rio São Francisco (PISF). Esta dissertação objetiva analisar a distribuição espaço temporal de variáveis hidrológicas e biofísicas no semiárido pernambucano em duas bacias dessa região, uma que já dispõe da oferta hídrica do PISF e enquanto a outra não, mas há projetos futuros de sua implementação através de ramal, são as bacias do rio Terra Nova e Brígida, respectivamente. Na bacia do rio Terra Nova objetivou-se avaliar a evapotranspiração real e mapear áreas cultivadas por meio de sensoriamento remoto em trecho perenizado. Imagens do satélite Landsat-8 de 2015 a 2020 foram selecionadas. As imagens foram processadas no Google Earth Engine (GEE) e editadas no software QGIS 3.16. Notou-se pelo NDVI, aumento no índice de cobertura vegetal espacialmente. Regiões com maiores valores de evapotranspiração real estão ligadas àquelas com temperaturas mais baixas. Observou-se uma menor quantidade de áreas cultivadas no trecho do rio Terra Nova nas imagens de 2015 e expansão da agricultura na região às margens desse rio, em seu trecho perenizado. Além do regime pluviométrico, a liberação das águas do PISF contribuiu para o aumento de áreas irrigadas na região. E na bacia do rio Brígida objetivou-se avaliar a distribuição da precipitação em anos sob diferentes regimes pluviométricos e seus impactos na dinâmica da cobertura vegetal, abordando o nexo água-vegetação para a região, onde o abastecimento de água é fortemente dependente da ocorrência de chuvas. Os dados de precipitação do Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) foram usados em conjunto com dados observados de 40 estações meteorológicas com uma série temporal anual de 55 anos (1962 a 2017). O Índice de Precipitação Padronizado (SPI) foi aplicado para avaliar a variabilidade anual da precipitação (SPI-12). Os dados foram submetidos à estatística clássica e análise geoestatística, sendo adotados os métodos de krigagem ordinária (KO) e Simulação Gaussiana Sequencial (SGS) para o mapeamento da distribuição espacial das chuvas. Analisou-se um conjunto abrangente de quinze imagens de sensoriamento remoto para anos com diferentes regimes pluviométricos, permitindo calcular o Índice de Vegetação por Diferença Normalizada (NDVI) e o Índice por Diferença Normalizada de Água Modificado (MNDWI). Verificou-se alta correlação entre os dados observados e os estimados. As análises geoestatísticas apresentaram modelos com forte dependência espacial para todos os anos adotados. Através de mapas de krigagem, verificou-se que a lâmina de chuvas na bacia aumenta fortemente com a altitude. Quando o número de realizações SGS aumenta, os mapas SPI tendem a ser estáveis e capturam variabilidades inerentes não representadas pelo procedimento de krigagem. Dentre os semivariogramas estabelecidos e validados, o modelo esférico foi o que melhor se ajustou ao conjunto de dados utilizado. Através da técnica SGS verificou-se a baixa incerteza dos dados CHIRPS e também que 100 realizações são suficientes para gerar mapas SGS adequados para o SPI na bacia. Mesmo em anos normais, o número de corpos d'água é baixo, o que pode comprometer a segurança hídrica na região.Submitted by (ana.araujo@ufrpe.br) on 2023-06-20T20:11:52Z No. of bitstreams: 1 Lizandra de Barros de Sousa.pdf: 2902126 bytes, checksum: 6c4a2de516dd1d0e958a2c0b908cea0c (MD5)Made available in DSpace on 2023-06-20T20:11:53Z (GMT). No. of bitstreams: 1 Lizandra de Barros de Sousa.pdf: 2902126 bytes, checksum: 6c4a2de516dd1d0e958a2c0b908cea0c (MD5) Previous issue date: 2022-02-23application/pdfporUniversidade Federal Rural de PernambucoPrograma de Pós-Graduação em Engenharia AgrícolaUFRPEBrasilDepartamento de Engenharia AgrícolaSemiáridoSensoriamento remotoEvapotranspiraçãoPrecipitação (Meteorologia)Recurso hídricoGeoestatísticaCIENCIAS AGRARIAS::ENGENHARIA AGRICOLAAnálise da distribuição espaço temporal de variáveis hidrológicas e biofísicas no semiárido de PernambucoAnalysis of the spatiotemporal distribution of hydrological and biophysical variables in the semiarid region of Pernambucoinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis-5347692450416052129600600600-28621161963550796749185445721588761555info:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UFRPEinstname:Universidade Federal Rural de Pernambuco (UFRPE)instacron:UFRPEORIGINALLizandra de Barros de Sousa.pdfLizandra de Barros de Sousa.pdfapplication/pdf2902126http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/9100/2/Lizandra+de+Barros+de+Sousa.pdf6c4a2de516dd1d0e958a2c0b908cea0cMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-82165http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/9100/1/license.txtbd3efa91386c1718a7f26a329fdcb468MD51tede2/91002023-06-20 17:11:53.105oai:tede2: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Biblioteca Digital de Teses e Dissertaçõeshttp://www.tede2.ufrpe.br:8080/tede/PUBhttp://www.tede2.ufrpe.br:8080/oai/requestbdtd@ufrpe.br ||bdtd@ufrpe.bropendoar:2024-05-28T12:37:49.978987Biblioteca Digital de Teses e Dissertações da UFRPE - Universidade Federal Rural de Pernambuco (UFRPE)false |
dc.title.por.fl_str_mv |
Análise da distribuição espaço temporal de variáveis hidrológicas e biofísicas no semiárido de Pernambuco |
dc.title.alternative.eng.fl_str_mv |
Analysis of the spatiotemporal distribution of hydrological and biophysical variables in the semiarid region of Pernambuco |
title |
Análise da distribuição espaço temporal de variáveis hidrológicas e biofísicas no semiárido de Pernambuco |
spellingShingle |
Análise da distribuição espaço temporal de variáveis hidrológicas e biofísicas no semiárido de Pernambuco SOUSA, Lizandra de Barros de Semiárido Sensoriamento remoto Evapotranspiração Precipitação (Meteorologia) Recurso hídrico Geoestatística CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA |
title_short |
Análise da distribuição espaço temporal de variáveis hidrológicas e biofísicas no semiárido de Pernambuco |
title_full |
Análise da distribuição espaço temporal de variáveis hidrológicas e biofísicas no semiárido de Pernambuco |
title_fullStr |
Análise da distribuição espaço temporal de variáveis hidrológicas e biofísicas no semiárido de Pernambuco |
title_full_unstemmed |
Análise da distribuição espaço temporal de variáveis hidrológicas e biofísicas no semiárido de Pernambuco |
title_sort |
Análise da distribuição espaço temporal de variáveis hidrológicas e biofísicas no semiárido de Pernambuco |
author |
SOUSA, Lizandra de Barros de |
author_facet |
SOUSA, Lizandra de Barros de |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
MONTENEGRO, Abelardo Antônio de Assunção |
dc.contributor.advisor-co1.fl_str_mv |
SILVA, Thieres George Freire da |
dc.contributor.referee1.fl_str_mv |
GIONGO, Pedro Rogério |
dc.contributor.referee2.fl_str_mv |
CARVALHO, Ailton Alves de |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/9251782672090033 |
dc.contributor.author.fl_str_mv |
SOUSA, Lizandra de Barros de |
contributor_str_mv |
MONTENEGRO, Abelardo Antônio de Assunção SILVA, Thieres George Freire da GIONGO, Pedro Rogério CARVALHO, Ailton Alves de |
dc.subject.por.fl_str_mv |
Semiárido Sensoriamento remoto Evapotranspiração Precipitação (Meteorologia) Recurso hídrico Geoestatística |
topic |
Semiárido Sensoriamento remoto Evapotranspiração Precipitação (Meteorologia) Recurso hídrico Geoestatística CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA |
dc.subject.cnpq.fl_str_mv |
CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA |
description |
The Brazilian semi-arid region has limited availability of water resources. In addition, profound changes in land use and occupation have occurred in watersheds of Pernambuco State, such as the implementation of the São Francisco River Integration Project (PISF). This dissertation aims to analyze the spatial distribution of hydrological variables in the semi-arid region of Pernambuco in two basins of this region, one that already has the PISF water supply and while the other does not, but there are future projects for its implementation through branch, are the basins of the Terra Nova and Brígida rivers, respectively. In the Terra Nova river basin, the objective was to evaluate the real evapotranspiration and map cultivated areas through remote sensing in a perennial stretch. Landsat-8 satellite images from 2015 to 2020 were selected. The images were processed in Google Earth Engine (GEE) and edited in QGIS 3.16 software. It was noticed by the NDVI, an increase in the vegetation cover index spatially. Regions with higher values of real evapotranspiration are linked to those with lower temperatures. A smaller amount of cultivated areas was observed in the Terra Nova River stretch in the 2015 images and the expansion of agriculture in the region on the banks of this river, in its perennial stretch. In addition to the pluviometric regime, the release of water from the PISF contributed to the increase in irrigated areas in the region. And in the Brígida river basin, the objective was to evaluate the distribution of precipitation in years under different rainfall regimes and its impacts on the dynamics of vegetation cover, addressing the water-vegetation nexus for the region, where water supply is strongly dependent on the occurrence of rains. Rainfall data from the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) was used in conjunction with observed data from 40 weather stations with an annual time series of 55 years (1962 to 2017). The Standardized Precipitation Index (SPI) was applied to assess the annual variability of precipitation (SPI-12). The data were submitted to classical statistics and geostatistical analysis, using ordinary kriging (KO) and Sequential Gaussian Simulation (SGS) methods to map the spatial distribution of rainfall. A comprehensive set of fifteen remote sensing images for years with different rainfall regimes was analyzed, allowing the calculation of the Normalized Difference Vegetation Index (NDVI) and the Modified Normalized Difference Water Index (MNDWI). There was a high correlation between observed and estimated data. The geostatistical analyzes showed models with strong spatial dependence for all the years adopted. Through kriging maps, it was found that the rainfall in the basin increases strongly with altitude. When the number of SGS realizations increases, SPI maps tend to be stable and capture inherent variability not represented by the kriging procedure. Among the established and validated semivariograms, the spherical model was the one that best fitted the data set used. Through the SGS technique, it was verified the low uncertainty of the CHIRPS data and also that 100 realizations are enough to generate SGS maps suitable for the SPI in the basin. Even in normal years, the number of water bodies is low, which can compromise water security in the region. |
publishDate |
2022 |
dc.date.issued.fl_str_mv |
2022-02-23 |
dc.date.accessioned.fl_str_mv |
2023-06-20T20:11:53Z |
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.citation.fl_str_mv |
SOUSA, Lizandra de Barros de. Análise da distribuição espaço temporal de variáveis hidrológicas e biofísicas no semiárido de Pernambuco. 2022. 110 f. Dissertação (Programa de Pós-Graduação em Engenharia Agrícola) - Universidade Federal Rural de Pernambuco, Recife. |
dc.identifier.uri.fl_str_mv |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9100 |
identifier_str_mv |
SOUSA, Lizandra de Barros de. Análise da distribuição espaço temporal de variáveis hidrológicas e biofísicas no semiárido de Pernambuco. 2022. 110 f. Dissertação (Programa de Pós-Graduação em Engenharia Agrícola) - Universidade Federal Rural de Pernambuco, Recife. |
url |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9100 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.program.fl_str_mv |
-5347692450416052129 |
dc.relation.confidence.fl_str_mv |
600 600 600 |
dc.relation.department.fl_str_mv |
-2862116196355079674 |
dc.relation.cnpq.fl_str_mv |
9185445721588761555 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal Rural de Pernambuco |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Engenharia Agrícola |
dc.publisher.initials.fl_str_mv |
UFRPE |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Departamento de Engenharia Agrícola |
publisher.none.fl_str_mv |
Universidade Federal Rural de Pernambuco |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações da UFRPE instname:Universidade Federal Rural de Pernambuco (UFRPE) instacron:UFRPE |
instname_str |
Universidade Federal Rural de Pernambuco (UFRPE) |
instacron_str |
UFRPE |
institution |
UFRPE |
reponame_str |
Biblioteca Digital de Teses e Dissertações da UFRPE |
collection |
Biblioteca Digital de Teses e Dissertações da UFRPE |
bitstream.url.fl_str_mv |
http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/9100/2/Lizandra+de+Barros+de+Sousa.pdf http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/9100/1/license.txt |
bitstream.checksum.fl_str_mv |
6c4a2de516dd1d0e958a2c0b908cea0c bd3efa91386c1718a7f26a329fdcb468 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações da UFRPE - Universidade Federal Rural de Pernambuco (UFRPE) |
repository.mail.fl_str_mv |
bdtd@ufrpe.br ||bdtd@ufrpe.br |
_version_ |
1810102271659212800 |