Utilização do uso e ocupação da terra obtida por sensoriamento remoto na modelagem hidrológica
Ano de defesa: | 2020 |
---|---|
Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | , , |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de Santa Maria
Centro de Tecnologia |
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Engenharia Ambiental
|
Departamento: |
Engenharia Ambiental
|
País: |
Brasil
|
Palavras-chave em Português: | |
Palavras-chave em Inglês: | |
Área do conhecimento CNPq: | |
Link de acesso: | http://repositorio.ufsm.br/handle/1/24883 |
Resumo: | In recent decades, extreme rainfall-runoff events have increased significantly as a result of climate change and anthropogenic impacts at the global scale. Several authors have reported the influence of land use and land cover (LULC) in this scenario. However, the effects of LULC on the mechanisms that govern the flow generation process, especially in watersheds, are not yet fully understood. The use of hydrological modeling with tools such as remote sensing has been used by researchers to describe the hydrological processes in the catchments. A highlight has been the information obtained from vegetation indexes such as the Enhanced Vegetation Index (EVI2), from the product MOD13. This satellite provides an image with a spatial resolution of 250 m, with a temporal resolution of 16 days, used in applications that describes the vegetations parameter. Using EVI2 information, this work aimed to evaluate the feasibility of using EVI2 information to improve the space-time parameterization of the NCRS-CN method and the SWAT model, in the simulation of the flow generation of two rural watersheds, called WS80 (0.8 km²) and WS140 (1.39 km²), located in the municipality of Júlio de Castilhos, Rio Grande do Sul - Brazil. The simulations used monitored rain-runoff data between 2010 and 2012, using the Curve Number (CN-NRCS) and Soil and Water Assessment Tool (SWAT) models. For the CN-NRCS method, the results showed that there was a correlation between the initial abstraction parameter (Ia) and the LULC variations described by the EVI2 vegetation index, being possible to use the CN-NRCS method with initial abstraction ratio (λ) (variable) by obtaining Ia via EVI2, the performance of this approach was superior to the traditional ones, with λ fixed, in the simulation of the total runoff in the basin rain events. The SWAT model can simulate the flow when no data was available to watersheds, when the rotations crop observed by EVI2 are described and the model setup with the parameters of a neighboring basin (donor). EVI2 demonstrated potential, either as an exploratory or research tool, contributing to the understanding of the behavioral hydrological processes of runoff generation from the two watersheds. |
id |
UFSM_c21ae23eadcfd66e46d9f94c7965eb5d |
---|---|
oai_identifier_str |
oai:repositorio.ufsm.br:1/24883 |
network_acronym_str |
UFSM |
network_name_str |
Biblioteca Digital de Teses e Dissertações do UFSM |
repository_id_str |
|
spelling |
2022-06-15T19:04:26Z2022-06-15T19:04:26Z2020-02-13http://repositorio.ufsm.br/handle/1/24883In recent decades, extreme rainfall-runoff events have increased significantly as a result of climate change and anthropogenic impacts at the global scale. Several authors have reported the influence of land use and land cover (LULC) in this scenario. However, the effects of LULC on the mechanisms that govern the flow generation process, especially in watersheds, are not yet fully understood. The use of hydrological modeling with tools such as remote sensing has been used by researchers to describe the hydrological processes in the catchments. A highlight has been the information obtained from vegetation indexes such as the Enhanced Vegetation Index (EVI2), from the product MOD13. This satellite provides an image with a spatial resolution of 250 m, with a temporal resolution of 16 days, used in applications that describes the vegetations parameter. Using EVI2 information, this work aimed to evaluate the feasibility of using EVI2 information to improve the space-time parameterization of the NCRS-CN method and the SWAT model, in the simulation of the flow generation of two rural watersheds, called WS80 (0.8 km²) and WS140 (1.39 km²), located in the municipality of Júlio de Castilhos, Rio Grande do Sul - Brazil. The simulations used monitored rain-runoff data between 2010 and 2012, using the Curve Number (CN-NRCS) and Soil and Water Assessment Tool (SWAT) models. For the CN-NRCS method, the results showed that there was a correlation between the initial abstraction parameter (Ia) and the LULC variations described by the EVI2 vegetation index, being possible to use the CN-NRCS method with initial abstraction ratio (λ) (variable) by obtaining Ia via EVI2, the performance of this approach was superior to the traditional ones, with λ fixed, in the simulation of the total runoff in the basin rain events. The SWAT model can simulate the flow when no data was available to watersheds, when the rotations crop observed by EVI2 are described and the model setup with the parameters of a neighboring basin (donor). EVI2 demonstrated potential, either as an exploratory or research tool, contributing to the understanding of the behavioral hydrological processes of runoff generation from the two watersheds.Nas últimas décadas os eventos extremos de chuva e de vazão aumentaram significativamente em decorrência das mudanças climáticas e das alterações antropogênicas em nível global. Vários autores reportaram a influência das mudanças de uso e ocupação da terra (LULC) neste cenário. Todavia, os efeitos do LULC nos mecanismos que governam o processo de geração de escoamento, principalmente em bacias hidrográficas, ainda não estão totalmente elucidados. Para o melhor entendimento desses fenômenos, o uso de modelos hidrológicos aliados a ferramentas como o sensoriamento remoto tem sido utilizado por pesquisadores para descrever os processos hidrológicos das bacias. Um destaque tem sido a utilização de informações obtidas a partir de índices de vegetação como o EVI2 (Enhanced Vegetation Index - 2), obtido a partir do produto MOD13. Esse satélite fornece uma imagem com resolução espacial de 250 m para toda a superfície da Terra, com uma resolução temporal de 16 dias, que é usado em aplicações que descrevem os atributos da cobertura vegetal do solo. Utilizando informações de EVI2, este trabalho teve como objetivo principal avaliar a viabilidade de uso da informação do EVI2 para aprimorar a parametrização espaço-temporal do método NCRS-CN e do modelo SWAT, na simulação da geração de escoamento de duas bacias hidrográficas rurais, denominadas WS80 (0.8 km²) e WS140 (1.39 km²), localizadas no município de Júlio de Castilhos, Rio Grande do Sul – Brasil. As informações de EVI2 foram utilizadas para descrever o LULC. As simulações utilizaram dados monitorados de chuva-vazão entre 2010 e 2012, sendo empregado os modelos Curve Number (CN-NRCS) e Soil and Water Assessment Tool (SWAT). Para o método CN-NRCS os resultados demonstraram que houve correlação entre o parâmetro de abstração inicial (Ia) e as variações de LULC descritas pelo índice de vegetação EVI2, sendo possível utilizar o método CNNRCS com taxa de abstração inicial (λ) observada (variável) obtendo-se a Ia via EVI2, o desempenho desta abordagem foi superior as tradicionais, com λ fixo, na simulação do escoamento total nos eventos de chuva das bacias. O modelo SWAT pode simular a vazão de bacias sem dados, quando descritas as rotações de cultura observadas pelo EVI2 e configurado com os parâmetros de uma bacia vizinha (doadora). O EVI2 demonstrou potencial, seja como ferramenta exploratória ou de pesquisa, contribuindo para a compreensão dos processos hidrológicos que comandam a geração de escoamento das duas bacias.porUniversidade Federal de Santa MariaCentro de TecnologiaPrograma de Pós-Graduação em Engenharia AmbientalUFSMBrasilEngenharia AmbientalAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessÍndice de vegetaçãoSWATCurve numberVegetation indexCurve numberCNPQ::ENGENHARIASUtilização do uso e ocupação da terra obtida por sensoriamento remoto na modelagem hidrológicaApplications of land use and land cover remote sensing for hydrologic modelinginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisPiccilli, Daniel Gustavo Allasiahttp://lattes.cnpq.br/3858010328968944Santos, Danilo Rheinheimer dosSantos, Danilo Rheinheimer dosTassi, RutineiaTornquist, Carlos Gustavohttp://lattes.cnpq.br/6462704767442339Rippel, Elzon Cassio3000000000096006006006006006006001c2baa5d-393c-455f-a5e2-fb47cd900c30bf279849-56d7-4296-abb3-3f723e775358b1caca50-0dc7-4a83-88d7-b77e552bd2c0d41c65ce-23ef-44ce-aecc-cfc113b6b9243ec07027-cc34-4a52-9c01-1d1c434ac9d40beed3da-ff69-420e-804d-be3d3ace855dreponame:Biblioteca Digital de Teses e Dissertações do UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805http://repositorio.ufsm.br/bitstream/1/24883/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81956http://repositorio.ufsm.br/bitstream/1/24883/3/license.txt2f0571ecee68693bd5cd3f17c1e075dfMD53ORIGINALDIS_PPGEA_2020_RIPPEL_ELZON.pdfDIS_PPGEA_2020_RIPPEL_ELZON.pdfDissertação de mestradoapplication/pdf2693014http://repositorio.ufsm.br/bitstream/1/24883/1/DIS_PPGEA_2020_RIPPEL_ELZON.pdf5624db23490970ca50ecdc094f63d8c6MD511/248832022-06-15 16:04:26.133oai:repositorio.ufsm.br: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 Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2022-06-15T19:04:26Biblioteca Digital de Teses e Dissertações do UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.por.fl_str_mv |
Utilização do uso e ocupação da terra obtida por sensoriamento remoto na modelagem hidrológica |
dc.title.alternative.eng.fl_str_mv |
Applications of land use and land cover remote sensing for hydrologic modeling |
title |
Utilização do uso e ocupação da terra obtida por sensoriamento remoto na modelagem hidrológica |
spellingShingle |
Utilização do uso e ocupação da terra obtida por sensoriamento remoto na modelagem hidrológica Rippel, Elzon Cassio Índice de vegetação SWAT Curve number Vegetation index Curve number CNPQ::ENGENHARIAS |
title_short |
Utilização do uso e ocupação da terra obtida por sensoriamento remoto na modelagem hidrológica |
title_full |
Utilização do uso e ocupação da terra obtida por sensoriamento remoto na modelagem hidrológica |
title_fullStr |
Utilização do uso e ocupação da terra obtida por sensoriamento remoto na modelagem hidrológica |
title_full_unstemmed |
Utilização do uso e ocupação da terra obtida por sensoriamento remoto na modelagem hidrológica |
title_sort |
Utilização do uso e ocupação da terra obtida por sensoriamento remoto na modelagem hidrológica |
author |
Rippel, Elzon Cassio |
author_facet |
Rippel, Elzon Cassio |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Piccilli, Daniel Gustavo Allasia |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/3858010328968944 |
dc.contributor.advisor-co1.fl_str_mv |
Santos, Danilo Rheinheimer dos |
dc.contributor.referee1.fl_str_mv |
Santos, Danilo Rheinheimer dos |
dc.contributor.referee2.fl_str_mv |
Tassi, Rutineia |
dc.contributor.referee3.fl_str_mv |
Tornquist, Carlos Gustavo |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/6462704767442339 |
dc.contributor.author.fl_str_mv |
Rippel, Elzon Cassio |
contributor_str_mv |
Piccilli, Daniel Gustavo Allasia Santos, Danilo Rheinheimer dos Santos, Danilo Rheinheimer dos Tassi, Rutineia Tornquist, Carlos Gustavo |
dc.subject.por.fl_str_mv |
Índice de vegetação SWAT Curve number |
topic |
Índice de vegetação SWAT Curve number Vegetation index Curve number CNPQ::ENGENHARIAS |
dc.subject.eng.fl_str_mv |
Vegetation index Curve number |
dc.subject.cnpq.fl_str_mv |
CNPQ::ENGENHARIAS |
description |
In recent decades, extreme rainfall-runoff events have increased significantly as a result of climate change and anthropogenic impacts at the global scale. Several authors have reported the influence of land use and land cover (LULC) in this scenario. However, the effects of LULC on the mechanisms that govern the flow generation process, especially in watersheds, are not yet fully understood. The use of hydrological modeling with tools such as remote sensing has been used by researchers to describe the hydrological processes in the catchments. A highlight has been the information obtained from vegetation indexes such as the Enhanced Vegetation Index (EVI2), from the product MOD13. This satellite provides an image with a spatial resolution of 250 m, with a temporal resolution of 16 days, used in applications that describes the vegetations parameter. Using EVI2 information, this work aimed to evaluate the feasibility of using EVI2 information to improve the space-time parameterization of the NCRS-CN method and the SWAT model, in the simulation of the flow generation of two rural watersheds, called WS80 (0.8 km²) and WS140 (1.39 km²), located in the municipality of Júlio de Castilhos, Rio Grande do Sul - Brazil. The simulations used monitored rain-runoff data between 2010 and 2012, using the Curve Number (CN-NRCS) and Soil and Water Assessment Tool (SWAT) models. For the CN-NRCS method, the results showed that there was a correlation between the initial abstraction parameter (Ia) and the LULC variations described by the EVI2 vegetation index, being possible to use the CN-NRCS method with initial abstraction ratio (λ) (variable) by obtaining Ia via EVI2, the performance of this approach was superior to the traditional ones, with λ fixed, in the simulation of the total runoff in the basin rain events. The SWAT model can simulate the flow when no data was available to watersheds, when the rotations crop observed by EVI2 are described and the model setup with the parameters of a neighboring basin (donor). EVI2 demonstrated potential, either as an exploratory or research tool, contributing to the understanding of the behavioral hydrological processes of runoff generation from the two watersheds. |
publishDate |
2020 |
dc.date.issued.fl_str_mv |
2020-02-13 |
dc.date.accessioned.fl_str_mv |
2022-06-15T19:04:26Z |
dc.date.available.fl_str_mv |
2022-06-15T19:04:26Z |
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 |
http://repositorio.ufsm.br/handle/1/24883 |
url |
http://repositorio.ufsm.br/handle/1/24883 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.cnpq.fl_str_mv |
300000000009 |
dc.relation.confidence.fl_str_mv |
600 600 600 600 600 600 600 |
dc.relation.authority.fl_str_mv |
1c2baa5d-393c-455f-a5e2-fb47cd900c30 bf279849-56d7-4296-abb3-3f723e775358 b1caca50-0dc7-4a83-88d7-b77e552bd2c0 d41c65ce-23ef-44ce-aecc-cfc113b6b924 3ec07027-cc34-4a52-9c01-1d1c434ac9d4 0beed3da-ff69-420e-804d-be3d3ace855d |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Tecnologia |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Engenharia Ambiental |
dc.publisher.initials.fl_str_mv |
UFSM |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Engenharia Ambiental |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Tecnologia |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações do UFSM instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Biblioteca Digital de Teses e Dissertações do UFSM |
collection |
Biblioteca Digital de Teses e Dissertações do UFSM |
bitstream.url.fl_str_mv |
http://repositorio.ufsm.br/bitstream/1/24883/2/license_rdf http://repositorio.ufsm.br/bitstream/1/24883/3/license.txt http://repositorio.ufsm.br/bitstream/1/24883/1/DIS_PPGEA_2020_RIPPEL_ELZON.pdf |
bitstream.checksum.fl_str_mv |
4460e5956bc1d1639be9ae6146a50347 2f0571ecee68693bd5cd3f17c1e075df 5624db23490970ca50ecdc094f63d8c6 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações do UFSM - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
atendimento.sib@ufsm.br||tedebc@gmail.com |
_version_ |
1793239962978615296 |