Interferência do intervalo de medição da precipitação na predição da infiltração de água no solo pelos modelos Hydrus- 1D e Green Ampt
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 Ciências Rurais |
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Ciência do Solo
|
Departamento: |
Agronomia
|
País: |
Brasil
|
Palavras-chave em Português: | |
Palavras-chave em Inglês: | |
Área do conhecimento CNPq: | |
Link de acesso: | http://repositorio.ufsm.br/handle/1/22003 |
Resumo: | Mathematical modeling of water infiltration into the soil by means of physical-based models is a valuable tool in forecasting scenarios that assist in solving environmental problems such as floods, soil erosion, runoff and landslides. Therefore, research aimed at investigating factors that could compromise the estimates of these models is useful. In this dissertation, we investigate how the precipitation measurement interval (PMI) affects the prediction of water infiltration in the soil of two physical-based models: HYDRUS-1D and Green Ampt (GA). We also determine whether the weather station's PMI is sufficiently detailed for these models to make accurate predictions of infiltration. The infiltration of water in the soil was simulated for precipitation events that occurred in two experimental areas, with 13 precipitation events in experimental area I (AI) and 5 events in experimental area II (AII). The accumulated rainfall of the events analyzed in AI and AII, measured every 2 and 5 min, respectively, was converted into discrete precipitation intensity profiles every 2 min, 5 min, 15 min, 30 min, 1 h, 2 h, 6 h, 12 h and 24 h, simulating the increase in PMI. The calibration of the models was done by modifying the hydraulic conductivity of the saturated soil in order to approximate the estimated accumulated runoff (Eest) by the models of the observed accumulated runoff (Eobs). The performance of the models was assessed by the square root of the mean square error (RMSE), comparing Eest with Eobs. The more detailed the PMI, the lower the RMSE. Precipitation from meteorological stations with an PMI of 60 min does not allow an efficient calibration and is not detailed enough for the models to accurately simulate infiltration. With the models calibrated using precipitation with an PMI of 2 min, changing the PMI of the same precipitation to 5 min caused an underestimation of the runoff in the order of 40% for HYDRUS-1D and 45% for GA. Thus, we conclude that the PMI dramatically compromises the accuracy of the estimates of the models. |
id |
UFSM_e97914d1bf800e56daa8e53bd17d4197 |
---|---|
oai_identifier_str |
oai:repositorio.ufsm.br:1/22003 |
network_acronym_str |
UFSM |
network_name_str |
Biblioteca Digital de Teses e Dissertações do UFSM |
repository_id_str |
|
spelling |
2021-08-19T17:22:37Z2021-08-19T17:22:37Z2020-02-19http://repositorio.ufsm.br/handle/1/22003Mathematical modeling of water infiltration into the soil by means of physical-based models is a valuable tool in forecasting scenarios that assist in solving environmental problems such as floods, soil erosion, runoff and landslides. Therefore, research aimed at investigating factors that could compromise the estimates of these models is useful. In this dissertation, we investigate how the precipitation measurement interval (PMI) affects the prediction of water infiltration in the soil of two physical-based models: HYDRUS-1D and Green Ampt (GA). We also determine whether the weather station's PMI is sufficiently detailed for these models to make accurate predictions of infiltration. The infiltration of water in the soil was simulated for precipitation events that occurred in two experimental areas, with 13 precipitation events in experimental area I (AI) and 5 events in experimental area II (AII). The accumulated rainfall of the events analyzed in AI and AII, measured every 2 and 5 min, respectively, was converted into discrete precipitation intensity profiles every 2 min, 5 min, 15 min, 30 min, 1 h, 2 h, 6 h, 12 h and 24 h, simulating the increase in PMI. The calibration of the models was done by modifying the hydraulic conductivity of the saturated soil in order to approximate the estimated accumulated runoff (Eest) by the models of the observed accumulated runoff (Eobs). The performance of the models was assessed by the square root of the mean square error (RMSE), comparing Eest with Eobs. The more detailed the PMI, the lower the RMSE. Precipitation from meteorological stations with an PMI of 60 min does not allow an efficient calibration and is not detailed enough for the models to accurately simulate infiltration. With the models calibrated using precipitation with an PMI of 2 min, changing the PMI of the same precipitation to 5 min caused an underestimation of the runoff in the order of 40% for HYDRUS-1D and 45% for GA. Thus, we conclude that the PMI dramatically compromises the accuracy of the estimates of the models.A modelagem matemática da infiltração de água no solo por meio de modelos de base física é uma ferramenta valiosa na previsão de cenários que auxiliam na solução de problemas ambientais como inundações, erosão do solo, escoamento superficial e deslizamentos de terra. Portanto, pesquisas que visam investigar fatores que possam comprometer as estimativas desses modelos são úteis. Nesta dissertação, investigamos como o intervalo de medição da precipitação (IMP) afeta a predição de infiltração de água no solo de dois modelos de base física: o HYDRUS-1D e Green Ampt (GA). Também determinamos se o IMP das estações meteorológicas é suficientemente detalhado para que esses modelos façam predições acuradas da infiltração. A infiltração de água no solo foi simulada para eventos de precipitação ocorridos em duas áreas experimentais, sendo 13 eventos de precipitação na área experimental I (AI) e 5 eventos na área experimental II (AII). O acumulado de precipitação dos eventos analisados em AI e AII, medidos a cada 2 e 5 min, respectivamente, foi convertido em perfis discretos de intensidade de precipitação a cada 2 min, 5 min, 15 min, 30 min,1 h, 2 h, 6 h, 12 h e 24 h, simulando o aumento do IMP. A calibração dos modelos foi feita com a modificação da condutividade hidráulica do solo saturado de modo a aproximar o escoamento superficial acumulado estimado (Eest) pelos modelos do escoamento superficial acumulado observado (Eobs). O desempenho dos modelos foi avaliado pela raiz quadrática do erro médio quadrático (RMSE em inglês), comparando o Eest com o Eobs Quanto mais detalhado o IMP, menor a RMSE. As precipitações das estações meteorológicas com IMP de 60 min não possibilitam boa calibração e não são suficientemente detalhadas para que os modelos simulem com acurácia a infiltração. Com os modelos calibrados usando precipitação com IMP de 2 min, a mudança do IMP da mesma precipitação para 5 min causou uma subestimativa do escoamento na ordem de 40% para o HYDRUS-1D e 45% para o GA. Assim, concluímos que o IMP compromete drasticamente a acurácia das estimativas dos modelos.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESporUniversidade Federal de Santa MariaCentro de Ciências RuraisPrograma de Pós-Graduação em Ciência do SoloUFSMBrasilAgronomiaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessEscoamento superficialEstações meteorológicasModelagemSurface runoffWeather stationsModelingCNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLOInterferência do intervalo de medição da precipitação na predição da infiltração de água no solo pelos modelos Hydrus- 1D e Green AmptInterference of the precipitation measurement interval on prediction of water infiltration in soil by Hydrus-1D and Green Ampt modelsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisGubiani, Paulo Ivonirhttp://lattes.cnpq.br/7251203817503318Reinert, Dalvan JoséMallmann, Fábio Joel KochemPinheiro, Everton Alves Rodrigueshttp://lattes.cnpq.br/5881077675915160Fachi, Suelen Matiasso500100100005600600600600d1a52158-63ad-4c62-8e58-1558d624b50f4fa9553f-7f5f-488c-b868-3e12e36cd6d9ee327c38-9972-43bb-b34c-6fc577288ad4e344ba28-5d80-4e33-9d5b-af44ab3ccc1f1f0070a3-ddfa-4ab8-aa9d-a1a7b780745creponame:Biblioteca Digital de Teses e Dissertações do UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALDIS_PPGCS_2020_FACHI_SUELEN.pdfDIS_PPGCS_2020_FACHI_SUELEN.pdfDissertaçãoapplication/pdf995204http://repositorio.ufsm.br/bitstream/1/22003/1/DIS_PPGCS_2020_FACHI_SUELEN.pdf29d01a7a49ad6673b2f31c8eac91152bMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805http://repositorio.ufsm.br/bitstream/1/22003/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81956http://repositorio.ufsm.br/bitstream/1/22003/3/license.txt2f0571ecee68693bd5cd3f17c1e075dfMD53TEXTDIS_PPGCS_2020_FACHI_SUELEN.pdf.txtDIS_PPGCS_2020_FACHI_SUELEN.pdf.txtExtracted texttext/plain110412http://repositorio.ufsm.br/bitstream/1/22003/4/DIS_PPGCS_2020_FACHI_SUELEN.pdf.txt06b8ef933ac654deb73bdcd8744d86edMD54THUMBNAILDIS_PPGCS_2020_FACHI_SUELEN.pdf.jpgDIS_PPGCS_2020_FACHI_SUELEN.pdf.jpgIM Thumbnailimage/jpeg4365http://repositorio.ufsm.br/bitstream/1/22003/5/DIS_PPGCS_2020_FACHI_SUELEN.pdf.jpgf7c1b95dd40bf5b060d700c319edda08MD551/220032021-08-20 03:00:48.175oai: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:2021-08-20T06:00:48Biblioteca Digital de Teses e Dissertações do UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.por.fl_str_mv |
Interferência do intervalo de medição da precipitação na predição da infiltração de água no solo pelos modelos Hydrus- 1D e Green Ampt |
dc.title.alternative.eng.fl_str_mv |
Interference of the precipitation measurement interval on prediction of water infiltration in soil by Hydrus-1D and Green Ampt models |
title |
Interferência do intervalo de medição da precipitação na predição da infiltração de água no solo pelos modelos Hydrus- 1D e Green Ampt |
spellingShingle |
Interferência do intervalo de medição da precipitação na predição da infiltração de água no solo pelos modelos Hydrus- 1D e Green Ampt Fachi, Suelen Matiasso Escoamento superficial Estações meteorológicas Modelagem Surface runoff Weather stations Modeling CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLO |
title_short |
Interferência do intervalo de medição da precipitação na predição da infiltração de água no solo pelos modelos Hydrus- 1D e Green Ampt |
title_full |
Interferência do intervalo de medição da precipitação na predição da infiltração de água no solo pelos modelos Hydrus- 1D e Green Ampt |
title_fullStr |
Interferência do intervalo de medição da precipitação na predição da infiltração de água no solo pelos modelos Hydrus- 1D e Green Ampt |
title_full_unstemmed |
Interferência do intervalo de medição da precipitação na predição da infiltração de água no solo pelos modelos Hydrus- 1D e Green Ampt |
title_sort |
Interferência do intervalo de medição da precipitação na predição da infiltração de água no solo pelos modelos Hydrus- 1D e Green Ampt |
author |
Fachi, Suelen Matiasso |
author_facet |
Fachi, Suelen Matiasso |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Gubiani, Paulo Ivonir |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/7251203817503318 |
dc.contributor.advisor-co1.fl_str_mv |
Reinert, Dalvan José |
dc.contributor.referee1.fl_str_mv |
Mallmann, Fábio Joel Kochem |
dc.contributor.referee2.fl_str_mv |
Pinheiro, Everton Alves Rodrigues |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/5881077675915160 |
dc.contributor.author.fl_str_mv |
Fachi, Suelen Matiasso |
contributor_str_mv |
Gubiani, Paulo Ivonir Reinert, Dalvan José Mallmann, Fábio Joel Kochem Pinheiro, Everton Alves Rodrigues |
dc.subject.por.fl_str_mv |
Escoamento superficial Estações meteorológicas Modelagem |
topic |
Escoamento superficial Estações meteorológicas Modelagem Surface runoff Weather stations Modeling CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLO |
dc.subject.eng.fl_str_mv |
Surface runoff Weather stations Modeling |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLO |
description |
Mathematical modeling of water infiltration into the soil by means of physical-based models is a valuable tool in forecasting scenarios that assist in solving environmental problems such as floods, soil erosion, runoff and landslides. Therefore, research aimed at investigating factors that could compromise the estimates of these models is useful. In this dissertation, we investigate how the precipitation measurement interval (PMI) affects the prediction of water infiltration in the soil of two physical-based models: HYDRUS-1D and Green Ampt (GA). We also determine whether the weather station's PMI is sufficiently detailed for these models to make accurate predictions of infiltration. The infiltration of water in the soil was simulated for precipitation events that occurred in two experimental areas, with 13 precipitation events in experimental area I (AI) and 5 events in experimental area II (AII). The accumulated rainfall of the events analyzed in AI and AII, measured every 2 and 5 min, respectively, was converted into discrete precipitation intensity profiles every 2 min, 5 min, 15 min, 30 min, 1 h, 2 h, 6 h, 12 h and 24 h, simulating the increase in PMI. The calibration of the models was done by modifying the hydraulic conductivity of the saturated soil in order to approximate the estimated accumulated runoff (Eest) by the models of the observed accumulated runoff (Eobs). The performance of the models was assessed by the square root of the mean square error (RMSE), comparing Eest with Eobs. The more detailed the PMI, the lower the RMSE. Precipitation from meteorological stations with an PMI of 60 min does not allow an efficient calibration and is not detailed enough for the models to accurately simulate infiltration. With the models calibrated using precipitation with an PMI of 2 min, changing the PMI of the same precipitation to 5 min caused an underestimation of the runoff in the order of 40% for HYDRUS-1D and 45% for GA. Thus, we conclude that the PMI dramatically compromises the accuracy of the estimates of the models. |
publishDate |
2020 |
dc.date.issued.fl_str_mv |
2020-02-19 |
dc.date.accessioned.fl_str_mv |
2021-08-19T17:22:37Z |
dc.date.available.fl_str_mv |
2021-08-19T17:22:37Z |
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/1/22003 |
url |
http://repositorio.ufsm.br/handle/1/22003 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.cnpq.fl_str_mv |
500100100005 |
dc.relation.confidence.fl_str_mv |
600 600 600 600 |
dc.relation.authority.fl_str_mv |
d1a52158-63ad-4c62-8e58-1558d624b50f 4fa9553f-7f5f-488c-b868-3e12e36cd6d9 ee327c38-9972-43bb-b34c-6fc577288ad4 e344ba28-5d80-4e33-9d5b-af44ab3ccc1f 1f0070a3-ddfa-4ab8-aa9d-a1a7b780745c |
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 Ciências Rurais |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Ciência do Solo |
dc.publisher.initials.fl_str_mv |
UFSM |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Agronomia |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Ciências Rurais |
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/1/22003/1/DIS_PPGCS_2020_FACHI_SUELEN.pdf http://repositorio.ufsm.br/bitstream/1/22003/2/license_rdf http://repositorio.ufsm.br/bitstream/1/22003/3/license.txt http://repositorio.ufsm.br/bitstream/1/22003/4/DIS_PPGCS_2020_FACHI_SUELEN.pdf.txt http://repositorio.ufsm.br/bitstream/1/22003/5/DIS_PPGCS_2020_FACHI_SUELEN.pdf.jpg |
bitstream.checksum.fl_str_mv |
29d01a7a49ad6673b2f31c8eac91152b 4460e5956bc1d1639be9ae6146a50347 2f0571ecee68693bd5cd3f17c1e075df 06b8ef933ac654deb73bdcd8744d86ed f7c1b95dd40bf5b060d700c319edda08 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 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_ |
1793240160226246656 |