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 | Acesso ao texto completo restrito à biblioteca da Embrapa Cerrados. Para informações adicionais entre em contato com cpac.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Cerrados. |
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Data corrente: |
20/08/2021 |
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Data da última atualização: |
20/08/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
ALTHOFF, D.; RODRIGUES, L. N. |
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Afiliação: |
DANIEL ALTHOFF; LINEU NEIVA RODRIGUES, CPAC. |
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Título: |
Goodness-of-fit criteria for hydrological models: Model calibration and performance assessment. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Journal of Hydrology, v. 600, 2021. |
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Páginas: |
15 p. |
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DOI: |
https://doi.org/10.1016/j.jhydrol.2021.126674 |
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Idioma: |
Inglês |
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Conteúdo: |
ABSTRACT This study provides guidelines for the selection of proper goodness-of-fit criteria for the calibration and evaluation of hydrological models. Popular goodness-of-fit criteria and good practices for hydrological modeling are reviewed. The review discusses the advantages and disadvantages of several criteria and is followed by a case study that focuses on the review?s main findings. The main recommendation is for hydrologists to avoid using threshold values to assess model performance and preferably set a proper benchmark series. The case study was developed using the GR5J hydrological model and data from 179 watersheds in the Brazilian Cerrado biome. Several single- and multi-objective functions are used in optimization runs to assess the outcome for different goodness-of-fit criteria. The model performance is evaluated for each optimization run considering overall conditions, i.e., entire time series, and conditions under low- and peak-flow conditions. The study case reinforces that the popular Nash-Sutcliffe efficiency index should be avoided as an objective function. Alternatively, the Kling-Gupta efficiency index showed to be a more reliable criterion, resulting in lower bias for both calibration and validation, and balanced results for both low- and peak-flow conditions. Additionally, combining different criteria in multi-objective functions can result in robust trade-offs. General guidelines are summarized and additional emphasis is given to tropical watersheds where low flows deserve due attention. MenosABSTRACT This study provides guidelines for the selection of proper goodness-of-fit criteria for the calibration and evaluation of hydrological models. Popular goodness-of-fit criteria and good practices for hydrological modeling are reviewed. The review discusses the advantages and disadvantages of several criteria and is followed by a case study that focuses on the review?s main findings. The main recommendation is for hydrologists to avoid using threshold values to assess model performance and preferably set a proper benchmark series. The case study was developed using the GR5J hydrological model and data from 179 watersheds in the Brazilian Cerrado biome. Several single- and multi-objective functions are used in optimization runs to assess the outcome for different goodness-of-fit criteria. The model performance is evaluated for each optimization run considering overall conditions, i.e., entire time series, and conditions under low- and peak-flow conditions. The study case reinforces that the popular Nash-Sutcliffe efficiency index should be avoided as an objective function. Alternatively, the Kling-Gupta efficiency index showed to be a more reliable criterion, resulting in lower bias for both calibration and validation, and balanced results for both low- and peak-flow conditions. Additionally, combining different criteria in multi-objective functions can result in robust trade-offs. General guidelines are summarized and additional emphasis is given to tropical watershed... Mostrar Tudo |
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Palavras-Chave: |
Assinatura hidrológica; Bacia hidrográfica tropical; Modelo GR5J; Otimização de enxame de particulas; Otimização multi-objetivo. |
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Thesagro: |
Recurso Hídrico. |
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Categoria do assunto: |
-- |
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Marc: |
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008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.jhydrol.2021.126674$2DOI
100 1 $aALTHOFF, D.
245 $aGoodness-of-fit criteria for hydrological models$bModel calibration and performance assessment.$h[electronic resource]
260 $c2021
300 $a15 p.
520 $aABSTRACT This study provides guidelines for the selection of proper goodness-of-fit criteria for the calibration and evaluation of hydrological models. Popular goodness-of-fit criteria and good practices for hydrological modeling are reviewed. The review discusses the advantages and disadvantages of several criteria and is followed by a case study that focuses on the review?s main findings. The main recommendation is for hydrologists to avoid using threshold values to assess model performance and preferably set a proper benchmark series. The case study was developed using the GR5J hydrological model and data from 179 watersheds in the Brazilian Cerrado biome. Several single- and multi-objective functions are used in optimization runs to assess the outcome for different goodness-of-fit criteria. The model performance is evaluated for each optimization run considering overall conditions, i.e., entire time series, and conditions under low- and peak-flow conditions. The study case reinforces that the popular Nash-Sutcliffe efficiency index should be avoided as an objective function. Alternatively, the Kling-Gupta efficiency index showed to be a more reliable criterion, resulting in lower bias for both calibration and validation, and balanced results for both low- and peak-flow conditions. Additionally, combining different criteria in multi-objective functions can result in robust trade-offs. General guidelines are summarized and additional emphasis is given to tropical watersheds where low flows deserve due attention.
650 $aRecurso Hídrico
653 $aAssinatura hidrológica
653 $aBacia hidrográfica tropical
653 $aModelo GR5J
653 $aOtimização de enxame de particulas
653 $aOtimização multi-objetivo
700 1 $aRODRIGUES, L. N.
773 $tJournal of Hydrology$gv. 600, 2021.
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