Registro Completo
Biblioteca(s): |
Embrapa Cerrados. |
Data corrente: |
20/08/2021 |
Data da última atualização: |
20/08/2021 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
ALTHOFF, D.; RODRIGUES, L. N. |
Afiliação: |
DANIEL ALTHOFF; LINEU NEIVA RODRIGUES, CPAC. |
Título: |
Goodness-of-fit criteria for hydrological models: Model calibration and performance assessment. |
Ano de publicação: |
2021 |
Fonte/Imprenta: |
Journal of Hydrology, v. 600, 2021. |
Páginas: |
15 p. |
DOI: |
https://doi.org/10.1016/j.jhydrol.2021.126674 |
Idioma: |
Inglês |
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 |
Palavras-Chave: |
Assinatura hidrológica; Bacia hidrográfica tropical; Modelo GR5J; Otimização de enxame de particulas; Otimização multi-objetivo. |
Thesagro: |
Recurso Hídrico. |
Categoria do assunto: |
-- |
Marc: |
LEADER 02279naa a2200229 a 4500 001 2133766 005 2021-08-20 008 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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Registro original: |
Embrapa Cerrados (CPAC) |
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