2017
DOI: 10.1590/2318-0331.011716090
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Multi-variable SWAT model calibration with remotely sensed evapotranspiration and observed flow

Abstract: Although intrinsic, uncertainty for hydrological model estimation is not always reported. The aim of this study is to evaluate the use of satellite-based evapotranspiration on SWAT model calibration, regarding uncertainty and model performance in streamflow simulation. The SWAT model was calibrated in a monthly step and validated in monthly (streamflow and evapotranspiration) and daily steps (streamflow only). The validation and calibration period covers the years from 2006 to 2009 and the study area is the up… Show more

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Cited by 31 publications
(24 citation statements)
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“…The best calibration achieved was an R 2 of 0.69, PBIAS of 4.86, ENS of 0.67, and KGE of 0.82. Note that KGE was used as an objective function type in the SUFI-2 calibration and validation because it could be decomposed into three terms that represented the correlation, bias, and relative variability between the measured and simulated values [65]. Hence, it allowed the simultaneous use of baseflow and streamflow in calibration and enabled comparison between different strategies.…”
Section: Swat Model Calibration and Validation Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The best calibration achieved was an R 2 of 0.69, PBIAS of 4.86, ENS of 0.67, and KGE of 0.82. Note that KGE was used as an objective function type in the SUFI-2 calibration and validation because it could be decomposed into three terms that represented the correlation, bias, and relative variability between the measured and simulated values [65]. Hence, it allowed the simultaneous use of baseflow and streamflow in calibration and enabled comparison between different strategies.…”
Section: Swat Model Calibration and Validation Resultsmentioning
confidence: 99%
“…However, streamflow was overestimated for most of the light rainfall events (dry climate periods) and showed very good agreement with the large rainfall events (wet periods). Previous studies have shown that SWAT performed better under more humid climatic conditions [65,66]. In addition, SWAT has some problems with precisely accounting for water loss through infiltration and evapotranspiration, especially during dry climate seasons, and evaluating the soil moisture storage [67][68][69].…”
Section: Swat Model Calibration and Validation Resultsmentioning
confidence: 99%
“…Estudos referentes à calibração e validação do modelo SWAT são realizados em todo mundo. No Brasil há trabalhos que realizaram estes procedimentos e obtiveram resultados satisfatórios (Rodrigues et al, 2015;Pereira et al, 2016;Brighenti et al, 2016;Monteiro et al, 2016;Pontes et al, 2016;Franco e Bonumá, 2017;Paz et al, 2018;Santos et al, 2018), comprovando, que o modelo se aplica às regiões edafoclimáticas diferentes das quais foi desenvolvido. O principal obstáculo para a calibração do modelo em bacias hidrográficas brasileiras é a disponibilidade de dados confiáveis, que quando existentes, geralmente apresentam elevado percentual de falhas, aumentando a dificuldade do processo de calibração (Brigenthi et al, 2016;Andrade et al, 2017).…”
Section: Introductionunclassified
“…There are five different calibration methods in SWAT-CUP: SUFI-2, PSO, GLUE, ParaSol and MSMC. The SUFI-2 method was selected because of the good results found in several studies (DAGUPPATI et al, 2015a;FRANCO;BONUMÁ, 2017;PONTES et al, 2016) and its applicability in developed countries in several regions of Brazil. The chosen method includes an uncertainty analysis and can work with a large number of parameters (Abbaspour, 2005).…”
Section: Analysis Of Sensitivity and Calibration Of The Modelmentioning
confidence: 99%
“…Most Brazilian studies have conducted sensitivity, calibration and validation analyses using data for only one watershed outlet, as can be seen in the works of Andrade, Mello and Beskow (2013), Pereira et al (2014aPereira et al ( , 2014b, Rodrigues et al (2015); Brighenti, Bonuma and Chaffe (2016), and Franco and Bonumá (2017); however, some studies have used more detailed calibration and validation techniques, for example, Lelis et al (2012), Bressiani et al (2015), and Eduardo et al (2016). Calibration using data from a single outlet, as indicated by Daggupati et al (2015a) may be adequate for small basins with uniform features, but for larger basins the results can produce mean parameter values that are overestimated or underestimated at several points, and require spatially distributed calibration.…”
Section: Introductionmentioning
confidence: 99%