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Multi-objective conditioning of a simple SVAT model.

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Multi-objective conditioning of a simple SVAT model. / Franks, S. W.; Beven, Keith J.; Gash, J. H. C.
In: Hydrology and Earth System Sciences, Vol. 3, No. 4, 1999, p. 477-489.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Franks, SW, Beven, KJ & Gash, JHC 1999, 'Multi-objective conditioning of a simple SVAT model.', Hydrology and Earth System Sciences, vol. 3, no. 4, pp. 477-489. <http://www.hydrol-earth-syst-sci.net/3/477/1999/hess-3-477-1999.html>

APA

Franks, S. W., Beven, K. J., & Gash, J. H. C. (1999). Multi-objective conditioning of a simple SVAT model. Hydrology and Earth System Sciences, 3(4), 477-489. http://www.hydrol-earth-syst-sci.net/3/477/1999/hess-3-477-1999.html

Vancouver

Franks SW, Beven KJ, Gash JHC. Multi-objective conditioning of a simple SVAT model. Hydrology and Earth System Sciences. 1999;3(4):477-489.

Author

Franks, S. W. ; Beven, Keith J. ; Gash, J. H. C. / Multi-objective conditioning of a simple SVAT model. In: Hydrology and Earth System Sciences. 1999 ; Vol. 3, No. 4. pp. 477-489.

Bibtex

@article{a5bc9bfdc4894aa7a829ede326f04d8b,
title = "Multi-objective conditioning of a simple SVAT model.",
abstract = "It has previously been argued that current Soil Vegetation Atmosphere Transfer (SVAT) models are over-parameterised given the calibration data typically available. Using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology, multiple feasible model parameter sets are here conditioned on latent heat fluxes and then additionally on the sensible and ground heat fluxes at a single site in Amazonia. The model conditioning schemes were then evaluated with a further data set collected at the same site according to their ability to reproduce the latent, sensible and ground heat fluxes. The results indicate that conditioning the model on only the latent heat flux component of the energy balance does not constrain satisfactorily the predictions of the other components of the energy balance. When conditioning on all heat flux objectives, significant additional constraint of the feasible parameter space is achieved with a consequent reduction in the predictive uncertainty. There are still, however, many parameter sets that adequately reproduce the calibration/validation data, leading to significant predictive uncertainty. Surface temperature measurements, whilst also subject to uncertainty, may be employed usefully in a multi-objective calibration of SWAT models.",
author = "Franks, {S. W.} and Beven, {Keith J.} and Gash, {J. H. C.}",
year = "1999",
language = "English",
volume = "3",
pages = "477--489",
journal = "Hydrology and Earth System Sciences",
issn = "1027-5606",
publisher = "Copernicus Gesellschaft mbH",
number = "4",

}

RIS

TY - JOUR

T1 - Multi-objective conditioning of a simple SVAT model.

AU - Franks, S. W.

AU - Beven, Keith J.

AU - Gash, J. H. C.

PY - 1999

Y1 - 1999

N2 - It has previously been argued that current Soil Vegetation Atmosphere Transfer (SVAT) models are over-parameterised given the calibration data typically available. Using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology, multiple feasible model parameter sets are here conditioned on latent heat fluxes and then additionally on the sensible and ground heat fluxes at a single site in Amazonia. The model conditioning schemes were then evaluated with a further data set collected at the same site according to their ability to reproduce the latent, sensible and ground heat fluxes. The results indicate that conditioning the model on only the latent heat flux component of the energy balance does not constrain satisfactorily the predictions of the other components of the energy balance. When conditioning on all heat flux objectives, significant additional constraint of the feasible parameter space is achieved with a consequent reduction in the predictive uncertainty. There are still, however, many parameter sets that adequately reproduce the calibration/validation data, leading to significant predictive uncertainty. Surface temperature measurements, whilst also subject to uncertainty, may be employed usefully in a multi-objective calibration of SWAT models.

AB - It has previously been argued that current Soil Vegetation Atmosphere Transfer (SVAT) models are over-parameterised given the calibration data typically available. Using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology, multiple feasible model parameter sets are here conditioned on latent heat fluxes and then additionally on the sensible and ground heat fluxes at a single site in Amazonia. The model conditioning schemes were then evaluated with a further data set collected at the same site according to their ability to reproduce the latent, sensible and ground heat fluxes. The results indicate that conditioning the model on only the latent heat flux component of the energy balance does not constrain satisfactorily the predictions of the other components of the energy balance. When conditioning on all heat flux objectives, significant additional constraint of the feasible parameter space is achieved with a consequent reduction in the predictive uncertainty. There are still, however, many parameter sets that adequately reproduce the calibration/validation data, leading to significant predictive uncertainty. Surface temperature measurements, whilst also subject to uncertainty, may be employed usefully in a multi-objective calibration of SWAT models.

M3 - Journal article

VL - 3

SP - 477

EP - 489

JO - Hydrology and Earth System Sciences

JF - Hydrology and Earth System Sciences

SN - 1027-5606

IS - 4

ER -