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Multivariate calibration of a water and energy balance model in the spectral domain

Valentijn Pauwels UGent and Gabriëlle De Lannoy UGent (2011) WATER RESOURCES RESEARCH. 47.
abstract
The objective of this paper is to explore the possibility of using multiple variables in the calibration of hydrologic models in the spectral domain. A simple water and energy balance model was used, combined with observations of the energy balance and the soil moisture profile. The correlation functions of the model outputs and the observations for the different variables have been calculated after the removal of the diurnal cycle of the energy balance variables. These were transformed to the frequency domain to obtain spectral density functions, which were combined in the calibration algorithm. It has been found that it is best to use the square root of the spectral densities in the parameter estimation. Under these conditions, spectral calibration performs almost equally as well as time domain calibration using least squares differences between observed and simulated time series. Incorporation of the spectral coefficients of the cross-correlation functions did not improve the results of the calibration. Calibration on the correlation functions in the time domain led to worse model performance. When the meteorological forcing and model calibration data are not overlapping in time, spectral calibration has been shown to lead to an acceptable model performance. Overall, the results in this paper suggest that, in case of data scarcity, multivariate spectral calibration can be an attractive tool to estimate model parameters.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
PARTICLE SWARM OPTIMIZATION, RAINFALL-RUNOFF MODELS, SHUFFLED COMPLEX EVOLUTION, PARAMETER-ESTIMATION, GLOBAL OPTIMIZATION, HYDROLOGIC-MODELS, MULTIOBJECTIVE OPTIMIZATION, UNCERTAINTY ASSESSMENT, AUTOMATIC CALIBRATION, GENETIC ALGORITHM
journal title
WATER RESOURCES RESEARCH
Water Resour. Res.
volume
47
article_number
W07523
pages
19 pages
Web of Science type
Article
Web of Science id
000292844300007
JCR category
WATER RESOURCES
JCR impact factor
2.957 (2011)
JCR rank
3/78 (2011)
JCR quartile
1 (2011)
ISSN
0043-1397
DOI
10.1029/2010WR010292
project
HPC-UGent: the central High Performance Computing infrastructure of Ghent University
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1860791
handle
http://hdl.handle.net/1854/LU-1860791
date created
2011-07-25 11:30:25
date last changed
2013-09-17 10:45:47
@article{1860791,
  abstract     = {The objective of this paper is to explore the possibility of using multiple variables in the calibration of hydrologic models in the spectral domain. A simple water and energy balance model was used, combined with observations of the energy balance and the soil moisture profile. The correlation functions of the model outputs and the observations for the different variables have been calculated after the removal of the diurnal cycle of the energy balance variables. These were transformed to the frequency domain to obtain spectral density functions, which were combined in the calibration algorithm. It has been found that it is best to use the square root of the spectral densities in the parameter estimation. Under these conditions, spectral calibration performs almost equally as well as time domain calibration using least squares differences between observed and simulated time series. Incorporation of the spectral coefficients of the cross-correlation functions did not improve the results of the calibration. Calibration on the correlation functions in the time domain led to worse model performance. When the meteorological forcing and model calibration data are not overlapping in time, spectral calibration has been shown to lead to an acceptable model performance. Overall, the results in this paper suggest that, in case of data scarcity, multivariate spectral calibration can be an attractive tool to estimate model parameters.},
  articleno    = {W07523},
  author       = {Pauwels, Valentijn and De Lannoy, Gabri{\"e}lle},
  issn         = {0043-1397},
  journal      = {WATER RESOURCES RESEARCH},
  keyword      = {PARTICLE SWARM OPTIMIZATION,RAINFALL-RUNOFF MODELS,SHUFFLED COMPLEX EVOLUTION,PARAMETER-ESTIMATION,GLOBAL OPTIMIZATION,HYDROLOGIC-MODELS,MULTIOBJECTIVE OPTIMIZATION,UNCERTAINTY ASSESSMENT,AUTOMATIC CALIBRATION,GENETIC ALGORITHM},
  language     = {eng},
  pages        = {19},
  title        = {Multivariate calibration of a water and energy balance model in the spectral domain},
  url          = {http://dx.doi.org/10.1029/2010WR010292},
  volume       = {47},
  year         = {2011},
}

Chicago
Pauwels, Valentijn, and Gabriëlle De Lannoy. 2011. “Multivariate Calibration of a Water and Energy Balance Model in the Spectral Domain.” Water Resources Research 47.
APA
Pauwels, V., & De Lannoy, G. (2011). Multivariate calibration of a water and energy balance model in the spectral domain. WATER RESOURCES RESEARCH, 47.
Vancouver
1.
Pauwels V, De Lannoy G. Multivariate calibration of a water and energy balance model in the spectral domain. WATER RESOURCES RESEARCH. 2011;47.
MLA
Pauwels, Valentijn, and Gabriëlle De Lannoy. “Multivariate Calibration of a Water and Energy Balance Model in the Spectral Domain.” WATER RESOURCES RESEARCH 47 (2011): n. pag. Print.