Calibration of a land surface model using multiple data sets
journal contribution
posted on 2023-05-17, 19:32authored byMcCabe, MF, Franks, SW, Kalma, JD
In order to assess performance and to improve predictions, land surface models are routinely calibrated against measurements of either latent heat or sensible heat fluxes. Generally, little regard is given to the multi-output nature of these models, resulting in a model evaluation that is inherently biased towards the calibration variable. In this paper, an assessment strategy that accounts for multiple outputs is explored and an examination of incorporating alternative sources of information to assess performance is undertaken. The benefits of such a multi-objective calibration framework are illustrated through comparison with traditional single objective calibration. Results indicate that combining different observation data streams for calibration purposes assists in producing a more robust process model and provides improved surface flux predictions. Further, the utility of using correlated, if not commensurate, sources of data, is demonstrated through analysis of a time series of surface temperature measurements.
History
Publication title
Journal of Hydrology
Volume
302
Issue
1-4
Pagination
209-222
ISSN
0022-1694
Department/School
School of Engineering
Publisher
Elsevier Science Bv
Place of publication
Po Box 211, Amsterdam, Netherlands, 1000 Ae
Rights statement
Copyright 2004 Elsevier B.V.
Repository Status
Restricted
Socio-economic Objectives
Other environmental management not elsewhere classified