Proposal and extensive test of a calibration protocol for crop phenology models

0574033 - ÚVGZ 2024 RIV DE eng J - Článek v odborném periodiku
Wallach, D. - Palosuo, T. - Thorburn, P. - Mielenz, H. - Buis, S. - Hochman, Z. - Gourdain, E. - Andrianasolo, F. - Dumont, B. - Ferrise, R. - Gaiser, T. - Garcia, C. - Gayler, S. - Harrison, M. - Hiremath, S. - Horan, H. - Hoogenboom, G. - Jansson, P.-E. - Jing, Q. - Justes, E. - Kersebaum, Kurt Christian - Launay, M. - Lewan, E. - Liu, K. - Mequanint, F. - Moriondo, M. - Nendel, Claas … celkem 40 autorů
Proposal and extensive test of a calibration protocol for crop phenology models.
Agronomy for Sustainable Development. Roč. 43, č. 4 (2023), č. článku 46. ISSN 1774-0746. E-ISSN 1773-0155
Grant CEP: GA MŠMT(CZ) EF16_019/0000797
Výzkumná infrastruktura: CzeCOS IV - 90248
Institucionální podpora: RVO:86652079
Klíčová slova: crop model * prediction error * protocol * model ensemble * variability
Obor OECD: Plant sciences, botany
Impakt faktor: 7.3, rok: 2022
Způsob publikování: Open access
https://link.springer.com/article/10.1007/s13593-023-00900-0

A major effect of environment on crops is through crop phenology, and therefore, the capacity to predict phenology for new environments is important. Mechanistic crop models are a major tool for such predictions, but calibration of crop phenology models is difficult and there is no consensus on the best approach. We propose an original, detailed approach for calibration of such models, which we refer to as a calibration protocol. The protocol covers all the steps in the calibration workflow, namely choice of default parameter values, choice of objective function, choice of parameters to estimate from the data, calculation of optimal parameter values, and diagnostics. The major innovation is in the choice of which parameters to estimate from the data, which combines expert knowledge and data-based model selection. First, almost additive parameters are identified and estimated. This should make bias (average difference between observed and simulated values) nearly zero. These are ,,obligatory,, parameters, that will definitely be estimated. Then candidate parameters are identified, which are parameters likely to explain the remaining discrepancies between simulated and observed values. A candidate is only added to the list of parameters to estimate if it leads to a reduction in BIC (Bayesian Information Criterion), which is a model selection criterion. A second original aspect of the protocol is the specification of documentation for each stage of the protocol. The protocol was applied by 19 modeling teams to three data sets for wheat phenology. All teams first calibrated their model using their ,,usual,, calibration approach, so it was possible to compare usual and protocol calibration. Evaluation of prediction error was based on data from sites and years not represented in the training data. Compared to usual calibration, calibration following the new protocol reduced the variability between modeling teams by 22% and reduced prediction error by 11%.
Trvalý link: https://hdl.handle.net/11104/0344394