The chaos in calibrating crop models: Lessons learned from a multi-model calibration exercise

0546886 - ÚVGZ 2022 RIV GB eng J - Journal Article
Wallach, D. - Palosuo, T. - Thorburn, P. - Hochman, Z. - Gourdain, E. - Andrianasolo, F. - Asseng, S. - Basso, B. - Buis, S. - Crout, N. - Dibari, C. - Dumont, B. - Ferrise, R. - Gaiser, T. - Garcia, C. - Gayler, S. - Ghahramani, A. - Hiremath, S. - Hoek, S. - Horan, H. - Hoogenboom, G. - Huang, M. - Jabloun, M. - Jansson, P.-E. - Jing, Q. - Justes, E. - Kersebaum, Kurt Christian - Klosterhalfen, A. - Launay, M. - Lewan, E. - Luo, Q. - Maestrini, B. - Mielenz, H. - Moriondo, M. - Zadeh, H. N. - Padovan, G. - Olesen, J. E. - Poyda, A. - Priesack, E. - Pullens, J. W. M. - Qian, B. - Schuetze, N. - Shelia, V. - Souissi, A. - Specka, X. - Srivastava, A. K. - Stella, T. - Streck, T. - Trombi, G. - Wallor, E. - Wang, J. - Weber, T. K.D. - Weihermueller, L. - de Wit, A. - Woehling, T. - Xiao, L. - Zhao, C. - Zhu, Y. - Seidel, S. J.
The chaos in calibrating crop models: Lessons learned from a multi-model calibration exercise.
Environmental Modelling & Software. Roč. 145, NOV (2021), č. článku 105206. ISSN 1364-8152. E-ISSN 1873-6726
R&D Projects: GA MŠMT(CZ) EF16_019/0000797
Research Infrastructure: CzeCOS III - 90123
Institutional support: RVO:86652079
Keywords : multiobjective calibration * parameterization * uncertainty * systems * identifiability * coefficients * simulation * phenology * software * gencalc * Calibration recommendations * Process-based models * Parameter estimation * Phenology
OECD category: Environmental sciences (social aspects to be 5.7)
Impact factor: 5.471, year: 2021
Method of publishing: Limited access
https://www.sciencedirect.com/science/article/pii/S1364815221002486?via%3Dihub

Calibration, the estimation of model parameters based on fitting the model to experimental data, is among the first steps in many applications of process-based models and has an important impact on simulated values. We propose a novel method of developing guidelines for calibration of process-based models, based on development of recommendations for calibration of the phenology component of crop models. The approach was based on a multi-model study, where all teams were provided with the same data and asked to return simulations for the same conditions. All teams were asked to document in detail their calibration approach, including choices with respect to criteria for best parameters, choice of parameters to estimate and software. Based on an analysis of the advantages and disadvantages of the various choices, we propose calibration recommendations that cover a comprehensive list of decisions and that are based on actual practices.
Permanent Link: http://hdl.handle.net/11104/0323271