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

dc.contributor.authorWallach, D
dc.contributor.authorPalosuo, T
dc.contributor.authorThorburn, P
dc.contributor.authorHochman, Z
dc.contributor.authorGourdain, E
dc.contributor.authorAndrianasolo, F
dc.contributor.authorAsseng, S
dc.contributor.authorBasso, B
dc.contributor.authorBuis, S
dc.contributor.authorCrout, N
dc.contributor.authorDibari, C
dc.contributor.authorDumont, B
dc.contributor.authorFerrise, R
dc.contributor.authorGaiser, T
dc.contributor.authorGarcia, C
dc.contributor.authorGayler, S
dc.contributor.authorGhahramani, A
dc.contributor.authorHiremath, S
dc.contributor.authorHoek, S
dc.contributor.authorHoran, H
dc.contributor.authorHoogenboom, G
dc.contributor.authorHuang, M
dc.contributor.authorJabloun, M
dc.contributor.authorJansson, P-E
dc.contributor.authorJing, Q
dc.contributor.authorJustes, E
dc.contributor.authorKersebaum, KC
dc.contributor.authorKlosterhalfen, A
dc.contributor.authorLaunay, M
dc.contributor.authorLewan, E
dc.contributor.authorLuo, Q
dc.contributor.authorMaestrini, B
dc.contributor.authorMielenz, H
dc.contributor.authorMoriondo, M
dc.contributor.authorNariman Zadeh, H
dc.contributor.authorPadovan, G
dc.contributor.authorOlesen, JE
dc.contributor.authorPoyda, A
dc.contributor.authorPriesack, E
dc.contributor.authorPullens, JWM
dc.contributor.authorQian, B
dc.contributor.authorSchütze, N
dc.contributor.authorShelia, V
dc.contributor.authorSouissi, A
dc.contributor.authorSpecka, X
dc.contributor.authorSrivastava, AK
dc.contributor.authorStella, T
dc.contributor.authorStreck, T
dc.contributor.authorTrombi, G
dc.contributor.authorWallor, E
dc.contributor.authorWang, J
dc.contributor.authorWeber, TKD
dc.contributor.authorWeihermüller, L
dc.contributor.authorde Wit, A
dc.contributor.authorWöhling, T
dc.contributor.authorXiao, L
dc.contributor.authorZhao, C
dc.contributor.authorZhu, Y
dc.contributor.authorSeidel, SJ
dc.date.accessioned2022-08-23T02:40:38Z
dc.date.available2021-09-20
dc.date.issued2021-11
dc.date.submitted2021-09-15
dc.date.updated2022-08-18T03:56:56Z
dc.description.abstractCalibration, 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.
dc.format.extent11 pages
dc.identifierhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=elements_prod&SrcAuth=WosAPI&KeyUT=WOS:000703667700002&DestLinkType=FullRecord&DestApp=WOS
dc.identifier.doi10.1016/j.envsoft.2021.105206
dc.identifier.eissn1873-6726
dc.identifier.issn1364-8152
dc.identifier.otherWB6GF (isidoc)
dc.identifier.urihttps://hdl.handle.net/10182/15369
dc.languageen
dc.language.isoen
dc.publisherElsevier Ltd
dc.relationThe original publication is available from Elsevier Ltd - https://doi.org/10.1016/j.envsoft.2021.105206 - http://dx.doi.org/10.1016/j.envsoft.2021.105206
dc.relation.isPartOfEnvironmental Modelling and Software
dc.relation.urihttps://doi.org/10.1016/j.envsoft.2021.105206
dc.rights© 2021 Elsevier Ltd. All rights reserved.
dc.subjectcalibration recommendations
dc.subjectparameter estimation
dc.subjectphenology
dc.subjectprocess-based models
dc.subject.anzsrc2020ANZSRC::401102 Environmentally sustainable engineering
dc.subject.anzsrc2020ANZSRC::461207 Software quality, processes and metrics
dc.subject.anzsrc2020ANZSRC::300207 Agricultural systems analysis and modelling
dc.subject.anzsrc2020ANZSRC::419999 Other environmental sciences not elsewhere classified
dc.titleThe chaos in calibrating crop models: Lessons learned from a multi-model calibration exercise
dc.typeJournal Article
lu.contributor.unitLU
lu.contributor.unitLU|Lincoln Agritech
lu.identifier.orcid0000-0003-2963-0965
pubs.article-number105206
pubs.publication-statusPublished
pubs.publisher-urlhttp://dx.doi.org/10.1016/j.envsoft.2021.105206
pubs.volume145
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