Crop models are used to estimate crop productivity under future climate projections, and modellers manage uncertainty by considering different scenarios and GCMs, using a range of crop simulators. Five crop models and 20 users were arranged in a randomized block design with four replicates. Parameters for maize (well studied by modellers) and rapeseed (almost ignored) were calibrated. While all models were accurate for maize (RRMSE from 16.5% to 25.9%), they were, to some extent, unsuitable for rapeseed. Although differences between biomass simulated by the models were generally significant for rapeseed, they were significant only in 30% of the cases for maize. This could suggest that in case of models well suited to a crop, user subjectivity (which explained 14% of total variance in maize outputs) can hide differences in model algorithms and, consequently, the uncertainty due to parameterization should be better investigated.
Uncertainty in crop model predictions : What is the role of users? / R. Confalonieri, F. Orlando, L. Paleari, T. Stella, C. Gilardelli, E. Movedi, V. Pagani, G. Cappelli, A. Vertemara, L. Alberti, P. Alberti, S. Atanassiu, M. Bonaiti, G. Cappelletti, M. Ceruti, A. Confalonieri, G. Corgatelli, P. Corti, M. Dell'Oro, A. Ghidoni, A. Lamarta, A. Maghini, M. Mambretti, A. Manchia, G. Massoni, P. Mutti, S. Pariani, D. Pasini, A. Pesenti, G. Pizzamiglio, A. Ravasio, A. Rea, D. Santorsola, G. Serafini, M. Slavazza, M. Acutis. - In: ENVIRONMENTAL MODELLING & SOFTWARE. - ISSN 1364-8152. - 81:(2016 Jul), pp. 165-173. [10.1016/j.envsoft.2016.04.009]
Uncertainty in crop model predictions : What is the role of users?
R. Confalonieri
;F. OrlandoSecondo
;L. Paleari;T. Stella;C. Gilardelli;E. Movedi;V. Pagani;G. Cappelli;A. Confalonieri;M. AcutisUltimo
2016
Abstract
Crop models are used to estimate crop productivity under future climate projections, and modellers manage uncertainty by considering different scenarios and GCMs, using a range of crop simulators. Five crop models and 20 users were arranged in a randomized block design with four replicates. Parameters for maize (well studied by modellers) and rapeseed (almost ignored) were calibrated. While all models were accurate for maize (RRMSE from 16.5% to 25.9%), they were, to some extent, unsuitable for rapeseed. Although differences between biomass simulated by the models were generally significant for rapeseed, they were significant only in 30% of the cases for maize. This could suggest that in case of models well suited to a crop, user subjectivity (which explained 14% of total variance in maize outputs) can hide differences in model algorithms and, consequently, the uncertainty due to parameterization should be better investigated.
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