Contribution of climate models and APSIM phenological parameters to uncertainties in spring wheat simulations: application of SUFI-2 algorithm in northeast Australia

Article

Collins, Brian, Najeeb, Ullah, Luo, Qunying and Tan, Daniel K. Y.. 2022. "Contribution of climate models and APSIM phenological parameters to uncertainties in spring wheat simulations: application of SUFI-2 algorithm in northeast Australia." Journal of Agronomy and Crop Science. 208 (2), pp. 225-242. https://doi.org/10.1111/jac.12575
Article Title

Contribution of climate models and APSIM phenological parameters to uncertainties in spring wheat simulations: application of SUFI-2 algorithm in northeast Australia

ERA Journal ID5314
Article CategoryArticle
AuthorsCollins, Brian, Najeeb, Ullah, Luo, Qunying and Tan, Daniel K. Y.
Journal TitleJournal of Agronomy and Crop Science
Journal Citation208 (2), pp. 225-242
Number of Pages18
Year2022
PublisherJohn Wiley & Sons
Place of PublicationGermany
ISSN0931-2250
1439-037X
Digital Object Identifier (DOI)https://doi.org/10.1111/jac.12575
Web Address (URL)https://onlinelibrary.wiley.com/doi/10.1111/jac.12575
Abstract

We used SUFI-2 for the first time to calibrate the phenology module of the APSIM-wheat model for 10 spring wheat cultivars cultivated in northeast Australia (south-eastern Queensland). Calibration resulted in an average root mean square error (RMSE) of 5.5 days for developmental stages from stem elongation up to flowering. Projections from 33 climate models under the representative concentration pathway 8.5 were used for simulations at 17 sites. Using adapted sowing times, we simulated significantly shorter crop cycles and grain yield improvements for the period 2036–2065 relative to 1990–2019 for three selected cultivars (Hartog, Scout and Gregory). Photoperiod and vernalisation sensitivities were shown to be the largest and smallest contributors to total uncertainties in the simulated flowering day and grain yield, respectively. Uncertainties in climate models had a relatively minor contribution to the total uncertainties in the simulated values of target traits. This contribution significantly increased when climate change impact on the target traits was quantified.

Keywordsclimate change; uncertainty analys; Australian wheatbelt; calibration; sensitivity analysis; crop model
Article Publishing Charge (APC) FundingOther
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020310806. Plant physiology
460207. Modelling and simulation
Public Notes

The accessible file is the accepted version of the paper. Please refer to the URL for the published version.

Byline AffiliationsJames Cook University
University of Queensland
Hillridge Technology, Australia
University of Sydney
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