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The chaos in calibrating crop models: Lessons learned from a multi-model calibration exercise., , , , , , , , , and 49 other author(s). Environ. Model. Softw., (2021)Calibration of the phenology sub-model of APSIM-Oryza: Going beyond goodness of fit., , , , , and . Environ. Model. Softw., (2015)The error in agricultural systems model prediction depends on the variable being predicted., and . Environ. Model. Softw., (2014)An open platform to build, evaluate and simulate integrated models of farming and agro-ecosystems., , , , , , , , , and 7 other author(s). Environ. Model. Softw., (2013)Crop modelling for integrated assessment of risk to food production from climate change., , , , , , , , , and 12 other author(s). Environ. Model. Softw., (2015)A Bayesian Approach to Crop Model Calibration Under Unknown Error Covariance, , and . Journal of Agricultural, Biological, and Environmental Statistics, 13 (3): 355-365 (2008)The implication of input data aggregation on up-scaling soil organic carbon changes., , , , , , , , , and 11 other author(s). Environ. Model. Softw., (2017)A package of parameter estimation methods and implementation for the STICS crop-soil model., , , , , , , , , and . Environ. Model. Softw., 26 (4): 386-394 (2011)Multi-wheat-model ensemble responses to interannual climate variability, , , , , , , , , and 38 other author(s). Environmental Modelling & Software, (July 2016)Estimating model prediction error: Should you treat predictions as fixed or random?, , , , , , , and . Environ. Model. Softw., (2016)