A framework for assessing the uncertainty in crop model predictions

Daniel Wallach, Mike Rivington


It is of major importance in modeling to understand and quantify the uncertainty in model predictions, both in order to know how much confidence to have in those predictions, and as a first step toward model improvement. Here we show that there are basically three different approaches to evaluating uncertainty, and we explain the advantages and drawbacks of each. This is a necessary first step toward developing protocols for evaluation of uncertainty and so obtaining a clearer picture of the reliability of crop models.


uncertainty, crop models

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Abedinpoura, M. et al., 2012. Performance evaluation of AquaCrop model for maize crop in a semi-arid environment. Agricultural Water Management, 110, pp.55–66.

Asseng, S. et al., 2013. Uncertainty in simulating wheat yields under climate change. Nature Climate Change, 3(9), pp.827–832.

Bassu, S. et al., 2014. How do various maize crop models vary in their responses to climate change factors? Global change biology, 20(7), pp.2301–20.

Biernath, C. et al., 2011. Evaluating the ability of four crop models to predict different environmental impacts on spring wheat grown in open-top chambers. European Journal of Agronomy, 35(2), pp.71–82.

Dzotsi, K.A., Basso, B. & Jones, J.W., 2013. Development, uncertainty and sensitivity analysis of the simple SALUS crop model in DSSAT. Ecological Modelling, 260, pp.62–76.

Iizumi, T., Yokozawa, M. & Nishimori, M., 2009. Parameter estimation and uncertainty analysis of a large-scale crop model for paddy rice: Application of a Bayesian approach. Agricultural and Forest Meteorology, 149(2), pp.333–348.

Mkhabela, M.S. & Bullock, P.R., 2012. Performance of the FAO AquaCrop model for wheat grain yield and soil moisture simulation in Western Canada. Agricultural Water Management, 110, pp.16–24.

Myers, R.H., 2007. Classical and modern regression with applications, Boston : PWS-Kent.

Ben Nouna, B., Katerji, N. & Mastrorilli, M., 2000. Using the CERES-Maize model in a semi-arid mediterranean environment. Evaluation of model performance. European Journal of Agronomy, 13, pp.309–322.

Palosuo, T. et al., 2011. Simulation of winter wheat yield and its variability in different climates of Europe: A comparison of eight crop growth models. European Journal of Agronomy, 35(3), pp.103–114.

Richter, G.M. et al., 2010. Sensitivity analysis for a complex crop model applied to Durum wheat in the Mediterranean. European Journal of Agronomy, 32(2), pp.127–136.

Rötter, R.P. et al., 2012. Simulation of spring barley yield in different climatic zones of Northern and Central Europe: A comparison of nine crop models. Field Crops Research, 133, pp.23–36.

Roux, S., Brun, F. & Wallach, D., 2014. Combining input uncertainty and residual error in crop model predictions: A case study on vineyards. European Journal of Agronomy, 52(Part B), pp.191–197.

Soler, C.M.T., Sentelhas, P.C. & Hoogenboom, G., 2007. Application of the CSM-CERES-Maize model for planting date evaluation and yield forecasting for maize grown off-season in a subtropical environment. European Journal of Agronomy, 27(2), pp.165–177.

Tao, F. et al., 2009. Modelling the impacts of weather and climate variability on crop productivity over a large area: A new super-ensemble-based probabilistic projection. Agricultural and Forest Meteorology, 149(8), pp.1266–1278.

Tao, F. & Zhang, Z., 2010. Adaptation of maize production to climate change in North China Plain: Quantify the relative contributions of adaptation options. European Journal of Agronomy, 33(2), pp.103–116.

Wallach, D. et al., 2012. Assessing the uncertainty when using a model to compare irrigation strategies. Agronomy Journal, 104, pp.1274–1283.

Wallach, D., 2011. Crop model calibration: A statistical perspective. Agronomy Journal, 103, pp.1144–1151.

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