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Crout, N.M.J.; Craigon, J.; Cox, G.M.; Jao, Y.; Tarsitano, D.; Wood, A.T.A.; Semenov, M. |
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Title |
An objective approach to model reduction: Application to the Sirius wheat model |
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Journal Article |
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Year |
2014 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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Volume |
189-190 |
Issue  |
100 |
Pages |
211-219 |
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Keywords |
Complexity; Crop model; Evaluation; Model reduction; Parsimony; Wheat |
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Abstract |
An existing simulation model of wheat growth and development, Sirius, was evaluated through a systematic model reduction procedure. The model was automatically manipulated under software control to replace variables within the model structure with constants, individually and in combination. Predictions of the resultant models were compared to growth analysis observations of total biomass, grain yield, and canopy leaf area derived from 9 trials conducted in the UK and New Zealand under optimal, nitrogen limiting and drought conditions. Model performance in predicting these observations was compared in order to evaluate whether individual model variables contributed positively to the overall prediction. Of the 1 1 1 model variables considered 16 were identified as potentially redundant. Areas of the model where there was evidence of redundancy were: (a) translocation of biomass carbon to grain; (b) nitrogen physiology; (c) adjustment of air temperature for various modelled processes; (d) allowance for diurnal variation in temperature; (e) vernalisation (f) soil nitrogen mineralisation (g) soil surface evaporation. It is not suggested that these are not important processes in real crops, rather, that their representation in the model cannot be justified in the context of the analysis. The approach described is analogous to a detailed model inter-comparison although it would be better described as a model intra-comparison as it is based on the comparison of many simplified forms of the same model. The approach provides automation to increase the efficiency of the evaluation and a systematic means of increasing the rigour of the evaluation. |
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2016-10-31 |
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ISSN |
0168-1923 |
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CropM |
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Call Number |
MA @ admin @ |
Serial |
4788 |
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Author |
Montesino-San Martín, M.; Olesen, J.E.; Porter, J.R. |
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Title |
Can crop-climate models be accurate and precise? A case study for wheat production in Denmark |
Type |
Journal Article |
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Year |
2015 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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Volume |
202 |
Issue |
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Pages |
51-60 |
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Keywords |
Uncertainty; Model intercomparison; Bayesian approach; Climate change; Wheat; Denmark; uncertainty analysis; simulation-models; bayesian-approach; change; impact; yields; variability; projections; scale; calibration; framework |
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Abstract |
Crop models, used to make projections of climate change impacts, differ greatly in structural detail. Complexity of model structure has generic effects on uncertainty and error propagation in climate change impact assessments. We applied Bayesian calibration to three distinctly different empirical and mechanistic wheat models to assess how differences in the extent of process understanding in models affects uncertainties in projected impact. Predictive power of the models was tested via both accuracy (bias) and precision (or tightness of grouping) of yield projections for extrapolated weather conditions. Yields predicted by the mechanistic model were generally more accurate than the empirical models for extrapolated conditions. This trend does not hold for all extrapolations; mechanistic and empirical models responded differently due to their sensitivities to distinct weather features. However, higher accuracy comes at the cost of precision of the mechanistic model to embrace all observations within given boundaries. The approaches showed complementarity in sensitivity to weather variables and in accuracy for different extrapolation domains. Their differences in model precision and accuracy make them suitable for generic model ensembles for near-term agricultural impact assessments of climate change. |
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0168-1923 |
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CropM, ftnotmacsur |
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Call Number |
MA @ admin @ |
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4572 |
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Author |
Graux, A.-I.; Bellocchi, G.; Lardy, R.; Soussana, J.-F. |
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Title |
Ensemble modelling of climate change risks and opportunities for managed grasslands in France |
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Journal Article |
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Year |
2013 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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Volume |
170 |
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114-131 |
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0168-1923 |
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CropM, LiveM, ftnotmacsur, IPCC-AR5 |
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Call Number |
MA @ admin @ |
Serial |
4926 |
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Rosenzweig, C.; Jones, J.W.; Hatfield, J.L.; Ruane, A.C.; Boote, K.J.; Thorburn, P.; Antle, J.M.; Nelson, G.C.; Porter, C.; Janssen, S.; Asseng, S.; Basso, B.; Ewert, F.; Wallach, D.; Baigorria, G.; Winter, J.M. |
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Title |
The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and pilot studies |
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Journal Article |
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Year |
2013 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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Volume |
170 |
Issue |
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Pages |
166-182 |
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0168-1923 |
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CropM, ftnotmacsur, IPCC-AR5 |
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MA @ admin @ |
Serial |
4927 |
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Author |
Teixeira, E.I.; Fischer, G.; van Velthuizen, H.; Walter, C.; Ewert, F. |
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Title |
Global hot-spots of heat stress on agricultural crops due to climate change |
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Journal Article |
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Year |
2013 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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Volume |
170 |
Issue |
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Pages |
206-215 |
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0168-1923 |
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CropM, ftnotmacsur, IPCC-AR5 |
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MA @ admin @ |
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4929 |
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