Agriculture system is complex, researchers in mono-field judge the response with regard to their own specific interest, which may be location specific.
Most of the instances for regional estimates, limited point results are used, without bothering about the large course of variability in bio-physical and socio-economic aspects
This problem is critical for NRM, Water management, Agro-advisories, Climate Change studies
Some of the models as DSSAT are very effective in cautioning us through its strength of sensitivity analysis, by which we can understand the importance of each input parameter, by which we can be careful in chosing those sensitive values
GIS, Remote sensing tools can be linked up with the crop models to capture the variability, somelocation specific demonstrations being published, but the operational feature still to be done on regional/country/global scale
regards
This question is very important from viewpoint of studies like climate change impacts- where results are published under specific boundary conditions, but thereafter extrapolated over regions while considering the spatio-temporal variability most of the time in a crude way, same thing is true in case of yield forecasting exercises, the purpose of asking this question is to sensitize the groups for evolving procedures to address these issues.
I also do not have the specific answer to this question, but definitely we should raise this issue for better results.
regards
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