Can measured data be force-fit into the model?


Is there a way we could force-fit the measured data (canopy cover, biomass) into the aquacrop model (let’s suppose during the mid of the crop season) and then have our model evolve the rest of the crop growth based on this newly inputted/adjusted data?



It would definitely be possible to calibrate the model to the data, and update that calibration throughout the season.

For example you could optimise the canopy cover growth coefficient (Crop.CGC) to mimize the mean squared error between aquacrop CC outputs and your measured CC.

That’s probably a better way then just setting the CC to a measured value.


Hello tom, I have the same need of the original poster. Btw I need to force input canopy cover data (measured), could you please explain how? Sorry, kind of python newbie. I think it’s the same amooly asked, your solution is good but I really need to force input my data.
Thank you for your wonderful work