Crop Production

I’ve run the crop production model to calculate the total future crop yields.
But I don’t know whether to use the percentile or regression model even if I saw InVEST user’s guide.
Please tell me how to solve that problem.

Have a nice day today!

Hi @soo,

The two crop production models offered in the InVEST suite are slightly different from one another: one (the percentile model) estimates crop yields based on existing data on observed yields from a global dataset that’s provided with the model. The regression model by contrast uses a regression to estimate crop yields (for a much smaller selection of crops) based on fertilizer used. So, which model you use will depend on what you’re trying to model.

Here are the descriptions of the two models, lifted from the InVEST User’s Guide chapter:

Percentile Model

The InVEST Crop Production Percentile model produces estimates of 175 crops’ yield from existing data, percentile summaries, and observed yields. These observations are based on FAO and sub-national datasets for 175 crops, as tons/ha (Monfreda et al. 2008) and nutrition information. The percentile yields are useful for exploring a range of intenstification levels, listing the yield for the 25th, 50th, 75th, and 95th percentiles, amongst observed yield data in each of the crop’s climate bins.

Regression Model

For 12 staple crops for which yields have been modeled globally by Mueller et al. (2011), the Crop Production Regression model can provide estimates of yields given fertilizer inputs. These crops include barley, maize, oil palm, potato, rapeseed, rice, rye, soybean, sugar beet, sugar cane, sunflower, and wheat. To run this model, the user must provide an additional table that corresponds crops with nitrogen, phosphate, and potash application rates (kg/ha) per crop. The model produces modeled and observed crop yields, as well as nutritional value.

Let us know if you have any further questions!