How We Do It

At the field scale we use a mechanistic cropping systems model (APSIM), weather forecasting, and in-season soil and crop measurements from about 20 site-crop-management replicated treatments across Iowa. We set up model calibrations for all experimental sites before the season begins. We then add historical, current, and forecasted weather to drive model simulations. Meanwhile, we measure everything we can at the field sites and check the model against these measurements. We then publish the results (simulated and measured data) on the website. At the end of the season, we perform a scenario analysis by making changes to the model, such as adjusting the amount of fertilizer, seed, plant spacing, or even precipitation. Then we evaluate what would have led to a greater yield, less environmental influence, and more economic gain.

At the regional scale we simulate 25-30 fields per county using APSIM. For yield predictions we used both APSIM and machine learning argorithms. 

About the APSIM modeling platform

The Agricultural Production Systems sIMulator ​​​​​​ is used to synthesize soil-crop-weather information and create in-season forecasts for crop yields and soil water-nitrogen and end-of-season evaluations and scenario analysis. The APSIM model simulates crop growth and development, soil water and N balances that includes water/nitrate leaching to tile drainage and GHG emissions on a daily basis. The yield predictions account for water and nitrogen limitations but not weeds, insects and diseases. Within APSIM, crop growth models are coupled with soil-environmental modes and thus interactions between crop and soil variables are explicitly considered. The model operates on a daily time step. The crop models simulate crop phenology, morphology, physiology and biomass production and partitioning. Water and nitrogen stresses on crop growth and development are simulated using a supply/demand approach. The model can simulate potential, water-limited and water-nitrogen-limited production situations. To simulate soil water in each layer APSIM runs a water balance that includes the following processes: precipitation, runoff, soil water evaporation, plant transpiration, water flow in tile drainage, water leaching from the bottom of the soil profile and capillary rise of watertable. Soil organic carbon and nitrogen cycling is simulated in each soil layer and a number of processes are considered: soil N mineralization, residue N immobilization, nitrification, denitrification, N20 and CO2 emissions, NO3-N leaching to tile drainage, NO3-N leaching from the bottom of the profile, atmospheric N deposition and N fixation for soybean.Additional details about the APSIM models can be found here: and in the following key references: Keating et al. (2003) and Holzworth et al. (2014).


Studies testing the performance of the APSIM model in the USA (click on the link to see the paper or the figure)

Reference Model processes tested
Archontoulis et al. 2014 Agronomy J


Soil water, soil nitrate, soil N mineralization, manure application, soil temperature, phenology, leaf area index, biomass production, grain yields response to N, leaf nitrogen concentration, root mass, triticale-corn double cropping systems


Archontoulis et al. 2014
Env. Modeling & Software


Temperature x photoperiod interactions on soybean development, soybean flowering, start grain filling, maturity days, grain yields, soybean varieties


Dietzel et al. 2016
Global Change Biology


Crop rotations, cover crops, biomass production, crop yields, soil temperature, soil water, subsurface tile drainage, crop growth, soil nitrate, root N concentration, soil-root CO2 emissions, water use efficiency


Basche et al. 2016
Agr. Ecos. & Envrionment


Cover crops, biomass production, crop yields, soil organic carbon, soil water


Archontoulis et al. 2016


Biochar, soil organic carbon, nitrogen cycling, soil pH, soil CEC, soil bulk density, crop yields, corn residue


Archontoulis et al. 2016
Inter. Crop Model. Conf.


Corn and soybean, biomass and grain growth, soil nitrate


Archontoulis et al. 2015
ASA meeting


Soil nitrate, soil water, soil temperature, groundwater table, corn and soybean yields, biomass production and partitioning, crop phenology, yield gaps,


Malone et al. 2007
Geoderma J


Corn and soybean yields, cover crops biomass, cover crops N concentration, subsurface tile drainage, subsurface NO3-N leaching


Martinez–Feria et al. 2016
Field Crops Research J



Corn yields, corn and rye cover crop biomass production, rye CN ratio, rye root and shoot biomass, tile drainage, N leaching


Puntel et al.
In prep/under review


Corn yield – N relationships, economic optimum N rate, crop rotations, soybean yields, soil organic carbon


Unpublished or in preparation for publication  

CROP: phenology, leaf area index, specific leaf area, biomass and grain accumulation, biomass partitioning to stems/leaf/organ/root, grain number and size, corn yields, leaf/stem/grain/cobs/roots N concentration, N uptake by plant tissue, plant counts, root depth and mass, soybean N fixation, crop sequence: corn/soybean, corn-corn, corn vs rye cover crop

SOIL: nitrate and ammonium, water and temperature, groundwater, subsurface drainage and N leaching, N2O emissions, soil organic carbon


FACTS is an ongoing project developed to forecast and evaluate in real-time soil-crop dynamics at  specific ISU research fields (field scale) and at regional scale. Predictions will be frequently updated as new information becomes available. The project investigators and Iowa State University are not responsible for extrapolations made by individuals to other fields. Information from this website can be used for presentations without further permission if used in its entirety and credit is given to the Iowa State University FACTS project. Information from this website cannot be used in publications or other model improvement activities without prior permission of the project investigators.