A SIMPLE crop model

•A simple crop model, called SIMPLE, was developed including 13 parameters to specify a crop type, with four of these for cultivar characteristics.•Commonly available inputs that are required for the SIMPLE model include daily weather data, crop management, and soil water holding parameters.•The initial SIMPLE model was calibrated for 14 different crops from 25 detailed field experiments resulting in a RRMSE of 25.4% for final yield. Crop models are important tools for assessing the impact of climate change on crop production. While multiple models have been developed over the past decades for the major food and fiber crops such as wheat, maize, soybean, rice, and cotton, there are few or none for many other crops. The goal of this study was to develop a simple generic crop model (SIMPLE) that could be easily modified for any crop to simulate development, crop growth and yield. The crop model SIMPLE includes 13 parameters to specify a crop type, with four of these for cultivar characteristics. Commonly available inputs that are required for the crop model SIMPLE include daily weather data, crop management, and soil water holding parameters. The initial SIMPLE model was calibrated and evaluated for 14 different annual crops using observations for biomass growth, solar radiation interception, and yield from 25 detailed field experiments for a total of 70 treatments from 17 sites, resulting in a RRMSE of 25.4% for final yield. A sensitivity analysis comparing a C3, C4 and a legume crop showed an expected response to a gradual increase in temperature and atmospheric CO2 concentrations. A regional gridded simulation for US potatoes reproduced the general observed patterns of spatial yield variability. Because the model is simple, it has several limitations, including the lack of response to vernalization and photoperiod effect on phenology. The model includes water, but no nutrient dynamics. However, an advantage of the model simplicity is that it can be easily adapted and evaluated for any new crop, based on literature data and field experiments, or general crop data such as sowing and harvest dates and yield statistics. The model is available in several simulation frameworks including a stand-alone version in R, Excel and as part of DSSAT.