This portal provides access to biophysical simulation models of agricultural and natural systems. These models range in complexity from point simulation (i.e. one dimensional) to spatially explicit watershed models. The links below provides information on how to install and execute each featured model.
CropSyst is a multi-year multi-crop daily time step cropping systems simulation model. The model has been developed to serve as an analytic tool to study the effect of cropping systems management on productivity and the environment. The model simulates the soil water budget, soil-plant nitrogen budget, soil carbon balance, crop canopy and root growth, dry matter production, yield, residue production and decomposition, and erosion. Management options include: cultivar selection, crop rotation (including fallow years), irrigation, nitrogen fertilization, tillage operations, and residue management. The model is currently written in C++ and is accessible through a user-friendly interface.
Cycles is an object-oriented agro-ecosystems simulations model that shares several modules with CropSyst. The model is an evolution of the model C-Farm originally devised to provide carbon balances for different cropping systems. Unlike CropSyst the model minimizes the choice of parameters to be modified by the user. The model allows simulating annual crops sequences, legume and none-legume cover crops, forage crops, and to obtain the daily and annual cumulative nutrient and water balance for each simulated system. The model is currently written in Visual Basic and the interface reads and writes from Excel to facilitate data input manipulation and analysis.
The Farm Energy Analysis Tool (FEAT), a static, deterministic, data-base model, was created to use a whole-farm approach to evaluate energy and greenhouse gas (GHG) emissions for different agricultural systems.
IFSM simulates all major farm components on a process level. This enables the integration and linking of components in a manner that adequately represents the major interactions among the many biological and physical processes on the farm. This provides a robust research and teaching tool for exploring the whole farm impact of changes in management and technology.