GOSSYM is a dynamic, process-level simulation model of cotton growth and yield. GOSSYM essentially is a materials balance model which keeps track of carbon and nitrogen in the plant and water and nitrogen in the soil root zone. GOSSYM predicts the response of the field crop to variations in the environment and to cultural inputs. Specifically, the model responds to weather inputs of daily total solar radiation, maximum and minimum air temperatures, daily total wind run, and rainfall and/or irrigation amount. The model also responds to cultural inputs such as preplant and withinseason applications of nitrogen fertilizer, row spacing and within row plant density as they affect total plant population, and cultivation practices.
Initially designed to help greenhouse growers determine heating costs and do simple simulations to figure out where heat savings could be achieved, it has slowly added features so that now, Virtual Grower can help not only identify those savings through different greenhouse designs, but predict crop growth, assist in scheduling, make real-time predictions of energy use, and see the impact of supplemental lighting on plant growth and development. In other words, the software can be a safety net and allow users to experiment with "what if" scenarios in a risk-free setting.
Root Zone Water Quality Model 2 (RZWQM2) is a whole-system model for studying crop production and environmental quality under current and changing climate conditions. It emphasizes the effects of agricultural management practices on physical, chemical and biological processes. RZWQM2 is a one-dimensional model with a pseudo 2-dimensional drainage flow. Crop simulation options include the generic plant growth model, DSSAT-CSM 4.0 and HERMES SUCROS models. It also can simulate surface energy balance with components from the SHAW model and water erosion from the GLEAMS model. An automated parameter estimation algorithm (PEST) was added to RZWQM2 for objective model calibration and uncertainty analysis.
A hydrologic simulation model for studying the effects of management practices on movement of sediment and chemicals in response to rainfall or irrigation on small field areas. Includes models for plant growth and nutrient cycling, and operates on a continuous basis. Weather conditions and rainfall may be stochastically simulated.
The Nitrogen Index is a tool written in the programming language Java that is used to calculate nitrogen uptake and leaching in farming techniques.
A computer-based model simulating the interactions of weather, bloom and honey bee foraging activity that culminate in 'Delicious' apple fruit-set. The model predicts the percentage of blossoms setting fruit based upon weather conditions, orchard design, tree characteistics, and honey bee colonies per hectare.
A new process-based cotton model, CPM, has been developed to simulate the growth and development of upland cotton (Gossypium hirsutum L.) throughout the growing season with minimal data input. CPM predicts final cotton yield for any combination of soil, weather, cultivar and sequence of management actions.
Data from: Agro-environmental consequences of shifting from nitrogen- to phosphorus-based manure management of corn.
This experiment was designed to measure greenhouse gas (GHG) fluxes and related agronomic characteristics of a long-term corn-alfalfa rotational cropping system fertilized with manure (liquid versus semi-composted separated solids) from dairy animals. Different manure-application treatments were sized to fulfill two conditions: (1) an application rate to meet the agronomic soil nitrogen requirement of corn (“N-based” without manure incorporation, more manure), and (2) an application rate to match or to replace the phosphorus removal by silage corn from soils (“P-based” with incorporation, less manure). In addition, treatments tested the effects of liquid vs. composted-solid manure, and the effects of chemical nitrogen fertilizer. The controls consisted of non-manured inorganic N treatments (sidedress applications). These activities were performed during the 2014 and 2015 growing seasons as part of the Dairy Coordinated Agricultural Project, or Dairy CAP, as described below. The data from this experiment give insight into the factors controlling GHG emissions from similar cropping systems, and may be used for model calibration and validation after careful evaluation of the flagged data.
This site provides access to the WEPS software version used for official purposes by NRCS field offices and Technical Service providers. NRCS developed and maintains the components of the WEPS Databases and information on this site. The USDA-Agricultural Research Service is the lead agency for developing the science in the WEPS model and the model interface. WEPS predicts many forms of soil erosion by wind such as saltation-creep and suspension including PM-10.