GOSSYM

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.

Plants and Crops

SolarCalc 1.0

Solar Calc: Estimating Hourly Incoming Solar Radiation from Limited Meteorological Data

Agroecosystems & Environment

Global TempSIM - Version 1.0

The purpose of this tool is to estimate daily maximum and minimum air temperatures for a yearly cycle at any location on the globe.

Agroecosystems & Environment

SHOOTGRO

SHOOTGRO emphasizes the development and growth of the shoot apex of small-grain cereals such as winter and spring wheat (Triticum aestivum L.) and spring barley (Hordeum vulgare L.). To better incorporate the variability typical in the field, up to six cohorts, or age classes, of plants are followed using a daily time step.

Plants and Crops

Stream Temperature Modeling and Monitoring: Air Temperature Based Thermal Stream Habitat Model

The Air Temperature Based Thermal Stream Habitat Model was originally developed from weather station information across the Columbia River basin in the Pacific Northwest. Multiple regression was used to predict mean annual air temperatures from elevation, latitude, and longitude with good success R^2 ~ 0.89). The model was developed as an alternative to PRISM data interpolations based on spline surface smoothing and should more accurately represent thermal conditions in stream valleys.

Data from: Quality controlled research weather data – USDA-ARS, Bushland, Texas

The dataset contains 15-minute mean weather data from the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU) research weather station, Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL) for all days in 2016. The data are from sensors deployed at standard heights over grass that is irrigated and mowed during the growing season to reference evapotranspiration standards.

Agroecosystems & Environment

pySnobal

Spatial Modeling for Resources Framework (SMRF) was developed at the USDA Agricultural Research Service (ARS) in Boise, ID, and was designed to increase the flexibility of taking measured weather data and distributing the point measurements across a watershed.

Agroecosystems & Environment

Automated Water Supply Model (AWSM)

Automated Water Supply Model (AWSM) was developed at the USDA Agricultural Research Service in Boise, ID, to streamline the workflow used to forecast the water supply of multiple water basins.