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.
The Rapid Carbon Assessment (RaCA) was initiated by the USDA-NRCS Soil Science Division in 2010 with the following objectives:
- To develop statistically reliable quantitative estimates of amounts and distribution of carbon stocks for U.S. soils under various land covers and to the extent possible, differing agricultural management.
- To provide data to support model simulations of soil carbon change related to land use change, agricultural management, conservation practices, and climate change.
- To provide a scientifically and statistically defensible inventory of soil carbon stocks for the U.S.
The Forest Insect and Pathogen Hazard Rating System Database is a collection of detailed summaries of published insect and disease hazard models and their associated citations organized in a SQL Server relational database. It currently contains over 700 citation records describing over 700 models. This…
The Soil and Water Hub is jointly developed by USDA Agricultural Research Service (USDA-ARS) and Texas A&M AgriLife Research, part of The Texas A&M University System. Modeling dataset resources are available for download for use with software tools Agricultural Policy/Environmental eXtender Model (APEX), Soil and Water Assessment Tool (SWAT), ArcSWAT, and related Conservation practices.
The Soil and Water Assessment Tool (SWAT) is a public domain model jointly developed by USDA Agricultural Research Service (USDA-ARS) and Texas A&M AgriLife Research, part of The Texas A&M University System. SWAT is a small watershed to river basin-scale model to simulate the quality and quantity of surface and ground water and predict the environmental impact of land use, land management practices, and climate change. SWAT is widely used in assessing soil erosion prevention and control, non-point source pollution control and regional management in watersheds.
SWIFT (Small Watershed Nutrient Forecasting Tool) is a web-based tool that allows the rapid estimation of sediment and nutrient loads from small watersheds for a given ecoregion in the US.
NLET (National Load Estimating Tool) is a web-based tool for estimating pollutant loads in watersheds across the contiguous United States. This tool helps visualize the effects of land use patterns, cultivated crops, and conservation practices through graphical representation.
Agricultural Policy/Environmental eXtender (APEX) has components for routing water, sediment, nutrients, and pesticides across complex landscapes and channel systems to the watershed outlet as well as groundwater and reservoir components. A watershed can be subdivided as much as necessary to assure that each subarea is relatively homogeneous in terms of soil, land use, management, and weather. APEX was constructed to evaluate various land management strategies considering sustainability, erosion (wind, sheet, and channel), economics, water supply and quality, soil quality, plant competition, weather, and pests. The routing of water, sediment, nutrient, and pesticide capabilities are some of the most comprehensive available in current landscape-scale models and can be simulated between subareas and channel systems within the model. APEX can perform long-term continuous simulations for modeling the impacts of different nutrient management practices, tillage operations, conservation practices, alternative cropping systems, and other management practices on surface runoff and losses of sediment, nutrients, and other pollutant indicators.
Process-based models are increasingly used to study mass and energy fluxes from agro-ecosystems, including nitrous oxide (N2O) emissions from agricultural fields. This data set is the output of three process-based models – DayCent, DNDC, and EPIC – which were used to simulate fluxes of N2O from dairy farm soils. The individual models' output and the ensemble mean output were evaluated against field observations from two agricultural research stations in Arlington, WI and Marshfield, WI. These sites utilize cropping systems and nitrogen fertilizer management strategies common to Midwest dairy farms.
To assess the magnitude of greenhouse gas (GHG) fluxes, nutrient runoff and leaching from dairy barnyards and to characterize factors controlling these fluxes, nine barnyards were built at the U.S. Dairy Forage Research Center Farm in Prairie du Sac, WI (latitude 43.33N, longitude 89.71W). The barnyards were designed to simulate outdoor cattle-holding areas on commercial dairy farms in Wisconsin. Each barnyard was approximately 7m x 7m; areas of barnyards 1-9 were 51.91, 47.29, 50.97, 46.32, 45.64, 46.30, 48.93, 48.78, 46.73 square meters, respectively. Factors investigated included three different surface materials (bark, sand, soil) and timing of cattle corralling. Each barnyard included a gravity drainage system that allowed leachate to be pumped out and analyzed. Each soil-covered barnyard also included a system to intercept runoff at the perimeter and drain to a pumping port, similar to the leachate systems.