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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.

    RZWQM2

      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.

      LANDFIRE

        LANDFIRE (LF), Landscape Fire and Resource Management Planning Tools, is a shared program between the wildland fire management programs of the U.S. Department of Agriculture Forest Service and U.S. Department of the Interior, providing landscape scale geo-spatial products to support cross-boundary planning, management, and operations. LANDFIRE is a program that provides over 20 national geo-spatial layers (e.g. vegetation, fuel, disturbance, etc.), databases, and ecological models that are available to the public for the US and insular areas.

        Dairy Gas Emissions Model (DairyGEM)

          The Dairy Gas Emissions Model (DairyGEM) uses process level simulation and process related emission factors to predict ammonia, hydrogen sulfide, VOC and greenhouse gas emissions along with the carbon, energy and water footprints of dairy production systems.

          International Soil Carbon Network

            The ISCN is a self-chartered, international, collaborative organization composed of scientists who recognize a need for and value in large-scale synthesis of soil carbon science.

            Data from: Underestimation of N2O emissions in a comparison of the DayCent, DNDC, and EPIC 1 models

              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.

              Data from: Soil organic carbon and isotope composition response to topography and erosion in Iowa

                The dataset includes topographic information, soil properties, and 137Cs levels collected from a 15 ha cropland under soybean/maize (C3/C4) rotation in June 2002. The cropland is located in the central-western part of the Walnut Creek watershed, Story County, Iowa. 128 sampling locations were collected and three soil samples were obtained using a 3.2 cm-diameter push probe from the 0 to 30 cm soil layer within a 1 m × 1 m quadrat at each sampling location. Deeper soil samples were collected from 30 to 50 cm layers in locations where sediment deposition was observed. The three samples from each sampling location were mixed and analyzed to determine soil properties, SOC content and its carbon (C) isotope composition (C12 to C13 ratio), and 137Cs levels. For landscape topography of each sampling location, topographic metrics were derived from a digital elevation mode using LiDAR (Light Detection and Ranging) data. These data are useful in investigating the fate of eroded SOC in croplands and its responses to landscape topography.

                Data from: Gas emissions from dairy barnyards

                  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.