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The Ag Data Commons is migrating

The Ag Data Commons is migrating to a new institutional portal on Figshare. The current system is available for search and download only. The new platform is open for submission with assistance from Ag Data Commons curators. Please contact NAL-ADC-Curator@usda.gov, if you need to publish or update your datasets.

Central Mississippi River Basin LTAR Dataset: NFARM, Inorganic N, & C Production, 2016-2018

    In situ denitrification rates in intact soil cores from the Central Mississippi River Basin (CMRB) LTAR site in MO quantified by directly measuring dinitrogen (N2) and nitrous oxide (N2O) production via the Nitrogen-Free Air Recirculation Method (N-FARM) from 2016-2018. 10-day laboratory incubations provided estimates of ancillary soil data, including microbial respiration and potential net N mineralization and nitrification.

    Gulf Atlantic Coastal Plain LTAR Dataset: NFARM, Inorganic N, & C Production, 2016-2018

      In situ denitrification rates in intact soil cores from the Gulf Atlantic Coastal Plain (GACP) LTAR site in GA quantified by directly measuring dinitrogen (N2) and nitrous oxide (N2O) production via the Nitrogen-Free Air Recirculation Method (N-FARM) from 2016-2018. 10-day laboratory incubations provided estimates of ancillary soil data, including microbial respiration and potential net N mineralization and nitrification.

      Upper Chesapake Bay LTAR Dataset: NFARM, Inorganic N, & C Production, 2016-2018

        In situ denitrification rates in intact soil cores from the Upper Chesapeake Bay (UCB) LTAR site in PA quantified by directly measuring dinitrogen (N2) and nitrous oxide (N2O) production via the Nitrogen-Free Air Recirculation Method (N-FARM) from 2016-2018. 10-day laboratory incubations provided estimates of ancillary soil data, including microbial respiration and potential net N mineralization and nitrification.

        Conservation Practice Effectiveness (CoPE) Database

          This database presents a compilation of data on the effectiveness of innovative practices developed to treat contaminants in surface runoff and tile drainage water from agricultural landscapes. Traditional conservation practices such as no-tillage and conservation crop rotation are included in the database, as well as novel practices such as drainage water management, blind inlets, and denitrification bioreactors.

          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.

            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.

              NUOnet (Nutrient Use and Outcome Network) database

                The Nutrient Uptake and Outcomes (NUOnet) database will be able to help establish baselines on nutrient use efficiencies; processes contributing to nutrient losses; and processes contributing to optimal crop yield, nutritional and organoleptic quality. This national database could be used to calculate many different environmental indicators from a comprehensive understanding of nutrient stocks and flows.