All code needed to reproduce the analyses in the manuscript IDENTIFICATION OF A KEY TARGET FOR ELIMINATION OF NITROUS OXIDE, A MAJOR GREENHOUSE GAS.
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.
- 3x csv
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.
- 3x csv
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.
- 3x csv
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.
Characterization of streams and rivers in the Minnesota River Basin Critical Observatory: water chemistry and biological field collections, 2013-2016
The dataset contains point locations, watershed areas and water quality information for 231 ditch, stream, river and wetland sites located in the Le Sueur River, Chippewa River, Cottonwood River, Cannon River, Wantonwan River and Blue Earth River basins of Minnesota.
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.