Keywords

reactive nitrogen, crop management, SWAT, hot spots and hot moments of reactive nitrogen emissions

Start Date

16-9-2020 8:40 AM

End Date

16-9-2020 9:00 AM

Abstract

Reactive nitrogen (Nr) occurs in various forms, e.g. nitrate (NO3-) and nitrous oxide (N2O). Nitrate in the environment mainly stems from N-fertilizer and has negative impacts on water quality, it also causes N2O emissions. In Austria in 2016, N2O emissions from the agricultural sector contributed 4.5% to national greenhouse gas emissions. Current process-based models face challenges to simulate N2O emissions due to the lack of observational data to verify the simulations and the deficiency in simulating by-products such as NOx from nitrification and denitrification processes. The objective of this study is to identify critical areas and times of the year for Nr emissions from Austrian cropland, in part by improving the ability to model N2O emissions. Many factors influence N2O emissions and these can be grouped into: management factors (e.g. types of fertilizer and crop), environmental factors (e.g. soil properties and climate) and measurement factors (e.g. sampling length). The eco-hydrological model SWAT (Soil and Water Assessment Tool (Arnold et al., 1998)) was used to identify hot spots and hot moments of Nr emissions in the Melk catchment (282 km2) located in Lower Austria in the foothills of the Alps. The catchment elevation ranges from 201 - 1050 m with a mean annual precipitation of 794 mm. The landscape is varied with rolling hills and mixed farming, occupied by 12% pasture, 22% forest and 63% cropland (22.8% winter wheat, 11.6% corn and 9.6% corn silage as the main crops). Challenges in the Melk catchment include soil and water erosion, nutrient loss due to agricultural intensification and the loss of cultural landscapes. A sensitivity analysis, calibration and validation for daily discharge and nitrate was carried out using the SWATplusR tool (Schürz, 2019). The NO3- and N2O variables will be analysed from the SWAT model and then used to improve a N2O module.

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Sep 16th, 8:40 AM Sep 16th, 9:00 AM

Hot spots and hot moments of reactive nitrogen emissions in an Austrian agricultural catchment simulated with the SWAT eco-hydrological model

Reactive nitrogen (Nr) occurs in various forms, e.g. nitrate (NO3-) and nitrous oxide (N2O). Nitrate in the environment mainly stems from N-fertilizer and has negative impacts on water quality, it also causes N2O emissions. In Austria in 2016, N2O emissions from the agricultural sector contributed 4.5% to national greenhouse gas emissions. Current process-based models face challenges to simulate N2O emissions due to the lack of observational data to verify the simulations and the deficiency in simulating by-products such as NOx from nitrification and denitrification processes. The objective of this study is to identify critical areas and times of the year for Nr emissions from Austrian cropland, in part by improving the ability to model N2O emissions. Many factors influence N2O emissions and these can be grouped into: management factors (e.g. types of fertilizer and crop), environmental factors (e.g. soil properties and climate) and measurement factors (e.g. sampling length). The eco-hydrological model SWAT (Soil and Water Assessment Tool (Arnold et al., 1998)) was used to identify hot spots and hot moments of Nr emissions in the Melk catchment (282 km2) located in Lower Austria in the foothills of the Alps. The catchment elevation ranges from 201 - 1050 m with a mean annual precipitation of 794 mm. The landscape is varied with rolling hills and mixed farming, occupied by 12% pasture, 22% forest and 63% cropland (22.8% winter wheat, 11.6% corn and 9.6% corn silage as the main crops). Challenges in the Melk catchment include soil and water erosion, nutrient loss due to agricultural intensification and the loss of cultural landscapes. A sensitivity analysis, calibration and validation for daily discharge and nitrate was carried out using the SWATplusR tool (Schürz, 2019). The NO3- and N2O variables will be analysed from the SWAT model and then used to improve a N2O module.