Aarhus University Seal / Aarhus Universitets segl

Quantifying the transport and fate of dissolved nitrogen at different scales in drained agricultural landscapes

Publikation: Bog/antologi/afhandling/rapportPh.d.-afhandlingForskning


  • David Nagy
Nitrogen (N) is an essential part of the agricultural crop production cycle. Farmers generally apply high amounts of N-fertilizer in order to secure the high crop yield, which potentially
increases the risk of N-loss from the root zone. In order to keep the N-concentration of the groundwater and surface water below the European limit for drinking water (11.3 mg N L − 1 ) and concurrently avoid exacerbating the eutrophication of coastal and surface water, N-leaching has to be reduced. Some leaching is an unavoidable part of the agro-ecosystem due to the timing of mineralization of soil organic N, to climate and to current agricultural field management practices. As a result of one of the most widely used practices being the installation of tile drain systems removing the excess water from fields with inadequate percolation, a direct N-transport pathway to surface water has been established. The aim of this PhD study was to identify factors and processes dominating the N-transport to tile drain systems at two different agricultural loamy fields, by numerical analysis of the water and N-balance.
Both fields are highly compacted macroporous soils with indicative hydraulic behaviour for preferential transport (PF). A Danish developed deterministic model, DAISY, was applied
to describe the potential processes involved in N-leaching. By using the dual permeability concept developed by the DAISY group, the model was calibrated and evaluated against hourly drainage loss of water and N, soil water N-concentration, crop dry matter yield and crop N-uptake. The water balance study of Silstrup field, which is presented in Manuscript 1, compared six different model concepts using the dual-permeability approach by incorporating three different macropore settings and two different groundwater table boundary conditions. The study revealed that the potential fraction of the total yearly precipitation transported by preferential flow to the tile drain system was 70%. To be able to simulate the bromide leaching measured in connection with a bromide tracer experiment in 2000 with this model, 54% of the water contributing to the drainage had to be transported via vertical macropores initiated in the plough layer. N-monitoring data obtained on the drainage is hereafter applied, to additionally confine the model and thereby identify the factors and processes which dominate the N-leaching in this hydrogeological agricultural field-setting. This work is described in Manuscript 2 and reveals that a large amount of N (48% to 80% of the total N-loss to drainage) was preferentially transported via macropores to drainage. regardless of the application method and concurrent occurrence of precipitation. The current standard denitrification abiotic water reduction factor in DAISY had to be modified. resulting in a reduction of approximately 50% in the denitrification of the field from a seasonal average of 75 kg N ha − 1 to 35 kg N ha − 1 .
To conduct a more detailed investigation on the impact of drainage conditions on N-leaching, the field-experiment at Tokkerup was initiated (Manuscript 3). Two wells having a flow-magnetometer and ISCO-sampler installed were established to monitor the drainage and conduct flow-proportional sampling of the drainage, for weekly estimation of the N-concentration. The wells were deployed to capture drainage from the PD and WD parts of the field. During a no crop season of 2017-2018 (too wet for sowing winter wheat), a 100 kg N ha − 1 mineral fertilizer was sprayed on the field in autumn 2017. Using the hourly climate and drainage data combined with the N-measurement of the drainage, two DAISY models, representing the PD and WD parts of the field, were set up to compare the leaching processes and their similarities and differences, focusing on preferential transport and denitrification. Model results were able to confirm that, under no crop condition, N can leach to drainage faster by PF than expected. N-transport through macropores was, direct (direct drain connection) and indirect (macropore ending below the drain depth in the matrix). Results showed that the indirect PF transport through the soil matrix transported N to the top of the saturated layer in the soil column, which appeared to be an intermediary stage before the N was transported further to the tile drain system.
The DAISY model describes water, solute and heat transport, crop development and nutrient conversion processes that involve numerous parameters, which have a substantial impact on model calibration. Since DAISY is an overparameterized model, there is a high risk of over-fitting or identifiability problems, as well as equifinality. To decrease the risk of the over-fitting and improve the calibration efficiency, the Morris sensitivity screening method was applied to those model parameters, which were believed to have an impact on the multi-objective function. Included were drainage dynamics (DD) and cumulative drainage (DD), solute transport dynamics of N and bromide (DD and BRD) respectively, and cumulative solute transport of N and bromide (NC and BRC) respectively, harvested dry matter yield (DM yield), harvested N-yield (N yield) and groundwater table fluctuations (GWT). The Morris screening method was applied separately on each objective alone, thereby creating a composite sensitivity screening.
The sensitive parameters were optimized by minimizing the multi-objective function, which was a sum of an error term between the field measurements (calibration objectives) and their simulated counterparts. The performance measures used were the normalized Root Mean Squared Error (nRMSE), normalized Mean Absolute Error (nMAE) and Kling-Gupta Efficiency (KGE). In Manuscript 1, 2 and 3, the differential evolution (DE) optimization was used for parameter optimization.
ForlagAarhus Universitet
Antal sider219
StatusUdgivet - 2020

Se relationer på Aarhus Universitet Citationsformater


Ingen data tilgængelig

ID: 161248256