Development of a new model for the simulation of N2O emissions from wheat
cropping systems in Spain
Gallejones, P.a, Aizpurua, A.b, Del Prado, A.a
aBC3.
Basque Centre for Climate Change. Bilbao, Spain.
Institute for Agricultural Research and Development, Derio, Spain.
bNEIKER-Basque
1. Introduction
Management practices involving fertilizer N should be efficient in order to maximize crop
production while minimizing adverse effects to the environment such as greenhouse gasses (GHG)
emissions. In order to overcome the limitation of the extremely simplified approaches for the field
sites used in some holistic methods (e.g. life cycle analysis (LCA) or GHG inventories), it is
important to develop simple modeling tools that can be integrated within these methods and help
predict the effect of management and site conditions on both GHG losses and crop production.
This paper describes the development of an empirical model that simulates the monthly N flows in
arable cropping systems based on readily available site information and fertilizer management.
2. Model description
The model has a monthly time-step and has been constructed based on data of several field
experiments under winter wheat, carried out in different areas of Spain (Quemada, 2006) and
taking some of the principles used for mass-balance N modeling in grasslands by Scholefield et al.
(1991); Brown et al. (2005) and del Prado et al. (2006).
The model initially computes the annual N mineralization coming from previous years soil organic
matter (SOM) based on soil texture as net mineralized N is generally associated to the soil aeration
and has to be parameterized for specific climatic conditions. Annual net mineralized N from
previous years SOM from the different soils and regions was derived from data obtained from the
zero-fertilized plots of Quemada, (2006) and it was distributed for the different months based on
temperature and moisture (Macduff and White, 1985).Total net soil N mineralisation is calculated
by adding to the previous mineralised pool the mineralisation from the current year´s plant N
residue and organic N applied to the soil. The inorganic N flux is calculated taking into account all
the N inputs to the system (N deposition, N fertiliser and total net N mineralisation). This soil
inorganic N flow will be the basis for empirically estimating the total N uptake by the crop for the
main crop growing stages (Fig. 1) and total yield. These flows are then calibrated for the simulated
weather conditions. For every month, soil inorganic N that is not taken up by the plant is subject to
different loss pathways (volatilisation, denitrification, nitrification and leaching). Some N is lost as
NH3 volatilised after fertiliser N is applied and some of the remaining soil inorganic N is emitted and
lost through denitrification and nitrification processes (Brown et al., 2005). The remaining inorganic
N can be leached, accumulated for the following months or immobilised into the SOM pool.
Following the equations from Rodda et al. (1995) the percentage of soil inorganic N that is monthly
leached is calculated depending on the soil texture and the total annual drainage volume.
N uptake (kg ha-1 )
400
y = 0.6063x + 8.8263
R² = 0.8014
300
200
100
0
0
100
200
300
Inorganic N (kg
400
500
ha-1 )
Fig. 1. Relationship between the annual flux of soil inorganic N and the N taken up by the crop.
A daily water balance submodel was also incorporated following the steps of Allen et al., (1998) in
order to simulate the water that is lost bellow the rooting zone on a daily basis. These soil water
calculations will be very important drivers to calculate plant uptake and soil N losses.
3. Preliminary results
The effect of three different N fertilizer rates as ammonium nitrate (100, 140 and 180 kg N ha-1) on
the N2O emissions was simulated (Fig. 2) for a wheat crop grown in the Basque Country. Nitrous
oxide results for the different treatments suggest that the relationship between annual N fertilizer
and N2O emissions is not lineal. Whereas the field fertilized with the lowest rate shows the highest
emission factor (EF) (ratio N2O: N fertilization), the lowest EF results after fertilizing the middle N
treatment. Although N2O emissions are regulated by multiple and complex processes in the soil,
the model is indirectly showing that the N2O emissions are also very much controlled by the plant
ability to absorb N too and thus, by the plant N use efficiency.
Fig 2. Monthly N2O emissions for each N fertilizer treatment applied to a winter crop in the Basque Country.
4. Conclusions
This work shows the importance of using simulation tools in order to improve existing
methodologies such as LCA for calculating GHG emissions. Model calibration and validation will be
essential to ensure a good approach.
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