Modelling nitrous oxide (N 2 O) emission from rice field in impacts of farming practices: A case study in Duy Xuyen district, Quang Nam province (Central Vietnam)

Nitrous oxide (N 2 O) emisison from paddy soil via the soil nitrification and denitrification processes makes an important contribution to atmospheric greenhouse gas concentrations. The soil N 2 O emission processes are controlled not only by biological, physical and chemical factors but also by farming practices. In recent years, modeling approach has become popular to predict and estimate greenhouse gas fluxes from field studies. In this study, the DeNitrification–DeComposition (DNDC) model were calibrated and tested by incorporating experimental data with the local climate, soil properties and farming management, for its simulation applicability for the irrigated rice system in Duy Xuyen district, a delta lowland area of Vu Gia-Thu Bon River Basin regions. The revised DNDC was then used to quantitatively estimate N 2 O emissions from rice fields under a range of three management farming practices (water management, crop residue incorporation and nitrogen fertilizer application rate). Results from the simulations indicated that (1) N 2 O emissions were significantly affected by water management practices; (2) increases in temperature, total fertilizer N input substantially increased N 2 O emissions. Finally, five 50-year scenarios were simulated with DNDC to predict their long-term impacts on crop yield and N 2 O emissions. The modelled results suggested that implementation of manure amendment or crop residue incorporation instead of increased nitrogen fertilizer application rates would more efficiently mitigate N 2 O emissions from the tested rice-based system.


Modelling nitrous oxide (N 2 O) emission from rice field in impacts of farming practices: A case study in Duy Xuyen district, Quang Nam province (Central Vietnam)
Mô hình hóa phát thải khí nitơ ôxít (N 2 O) từ ruộng lúa dưới tác động của các biện pháp canh tác: nghiên cứu điểm tại huyện Duy Xuyên, tỉnh Quảng Nam (Việt Nam) Nitrous oxide (N 2 O) emisison from paddy soil via the soil nitrification and denitrification processes makes an important contribution to atmospheric greenhouse gas concentrations. The soil N 2 O emission processes are controlled not only by biological, physical and chemical factors but also by farming practices. In recent years, modeling approach has become popular to predict and estimate greenhouse gas fluxes from field studies. In this study, the DeNitrification-DeComposition (DNDC) model were calibrated and tested by incorporating experimental data with the local climate, soil properties and farming management, for its simulation applicability for the irrigated rice system in Duy Xuyen district, a delta lowland area of Vu Gia-Thu Bon River Basin regions. The revised DNDC was then used to quantitatively estimate N 2 O emissions from rice fields under a range of three management farming practices (water management, crop residue incorporation and nitrogen fertilizer application rate). Results from the simulations indicated that (1) N 2 O emissions were significantly affected by water management practices; (2) increases in temperature, total fertilizer N input substantially increased N 2 O emissions. Finally, five 50-year scenarios were simulated with DNDC to predict their long-term impacts on crop yield and N 2 O emissions. The modelled results suggested that implementation of manure amendment or crop residue incorporation instead of increased nitrogen fertilizer application rates would more efficiently mitigate N 2 O emissions from the tested rice-based system.  , 2007). This standard reporting procedure has advantages in collating annual inventories but may mask significant variations in emission factors (EFs) on a regional scale (Laegreid et al, 2002) Given the considerable expense of establishing and maintaining relevant flux measurement sites, the use of simulation models to estimate N 2 O fluxes from agricultural soils using soil and climate data has obvious benefits.
Modelling also allows easy interpretation of the complex links between soil physical, chemical and microbial processes that underpin nitrification, denitrification and decomposition. Models can simulate the processes responsible for production, consumption and transport of N 2 O in both the long and short term, and also on a spatial scale (Williams et al., 1992).
Simulation models range from simple empirical relationships based on statistical analyses to complex mechanistic models that consider all factors affecting N 2 O production in the soil (Li et al., 1992;Frolking et al., 1998;Roelandt et al., 2005). Variations in soil moisture, soil temperature, carbon and nitrogen substrate for microbial nitrification and denitrification are critical to the determination of N 2 O emissions (Frissel and Van Veen, 1981). One widely used mechanistic model is DeNitrification DeComposition (DNDC) developed to assess N 2 O, NO, N 2 and CO 2 emissions from agricultural soils (Li et al., 1992a(Li et al., , 1994Li 2000). Advantages of DNDC are that it has been extensively tested and has shown reasonable agreement between measured and modelled results for many different ecosystems. The model has reasonable data requirement and is suitable for simulation at appropriate temporal and spatial scales.
This paper presents a field evaluation of DNDC for paddy land under 2 water regimes (Continuous flooding (CF) and Alternate Wetting-Drying (AWD)) with different crop residue incorporation and nitrogen fertilizer application rate. Results are discussed in terms of the suitability of DNDC model for estimating annual and seasonal fluxes of N 2 O from rice field in Vu Gia -Thu Bon river basin.

Experimental site and measurement
Study site is located in Vu Gia-Thu Bon River Basin, which is the largest river basins and also the key economic and agricultural zone of the Central Coast region of Vietnam. The rice is planted as a main food crop in the whole region with 120,000 ha of cultivated area occupying 61% agricultural land of basin (Ngo et al, 2015).
The experiments were caried out by Hue University of Agriculture and Forestry (HÙA) in summer-autumn crop season of 2012 at Duy Xuyen district of Quang Nam Province. The experiments included treatments varying in N sources and water management in plots of 5 m long and 5 m wide. Fourteen-day-old rice seedlings were transplanted by hand at 20 cm (row to row) x 15 cm (hill to hill) spacing. N 2 O emission was measured frequently from the plots following GHGs measurement for manual static/closed chamber method. Grain yield were measured at maturity. The measured data from field experiment were used for the calibration of the model. Daily ambient air temperature and precipitation data were collected from the local meteorological station. The soils, water and air temperature within the chambers were also recorded during each of gas samplings (Ngo et al, 2015).

Overview of DNDC model
The model of denitrification and decomposition (DNDC) is a generic model that simulates biogeochemical processes leading to greenhouse gas emissions from soil. As a process-based biogeochemical model, the DNDC can simulates carbon (C) and nitrogen (N) cycles in cropping systems (in a daily or subdaily time step) driven by both the environmental factors and management practices. The DNDC consists of two components reflect the two-level driving forces that control C and N dynamics. The first component is based on ecological and biophysical drivers (e.g. climate, soil, vegetation, and anthropogenic activity), consisting of soil climate, crop growth, and decomposition sub-models. The second component, which consists of fermentation, denitrification, and nitrification submodels, predicts NO, N 2 O, N 2 , CO 2 , CH 4 , and NH 3 gaseous fluxes based on the soil environmental variables [6].
The field experiments provided the field data of N2O emissions with relevant environmental conditions. The field data were firstly used for model validation. During the validation tests, the local daily climate data, soil properties and actual farming practices were utilized to compose input scenarios, and the modelled rice yields as well as the N2O flux were compared with the field observations. After that, model sensitivity test (for the same site but with varied climate, soil conditions and farming management) as well as long-term predictions was done with the validated model. Model sensitivity test was evaluated for changes in some farming practices (water regime, N application, straw incorporation) on rice yields and N emission using the baseline data (local weather, soil, location, and other inputs) (Ngo et al, 2015).

Model validation
Most of the crop physiological and phenological parameters set in the DNDC model were originally calibrated against datasets observed in the U.S, India, China or other temperate regions [6]. Discrepancies appeared when the model was applied for the rice crops in Vietnam. Validations were therefore made for the DNDC model to improve its performance in simulating crop yield and N 2 O emissions for Vietnamese rice fields. Originally, the N2O fluxes simulated by the model were higher than the measured fluxes in some rice paddies in Vietnam. DNDC was run with the local weather data (i.e., air maximum and minimum temperatures and precipitation) of 2012, soil properties (i.e., texture, bulk density, SOC content and pH), and farming management practices (i.e., crop type and rotation, planting and harvest dates, tillage, fertilization, and irrigation) as described in above section (Ngo et al, 2015). The simulations fairly captured the magnitudes and patterns of the observed N 2 O emissions for water regimes. DNDC quantifies N 2 O fluxes by simulating both nitrification and denitrification rates at daily time steps, respectively. The statistical analysis showed that the relative deviations between the observed and modelled N 2 O fluxes were about 45% with an absolute difference. The simulated data indicated that the modelled emissions of N 2 O were mostly from nitrification; and the episodic peak fluxes were dominated by denitrification. Several of the modelled high peaks of N 2 O emissions were induced by the N-fertilizer applications or irrigation. In general, DNDC predicted more N 2 O flux peaks which were not observed in the field in comparison with field observations. The discrepancies between simulated and observed seasonal fluxes were less than 20% of the field seasonal fluxes. The discrepancy on the N 2 O emissions could be related to the interpolation approach converting the observed daily N 2 O fluxes to seasonal total. Overall, it was encouraging to see how DNDC predicted the magnitudes and patterns of N2O emissions for rice-based system in Central Vietnam though discrepancies existed in some cases.

Model sensitivity analysis
In this study, DNDC was run with a one-year baseline scenario that was composed based on the actual climate, soil and management conditions in 2011. The sensitivity tests were conducted by varying a single input factor in the range, which was commonly observed in the local farmland within the county scope, while keeping all other input parameters constant as in the baseline scenario. The details of baseline and alternative scenarios are listed in Tables 2. DNDC was run with each of the scenarios to produce an annual flux of N 2 O for the tested site. The sensitivity order of the drivers was determined by comparison the annual N 2 O fluxes induced by varying each of the drivers.  (Table 3). The grain yield of rice increased with application rates up to 210 kg N/ha, but with smaller increases at rates above 150 kg N/ha. Emissions of N 2 O remained unchanged up to 180 kg N/ha. As the fields were continuously flooded, keeping them anaerobic throughout the growing period, the process of nitrification producing NO − 3 from NH + 4 was stopped, and denitrification was also inhibited because of the nonavailability of substrate (NO − 3 ) for this process. The nitrification and denitrification process were mainly responsible for the formation of N 2 O in soil. However, the application of N-fertilizer increased N 2 O emissions because of larger fluxes of NH 4 +-N.
Water management also influenced the simulated yield and emissions of N 2 O from soil (Table 3). There is no significant difference of rice yield in comparison between CF and AWD. N emissions however increased marginally by a range of 7% to 20% with ADW as compared to baseline CF treatment, respectively, which resulted in aerobic conditions of soil with enhanced nitrification forming N 2 O and NO 3 − . It also enhanced denitrification by supplying the substrate (NO 3 − ) for the denitrifies, resulting in more N 2 O emissions when the field was re-flooded (Aulakh et al 1992).

(Note: a & b; the significant difference between two means by T-test analysis at α=0,05)
Results from the sensitivity tests indicated that, among the tested natural factors (i.e., temperature, precipitation, soil texture, SOC content and pH), the SOC content showed the greatest impact on N 2 O fluxes. When SOC increased from 0.5% to 2%, the annual N 2 O emission rate increased from 10% to 35% ha -1 y -1 . The modelled data indicated that higher SOC produced more DOC and inorganic N (i.e., ammonium and nitrate) through decomposition that led to higher rates of nitrification and denitrification, the two processes producing N 2 O. In comparison with SOC, other natural factors such as temperature, precipitation, soil texture or pH had relatively moderate effects on N 2 O emissions from paddy soil at the study site.

Long-term impacts of management practices on N 2 O fluxes
The above-described one-year sensitivity tests indicated that N 2 O emissions were sensitively affected by certain natural or management factors. However, the long-term consequence of varying the natural or management factors could differ from the short-term results due to the accumulative effects of N in the soils. To test the long-term impacts, we used 4 long-term alternative management 50year-scenarios including: (1) decreasing the fertilizer application rate from the baseline (120 kg ha -1 ) to 90 kg ha -1 , (2) increasing the fertilizer application rate to 210 kg ha -1 (3) increasing the crop residue incorporation rate from the baseline (20%) to 100%, and (4) increasing FYM rate from 0 (baseline) to 6000 kg ha -1 . Except for the above-listed practices, other factors (e.g., climate, soil and management) were kept same as the actual conditions at study site. The climate data of 2012 were repeatedly utilized for the 50 years. DNDC was run for 50 years with each of the scenarios, and the modelled seasonal fluxes of N 2 O were recorded for assessment.
In comparison with the baseline, the modelled results indicated that manure amendment and elevated residue incorporation both increased SOC content that provided more substrates to stimulate N 2 O emissions through nitrification and denitrification in the soil. The increase in fertilizer application rate elevated N 2 O emissions; and the decrease in fertilizer application rate reduced N 2 O emissions (Figurre 1).

Figure 1. Impacts of management practices on longterm N 2 O fluxes
As a summary, in comparison with the baseline results, increase in nitrogen fertilizer application rate elevated soil C content but resulted in a higher N 2 O value and N leaching loss. Increase in manure application rate and crop residue incorporation had positive impacts on mitigating the global warming though the two practices led to a litter increase in N leaching loss due to increase in the soil N supply. In general, the modelled results suggested that implementation of manure amendment or crop residue incorporation instead of increased fertilizer application rates would more efficiently mitigate GHG emissions from the tested agroecosystem. Although the results reported in this paper were only for a specific site, the general trends resulted from the study could be applicable to other locations in the region with the same conditions.
As a summary, in comparison with the baseline results, increase in nitrogen fertilizer application rate elevated soil C content but resulted in a higher N 2 O value and N leaching loss. Increase in manure application rate and crop residue incorporation had positive impacts on mitigating the global warming though the two practices led to a litter increase in N leaching loss due to increase in the soil N supply. In general, the modelled results suggested that implementation of manure amendment or crop residue incorporation instead of increased fertilizer application rates would more efficiently mitigate GHG emissions from the tested agroecosystem. Although the results reported in this paper were only for a specific site, the general trends resulted from the study could be applicable to other locations in the region with the same conditions.

Conclusions
By comparing the modelled results on N 2 O emissions against observations for paddy field in Vu Gia-Thu Bon river basin, the applicability of DNDC for this kind of cropping system was confirmed. The sensitivity tests conducted with DNDC provided detailed information about how the environmental or management factors affected N 2 O emissions. The results indicated that (1) increases in temperature, initial SOC, total fertilizer N input, and manure amendment substantially significantly increased N 2 O emissions; and (2) temperature, initial SOC, tillage, and quantity and quality of the organic matter added in the soil all had significant effects on global warming. Finally, five 50year-scenarios were simulated with DNDC to predict their long-term impacts on crop yield and N 2 O emissions. The multi impacts provided a sound basis for comprehensive assessments on the management alternatives. In general, DNDC proved a decent model through the validations, sensitivity tests and long-term predictions conducted in the study. This kind of modelling tools should play an important role in not only environmental impacts but also agricultural production for a wide range of agro-ecosystems in Central Vietnam.