Modelling greenhouse gas emissions and mitigation potentials in fertilized paddy rice fields in Bangladesh

Abstract

Emissions of greenhouse gases (GHG) from paddy rice are significant, so reducing these emissions has significant potential for climate change mitigation. We investigated alternate wetting and drying (AWD) as part of an integrated management approach to enhance mitigation, together with combinations of mineral nitrogen (N), reduced tillage, a suitable combination of plant residues and well decomposed manure. To quantify GHG emissions, and the potential for mitigation without yield decline, a process-based model, DayCent, was used to simulate methane (CH4) and nitrous oxide (N2O) emissions from paddy rice (Oryza sativa L.) in Bangladesh. The four test sites selected were amended with mineral N fertilizer or an organic amendment (rice straw). A good agreement (p < 0.05) was observed between model simulated and measured daily CH4 flux at most of these test sites with no significant bias. The seasonal CH4 emission from a site receiving mineral N fertilizer at a rate of 110 kg N ha-1 was predicted by the model to be 210 and 150 kg ha-1 for the water management scenarios of continuous flood (CF) and AWD, respectively. These values compare well with estimates of CH4 emissions using Intergovernmental Panel on Climate Change tier 1 methods for the different water regimes. Our model results suggest emission factors for N2O of 0.4% and 0.6% of applied fertilizer under CF and AWD water regimes, respectively. Based on modelling studies, AWD was found to be an important strategy not only with respect to reducing GHG emissions, but also in terms of cost effectiveness. We also found that integrated management is a promising option for farmers and policy makers interested in either yield increase, GHG mitigation or both. Yield scaled emissions intensity under AWD was found to be about 24% lower than under CF, followed by integrated management.

Model Based Regional Estimates of Soil Organic Carbon Sequestration and Greenhouse Gas Mitigation Potentials from Rice Croplands in Bangladesh

“…ha −1 year −1 of N 2 O emissions reductions reported for Chinese rice cropland [1]. Irrigated rice fields have N 2 O emissions approximately 36% higher than emissions under CF conditions in DayCent simulations [36]. In this study, by observing N 2 O emissions separately for both growing seasons, simulated N 2 O emissions under irrigated rice, where AWD was applied only for this season, increased by 40% compared to CF conditions (not shown) but no change (or a reduction of 10%) was observed during the second cropping season.…”

“…A highly significant positive relationship (p < 0.001) between modelled and measured yields was observed under different management practices [35]. DayCent also captured the differences in variation for CH 4 emissions from the four irrigated rice treatments under different N fertilization regimes [36]. The model performance for N 2 O emissions, evaluated only for one experimental site, did not show a close agreement between modelled and measured N 2 O flux; however, there was no systematic bias in the modelled results, just large uncertainties due to a lack of precision in the model predictions.…”

“…The DayCent model has also been tested by the US government and is used for estimating GHG emissions in their national inventory for reporting to the UN Framework Convention on Climate Change [34]. Soil organic carbon changes, GHG emissions and yield under different management has also been tested by DayCent in Bangladeshi rice experimental sites [35,36]. The present study aimed to determine the mitigation potential for SOC sequestration, considering the impacts on CH 4 and N 2 O emissions, from double rice cropping systems in Bangladesh on a spatial basis.…”

The importance of management information and soil moisture representation for simulating tillage effects on N&lt;sub&gt;2&lt;/sub&gt;O emissions in LPJmL5.0-tillage

“…As simulating tillage effects on N 2 O emissions is generally challenging, we use the site-specific model DayCent (Del Grosso et al, 2009;Parton et al, 1996), which has previously been applied at the study sites, as a benchmark and to provide more detailed information on soil hydrology than the sparse observations. DayCent is a well-established model that has been used for questions related to agricultural impact assessments at various scales (e.g., Begum et al, 2019;Del Grosso et al, 2009, 2002Gryze et al, 2010). DayCent can be used as a benchmark with which the underlying mechanisms can be analyzed and for improvements of LPJmL5.0-tillage even though the performance of DayCent has to be compared to observations first.…”

The importance of management information and soil moisture representation for simulating tillage effects on N&lt;sub&gt;2&lt;/sub&gt;O emissions in LPJmL5.0-tillage

“…DayCent is a wellestablished model that has been used for questions related to agricultural impact assessments at various scales (e.g. Begum et al, 2019;Del Grosso et al, 2009;Del Grosso et al, 2002;Gryze et al, 2010). DayCent can be used as a benchmark for which the underlying mechanisms can be analyzed and used for improvements of LPJmL5.0-tillage, even though the performance of DayCent has to be compared to observations first.…”