Daycent Simulation of Methane Emissions, Grain Yield, and Soil Organic Carbon in a Subtropical Paddy Rice System

Weiler, Douglas Adams; Tornquist, Carlos Gustavo; Zschornack, Tiago; Ogle, Stephen M.; Carlos, Filipe Selau; Bayer, Cimélio

doi:10.1590/18069657rbcs20170251

Cited by 6 publications

(7 citation statements)

References 30 publications

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“…The Eh in soil changes based on the flooded or drainage conditions. Continuous flooding, whether by rainfall, irrigation or both, would be a FLOD 2 period in the model schedule, with maximum Eh of -250 mV (Cheng et al, 2013, Weiler et al, 2018. The water conditions under rainfall do not saturate in the model, therefore fixed values (-20 mV) were indicated as FLOD 1.…”

Section: Mitigation Scenarios and Net Ghg Balancementioning

confidence: 99%

“…Eh approximations are specific to the methane model. Further development of the Eh algorithm was suggested by Weiler et al, (2018), where they found contrasting results between simulated and observed CH4 emissions in flood-irrigated rice paddy fields under no tillage in southern Brazil. Soil water and gas filled pore space in the current version are normal inputs to the N2O emissions, but are not currently considered in the methane Eh equations.…”

Section: Mitigation Scenarios and Net Ghg Balancementioning

confidence: 99%

“…For this study, we selected the DayCent model (Parton et al, 1998) which has recently had a methanogenesis sub-model added. Early studies with this version showed adequate model performance in simulating trends in SOC content and CH4 fluxes in agricultural regions -in China (Cheng et al, 2013(Cheng et al, , 2014 and Brazil (Weiler et al, 2018). The DayCent was also applied in Bangladesh rice croplands to determine SOC sequestration potential at site level (Begum et al, 2018b) and the GHG mitigation potential in regional scale (Begum et al, 2018a).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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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.

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Section: Mitigation Scenarios and Net Ghg Balancementioning

confidence: 99%

Section: Mitigation Scenarios and Net Ghg Balancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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“…This finding is in accordance with other studies conducted with the DayCent model under different agricultural management systems (Del Grosso et al, 2001;Del Grosso et al, 2008;Smith et al, 2012;Begum et al, 2018;Weiler et al, 2019). As was also observed by Oliveira et al (2017) and Weiler et al (2018), the model modified in this study overestimated the soil C and N stocks. However, this result is considered acceptable considering the complexity of the management systems evaluated in these studies.…”

Section: Model Simulation Efficiencysupporting

confidence: 93%

Intensification and diversification of degraded pasture areas in Brazil: potential of soil C accumulation and mitigation of the climate changes

Damian¹

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Intensification and diversification of degraded pasture areas in Brazil: potential of soil C accumulation and mitigation of the climate changesPasture improvements in Brazil, where pastures occupy ~167 million ha, have great potential for soil carbon (C) accumulation and to mitigate of greenhouse gases (GHG), such as the carbon dioxide (CO2). However, soil degradation on current pasture areas (> 50% are degraded) is an issue to be solved through sustainable management. The aim of our current field study was to quantify soil C stocks and to elucidate the processes, involved in the soil C accumulation in areas subjected to different intensive and diversified systems of pasture management in Brazil. Treatments included fertilized pasture (FP), integrated crop-livestock (ICL) and integrated livestock-forest (ILF), compared to the extensive form (conventional management system) under contrasting climatic conditions (tropical humid, tropical mesic and subtropical). To meet this goals, there were avaluaded i) the soil C stocks changes and the soil organic matter (SOM) quality; ii) the relationships between the soil C and N stocks with the different phosphorus (P) fractions; iii) the soil chemical and biochemical properties and, the soil bacterial community structure to assess the controlling factors on soil C accumulation and, iv) the use mathematical modeling to predict the soil C changes and GHG emissions. In general, the adoption of more intensive and diversified systems of pasture management in areas previously used with extensive management systems increased the soil C stocks and the soil C lability. Likewise, there was an improvement in the soil chemical properties related to soil fertility, especially in soil P. The increase in the labile P contents was directly proportional to the increase of the more labile SOM fractions. Furthermore, the conversion of conventional management system to more intensive and diversified pasture management systems, besides changing the soil chemical and biochemical properties and the soil bacterial community structure, also modified the mechanisms that control the soil C accumulation. According to the structural equation modeling, the improvement in the soil chemical properties was the factor that most influenced in soil C accumulation. In addition, through long-term predictions performed with the DayCent model, it was found that while extensively managed pastures were a GHG source to the atmosphere, systems of pasture management, such as FP, ICL and ILF were GHG sinks. Thus, for the conditions tested in this study the DayCent model proved to be an a efficient and costeffective tool to predict soil C pool changes and to monitor GHG emissions. Finally, it is believed that the results found in this thesis can assist national initiatives aimed at restoring degraded pasture areas (e.g., "ABC Plan"), as well as fits the scope of the Brazil's NDC (Nationally Determined Contribution) for mitigating GHG emissions (reduce emissions 37% by 2025 and 43% by 2030) through the increase of the soi...

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“…For the four paddocks independently evaluated, the behavior of aboveground biomass shows that even with some differences, it was still possible to represent the ICLS (Figure 9). The model did not overestimate or underestimate aboveground biomass for the study period; previous studies have reported a DayCent tendency to underestimate grain yield and aboveground biomass [11,78,79]. Generally, significant errors may occur because the model does not consider several processes that depend on crop management, such as those associated with biotic stresses from weeds, diseases, or insects [80].…”

Section: Validated Modelmentioning

confidence: 83%

Intense Pasture Management in Brazil in an Integrated Crop-Livestock System Simulated by the DayCent Model

et al. 2022

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Process-based models (PBM) are important tools for understanding the benefits of Integrated Crop-Livestock Systems (ICLS), such as increasing land productivity and improving environmental conditions. PBM can provide insights into the contribution of agricultural production to climate change and help identify potential greenhouse gas (GHG) mitigation and carbon sequestration options. Rehabilitation of degraded lands is a key strategy for achieving food security goals and can reduce the need for new agricultural land. This study focused on the calibration and validation of the DayCent PBM for a typical ICLS adopted in Brazil from 2018 to 2020. We also present the DayCent parametrization for two forage species (ruzigrass and millet) grown simultaneously, bringing some innovation in the modeling challenges. We used aboveground biomass to calibrate the model, randomly selecting data from 70% of the paddocks in the study area. The calibration obtained a coefficient of determination (R2) of 0.69 and a relative RMSE of 37.0%. During the validation, we used other variables (CO2 flux, grain biomass, and soil water content) measured in the ICLS and performed a double validation for plant growth to evaluate the robustness of the model in terms of generalization. R2 validations ranged from 0.61 to 0.73, and relative RMSE from 11.3 to 48.3%. Despite the complexity and diversity of ICLS results show that DayCent can be used to model ICLS, which is an important step for future regional analyses and large-scale evaluations of the impacts of ICLS.

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Daycent Simulation of Methane Emissions, Grain Yield, and Soil Organic Carbon in a Subtropical Paddy Rice System

Cited by 6 publications

References 30 publications

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

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

Intensification and diversification of degraded pasture areas in Brazil: potential of soil C accumulation and mitigation of the climate changes

Intense Pasture Management in Brazil in an Integrated Crop-Livestock System Simulated by the DayCent Model

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