The Impacts Of Paddy Field Management On Greenhouse Gas Emissions

Greenhouse gas emissions from agricultural fields, particularly CH₄ （methane） and N₂O （nitrous oxide） from paddy rice in a subtropical environment, have been blamed for regional climate change. The subtropical Zhejiang Province has been known for its tradition of paddy rice farming and thus a quantitative understanding how paddy rice management can effectively mitigate CH₄ and N₂O emission is of great interest in global change research. In addition to greenhouse gas emission, paddy rice management can also have a significant impact on nitrogen leaching that can be transported to oceans and lakes and cause eutrophication and algal blooms or red tides in the coastal zone waters.This thesis selected some typical paddy rice fields in Dasong River Watershed in the Yinzhou District, Ningbo City, a geographic area near the Xiangshangang Bay and characterized by the tradition of single rice cropping system. Field measurements of soil properties and questionnaire survey of management practices such as fertilizer application methods, seeding time, irrigation methods, and residue treatments were carried out to determine biophysical characteristics and management options that can be used in an already developed biogeochemical model to analyze their impacts on greenhouse gas emissions. The overall goal of this thesis research is to better understand the interactive nature of soil properties, climate, paddy yields, and management practices of paddy rice in typical subtropical climate environment like Zhejiang.The biogeochemical model used in this thesis is the DNDC （DeNitrification-DeComposition）, developed and calibrated by a large number of scholars over the past twenty years including Dr. Changsheng LI （see reference）. This model simulates rice yields and GHG emissions, as well as nitrogen leaching. By providing different management options, with varying soil and cultivar information as inputs to the DNDC model, GHG emission pattern and their associated input variables can be analyzed to determine significant environmental and management factors affecting greenhouse emissions.The results showed that there is a large variation in CH₄ fluxes among the different paddy fields, suggesting that management practices and soil conditions are dominant factors affecting CH₄ emissions. During the winter fallow and field drying periods, CHU fluxes were almost at zero level, suggesting the vegetation （paddy rice） is critical in biological decomposition processes to generate greenhouse gases. After rice transplanting, CH₄ fluxes increased gradually and reached peak values at the times when paddy rice develops branches, elongates and ears, respectively. Similarly, N₂O fluxes showed three pulses occurring at transplanting period, non-flood period, and field drying period, respectively.There existed significant differences in the factors affecting CH₄ and N₂O emissions in 2014. Factors affecting CH₄ emissions from paddy fields included soil clay fraction, depth of submergence, and waterlogging days. Soil clay fraction affects CHU emissions through changing soil infiltration capability and decomposition rate of soil organic matter. Water column alters soil reduction-oxidation potential and in turn affects CH₄ emissions. Factors that affect N₂O emissions included nitrogen fertilizer amount and SOC （soil organic carbon）. Nitrogen fertilizer contributes directly to N₂O emissions, while soil organic matter provides source materials to soil microbial activities, and hence promotes N₂O emissions.Simulation results showed that there was no significant relationship between rice yield and CH₄ emission. Model sensitivity analyses showed that the CH₄ and N₂O emissions were sensitive to the changes in pH and SOC. Analyses further showed that nitrogen fertilizer was overused in the studied farm fields. There seems to be a transition point or tipping point in nitrogen fertilizer applications at 37.5 kgN/hm², at which rate both yields can be maintained and N₂O emission were kept minimal. By keeping flooding days to 70-80 days and selecting low drainage rice strains, the CH₄ emissions from paddy fields can be substantially reduced. Besides, leaving crop residues in the field is a common practice in the study area, and reducing residues in the field can also effectively reduce CH₄ emissions while maintaining rice yields.Overall, use of biogeochemical models such as DNDC allows an effective analysis of paddy rice yields, nitrogen leaching, greenhouse gas emissions and various management options that can be collectively optimized to achieve a win-win management option. Future research is needed to expand such research to larger geographic areas to encompass a much diverse soils, rice cultivars, climate and management options, with geospatial tools and methods.