Using the DayCent Ecosystem Model to Predict Methane Emissions from Wetland Rice Production in Support for Mitigation Efforts

Abstract:

Wetland rice production is a major source of greenhouse gas (GHG) emissions to the atmosphere, and rice production is predicted to increase dramatically in the future due to expected growth in human populations. Mitigating GHG emissions from future rice production is possible with best management practices for water management, residue management and organic amendments. Policy initiatives and programs that promote practices to reduce GHG emissions from rice production will likely need robust methods for quantifying emission reductions. Frameworks based on process-based model provide one alternative for estimating emissions reductions. The advantages of this approach are that the models are relatively inexpensive to apply, incorporate a variety of management and environmental drivers influencing emissions, and can be used to predict future emissions for planning purposes. The disadvantages are that the models can be challenging to parameterize and evaluate, and require a relatively large amount of data.

The DayCent ecosystem model simulates plant and soil processes, and is an example of a model that could be used to quantify emission reductions for reporting mitigation activities associated with rice production systems. DayCent estimates methane emissions, which is the major source of GHG emissions from wetland rice, but also estimates nitrous oxide emissions and soil organic C stock changes. DayCent has been evaluated using data from China, explaining 83% of the variation in methane emissions from 72 experimental rice fields. In addition, DayCent has been applied regionally in the United States to estimate methane, nitrous oxide emissions, and soil C stock changes, in compliance with the guidelines for reporting GHG emissions to the UN Framework Convention on Climate Change. Given the cost of alternatives, process-based models such as DayCent may offer the best way forward for estimating GHG emissions from rice production, and with quantification of uncertainty, could provide a robust framework for policy initiatives and programs in the future.