Combining upscaling and downscaling of methane emissions from rice fields : methodologies and preliminary results

The uncertainty in the methane (CH4) source strength of rice fields is among the highest of all sources in the global CH4 budget. Methods to estimate the source strength of rice fields can be divided into two scaling categories: bottom-up (upscaling) and top-down (downscaling). A brief review of upscaling and downscaling methodologies is presented. The combination of upscaling and downscaling methodologies is proposed as a potential method to reduce the uncertainty in the regional CH4 source strength of rice fields. Some preliminary results based on upscaling and downscaling are presented and the limitations of the approaches are discussed. The first case study focuses on upscaling by using a field-scale model in combination with spatial databases to calculate CH4 emissions for the island of Java. The reliability of upscaling results is limited by the uncertainty in model input parameters such as soil properties and organic carbon management. Because controlling variables such as harvested rice area may change on relatively short time scales, a land use change model (CLUE) was used to quantify the potential land use changes on Java in the period 1994–2010. The predicted changes were evaluated using the CH4 emission model. Temporal scaling by coupling land use change models and emission models is necessary to answer policy-related questions on future greenhouse gas emissions. In a downscaling case study, we investigate if inverse modeling can constrain the emissions from rice fields by testing a standard CH4 from rice scenario and a low CH4 from rice scenario (80 and 30 Tg CH4 yr-1, respectively). The results of this study are not yet conclusive; to obtain fine-resolution CH4 emission estimates over the Southeast Asian continent, the monitoring network atmospheric mixturing ratios need to be extended and located closer to the continental source