GC122-02
Methane emissions from rice production: a synthesis of 24 eddy covariance sites
Wednesday, 16 December 2020: 05:34
Virtual
Benjamin Runkle1, Zutao Yang2, Robert B Jackson3, Sara Knox4, Gavin McNicol5, Dario Papale6, Maricar C. R. Alberto7, Dennis D Baldocchi8, Alessandro Cescatti9, Chi-Ling Chen10, Bryant Fong11, Haiqiang Guo12, Hiroki Iwata13, Qingyu Jia14, Weimin Ju15, Minseok Kang16, Joon Kim17, Hong Li18, Hao Lu19, Michele L Reba11, Debora Regina Roberti20, Youngryel Ryu21, Ben-Jei Tsuang22, Wenping Yuan23 and Yongguang Zhang24, (1)University of Arkansas, Fayetteville, AR, United States, (2)Stanford University, Stanford, United States, (3)Stanford University, Stanford, CA, United States, (4)University of British Columbia, Geography, Vancouver, AB, Canada, (5)Stanford Earth Sciences, Earth System Science, Stanford, CA, United States, (6)University of Tuscia, Department for Innovation in Biological, Agro-food and Forest systems (DIBAF), Viterbo, Italy, (7)International Rice Research Institute, Laguna, Philippines, (8)University of California Berkeley, Department of Environmental Science, Policy, and Management, Berkeley, CA, United States, (9)European Commission, Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy, (10)Taiwan Agricultural Research Institute, Wufeng, Taichung, Taiwan, (11)USDA-ARS, Delta Water Management Research Unit, Jonesboro, AR, United States, (12)Fudan University, Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, and Coastal Ecosystems Research Station of the Yangtze River Estuary,, Shanghai, China, (13)Shinshu University, Matsumoto, Japan, (14)China Meteorological Administration, Institute of Atmospheric Environment, Shenyang, China, (15)Nanjing University, Nanjing, China, (16)Seoul National University, Seoul, South Korea, (17)Seoul National University, Department of Landscape Architecture & Rural Systems Engineering, Future Earth Program in Asia Center, Interdisciplinary Program in Agricultural and Forest Meteorology, Institute of Green Bio Science and Technology, Seoul, South Korea, (18)Chongqing University, Faculty of Architecture and Urban Planning,, Chongqing, China, (19)Nanjing University of Information Science and Technology, Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing, China, (20)UFSM Federal University of Santa Maria, Santa Maria, Brazil, (21)Seoul National University, Department of Landscape Architecture and Rural Systems Engineering, Seoul, South Korea, (22)National Chung Hsing University, Environmental Engineering, Taichung, Taiwan, (23)Sun Yat-sen University, School of Atmospheric Sciences, Guangzhou, China, (24)Nanjing University, International Institute for Earth System Sciences, Nanjing, China
Abstract:
Rice production annually contributes up to 8% of anthropogenic CH4 emissions, creating a higher per-calorie climate burden than other grains. It is still crucial to understand how production management and underlying field conditions contribute to CH4 production and emission in rice fields, at different time scales and locations. Landscape-scale greenhouse gas emissions measurements are possible with the eddy covariance method. They offer a different perspective from chamber- or laboratory-scale measurements by covering a larger area, integrating across smaller-scale soil and management heterogeneity, and providing a largely continuous record. We have assembled a unique global dataset from 24 rice field sites measured with eddy covariance. The diversity of agronomic, edaphic, and climate conditions enables a unique perspective on CH4 flux dynamics from these important agro-ecosystems. The dataset contains 46 growing seasons and it has been gap-filled and analyzed following a consistent protocol from the Fluxnet-CH4 project. The aims are (1) to quantify the range of CH4 emissions at different time scales (2) derive their key drivers and (3) to make the dataset available for further process-based modeling.
Emissions vary widely across locations: daily peak CH4 emissions range from 1-12 kg CH4-C ha-1 (median 2.6 kg CH4-C ha-1); seasonal emissions range from 4-606 kg CH4-C ha-1 (median 90 kg CH4-C ha-1). The median diurnal range (max-min daily flux) ranged from 0.11 to 2.3 kg CH4-C ha-1 hr-1 (median 0.5 kg CH4-C ha-1 hr-1). Seasonal emissions are correlated to N fertilization rate (R2=0.47 for sites not frequently drained) and can be reduced through frequent drainage (to 4-35 CH4-C ha-1). Fertilization rates may be representative of a number of other agronomic factors, including higher biomass and yields; a yield-normalized analysis will follow. Irrigation and agronomic management (including drainage dynamics, fertilizer applications, residue management, and crop rotations) play a strong role in determining net CH4 emissions. These findings highlight the need for clear biological and ancillary data and meta-data to be included in the dataset and offer a basis for climate-smart rice production management.
