Given the importance of the potential positive feedback between methane (CH4) emissions and climate change, it is critical to accurately estimate the magnitude and spatiotemporal patterns of CH4 emissions from global rice fields and better understand the underlying determinants governing the emissions. Here we used a coupled biogeochemical model in combination with satellite-derived contemporary inundation area to quantify the magnitude and spatiotemporal variation of CH4 emissions from global rice fields and attribute the environmental controls of CH4 emissions during 1901–2010. Our study estimated that CH4 emissions from global rice fields varied from 18.3 ± 0.1 Tg CH4/yr (Avg. ±1 SD) under intermittent irrigation to 38.8 ± 1.0 Tg CH4/yr under continuous flooding in the 2000s, indicating that the magnitude of CH4 emissions from global rice fields is largely dependent on different water schemes. Over the past 110 years, our simulated results showed that global CH4 emissions from rice cultivation increased by 85%. The expansion of rice fields was the dominant factor for the increasing trends of CH4 emissions, followed by elevated CO2 concentration, and nitrogen fertilizer use. On the contrary, climate variability had reduced the cumulative CH4 emissions for most of the years over the study period. Our results imply that CH4 emissions from global rice fields could be reduced through optimizing irrigation practices. Therefore, the future magnitude of CH4 emissions from rice fields will be determined by the human demand for rice production as well as the implementation of optimized water management practices.
|Number of pages||18|
|Journal||Global Biogeochemical Cycles|
|State||Published - Sep 1 2016|
Bibliographical noteFunding Information:
This study has been supported by the NASA Interdisciplinary Science Program (NNX10AU06G, NNX11AD47G, and NNG04GM39C), the NASA Land Cover/Land Use Change Program (NNX08AL73G and NNX14AD94G), the NASA Carbon Monitoring System Program (NNX14AO73G), and the National Science Foundation (1243232 and 1243220). We acknowledge Prigent Catherine for providing the dynamic inundation extent data sets and Felix Portmann for providing the MIRCA2000 data sets. We thank associated editor and two anonymous referees for their constructive comments and suggestions to improve the manuscript. All input data and output files used in this manuscript are available from the author upon request (email@example.com).
©2016. American Geophysical Union. All Rights Reserved.
- biogeochemical modeling
- climate change
- optimized water management
- rice field
ASJC Scopus subject areas
- Global and Planetary Change
- Environmental Chemistry
- Environmental Science (all)
- Atmospheric Science