Evaluation of CH4MOD(wetland) and Terrestrial Ecosystem Model (TEM) used to estimate global CH4 emissions from natural wetlands

Wetlands are the largest and most uncertain natural sources of atmospheric methane (CH4). Several process-based models have been developed to quantify the magnitude and estimate spatial and temporal variations in CH4 emissions from global wetlands. Reliable models are required to estimate global wet...

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Bibliographic Details
Published in:Geoscientific Model Development
Main Authors: Li, Tingting, Lu, Yanyu, Yu, Lingfei, Sun, Wenjuan, Zhang, Qing, Zhang, Wen, Wang, Guocheng, Qin, Zhangcai, Yu, Lijun, Li, Hailing, Zhang, Ran
Format: Article in Journal/Newspaper
Language:English
Published: COPERNICUS GESELLSCHAFT MBH 2020
Subjects:
CO2
Online Access:http://ir.ibcas.ac.cn/handle/2S10CLM1/18347
https://doi.org/10.5194/gmd-13-3769-2020
Description
Summary:Wetlands are the largest and most uncertain natural sources of atmospheric methane (CH4). Several process-based models have been developed to quantify the magnitude and estimate spatial and temporal variations in CH4 emissions from global wetlands. Reliable models are required to estimate global wetland CH4 emissions. This study aimed to test two process-based models, CH4 MODwetland and Terrestrial Ecosystem Model (TEM), against the CH4 flux measurements of marsh, swamp, peatland and coastal wetland sites across the world; specifically, model accuracy and generality were evaluated for different wetland types and in different continents, and then the global CH4 emissions from 2000 to 2010 were estimated. Both models showed similar high correlations with the observed seasonal/annual total CH4 emissions, and the regression of the observed versus computed total seasonal/annual CH4 emissions resulted in R-2 values of 0.81 and 0.68 for CH4 MODwetland and ILM, respectively. The CH4MOD(wetland )produced accurate predictions for marshes, peatlands, swamps and coastal wetlands, with model efficiency (EF) values of 0.22, 0.52, 0.13 and 0.72, respectively. TEM produced good predictions for peatlands and swamps, with EF values of 0.69 and 0.74, respectively, but it could not accurately simulate marshes and coastal wetlands (EF < 0). There was a good correlation between the simulated CH4 fluxes and the observed values on most continents. However, CH4MOD(wetland) showed no correlation with the observed values in South America and Africa. TEM showed no correlation with the observations in Europe. The global CH4 emissions for the period 2000-2010 were estimated to be 105.31 +/- 2.72 Tg yr(-1) by CH4 MODwetland and 134.31 +/- 0.84 Tg yr(-1) by MM. Both models simulated a similar spatial distribution of CH4 emissions globally and on different continents. Marshes contribute 36 %-39 % of global CH4 emissions. Lakes/rivers and swamps are the second and third greatest contributors, respectively. Other wetland types account for only approximately 20 % of global emissions. Based on the model applicability, if we use the more accurate model, i.e., the one that performs best as evidenced by a higher model efficiency and a lower model bias, to estimate each continent and wetland type, we obtain a new assessment of 116.99-124.74 Tg yr(-1) for the global CH4 emissions for the period 2000-2010. Our results imply that performance at a global scale may conceal model uncertainty. Efforts should be made to improve model accuracy for different wetland types and regions, particularly hotspot regions, to reduce the uncertainty in global assessments.