Contributions of photosynthate carbon to methane emissions from rice paddies cultivated using different organic amendment methods: Results from an in-situ 13C-labelling study

Abstract. Methane emissions from natural wetlands and rice paddies constitute a large proportion of atmospheric methane, but the magnitude and year-to-year variation of these methane sources are still unpredictable. Here we describe and evaluate the integration of a methane biogeochemical model (CLM4Me; Riley et al., 2011) into the Community Land Model 4.0 (CLM4CN) in order to better explain spatial and temporal variations in methane emissions. We test new functions for soil pH and redox potential that impact microbial methane production in soils. We also constrain aerenchyma in plants in always-inundated areas in order to better represent wetland vegetation. Satellite inundated fraction is explicitly prescribed in the model, because there are large differences between simulated fractional inundation and satellite observations, and thus we do not use CLM4-simulated hydrology to predict inundated areas. A rice paddy module is also incorporated into the model, where the fraction of land used for rice production is explicitly prescribed. The model is evaluated at the site level with vegetation cover and water table prescribed from measurements. Explicit site level evaluations of simulated methane emissions are quite different than evaluating the grid-cell averaged emissions against available measurements. Using a baseline set of parameter values, our model-estimated average global wetland emissions for the period 1993–2004 were 256 Tg CH4 yr−1 (including the soil sink) and rice paddy emissions in the year 2000 were 42 Tg CH4 yr−1. Tropical wetlands contributed 201 Tg CH4 yr−1, or 78% of the global wetland flux. Northern latitude (>50 N) systems contributed 12 Tg CH4 yr−1. However, sensitivity studies show a large range (150–346 Tg CH4 yr−1) in predicted global methane emissions (excluding emissions from rice paddies). The large range is sensitive to (1) the amount of methane transported through aerenchyma, (2) soil pH (±100 Tg CH4 yr−1), and (3) redox inhibition (±45 Tg CH4 yr−1). Results are sensitive to biases in the CLMCN and to errors in the satellite inundation fraction. In particular, the high latitude methane emission estimate may be biased low due to both underestimates in the high-latitude inundated area captured by satellites and unrealistically low high-latitude productivity and soil carbon predicted by CLM4.

Download Full-text

In situ 15N and 13C labelling of indigenous and plantation tree species in a tropical mountain forest (Munessa, Ethiopia) for subsequent litter and soil organic matter turnover studies

Organic Geochemistry ◽

10.1016/j.orggeochem.2011.06.010 ◽

2012 ◽

Vol 42 (12) ◽

pp. 1461-1469 ◽

Cited By ~ 11

Author(s):

Bruno Glaser ◽

Marianne Benesch ◽

Michaela Dippold ◽

Wolfgang Zech

Keyword(s):

Organic Matter ◽

Soil Organic Matter ◽

Tree Species ◽

Mountain Forest ◽

Tropical Mountain ◽

Organic Matter Turnover ◽

Soil Organic Matter Turnover ◽

13C Labelling

Download Full-text

Uncertainties in estimating regional methane emissions from rice paddies due to data scarcity in the modeling approach

Geoscientific Model Development ◽

10.5194/gmd-7-1211-2014 ◽

2014 ◽

Vol 7 (3) ◽

pp. 1211-1224 ◽

Cited By ~ 5

Author(s):

W. Zhang ◽

Q. Zhang ◽

Y. Huang ◽

T. T. Li ◽

J. Y. Bian ◽

...

Keyword(s):

Monte Carlo ◽

Standard Deviation ◽

Rice Variety ◽

Scale Up ◽

Methane Emissions ◽

Data Availability ◽

Scale Model ◽

Anthropogenic Source ◽

Rice Paddies ◽

Data Scarcity

Abstract. Rice paddies are a major anthropogenic source of the atmospheric methane. However, because of the high spatial heterogeneity, making accurate estimations of the methane emission from rice paddies is still a big challenge, even with complicated models. Data scarcity is one of the substantial causes of the uncertainties in estimating the methane emissions on regional scales. In the present study, we discussed how data scarcity affected the uncertainties in model estimations of rice paddy methane emissions, from county/provincial scale up to national scale. The uncertainties in methane emissions from the rice paddies of China was calculated with a local-scale model and the Monte Carlo simulation. The data scarcities in five of the most sensitive model variables, field irrigation, organic matter application, soil properties, rice variety and production were included in the analysis. The result showed that in each individual county, the within-cell standard deviation of methane flux, as calculated via Monte Carlo methods, was 13.5–89.3% of the statistical mean. After spatial aggregation, the national total methane emissions were estimated at 6.44–7.32 Tg, depending on the base scale of the modeling and the reliability of the input data. And with the given data availability, the overall aggregated standard deviation was 16.3% of the total emissions, ranging from 18.3–28.0% for early, late and middle rice ecosystems. The 95% confidence interval of the estimation was 4.5–8.7 Tg by assuming a gamma distribution. Improving the data availability of the model input variables is expected to reduce the uncertainties significantly, especially of those factors with high model sensitivities.

Download Full-text