A semi‐empirical model of methane emission from flooded rice paddy soils

Abstract

Reliable regional or global estimates of methane emissions from flooded rice paddy soils depend on an examination of methodologies by which the current high variability in the estimates might be reduced. One potential way to do this is the development of predictive models. With an understanding of the processes of methane production, oxidation and emission, a semi‐empirical model, focused on the contributions of rice plants to the processes and also the influence of environmental factors, was developed to predict methane emission from flooded rice fields. A simplified version of the model was also derived to predict methane emission in a more practical manner. In this study, it was hypothesized that methanogenic substrates are primarily derived from rice plants and added organic matter. Rates of methane production in flooded rice soils are determined by the availability of methanogenic substrates and the influence of environmental factors. Rice growth and development control the fraction of methane emitted. The amount of methane transported from the soil to the atmosphere is determined by the rates of production and the emitted fraction. Model validation against observations from single rice growing seasons in Texas, USA demonstrated that the seasonal variation of methane emission is regulated by rice growth and development. A further validation of the model against measurements from irrigated rice paddy soils in various regions of the world, including Italy, China, Indonesia, Philippines and the United States, suggests that methane emission can be predicted from rice net productivity, cultivar character, soil texture and temperature, and organic matter amendments.

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

“…Improving the data abundance of model inputs is expected to reduce the uncertainties in estimating terrestrial greenhouse gas emissions, in which the sensitivity of the model inputs also plays a key role. CH4MOD is an semi-empirical model that simulates methane production and emissions from rice paddies under various environmental conditions and agricultural practices (Huang et al, 1998aXie et al, 2010). This model calculates the production of methanogenic substrates from the rice plant's root exudates and added organic matter (OM) decomposition.…”

“…CH4MOD is a semi-empirical model that simulates methane production and emissions from rice paddies under various environmental conditions and agricultural practices (Huang et al, 1998aXie et al, 2010). The CH4MOD model runs with a daily step and is driven by air temperature.…”

“…Rice paddy methane emissions vary notably with rice variety (Singh et al, 1997). The variety index (VI), which accounts for the methane emission differences between rice varieties (Huang et al, 1998a, ranges from 0.5 to 1.5, and it typically has a value close to 1.0 for most rice varieties (Huang et al, 1997. We assumed that the 95 % confidence interval (CI) for VI was 0.5 to 1.5 and that it exhibited a normal distribution.…”

“…In CH4MOD, the impact of rice variety on methane emissions was parameterized as the VI (Huang et al, 1998a. The VI ranges from 0.5 to 1.5 and typically has a value of approximately 1.0 for most rice varieties (Huang et al, 1997.…”

Model comparisons of methane oxidation across a management gradient: Wetlands, rice production systems, and landfill

“…The rice model is a semiempirical process-level model derived from field research on the mechanisms of methane production, oxidation, and emission in irrigated rice fields [Huang et al, 1997[Huang et al, , 1998a[Huang et al, , 1998b. The model is based on the observations that (1) rice growth and development is a key factor governing the processes of methane production, oxidation, and emission in flooded rice fields, (2) methanogenic substrates are primarily derived from rice plants via root exudation or biomass liter and from organic amendments, (3) soil redox potential functions as a threshold in methane production, and (4) soil texture and soil temperature significantly influence methane production and emission.…”