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Related Experiment Video

Updated: Aug 22, 2025

Assessment of Methane and Nitrous Oxide Fluxes from Paddy Field by Means of Static Closed Chambers Maintaining Plants Within Headspace

Assessment of Methane and Nitrous Oxide Fluxes from Paddy Field by Means of Static Closed Chambers Maintaining Plants Within Headspace

Published on: September 6, 2018

A GIS-based method for modeling methane emissions from paddy fields by fusing multiple sources of data.

Linhua Ma¹, Yuanlai Cui¹, Bo Liu²

¹State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China.

The Science of the Total Environment

|November 7, 2022

Summary

A new GIS-based Regional Methane (CH4) Emission Calculation (GRMC) method accurately quantifies methane emissions from paddy fields. This approach integrates remote sensing data and soil moisture to improve climate change mitigation strategies.

Keywords:

CH(4) flux Paddy fields Remote sensing Semi-empirical model

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Last Updated: Aug 22, 2025

Assessment of Methane and Nitrous Oxide Fluxes from Paddy Field by Means of Static Closed Chambers Maintaining Plants Within Headspace

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Published on: September 6, 2018

Measurement of Greenhouse Gas Flux from Agricultural Soils Using Static Chambers

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Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions

Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions

Published on: June 12, 2016

Area of Science:

Environmental Science
Remote Sensing
Agricultural Science

Background:

Quantifying regional methane (CH4) emissions from paddy fields is crucial for climate change mitigation.
Existing models (mechanism and empirical) have limitations in parameterization and spatial resolution.
There is a need for a more accurate and scalable method to estimate CH4 emissions from rice cultivation.

Purpose of the Study:

To develop and validate a GIS-based Regional Methane (CH4) Emission Calculation (GRMC) method for paddy fields.
To integrate remote sensing data and soil moisture dynamics for improved CH4 emission quantification.
To assess the spatial-temporal variations of CH4 emissions on a regional scale.

Main Methods:

Developed a GIS-based Regional Methane (CH4) Emission Calculation (GRMC) method, adapting the CH4MOD model.
Utilized remote sensing data (MOD09A1, MOD11A2, MOD15A2H) and local water management standards.
Quantified soil moisture stress (f(water)) using redox potential (Eh) and analyzed its relationship with CH4 emissions.

Main Results:

The GRMC method demonstrated strong performance in tracking seasonal CH4 emission dynamics across four Eddy Covariance (EC) sites (R²: 0.738-0.848).
Applied to the Ganfu Plain Irrigation System (GFPIS), the method revealed significant spatial-temporal variations in CH4 emissions.
Total late rice CH4 emissions in GFPIS ranged from 14.47-20.48 (10³ t CH4-C) between 2001-2013.

Conclusions:

The GRMC method is effective for regional-scale CH4 emission estimation from rice fields.
Soil moisture and temperature are key factors influencing spatial variations in CH4 production and emission.
The developed method provides a valuable tool for climate change research and agricultural management.