Methane is one of the principal greenhouse gases. Irrigated rice paddies are recognized to contribute to the atmospheric methane concentration. Methane emission from rice paddies is among the most uncertain estimates of the agricultural sector in rice-growing countries. Efforts have been made over the last decade to estimate CH4 emission from Chinese rice paddies via model method. However, these estimates showed great uncertainties due to different models and up scaling methods. Reduction in the uncertainties might be achieved by coupling field-scale model to regional databases. The objective of this paper is to develop a methodology of coupling a CH4 emission model to regional databases by which the CH4 emission from Chinese rice paddies is then estimated.
CH₄MOD, a model for simulating CH₄ emission from rice paddies with a minimal number of inputs and parameters that are commonly available, is of great potential for up scaling as it has provided a realistic estimate of the observed results from various soils, climates and agricultural practices. By linking spatial databases to CH4MOD, CH4 emission from Chinese paddies in 2000 ricegrowing season was simulated with a daily step. The spatial databases were created by GIS with a spatial resolution of 10km×10km, which include soil sand percentage, amounts of crop straw and roots from previous season as well as farm manure, water management pattern, dates of rice transplanting and harvesting, acreage of rice planted, rice grain yield and daily air temperature. The software of ArcGIS was used for all of the GIS needs, including the data access, the projection definition, the overlaying of different vector layers, the creation of grids (an raster format of ArcGIS software) by converting vector data, and the conversion of data between grid and ASCII formats.
Methane emission from rice paddies of mainland China in 2000 rice-growing season was estimated to be 6.02 Tg (1 Tg=109 kg). (1.46Tg) are from the early-rice and the late-rice growing seasons, respectively.
It was concluded that regional CH₄ emission from rice paddies could be estimated by coupling CH4MOD to regional databases with a high spatial resolution. A further effort should be focused on improving the quality of the spatial databases, especially in the amount of added organic matter and water regime. It is also necessary to evaluate the uncertainties of the present estimates by which the way to improving accuracy could be approached.