Simulation of global warming potential (GWP) from rice fields in the Tai-Lake region, China by coupling 1:50,000 soil database with DNDC model

Quantifying greenhouse gas (GHG) emissions from wetland ecosystems is a relatively new issue in global climate change studies. China has approximately 22% of the world's rice paddies and 38% of the world's rice production, which are crucial to accurately estimate the global warming potential (GWP) at regional scale. This paper reports an application of a biogeochemical model (DeNitrification and DeComposition or DNDC) for quantifying GWP from rice fields in the Tai-Lake region of China. For this application, DNDC is linked to a 1:50,000 soil database, which was derived from 1107 paddy soil profiles compiled during the Second National Soil Survey of China in the 1980-1990s. The simulated results show that the 2.34 Mha of paddy soil cultivated in rice-wheat rotation in the Tai-Lake region emitted about -1.48 Tg C, 0.84 Tg N and 5.67 Tg C as CO2, N2O, and CH4 respectively, with a cumulative GWP of 565 Tg CO2 equivalent from 1982 to 2000. As for soil subgroups, the highest GWP (26,900 kg CO2 equivalent ha(-1) yr(-1)) was linked to gleyed paddy soils accounting for about 4.4% of the total area of paddy soils. The lowest GWP (5370 kg CO2 equivalent ha(-1) yr(-1)) was associated with submergenic paddy soils accounting for about 0.32% of the total area of paddy soils. The most common soil in the area was hydromorphic paddy soils, which accounted for about 53% of the total area of paddy soils with a GWP of 12,300 kg CO2 equivalent ha(-1) yr(-1). On a regional basis, the annual averaged GWP in the polder, Tai-Lake plain, and alluvial plain soil regions was distinctly higher than that in the low mountainous and Hilly soil regions. As for administrative areas, the average annual GWP of counties in Shanghai city was high. Conversely, the average annual GWP of counties in Jiangsu province was low. The high variability in soil properties throughout the Tai-Lake region is important and affects the net greenhouse gas emissions. Therefore, the use of detailed soil data sets with high-resolution digital soil maps is essential to improve the accuracy of GWP estimates with process-based models at regional and national scales. (C) 2009 Elsevier Ltd. All rights reserved.