Carbon sequestration potential of recommended management practices for paddy soils of China, 1980-2050

China's rice paddies, accounting for 19% of the world's total, play an important role in soil carbon (C) sequestration. In order to reduce uncertainties from upscaling spatial processes of the DeNitrification-DeComposition (DNDC) model for improving the understanding of C sequestration under recommended management practices (RMPs), we parameterized the DNDC model with a 1:1,000,000 polygonal soil database to estimate how RMPs influence potential C sequestration of the top 30 cm of Chinese paddy soils and to identify which management practices have the greatest potential to increase soil organic carbon (SOC) in these soils. These practices include reduced/no tillage, increasing crop residue return, and increasing manure applications. A baseline and eleven RMP scenarios were projected from 2009 to 2080, including traditional and conservation tillage, increasing crop residue return, increasing manure incorporation, and the combination of these practices. The results indicated that C sequestration potential under modeled RMPs increased compared to the baseline scenario, and varied greatly from 29.2 to 847.7 Tg C towards the end of the study period with an average rate of 0.7 to 20.2 Tg C yr^− 1. In general, increasing crop residue return was associated with higher rates of C sequestration when compared to increasing manure application or practicing conservation tillage. The simulations demonstrated that the most effective soil C sequestration strategy probably involves the implementation of a combination of RMPs, and that they vary by location.     

不同气候-土壤-耕作组合条件下水稻土有机碳长期演变模拟的不确定性和敏感性分析

Reporting modeling results with uncertainty information can benefit decision making by decreasing the extent that variability exerts a disproportionate influence on the options selected. For making decisions with more confidence, the uncertainty interval should be as narrow as possible. Here, the soil organic carbon(SOC) dynamics of the major paddy soil subgroup from 4 different paddy field regions of China(located in 4 counties under different climate-soil-management combinations) were modeled using the De NitrificationDe Composition(DNDC) model for the period from 1980 to 2008. Uncertainty intervals associated with the SOC dynamics for these 4 subgroups were estimated by a long-term global sensitivity and uncertainty analysis(i.e., the Sobol′method), and their sensitivities to 7 influential factors were quantified using the total effect sensitivity index. The results, modeled with high confidence, indicated that in the past 29 years, the studied paddy soils in Xinxing, Yixing, and Zhongjiang counties were carbon(C) sinks, while the paddy soil in Helong County was a C source. The 3 C sinks sequestered 12.2(5.4, 19.6), 17.1(8.9, 25.0), and 16.9(-1.2, 33.6) t C ha~(-1)(values in the parentheses are the 5th and 95th percentiles, respectively). Conversely, the C source had a loss of -5.4(-14.2, 0.06) t C ha~(-1) in the past 29 years. The 7 factors, which changed with the climate-soil-management context, exhibited variable influences on modeled SOC. Measures with potential to conserve or sequestrate more C into paddy soils, such as incorporating more crop residues into soils and reducing chemical fertilizer application rates, were recommended for specific soils based on the sensitivity analysis results.     

基于不同空间分辨率土壤数据库的中国江苏省水稻土有机碳的动态模拟

A number of process-based models have been developed for quantifying carbon(C)sequestration in agro-ecosystems.The DeNitrification-DeComposition(DNDC)model was used to simulate and quantify long-term(1980-2008)soil organic carbon(SOC)dynamics in the important rice-producing province,Jiangsu,China.Changes in SOC storages were estimated from two soil databases differing in spatial resolution:a county database consisting of 68 polygons and a soil patch-based database of 701 polygons for all 3.7 Mha of rice fields in Jiangsu.The simulated SOC storage with the coarse resolution county database ranged between 131.0-320.6 Tg C in 1980 and 170.3-305.1 Tg C in 2008,respectively,while that estimated with the fine resolution database was 201.6 and 216.2 Tg C in 1980 and 2008,respectively.The results modeled with the soil databases differing in spatial resolution indicated that using the soil input data with higher resolution substantially increased the accuracy of the modeled results;and when lacking detailed soil datasets,the DNDC model,parameterized with the most sensitive factor(MSF) method to cope with attribute uncertainty,could still produce acceptable results although with deviations of up to 60% for the case study reported in this paper.