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.

Uncertainty and sensitivity analyses for modeling long-term soil organic carbon dynamics of paddy soils under different climate-soil-management combinations

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 DeNitrificationDeComposition (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.