4.4 Article

Uncertainty in CENTURY-modelled changes in soil organic carbon stock in the uplands of Northeast China, 1980-2050

Journal

NUTRIENT CYCLING IN AGROECOSYSTEMS
Volume 113, Issue 1, Pages 77-93

Publisher

SPRINGER
DOI: 10.1007/s10705-018-9963-1

Keywords

Agricultural SOC; Uncertainty analysis; Global sensitivity analysis; CENTURY model

Categories

Funding

  1. National Key Research and Development Program of China [2017YFA0603002]
  2. Natural Science Foundation of China [41471177, 31800358]
  3. Research Fund of State Key Laboratory of Soil and Sustainable Agriculture [Y412201417]

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Process-based models have been successfully applied to predict long-term changes in soil organic carbon (SOC) at plot scales, but considerable uncertainties are still introduced into regional or national extrapolations due to the lack of spatially explicit information on the model input parameters. Using the CENTURY model we predicted SOC changes in the uplands of Northeast China during the period from 1980 to 2050 and provided 95% confidence intervals regarding the uncertainties associated with variability in the key input parameters. Regional SOC estimation predicted by CENTURY was reliable for the uplands of Northeast China when considering the uncertainty associated with heterogeneous key input parameters. SOC stocks were estimated to be 0.99, 0.88 and 0.87 Pg C in 1980, 2010 and 2050, with 95% confidence intervals ranging from 0.69 to 1.31, 0.66 to 1.11, and 0.69 to 1.07 Pg C, respectively. Overall, the upland soils of Northeast China functioned as a carbon source from 1980 to 2010, with a net decrease of 106 (9-207) Tg C. The SOC losses mainly occurred where SOC contents were high (Heilongjiang Province and eastern Jilin Province). However, assuming unchanged management, whether the uplands of Northeast China will serve as a carbon sink/source over the next 40 years remains uncertain. Information collection on the most influential input parameters (the initial SOC content and clay content) is critical to reduce uncertainty and to provide meaningful information for decision makers.

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