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Improved Estimation of Soil Organic Carbon Storage Uncertainty Using First‐Order Taylor Series Approximation
Author(s) -
Panda Dileep K.,
Singh R.,
Kundu D. K.,
Chakraborty H.,
Kumar A.
Publication year - 2008
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj2007.0242n
Subject(s) - soil carbon , taylor series , covariance , carbon sequestration , context (archaeology) , econometrics , carbon capture and storage (timeline) , land use, land use change and forestry , environmental science , series (stratigraphy) , climate change , soil survey , soil science , mathematics , statistics , land use , soil water , carbon dioxide , engineering , chemistry , mathematical analysis , paleontology , ecology , organic chemistry , civil engineering , biology
Assessment of soil organic C (SOC) stocks is important for monitoring the effect of land use change in the C cycle and for formulation of C sequestration strategies in the context of global climate change. Discrepancies among the recent global SOC estimates by different researchers underscore the importance of precise estimation of the uncertainty associated with the SOC stocks. A method was recently proposed to estimate the SOC storage uncertainty using the Taylor series of approximations. Here we show that the accuracy of SOC storage uncertainty can be improved by incorporating the covariance among the input variables. Measurement of input variables from independent samples or use of an incomplete model leads to either over‐ or underestimation of the SOC storage uncertainty. The application of the method to an experimental data set indicated that ignoring covariance would lead to a substantial overestimate of the uncertainty.