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Combining Model Estimates and Measurements Through an Ensemble Kalman Filter to Estimate Carbon Sequestration

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Paper number  033042,  2003 ASAE Annual Meeting . (doi: 10.13031/2013.13848) @2003
Authors:   W. McNair Bostick, Jawoo Koo, James W. Jones, Arjan J. Gijsman, P. Sibiry Traoré, B. Vincent Bado
Keywords:   Ensemble Kalman Filter, Data Assimilation, Carbon Trading, Modeling

Rapidly increasing atmospheric CO2 concentrations have stimulated interest in enhancing carbon (C) sequestration in land stocks through C trading. In C trading, one party offsets a portion of their CO2 emissions by paying another party to sequester C. One challenge to implementing C trading is verifying sequestration over large areas. In this study, a data assimilation technique, the Ensemble Kalman Filter (EnKF), was used to improve C sequestration estimates. The EnKF combines measurements, model estimates, and the uncertainties thereof to optimally estimate system state variables and parameters. The EnKF also provides a measure of confidence in these estimates. Our EnKF was implemented with a C model containing fresh, humic, and stable soil C pools and a plant biomass pool. The latter can be estimated using a cropping system model, remote sensing-based model or direct measurements. Our EnKF was used to update the status of the soil C pools and selected rate parameters for a 50-year simulation. A sensitivity analysis was conducted to evaluate the effects of uncertainties in measurements, model predictions, and selected rate parameters on EnKF estimates. Data from the Highland bare fallow plot at the Institute of Arable Crops Research, Rothamsted, UK were used as measurements for the analysis. The largest EnKF updates occurred with the humic C pool and the rate parameter for this pool (KH). These updates were most sensitive to uncertainties in the initial value of KH and measurements of total soil C. The EnKF provides a framework for handling the uncertainty involved with verifying C sequestration.

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