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Estimating soil carbon sequestration in Ghana

Posted on:2008-09-19Degree:Ph.DType:Dissertation
University:University of FloridaCandidate:Koo, JawooFull Text:PDF
GTID:1443390005955695Subject:Engineering
Abstract/Summary:PDF Full Text Request
Soil carbon sequestration is often referred to as a win-win strategy for developing countries to improve food security while mitigating atmospheric CO2 increase. However, to accept the soil carbon sequestration as a mechanism for reducing atmospheric CO2 levels, its regional potential should be assessed, and a reliable soil carbon monitoring system needs to be developed. Based on in situ measurements and cropping systems survey in the study area located in Northern Ghana in 2004 and 2006, smallholders' cropping systems in 132 fields were characterized and simulated for 20 years using the DSSAT-Century model. Soil carbon sequestration potential under the adoption of recommended management practices (e.g., no-till practice, fertilization of cereals, and retention of crop residues in the field) was assessed. The potential soil carbon sequestration rate was estimated as a tradable amount when regionally aggregated. To reduce estimation variability in soil carbon measurements, the potential of using a data assimilation method that assimilates measurements with simulated outputs was studied. Using an ensemble Kalman filter with simulated cropping systems, this approach reduced uncertainty in soil carbon measurements by 60% in a single-field study. The ensemble Kalman filter was also used to spatially assimilate soil carbon measurements and aggregate estimations over landscape. Compared with a geostatistical interpolation method, the data assimilation method showed superior estimation accuracy with less uncertainty. Overall, results of this study showed a potential of soil carbon sequestration in the study area and the potential of using a data assimilation method to develop a reliable soil carbon monitoring system.
Keywords/Search Tags:Soil carbon, Data assimilation method, Potential, Study area, Atmospheric CO2, Ensemble kalman filter
PDF Full Text Request
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