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ARS Home » Pacific West Area » Pendleton, Oregon » Columbia Plateau Conservation Research Center » Research » Publications at this Location » Publication #124064

Title: CQESTR, A FIELD-LEVEL FARM CARBON SEQUESTRATION PLANNING TOOL

Author
item RICKMAN, RONALD
item DOUGLAS, CLYDE
item Albrecht, Stephan
item BERC, JERI

Submitted to: Proceedings International Global Warming Conference
Publication Type: Proceedings
Publication Acceptance Date: 6/6/2001
Publication Date: 11/1/2001
Citation: N/A

Interpretive Summary: A new predictive model, CQESTR was developed using an existing organic carbon decomposition model (D3R). Observed soil organic carbon data from long term management plots established in 1931 on the Research Center at Pendleton OR were used to calibrate the model. Results from validation studies using data from numerous long-term sites with crop rotation, tillage, and soil organic matter content records will be provided. CQESTR utilizes annual input of organic biomass both above and below ground, residue burial by tillage, biomass nitrogen content, soil density and organic matter content by layer, and climate, to predict changes of organic matter induced by amendment practices, crop and tillage sequences. The model, in a Windows environment, which may be used in conjunction with the Revised Universal Soil Loss Equation (RUSLE), taping into existing RUSLE databases, is being field tested at the farm level, in the U.S. and Canada. Preliminary results of the performance of the model as a field- level planning tool, to assist farm managers select rotations/tillage practices and the use of organic amendments to meet carbon sequestration objectives will also be presented.

Technical Abstract: A new predictive model, CQESTR was developed using an existing organic carbon decomposition model (D3R). CQESTR utilizes annual input of organic biomass both above and below ground, residue burial by tillage, biomass nitrogen content, soil density and organic matter content by layer, and climate, to predict changes of organic matter induced by management practices, including amendments, and crop and tillage sequences. Observed soil organic carbon data from long-term management plots established in 1931 on the Research Center at Pendleton OR were used to calibrate the model. Results from validation studies using data from numerous long-term sites throughout the United States and in parts of Canada, with crop rotation, tillage, and soil organic matter content records is provided. Examples of model predictions for various short-term farm management scenarios are presented. The model, in a Windows environment, which may be used in conjunction with the Revised Universal Soil Loss Equation (RUSLE), taping into existing RUSLE databases, is being beta-tested at the farm level, in universities, and research laboratories in the U.S. and Canada. Preliminary results of the beta tests to assess the model are presented.