Abstract Purpose The CQESTR model is a process-based C model recently developed to simulate soil organic matter (SOM) dynamics and uses readily available or easily measurable input parameters. The current version of CQESTR (v. 2.0) has been validated successfully with a number of datasets from agricultural sites in North America but still needs to be tested in other geographic areas and soil types under diverse organic management systems. Materials and methods We evaluated the predictive performance of CQESTR to simulate long-term (34 years) soil organic C (SOC) changes in a SOM-depleted European soil either unamended or amended with solid manure, liquid manure, or crop residue. Results and discussion Measured SOC levels declined over the study period in the unamended soil, remained constant in the soil amended with crop residues, and tended to increase in the soils amended with manure, especially with solid manure. Linear regression analysis of measured SOC contents and CQESTR predictions resulted in a correlation coefficient of 0.626 (P<0.001) and a slope and an intercept not significantly different from 1 and 0, respectively (95% confidence level). The mean squared deviation and root mean square error were relatively small. Simulated values fell within the 95% confidence interval of the measured SOC, and predicted errors were mainly associated with data scattering. Conclusions The CQESTR model was shown to predict, with a reasonable degree of accuracy, the organic C dynamics in the soils examined. The CQESTR performance, however, could be improved by adding an additional parameter to differentiate between pre-decomposed organic amendments with varying degrees of stability.

Plaza C., Gollany H.T., Baldoni G., Polo A., Ciavatta C. (2012). Predicting long-term organic carbon dynamics in organically-amended soils using the CQESTR model. JOURNAL OF SOILS AND SEDIMENTS, 12, 486-493 [10.1007/s11368-012-0477-1].

Predicting long-term organic carbon dynamics in organically-amended soils using the CQESTR model

BALDONI, GUIDO;CIAVATTA, CLAUDIO
2012

Abstract

Abstract Purpose The CQESTR model is a process-based C model recently developed to simulate soil organic matter (SOM) dynamics and uses readily available or easily measurable input parameters. The current version of CQESTR (v. 2.0) has been validated successfully with a number of datasets from agricultural sites in North America but still needs to be tested in other geographic areas and soil types under diverse organic management systems. Materials and methods We evaluated the predictive performance of CQESTR to simulate long-term (34 years) soil organic C (SOC) changes in a SOM-depleted European soil either unamended or amended with solid manure, liquid manure, or crop residue. Results and discussion Measured SOC levels declined over the study period in the unamended soil, remained constant in the soil amended with crop residues, and tended to increase in the soils amended with manure, especially with solid manure. Linear regression analysis of measured SOC contents and CQESTR predictions resulted in a correlation coefficient of 0.626 (P<0.001) and a slope and an intercept not significantly different from 1 and 0, respectively (95% confidence level). The mean squared deviation and root mean square error were relatively small. Simulated values fell within the 95% confidence interval of the measured SOC, and predicted errors were mainly associated with data scattering. Conclusions The CQESTR model was shown to predict, with a reasonable degree of accuracy, the organic C dynamics in the soils examined. The CQESTR performance, however, could be improved by adding an additional parameter to differentiate between pre-decomposed organic amendments with varying degrees of stability.
2012
Plaza C., Gollany H.T., Baldoni G., Polo A., Ciavatta C. (2012). Predicting long-term organic carbon dynamics in organically-amended soils using the CQESTR model. JOURNAL OF SOILS AND SEDIMENTS, 12, 486-493 [10.1007/s11368-012-0477-1].
Plaza C.; Gollany H.T.; Baldoni G.; Polo A.; Ciavatta C.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/110646
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