CQESTR Simulated Changes in Soil Organic Carbon under Residue Management Practices in Continuous Corn Systems

被引:0
|
作者
Brian J. Wienhold
Marty R. Schmer
Virginia L. Jin
Gary E. Varvel
Hero Gollany
机构
[1] USDA-ARS,Agroecosystem Management Research Unit
[2] Retired USDA-ARS,Agroecosystem Management Research Unit
[3] USDA-ARS,Columbia Plateau Conservation Research Center
来源
BioEnergy Research | 2016年 / 9卷
关键词
Maize; Nebraska; Feedstock; Soil quality; Irrigation; Tillage; N fertilization;
D O I
暂无
中图分类号
学科分类号
摘要
Soil organic carbon (SOC) is an important soil property and is strongly influenced by management. Changes in SOC stocks are difficult to measure through direct sampling, requiring both long time periods and intensive sampling to detect small changes in the large, highly variable pool. Models have the potential to predict management-induced changes in SOC stocks, but require long-term data sets for validation. CQESTR is a processed-based C model that uses site weather, management, and crop data to estimate changes in SOC stocks. Crop residue removal for livestock feed or future biofuel feedstock use is a management practice that potentially affects SOC stocks. Simulated changes in SOC using CQESTR were compared to measured SOC changes over 10 years for two contrasting residue removal studies in eastern Nebraska. The rainfed study compared SOC changes in no-tillage continuous corn grown under two N fertilizer rates (120 or 180 kg N ha−1) and two residue removal rates (0 or 50 %). The irrigated study compared SOC changes in continuous corn grown under no-tillage or disk tillage and three residue removal rates (0, 35, or 70 %). After 10 years under these management scenarios, CQESTR-estimated SOC stocks agreed well with the measured SOC stocks at both sites (r2 = 0.93 at the rainfed site and r2 = 0.82 at the irrigated site). These results are consistent with other CQESTR validation studies and demonstrate that this process-based model can be a suitable tool for supporting current management and long-term planning decisions.
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页码:23 / 30
页数:7
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