中国农业科学 ›› 2005, Vol. 38 ›› Issue (05): 956-964 .

• 土壤肥料·节水灌溉 • 上一篇    下一篇

集约农作条件下土壤有机碳动态模拟及其在黄淮海平原区的应用

雷宏军,李保国,白由路,黄元仿,吕贻忠,李贵桐,李科江   

  1. 中国农业大学资源环境学院土壤与水农业部重点实验室,土壤植物相互作用教育部重点实验室
  • 收稿日期:2005-01-05 修回日期:1900-01-01 出版日期:2005-05-10 发布日期:2005-05-10
  • 通讯作者: 李保国

Modeling and Applications of Soil Organic Matter in Intensive Cropping in China's Huang-Huai-Hai Plain

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  1. 中国农业大学资源环境学院土壤与水农业部重点实验室,土壤植物相互作用教育部重点实验室
  • Received:2005-01-05 Revised:1900-01-01 Online:2005-05-10 Published:2005-05-10

摘要: 集约农田土壤有机碳动态对作物可持续生产有重要意义。本研究基于碳固持CQESTR模型,在国内短期、中长期物料填埋试验资料基础上进行修正,将CQESTR模型按照物料降解与累积积温关系划分4个阶段,确定了不同降解阶段的物料类型因子。通过对黄淮海平原集约化农区7个独立肥料长期定位点1 151组耕层土壤有机质观测值与模拟值进行验证,模型模拟95%置信区间为1.91 g·kg-1,r2=0.91。修正的CQESTR模型可以预测不同种植和管理措施下作物残体、外源有机物料及土壤有机质的矿化,从而对集约耕作条件下土壤有机碳矿化和固持进行评价。

关键词: 黄淮海平原, CQESTR模型, 有机碳, 模拟, 农田土壤, 集约化种植

Abstract: Organic carbon dynamics in intensive agricultural soils is significant for sustainable crop production. Based on the short-, mid-term buried organic material experiments in China's Huang-Huai-Hai Plain, the CQESTR model is modified with the division of 4 decomposition stages according to the relation between biomass decomposition and cumulative degree days and the biomass type factors in different stages are determined. Through the validation of soil organic matter (OM) by 7 independent long-term soil fertility and fertilizer efficiency experiments in China's Huang-Huai-Hai Plain, the modified CQESTR model can be used to predict the mineralization of residue, added organic amendment and native soil OM based on cropping and management practices, thus predicting the effect of tillage and crop rotation on organic carbon decomposition and storage in agricultural soils. The modified model provides estimates with a 95% confidence interval of 1.91 g·kg-1 OM and regression coefficient r2 of 0.91 on 1 151 pairs of fitted and observed soil OM from 7 independent fertility experiments in the plough layer. The modified model performs better than the original one.

Key words: Huang-Huai-Hai Plain, CQESTR model, Organic carbon, Modeling, Agricultural soil, Intensive cropping