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中国农学通报 ›› 2013, Vol. 29 ›› Issue (11): 139-144.doi: 10.11924/j.issn.1000-6850.2012-2458

• 资源 环境 生态 土壤 气象 • 上一篇    下一篇

土壤类型信息在土壤有机碳空间预测中的应用研究

张忠启 于法展   

  • 收稿日期:2012-07-11 修回日期:2012-07-26 出版日期:2013-04-15 发布日期:2013-04-15
  • 基金资助:
    江苏师范大学自然科学研究基金项目

Study on the Application of Soil Type Information in Spatial Prediction of Soil Organic Carbon

  • Received:2012-07-11 Revised:2012-07-26 Online:2013-04-15 Published:2013-04-15

摘要: 为了探讨土壤类型作为辅助信息提高潮土区土壤有机碳(SOC)空间预测精度的可行性,基于江苏省沛县212个土壤预测样点和80个验证点,比较分析了普通克里格(OK)和结合土壤类型信息的克里格(STK)2种方法对土壤有机碳的空间预测精度。结果表明,各土壤类型间的SOC含量存在较大差异,其中淤土的含量最高(16.35 g/kg),而沙土含量最低(8.58 g/kg),两合土和轻盐碱土介于两者之间;直接利用OK方法对区域SOC预测时的平滑效应较强,导致误差较大,其80个验证点的真实与预测值的散点图相关系数r为0.45,均方根误差(RMSE)为7.36 g/kg;而STK相应的相关系数r为0.75,RMSE为4.90 g/kg,较前者降低了33.5%;同时,STK预测图斑能较OK更好地反映SOC在各土壤类型间的变异特征。说明STK方法消除了土壤类型间SOC含量差异较大的影响,降低了克里格平滑效应,从而较大幅度地提高了预测精度。表明与SOC关系密切的土壤类型信息,可在潮土区作为辅助信息以提高区域SOC的空间预测精度。

关键词: 生长习性, 生长习性

Abstract: In order to evaluate the feasibility of soil types being used as auxiliary information to improve the spatial prediction accuracy of soil organic carbon in fluvo-aquic soil area, 212 prediction samples and 80 validation samples were collected throughout the Pei County, and the spatial prediction accuracy of the two methods of ordinary kriging (OK) and the kriging combined with soil types information (STK) were compared for soil organic carbon (SOC) content. The results showed that there were great differences for SOC content among the main soil types. The content was highest in silted soil (16.35 g/kg), while the one was lowest in sandy soil (8.58 g/kg). The ones of mixed soil and light saline-alkali soil were between them. The prediction accuracy using OK directly was low due to the great smoothing effect, and the corresponding correlation coefficient and the RMSE were 0.45-8.31 g/kg, while the ones of STK was 0.75-6.02 g/kg, and the RMSE was 20% lower than the former. Furthermore, the SOC spatial distribution from STK reflected the difference of SOC content among soil types better and was closer to the regional reality than the one from OK. It was indicated that STK could reduce the smoothing effect and improve the prediction accuracy by eliminating the difference of SOC contents among soil types. The information of soil type, which was closely related to SOC content, could be used as auxiliary information to improve prediction accuracy of SOC in the alluvial soil areas of North Jiangsu.

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