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出 处:《水文地质工程地质》2007年第5期67-72,共6页Hydrogeology & Engineering Geology
基 金:中国科学院知识创新工程重要方向资助项目(KZCX2-YW-406-3);国家重点基础研究发展规划项目(2005CB121108)
摘 要:针对目前黄河三角洲地区存在的土壤盐渍化问题,以该地区分布最广泛的表聚型盐分剖面类型为研究对象,运用磁感大地电导率仪EM38,建立了磁感式表观电导率和土壤盐分之间的(多元)回归模型,在分析土壤盐分剖面分布特征的基础上提出了指数衰减模型,并运用该模型对盐分剖面进行了参数拟合和验证。结果表明:磁感式表观电导率EMh和EMv呈极显著的线性相关,土壤盐分在垂直方向上的变异主要表现在表层0~25cm的深度范围内。统计分析和Friedman检验结果表明,回归模型和指数衰减模型均具有较好的拟合结果和预测效果,二者的预测精度差异也不显著,表明本文提出的指数衰减模型不仅能降低待估参数的数量、提高土壤盐分剖面磁感式解译的实用性,同时还具有较高的预测精度。该研究结果为利用电磁感应仪快速、精确地进行土壤盐分预测以及盐分剖面解译提供了一定的理论参考和实践依据。Taking into account the problem of soil salinization existing in the Yellow River Delta at present, (multiple) linear regression models between apparent electrical conductivity and soil salinity were established with the application of electromagnetic induction EM38 on the inverted salinity profiles extensively distributed in the study area. Based on the analyses of soil salinity profile characteristics, exponential decay models were propounded and fitted for all calibration salinity profiles, and the obtained exponential decay models were then used to test the validation salinity profiles. Results show that apparent electrical conductivity EMh is linearly correlated with EMv significantly, and the variation in soil salinity in the vertical direction mainly exhibits at soil surface layer of less than 25 cm in depth. Statistical analysis and Friedman test results indicate that linear regression models and exponential decay models all exhibit high precision in simulation and prediction, and the difference of prediction accuracy between them is statistically insignificant, suggesting that the exponential decay models proposed in this paper can not only reduce the amount of parameters and improve the practicability, but also exhibit high prediction accuracy. The research results can serve as a theoretical and practical reference to the rapid determination of soil salinity and the accurate interpretation of salinity distribution profiles by using electromagnetic induction.
关 键 词:电磁感应仪 表聚型盐分剖面 表观电导率 回归模型 指数衰减模型
分 类 号:S151.9[农业科学—土壤学] S159.3[农业科学—农业基础科学]
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