中文摘要：

应用一种先进的双变量（土壤圆锥指数与水分）传感器复合测量系统，基于前人提出的土壤圆锥指数、水分与容重的4种半经验模型（Ayers，Upadhyaya，Busscher与Hernanz模型），以相关系数R^2与统计残差作为检验指标，根据各模型的结构特点，结合两种质地土壤（粘土与粉质壤土），针对容重预测精度与可应用性进行了深入试验研究．结果表明，Ayers和Upadhyaya模型虽然预测精度较高，但与土壤容重的解析关系为隐函数，在线辨识计算工作量只能取决迭代过程的收敛性，因而在实际应用上受到一定程度的限制．相比之下Busscher与Hernanz模型计算土壤容重方便快捷，但预测精度较低．

英文摘要：

Using an advanced dual-sensor technique for the simultaneous measurement of soil cone index and volumetric water content, four proposed semi-empirical models （Ayers-, Upadhyaya-, Busscher- and Hemanz-model ） have been validated with R2（ coefficient of determination） and RMSE （Root Means Square Error）. For this objective, two types of soil samples, clay and silt-loam, were used in the experiment. Moreover, soil bulk density acted as a predicted parameter for evaluating the performance of each model. The experimental and computational results demonstrate that both Ayers- and Upadhyaya-model can achieved better predication for the system identification but they are unable to be an explicit function among volumetric water content, cone index and bulk density. Therefore, the applicability of both models in the field depends on their convergence of the iterative process. Alternatively, Busscher- and Hernanz-model have no any restriction during on-line computation, although their predicting performance seems relatively poor.