Abstract: Soil hydraulic property parameters are necessary for the solution of the basic soil hydraulic properties equation. Unsaturated soil hydraulic properties are important physical parameters for modeling soil water and salt movement，in which soil water diffusivity is one of the most important parameters. However，because these parameters have a strong spatial variability，making a direct determination of them in a larger region is often not feasible，and the determination of soil variability by the spatial structure often has a large number of errors. To overcome these shortcomings，soil structure and hydraulic parameters of the function must be established in order to find a determination of soil moisture characteristics of the more simple and effective method. In the paper，soil water diffusivity of typical clay loam in Yangling City，Shaanxi Province，China was measured with horizontal soil column method，then single and double logarithm models of soil water diffusivity were applied to fit above measured values，based on above fitted results，a single parameter model was established，and on this basis a BP artificial neural network of single parameter model was established based on the principal components analysis. The results showed that bulk density，organic matter content，clay content，silt content and sand content could be converted into three principal components；RMSE of parameter B which were fitted with established BP artificial neural network model was 0.308 2；Except large values of soil water diffusivity that its forecasted value was low，soil water diffusivity forecasted based on fitted parameter B was close to its measured value，and RMSE of forecasted soil water diffusivity was 0.257 8，which indicated that established BP artificial neural network model could be used to forecast parameter B in single parameter model.

Key words: moisture diffusion rate, single parameter model, principal components analysis, neural network model