Abstract: Surface micro-topography is one of the most important factors affecting irrigation process and performances. In view of the interpolation problem of surface micro-topography in irrigation model, using observed data on surface relative elevation of 4 different size ridge field, this study firstly compared the interpolation accuracy and program running time of Kriging interpolation, cubic spline interpolation and inverse distance weighted interpolation (IDW), and then analyzed the trend of Kriging interpolation program running time with the change of interpolation grid numbers under different sizes of ridged field. Furthermore, the combination interpolation methods of Kriging interpolation and cubic spline interpolation, and Kriging interpolation and inverse distance weighted interpolation were proposed, and the surface flow advance processes simulated based on data on surface relative elevation interpolated by the combination method and kriging interpolation were compared with observed surface flow advance process. The results showed that compared to the cubic spline interpolation and IDW, the interpolation accuracy of Kriging interpolation was the highest and Kriging interpolation could truthfully reflect the spatial distribution of micro-topography but the program running time was the longest, which had a great impact on the computational efficiency of irrigation model, while the program running time of cubic spline interpolation and IDW was relatively short, but their accuracies were low, which affected greatly the simulation accuracy of irrigation model. The running time of Kriging interpolating program increased with the size of ridge field and the number of interpolation grid. The reason of that might be there was an increase trend of equations and equations number in Kriging interpolation with the increase of ridge field size and interpolation gird numbers. The program running time of the combination interpolation method of Kriging interpolation and cubic spline interpolation and that of combination interpolation method Kriging interpolation and inverse distance weighted interpolation was the same, but the interpolation accuracy of the former was higher. In order to both meet the requirements of interpolation accuracy and computational efficiency of irrigation model, it was feasible to use the combination method of Kriging interpolation and cubic spline interpolation for surface elevation interpolation in irrigation model. For those ridge fields with their area less than 2700 m2, the combination interpolation could satisfy the requirements of mean absolute error less than 0.5 mm and program running time less than 10 s. For those ridge fields with their area more than 2700 m2, the combination interpolation could satisfy the requirements of mean absolute error less than 0.5mm and program running time less than 20s when the intermediate interpolation grid number was 1/4 of irrigation model grid number and meet the requirements of mean absolute error less than 1 mm and program running time less than 10s when the intermediate interpolation grid number was 1/8 of irrigation model grid number. The surface flow advance processes simulated based on the surface elevation data interpolated by the combination method with the 1/4 and 1/8 irrigation model grid numbers and Kriging interpolation were similar with the observed data. Therefore, the intermediate interpolation grid number could be selected between 1/4 and 1/8 of irrigation model grid number depending on the requirements of interpolation accuracy and running time.