Comparison of Spatial Interpolation Methods of Snow Depth in the West of China

The spatial interpolation methods of Inverse Distance Weighted(IDW),Spline and Kriging are utilized for comparison study on spatial interpolation of annual average snow depth from 113 observatories in the west of China(79.05°～103.57°E,27.17°～48.05°N).The principles of these three methods are different from each other.IDW determines cell values using a linear-weighted combination set of sample points.Spline estimates values using a mathematical function that minimizes overall surface curvature.And ordinary Kriging is a powerful statistical interpolation method which assumes that the distance or direction between sample points reflects a spatial correlation that can be used to explain variation in the surface.Compared with the unsatisfactory interpolation results of IDW and Spline,the result of ordinary Kriging is more close to the real snow depth distribution and can represents the spatial structure of snow depth distribution better.The main reasons which affect the precision are the small number of observatories and their asymmetric spatial distribution.However,the accuracy of spatial interpolation can be improved through reasonable design of sampling,combining deterministic and stochastic methods,and considering the influencing factors of snow distribution such as the terrain and climate.