In order to obtain the optimal interpolation methods and simulate the spatial distribution of annual average precipitation in Hunan Province, this paper selects ordinary Kriging (OK), inverse distance weighting (IDW), Trend surface analysis (Trend), Spline function method (Spline) to interpolate based on data from 87 meteorological stations in Hunan Province from 1960 to 2015 under the support of ArcGIS 10.2 platform, and compares the interpolation precision of each interpolation method using cross validation method. Results indicate that: ① the spatial interpolation of precipitation in Hunan Province has uncertainties affected by many factors. ② IDW4 has the lowest interpolation error and higher accuracy, followed by Spline based on TENSION model, OK based on the trigonometric function model has slightly lower accuracy, and Trend of Order 2 has the worst interpolation accuracy. Those four methods can reflect the characteristics of the spatial distribution of annual average rainfall in Hunan Province to some extent. ③ There are certain differences in local areas among different methods, for example, OK's interpolation surface is rough, IDW and Spline have relatively smooth surfaces, and Trend's interpolation results are monotonous.
Key words
annual average precipitation /
interpolation /
cross-validation /
ArcGIS /
Hunan Province
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