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The objective of this article was to study the spatial distribution patte of rainfall erosivity.The precipitation data at each climatological station in Hebei Province,China were collected and analyzed and modeled with SPSS and ArcGIS.A simple model of estimating rainfall erosivity was developed based on the weather station data.Also,the annual average rainfall erosivity was calculated with this model.The predicted errors,statistical feature values and prediction maps obtained by using different interpolation methods were compared.The result indicated that second-order ordinary Kriging method performed better than both zero and first-order ordinary Kriging methods.Within the method of second-order trend,Gaussian semi-variogram model performed better than other interpolation methods with the spherical or exponential models.Applying geostatistics to study rainfall erosivity spatial patte will help to accurately and quantitatively evaluate soil erosion risk.Our research also provides digital maps that can assist in policy making in the regional soil and water conservation planning and management strategies.