Abstract: This study used GIS and geostatistics to analyze the spatial variability and content distribution of available N, P and K as part of a comprehensive management of soil nutrients in Gaoyang County of Hebei Province. Results showed that available N and P distribution was lognormal while that of available K was normal. The averages of soil available N, P and K were respectively 76.32 mg·kg^-1, 22.28 mg·kg^-1 and 128.34 mg·kg^-1. The coefficients of variation ranged from 36.11% to 79.71%, which suggested that the variations were at medium levels. The result showed that C0/(C+C0) of available N, P and K were respectively 38.79%, 74.27% and 32.33%, which suggested moderate spatial self-correlations. The spatial variability was caused by structural and random factors. Available K had the longest correlation range (51.94 km), available P the shortest (1.05 km) and that of available N was 43.96 km. Integrated comparisons in interpolation errors were conducted, and the best theoretical model of semivariogram of soil available N, P and K were established, which turned out to be spherical, exponential, spherical models, respectivley, with preferable 0-order trend effect. Spatial distribution maps of available N, P and K contents in cropland soils constructed by using universal Kriging interpolation objectively reflected nutrient abundance/deficiency in the study area. The maps suggested that the characteristics of the spatial distribution of available N was insignificant, available P was mainly with a banding distribution and available K was with both banding and island distribution. The content of available N was low, the area of land with 60~90 mg·kg^-1 available N accounted for 93.13% of the investigated region. This suggested that there was the need to increase soil nitrogen in the study area. The contents of available P and K were in the medium-to-high range in most of the study area. Also the spatial distribution of available P showed that areas of low, medium, high and very high grades were respectively 0.34%, 31.97%, 46.98% and 20.71% of the study area. Available K map showed that the areas of low, medium, high and very high grades were respectively 0.04%, 40.36%, 54.12% and 5.48% of the study area. The figures of the GIS-based nutrient variability reflected the spatial distribution of soil nutrients and provided the theoretical basis for decision-making and soil nutrient management in the study area.