Abstract: Based on the daily data observed in 14 meteorology stations in the Yongding River Basin from 1957 to 2018, this paper analyzes the spatial-temporal characteristics of precipitation by using linear propensity estimation, anomalies analysis and wavelet analysis.The Rotated Empirical Orthogonal Function（REOF） method is used to divide characteristic zones and reveal the main correlative factors of precipitation in the basin through correlation analysis. Results show that under the background of global warming, the precipitation of the Yongding River Basin shows a decreasing trend with a rate of-2.88 mm/10 a with the average annual precipitation of 389.22 mm. From seasonal means, the precipitation in spring and autumn shows an increasing trend and the increase in precipitation is the most obvious in autumn with increasing rate of 3.75mm/10a.On the contrary, the precipitation in summer and winter shows a decreasing trend and the decrease in precipitation is the most obvious in summer with decreasing rate of-8.14 mm/10 a. Wavelet analysis shows that there are three cycles of 28, 15 and 4 a in the variation of precipitation, with 28 a as the main cycle. The main cycle time of precipitation in the Basin is 28 years. From spatial means, precipitation is significantly different, precipitation in the Basin decreases from the southeastern plain areas to the northwestern mountainous areas. The REOF analysis shows that first six modes can reflect the spatial distribution of precipitation in Yongding River Basin.According to the distribution of high load area in each mode,the Yongding River Basin can be divided into six zones: Zone Ⅰ is southwestern Datong Basin, Zone Ⅱ is northern Zhangjiakou, Zone Ⅲ is Yanhuai Basin, Zone Ⅳ is Beijing and northwestern Hebei Basin, Zone Ⅴis northwestern Inner Mongolia mountains and Zone Ⅵ is Coastal plains.Among these zones, Zone Ⅰ, Zone Ⅳ and Ⅵ are affected by continental climate and monsoon climate, respectively. Zone Ⅱ and Ⅲ are significantly affected by local topography. The correlation analysis results show that the Southern Indian Ocean Dipole（SIOD）, evaporation, maximum temperature, sunshine time and scattering are significantly correlated with precipitation.