| The rainstorm is one of important weathers in the eastern regions of Gansu. Firstly, it plays the roles of relieving the droughty situation and meeting the water need of people's life and the economic development as the basic water resource. Secondly, because it is arid and there are many mountains in the eastern regions of Gansu, the frequent occurrences of rainstorm often cause geological hazards, such as landslide, debris flow, flood and soil erosion which cause the severe loss to the people's life and property. This requests us to carry on the analysis of the rainstorm's spatial distribution pattern and the terrain influence. The analysis can provides the related department's monitor and the forecast with uses for reference, thus, people can carry on more effective controls on the related hazards.Based on the maximum rainstorm data for 5 time intervals known as 10 minutes, 60 minutes, 6hours, 24 hours and 3days of more than 200 stations located in the eastern regions of Gansu, the structure of spatial distribution has been analyzed. It is shown that the storm lasting longer its spatial distribution's zonal rule is stronger .The spatial distributions of the maximum rainstorm for 3days and 24hours present the descending horizontal zonal rule from the southeast to the northwest because of the influence of Monsoon. The terrain makes the maximum rainstorm for 10 minutes present the "u" configuration .Because of the influences of Southeast Monsoon and terrain, the spatial distributions of the maximum rainstorm for 6hours and 60minutes present the transitional trait.Taking Jinghe watershed and Taohe watershed as examples, based on the 90m, 180m, 250m, 500m, 1000m, 1500m, 2000m, 3000m and 5000m resolution of DEM, the correlation between the terrain influence factor and the extreme value of rainstorm for 5 time intervals has been analyzed. Firstly, it is shown that the correlation between the extreme value of rainstorm for long time intervals and PWEI is stronger. In a way, the correlation can explain that the spatial patterns of the extreme values for long time intervals are mainly influenced by Monsoon. Secondly, the terrain influence on rainstorm can be represented better by S-PWEI and H-S-PWEI than the single terrain factor. Thirdly, along with the intervals becoming shorter, the complexity of the terrain influence on rainstorm is more intensely, the influence of the terrain is stronger, but the influence of Monsoon is weaker. Last but not least, when the analysis of the terrain influence is carried on, the reasonable resolution of data should be used. Otherwise, if different resolution is used the mainly influence factor is different.
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