PROGRESS IN GEOGRAPHY ›› 2004, Vol. 23 ›› Issue (2): 34-42.doi: 10.11820/dlkxjz.2004.02.005

• Original Articles • Previous Articles     Next Articles

Uncertainty in the Spatial Interpolation of Rainfall Data

ZHU Huiyi, JIA Shaofeng   

  1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101,China
  • Received:2004-01-01 Revised:2004-02-01 Online:2004-03-25 Published:2004-03-25


Taking Chaobaihe Basin as a study area, and using the data from 58 stations in 1990, this paper analyzes the uncertainty in the spatial interpolation of rainfall data caused mainly by the number of stations, temporal scale, cell size of interpolation grid and different interpolation methods. IDW, Kriging, Spline and Trend methods are all adopted in the paper work. The results imply that:(1) the more the number of stations in the interpolation,the less the uncertainty reflected by MAE in rainfall data interpolation; but for certain point, adding some more stations will not absolutely increase its accuracy because of their spatial distribution;(2) the variations of cell size from 50m, 100m, 200m to 1000m does not affect the accuracy remarkably; (3) when temporal scale is shortened from year to month and day, the uncertainty of interpolation results based on the same number of stations increases greatly; (4) different interpolation methods bring different levels of uncertainty. According to the analysis above, the basic way to reduce the uncertainty in rainfall data interpolation is to introduce other relative variations with high sample density, and to integrate them in present interpolation methods. So the choice of those relative variations and their integration with interpolation methods should be the core of the future research in rainfall interpolation.

Key words: rainfall data, spatial interpolation, uncertainty