[1]XIE Hengyan,ZHANG Shenyuan,HOU Shance,et al.Comparison Research on Rainfall Interpolation Methods for Small Sample Areas[J].Research of Soil and Water Conservation,2018,25(03):117-121.
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Comparison Research on Rainfall Interpolation Methods for Small Sample Areas
Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
25
Number of periods:
2018 03
Page number:
117-121
Column:
Public date:
2018-04-10
- Title:
- Comparison Research on Rainfall Interpolation Methods for Small Sample Areas
- Keywords:
- precipitation; spatial interpolation method; small sample area; precision of interpolation
- CLC:
- P426.6
- DOI:
- -
- Abstract:
- For small sample areas with few precipitation observation stations, it is necessary to seek spatial interpolation method to forecast the precipitation of certain point by using the existing precipitation from the observation stations. The reliable precipitation forecast data are significant for the local production and life. Based on analyzing the average precipitation data of nine stations in seventy-two months in Upper Sangamon watershed in Illinois, USA, the interpolation results of precipitation and the observed data were compared on the basis of ArcGIS, where four methods were used, Ordinary Kriging method (Kriging), Inverse Distance Weighting method (IDW), Spline function method (Spline) and Trend surface method (Trend). The precision of the four methods was analyzed on inner insert and the outer insert, and the influence of the number of the observation station on the precision of interpolation method was analyzed. The results show that IDW is better than the other three spatial interpolation methods. The precision of spatial interpolation methods varies with different numbers of observation station. The precision of IDW interpolation is higher when the number of the observation station decreases according to the distance from the observation to the certain point. And IDW is little affected by the number of observation station. Spline and Trend are greatly affected by the number of observation station, and performance of Kriging is between Spline and Trend.
- References:
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1900-01-01