Spatial Extension Method for Computing Areal Precipitation
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Abstract:
Taking the monthly mean precipitation of Wenzhou (90 stations) from 1991 to 2001 as an example, with the aid of GIS, a comparison is conducted of three interpolation methods: the spline, Kriging, and inverse distance square methods. The different station densities are used to determine the minimum number of the stations that can make the results stable, and the effect of spatial resolution on interpolation results is considered. After a great deal of calculation and statistic analysis, the results are as following: (1) the inverse distance square and spline methods are better for calculating monthly mean precipitation; (2) compared the interpolation results for the two methods applied to different station density cases with different spatial resolutions, it is shown that when selecting 50 stations, the inverse distance square method is most stable with the minimum error, and the effect of spatial resolution is very little, can be neglected. The inverse distance square method and 50 stations are selected finally to calculate the precipitation of the 1km×1km area. This method offers a good areal precipitation estimating method for hydrology prediction service.
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Supported by:Beijing E-Tiller Technology Development Co., Ltd.
Supported by:Beijing E-Tiller Technology Development Co., Ltd.