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Spatial interpolation of precipitation considering geographic and topographic influences - A case study in the Poyang Lake Watershed, china | IEEE Conference Publication | IEEE Xplore

Spatial interpolation of precipitation considering geographic and topographic influences - A case study in the Poyang Lake Watershed, china


Abstract:

Precipitation is important in many fields. It is meaningful and valuable to estimate the spatial distribution of precipitation. However, existing methods introduced for p...Show More

Abstract:

Precipitation is important in many fields. It is meaningful and valuable to estimate the spatial distribution of precipitation. However, existing methods introduced for precipitation interpolation are not satisfactory. In this paper, geographic and topographic factors are taken into consideration and put into Cokriging method to interpolate the precipitation maps of annual precipitation in Poyang Lake Watershed of China. At the same time, IDW (Inverse distance weight) method, Ordinary Kriging method and Cokriging method considering elevation only has been used to interpolate the precipitation. Evaluating by MAE (mean absolute error), MRE (mean relative error), as well as RMSIE(Root mean squared interpolation error). The results indicate that Cokriging method considering geographic and topographic facotors is suoprior than IDW method and Cokriging method considering elevation only, and it has no obvious advantage compared with ordinary Kriging method.
Date of Conference: 25-30 July 2010
Date Added to IEEE Xplore: 03 December 2010
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ISSN Information:

Conference Location: Honolulu, HI, USA

1. INTRODUCTION

As an important part of water cycle, precipitation spatial information plays a crucial role in many fields, such as water resource management, drought and flood disaster predication, as well as regional sustainable development. With the development of earth sciences and cross-disciplinary, it is more and more meaningful and valuable to analyze and estimate precipitation spatial distribution. It is unrealistic to get the accurate predication of a specific region, because the formation and distribution of precipitation is a complex process. Therefore, only interpolate with precipitation data of the limited sites in the particular region, can the precipitation throughout the region be achieved. For the complex process, it is a big challenge to build a general precipitation interpolation model.

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References

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