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《Journal of Zhejiang University(Science Edition)》 2010-02
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Methods for calculating precipitation spatial distribution of Zhejiang Province based on GIS.

LI Bo1,2,HUANG Jing-feng3,4,JIN Zhi-feng5,LIU Zhan-yu(1.Institute of Public Administration,Zhejiang University,Hangzhou 310028,China;2.Key Laboratory of Agricultural Remote Sensing & Information System in Zhejiang Province,Hangzhou 310029,China;3.Institute of Agricultural Remote Sensing & Information Technology,College of Environmental and Resource Sciences,Zhejiang University,Hangzhou 310029,China;4.Key Laboratory of Environmental Remediation and Ecological Health of Ministry of Education in Zhejiang Province,Hangzhou 310029,China;5.Climate Center in Zhejiang Province,Hangzhou 310017,China)  
High precision spatial precipitation information is greatly significant in many fields such as regional water resource management,ecological environment protection and crop suitability assessment.In this paper mean yearly precipitation of 72 meteorological stations from 1971 to 2008 was adopted,with some topography and geographical factors such as slope,aspect,distance to the coastline,the average elevation around the 10km range,the highest altitude around the 10km range.A variety of interpolation methods were used to study mean yearly precipitation spatial distribution in study area based on geo-statistics technology and geography information system(GIS).Different interpolation methods such as the combination of stepwise regression and inverse distance weighing interpolation method,the combination of stepwise regression and kriging interpolation method,the combination of stepwise regression and spline interpolation method,the combination of stepwise regression and trend interpolation method were analyzed by the prediction accuracy verified by 10 validated stations,and maps of mean yearly precipitation spatial distribution were carried out a comparative analysis.The result demonstrated that the combination of stepwise regression and inverse distance weighting interpolation method had the highest prediction accuracy,and was better than others.
【Fund】: 科技部农业科技成果转化资金资助项目(2008GB24160442)
【CateGory Index】: P208;P426.613
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