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黄土高原降水量的空间插值方法研究 被引量:46

Research on spatial interpolation methods of pricipitation on loess plateau
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摘要 在地统计学和地理信息系统支持下,采用多种插值方法对黄土高原降水量进行了空间插值研究, 并探讨了气象站点密度与布局对插值结果的影响。结果表明,地统计学方法优于传统的反距离加权插值、多项式插值和径向基函数插值方法;考虑高程影响的普通协克里金方法优于一般的克里金方法和简单协克里金方法。通过空间插值得到了黄土高原降水量分布图,由该降水量分布图可知,黄土高原降水量总体呈现西北低、东南高的态势,界限很明显;年均降水量在100-800 mm,主要集中在200-600 mm内,以半湿润-半干旱气候为主。 Based on geostatistical method and GIS,the paper use several interpolation methods to estimate the pricipitation on loess plateau. Of several interpolation methods ,the Kriging method is better than the reverse distance weighting method,polynomial interpolation method and radial basis funcions method, Ordinary CoKriging ,in consideration of great influences of the elevation information,is better than CoKriging method and Kriging is best. At the same time,the paper also analysed the interpolation inferance of the distribution of stations. The trend of pricipitation on loess plateau shows a clear ambit with more pricipitation in sontheast,and southeast the annual pricipitation is 100--800 mm ,centeralized at 200--600 mm.
出处 《西北农林科技大学学报(自然科学版)》 CSCD 北大核心 2006年第3期83-88,共6页 Journal of Northwest A&F University(Natural Science Edition)
基金 国家科技部重点科技项目(20002BA901A43) 国家重点基础研究发展规划项目(G2000018606) 国家"十五"科技攻关项目(2004BA508B14)
关键词 黄土高原 降水量 插值 克里金方法 协克里金方法 Loess Plateau precipitation spatial interpolation Kriging Co-Kriging
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参考文献13

  • 1Mohamed A S.Reliabilty estimation of rainfall-runoff models[D].New York:State University of New York,1999.
  • 2Lamn.Spatial interpolation methods:a review[J].The Amercian Cartographer,1983,10(2):129-149.
  • 3Dirks K N,Hayl E,Stow C D,et al.High-resolution studies of rainfall on Norfolk Island.PartⅡ:interpolation of rainfall data[J].J Hydrol,1998,208(3/4):187-193.
  • 4Borga M,Vizzaccaro A.On the interpolation of hydrologic variables:formal equivalence of multiquadratic surface fitting and Kriging[J].J Hydrol,1997,195(1-4):160-171.
  • 5中国科学院水利部水土保持研究所.黄土高原水土保持数据库[EB/OL].[2005-08-20].http://www.loess.csdb.cn
  • 6党安荣,贾海峰,易善桢,等.ArcGIS 8 Deskt op地理信息系统应用指南[M].北京:清华大学出版社,2005:1-9.
  • 7Hevesi J A,Flint A L,Isto J D.Precipitation estimation in mountainous terrain using multivariate geostatistics.part Ⅰ:structural analysis[J].J Appl Meteor,1992,31:661-676.
  • 8朱会义,贾绍凤.降雨信息空间插值的不确定性分析[J].地理科学进展,2004,23(2):34-42. 被引量:127
  • 9祝青林,张留柱,于贵瑞,戴东,蔡福,刘新安.近30年黄河流域降水量的时空演变特征[J].自然资源学报,2005,20(4):477-482. 被引量:73
  • 10石朋,芮孝芳.降雨空间插值方法的比较与改进[J].河海大学学报(自然科学版),2005,33(4):361-365. 被引量:102

二级参考文献77

  • 1于贵瑞,何洪林,刘新安,牛栋.中国陆地生态信息空间化技术研究(Ⅰ)——气象/气候信息的空间化技术途径[J].自然资源学报,2004,19(4):537-544. 被引量:69
  • 2李恩羊,袁新.作物需水量的最优估计[J].水利学报,1989,21(10):45-49. 被引量:19
  • 3Running S.W.,R.R.Nemaini,R.D.Hungerford, Extrapolation of synoptic meteorological data in mountainous terrain and its use simulating forest evapotranspiration rate and photosynthese, Canadian Journal of Forest Research, 1987, 17,472~483.
  • 4Band et. al., Forest ecosystem processes at the watershed scale: basis for distributed simulation, Ecological Modelling,1991, 56, 171-196.
  • 5Lam,N, Spatial Interpolation Methods: A Review, The American Cartographer 1983,10(2):129-149.
  • 6Price D.T.,et.al., A comparison of two statistical methods for spatial interpolation of Canadian monthly mean climate data,Agricultural and Forest meteorology, 2000, 10(1):81-94.
  • 7Collins F.C. A comparison of spatial interpolation techniques in temperature estimation, http://www.ncgia.ucsb.edu/conf/santa fe cd-rom/sf papers/collins fred/collins.html,1999.
  • 8Husar R.B., Falke S.R., Uncertainty in the spatial interpolation of PM10 monitoring data in Southern California, http://capita.wustl.edu/capit a/capitareports/cainterp/caint erp.html.
  • 9Waters N.M. Unit40-spatial interpolation1,http://www.gisca. adelaide.edu.au/kea/gisrs/ncgia/u40.html, 1999.
  • 10Waters N.M. Unit41-spatial interpolation2, http://www.gisca.adelaide.edu.au/kea/gisrs/ncgia/u41.html, 1999.

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