期刊文献+

日降水量的空间插值方法与应用对比分析--以深圳市为例 被引量:43

On Comparison of Spatial Interpolation Methods of Daily Rainfall Data:A Case Study of Shenzhen
下载PDF
导出
摘要 综合分析了四种空间插值方法,即距离权重倒数法、局部多项式法、普通克里金法和考虑海拔的协克里金法的特点,并以深圳市36个雨量站2006年雨季27天的日累计降水量数据为实例进行了研究和验证,采用交叉检验的方法对插值结果进行比较。研究表明,四种方法均能反映降水总体情况,但插值曲面相对真实曲面较平滑,距离权重倒数法的插值曲面最为平滑;多项指标比较显示,克里金法优于距离权重倒数法和局部多项式法。与普通克里金法相比,考虑海拔的协克里金法对插值精度没有明显提高。依照雨量站海拔、日均降水量分别对插值结果数据分组统计比较表明,海拔高的雨量站插值结果普遍大于实测结果,海拔低的雨量站则相反;日均降水量较大时(>50mm),插值误差明显增大。 Discrete or continuous rainfall data are required to run many GIS models for environment and planning. The paper attempts to make a general comparison on different spatial interpolation methods. It carried out a study on four spatial interpolation methods: Inverse Distance Weighing (IDW), Local Polynomial, Ordinary Kriging and co-Kriging with respect to elevation. Daily rainfall data,obtained from 36 rainfall stations during 27 inconsecutive days in the rainy season of 2006 in Shenzhen was employed in this study. Cross validation of the results shows that the four methods could to some extent reflect the rainfall situation of the region, yet the four interpolated surfaces are more smoothing than the practical circumstance. Particularly, IDW is the most smoothing one of the four. Besides, all the criteria (Mean Error, Mean Absolute Error, Root Mean Square Error and Percentage Error) that brought up in our study to measure accuracy of the four methods demonstrated that Ordinary Kriging and co-Kriging methods are superior to Local Polynomial and IDW. Inclusion of elevation in the co-Kriging method does not lead to improvement of result compared with Ordinary Kriging method. Furthermore, the interpolation data was grouped according to elevation and average daily rainfall and the same criteria above was bought to the statistics of those groups. Comparison on the criteria reveals that, the interpolated result on rain gauge stations with high elevation tend to larger than the observed data, and those rain gauge stations with low elevation are on the contrary. The interpolation error increases sharply while the average daily rainfall is bigger than 50mm.
出处 《地球信息科学》 CSCD 2008年第5期566-572,共7页 Geo-information Science
基金 国家自然科学基金项目(40701134) 国家863计划项目(2007AA12Z216)
关键词 日降水量 空间插值 距离权重倒数法 局部多项式法 普通克里金法 协克里金法 daily rainfall spatial interpolation inverse distance weighing local polynomial ordinary kriging co-kriging
  • 相关文献

参考文献26

  • 1Burrough P, McDonnell R. Principles of Geographical Information Systems. Oxford University Press, 1998, New York.
  • 2Dirks KN, Hay JE, Stow CD, et al. High-resolution studies of rainfall on Norfolk Island, Part Ⅱ : Interpolation of rainfall data. Journal of Hydrology, 1998, 208 ( 3 - 4) : 187 - 193.
  • 3Tomczak M. Spatial interpolation and its uncertainty using automated anisotropic Inverse Distance Weighting (IDW) -Cross-Validation/Jack knife Approach. Journal of Geographic Information and Decision Analysis, 1998, 2(2): 18 -30.
  • 4Cheng S J, Hsieh HH, Wang YM. Geostatistical interpolation of space-time rainfall on Tamshui River basin. Taiwan: Hydrology Process, 2007, 3136 - 3145.
  • 5高歌,龚乐冰,赵珊珊,张强.日降水量空间插值方法研究[J].应用气象学报,2007,18(5):732-736. 被引量:57
  • 6Goovaerts P, Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology, 2000, 228:113 -129.
  • 7刘胤雯,赖格英,陈元增,黄丽.梅江河流域年均降雨量空间插值方法研究[J].亚热带资源与环境学报,2007,2(3):29-34. 被引量:24
  • 8Hutchinson MF. Interpolation of rainfall data with thin plate smoothing splines - Part I: Two dimensional smoothing of data with short range correlation. Journal of Geographic Information and Decision Analysis, 1998, 2(2) : 139 - 151.
  • 9Grimes D I F, Pardo-Iguzquiza E, Bonifacio R. Optimal areal rainfall estimation using rain gauges and satellite data. Journal of Hydrology, 1999, 222, 93 -108.
  • 10Thomas A, Herzfeld UC. REGEOTOP: New climatic data fields for East Asia based on localized relief information and geostatistical methods. International Journal of Climatology, 2004, 24:1283 - 1306.

二级参考文献23

  • 1魏凤英,曹鸿兴.我国月降水和气温网格点资料的处理和分析[J].气象,1994,20(10):26-30. 被引量:25
  • 2周允华 中国科学院北京农业生态系统试验站.中国地区光合有效辐射能量和光量子通量的时空分布.农田作物环境实验研究[M].北京:气象出版社,1990.15-39.
  • 3[8]Hevesi 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.
  • 4[9]Pebesma E J,Wesseling C G.GSTAT:A program for geostatistical modeling,prediction and simulation[J].Computers & Geosciences,1998,24(1):17-31.
  • 5MOHAMED A S. Reliabilty estimation of rainfall-runoff models[ D]. New York: State University of New York, 1999.
  • 6LAM N. Spatial interpolation methods: a review[J] .The Amercian Cartographer, 1983,10(2): 129-149.
  • 7DIRKS K N,HAY J E,STOW C D,et al. High-resolution studies of rainfall on Norfolk Island. Part Ⅱ: interpolation of rainfall data[J].J Hydrol, 1998,208(3,4): 187-193.
  • 8BORGA 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.
  • 9HEVESI 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.
  • 10David T Price, McKenney Daniel W, Nalder Ian A, et al. A comparison of two statistical methods for spatial interpolation of Canadian monthly mean climate data. Agricultural and Forest Meteorology .2000,101 : 81-94.

共引文献510

同被引文献490

引证文献43

二级引证文献306

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部