院报 ›› 2017, Vol. 34 ›› Issue (10): 11-16.DOI: 10.11988/ckyyb.20160553

• 水资源与环境 • 上一篇    下一篇

基于地理因子的福建省年降水空间估算模型研究

王亚琼a,卢毅敏b   

  1. 福州大学 a.福建省空间信息工程研究中心;b.空间数据挖掘与信息共享教育部重点实验室,福州 350002
  • 收稿日期:2016-06-01 修回日期:2016-07-11 出版日期:2017-10-01 发布日期:2017-10-25
  • 通讯作者: 卢毅敏(1973-),男,福建仙游人,副研究员,博士,主要从事资源环境模型与系统模拟研究工作,(电话)13850159899(电子信箱)luym@lreis.ac.cn。
  • 作者简介:王亚琼(1992-),女,河南周口人,硕士研究生,主要从事空间数据挖掘与地理知识工程的研究,(电话)18805909605(电子信箱)wyq920506@163.com。

Simulation of Annual Precipitation Based onGeographic Factors in Fujian Province

WANG Ya-qiong1, LU Yi-min2   

  1. 1.Spatial Information Research Center of Fujian Province, Fuzhou University, Fuzhou 350002, China;
    2.Key Laboratory of Data Mining & Information Sharing of Ministry of Education, Fuzhou University,Fuzhou 350002, China
  • Received:2016-06-01 Revised:2016-07-11 Online:2017-10-01 Published:2017-10-25

摘要: 为研究福建省多年平均降水量的空间分布格局,为工农业生产、自然灾害预测、生态环境建设提供科学依据,利用福建省及周边区域35个气象站点1951—2011年降水资料,分析年均降水量与海拔、纬度、距海岸距离、坡向的相关性;同时,结合多元回归方程和克里金插值构建降水空间估算模型,反映出年均降水量空间分布的总体趋势,突出局部地区降水的差异,估算福建省1951—2011年年均降水量空间分布。结果表明:已知气象站点年均降水量估算的平均相对误差为3.4%,绝对误差为56 mm,验证站点的平均相对误差为3.6%;福建省年均降水量从东南沿海向西北山区呈现波动式上升的特点。

关键词: 地理因子, 年降水量, 回归拟合, 克里金插值, 空间分布, 福建省

Abstract: The aim of this research is to estimate the spatial distribution of annual mean precipitation in Fujian Province, hence offering scientific basis for industrial and agricultural production, natural disaster forecasting, and eco-environmental construction. According to precipitation data at 35 meteorological stations in Fujian province and its surrounding areas, the correlation between annual precipitation and four geological factors respectively (elevation, latitude, distance to sea shore, and slope gradient) were analyzed. Furthermore, a model was established in association with the multiple regression equation and the Kriging interpolation to estimate the spatial distribution of annual mean precipitation in Fujian Province from 1951 to 2011. The model reflects the general trend of the spatial distribution of annual precipitation, and also highlights the difference of precipitation in local areas. Results revealed that the relative average error of the fitted stations is 3.4%, and the mean absolute error is 56 mm; while the mean absolute error of the precision verification result is 3.6%. The annual precipitation displayed a wave-like rising trend from the southeast coast to the northwest mountains.

Key words: geographical factors, annual precipitation, regression fitting, Kriging interpolation, spatial distribution, Fujian Province

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