自然资源学报 ›› 2013, Vol. 28 ›› Issue (2): 321-327.doi: 10.11849/zrzyxb.2013.02.013

• 资源研究方法 • 上一篇    下一篇

降雨资料时间序列长度对降雨侵蚀力平均值置信度的影响

闫业超1, 岳书平1, 张树文2   

  1. 1. 南京信息工程大学 遥感学院, 南京 210044;
    2. 中国科学院 东北地理与农业生态研究所, 长春 130102
  • 收稿日期:2011-06-16 修回日期:2012-06-24 出版日期:2013-02-20 发布日期:2013-01-30
  • 作者简介:闫业超(1979- ),男,山东枣庄人,副教授,博士,主要从事GIS分析与应用研究.E-mail:yechaosd@yahoo.com.cn
  • 基金资助:

    国家自然科学基金青年基金项目(40901062).

The Confidence Coefficient of Mean Annual Rainfall Erosivity Influenced by Record Length of Rainfall Datasets

YAN Ye-chao1, YUE Shu-ping1, ZHANG Shu-wen2   

  1. 1. College of Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China;
    2. Northeast Institute of Geography and Agroecology, CAS, Changchun 130102, China
  • Received:2011-06-16 Revised:2012-06-24 Online:2013-02-20 Published:2013-01-30

摘要:

降雨资料时间序列长度是计算多年平均降雨侵蚀力过程中的重要不确定性因素.论文以中国601个气象站1980—2009年逐月降雨资料为数据源,利用Wischmeier经验公式计算了各气象站逐年降雨侵蚀力(R因子),用简单随机抽样方法抽取样本容量分别为30 a、 20 a、 10 a和5 a 四种不同的R值样本,计算了R平均值相对允许误差10%和25%条件下抽样估计的置信度.结果表明:降雨资料的时间序列长度对R平均值的估计置信度有显著影响;R平均值置信度存在明显的地域差异,长江以南、 青藏高原东部以及河西走廊南部的祁连山地区置信度较高;在降雨资料有限的情况下,必须根据土壤侵蚀研究的精度要求分析R平均值的抽样误差及其置信度,以保证土壤侵蚀定量预报的客观性与准确性.

关键词: 地理信息系统, 降雨侵蚀力, 概率统计, 时间序列长度, 不确定性

Abstract:

Record length of rainfall datasets is an important element which should be taken into account in the process of computing the mean annual rainfall erosivity. Based on the monthly rainfall datasets for the period 1980-2009, the annual rainfall erosivity for 601 weather stations of China was calculated using a simplified method originally proposed by Wischmeier and Smith. According to the theory of statistics, by drawing simple random samples of 30 years, 20 years, 10 years and 5 years of the datasets, the confidence coefficients of the mean annual rainfall erosivity were calculated based on the percent sampling errors of 10% and 25%. The results suggest that: 1) record length of datasets does have an effect on the confidence level for the mean annual rainfall erosivity; 2) the confidence coefficients for the mean annual rainfall erosivity vary greatly across China, and higher confidence level lies in south of the Yangtze River, eastern Tibetan Plateau and the mountainous area in southern part of Hexi Corridor; 3) when modeling soil erosion with limited rainfall data, it’s necessary to analyze the confidence level of sampling error by setting the allowable errors of the mean annual rainfall erosivity according to the research goal and predefined accuracy.

Key words: GIS, rainfall erosivity, probability and mathematical statistics, record length of rainfall data sets, uncertainty

中图分类号: 

  • S157.1