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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
引用本文:闫业超,岳书平,张树文.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[J].自然资源学报,2013,28(2):321-327.
作者姓名:闫业超  岳书平  张树文
作者单位: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
基金项目:国家自然科学基金青年基金项目(40901062).
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  
收稿时间:2011-06-16
修稿时间:2012-06-24

The Confidence Coefficient of Mean Annual Rainfall Erosivity Influenced by Record Length of Rainfall Datasets
YAN Ye-chao,YUE Shu-ping,ZHANG Shu-wen.The Confidence Coefficient of Mean Annual Rainfall Erosivity Influenced by Record Length of Rainfall Datasets[J].Journal of Natural Resources,2013,28(2):321-327.
Authors:YAN Ye-chao  YUE Shu-ping  ZHANG Shu-wen
Institution: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
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.
Keywords:GIS  rainfall erosivity  probability and mathematical statistics  record length of rainfall data sets  uncertainty
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