欢迎访问《应用生态学报》官方网站,今天是 分享到:

应用生态学报 ›› 2011, Vol. 22 ›› Issue (01): 159-164.

• 研究报告 • 上一篇    下一篇

不同尺度流域日径流分形特征

赵 辉1 郭索彦2 解明曙3 雷廷武1**   

  1. 1中国农业大学水利与土木工程学院, 北京 100083;2水利部水土保持监测中心, 北京 100053;3北京林业大学水土保持学院,北京 100083
  • 出版日期:2011-01-18 发布日期:2011-01-18

Fractal characteristics of daily discharge in different scales watersheds.

ZHAO Hui1, GUO Suo-yan2, XIE Ming-shu3, LEI Ting-wu1   

  1. 1College of Water Conservancy &Civil Engineering, China Agricultural University, Beijing 100083, China|2Soil and Water Conservation Monitoring Center of Ministry of Water Resources, Beijing 100053, China|3School of Water and Soil Conservation, Beijing Forestry University, Beijing 100083, China
  • Online:2011-01-18 Published:2011-01-18

摘要: 基于分形理论和实测流域日径流长序列资料,研究了中尺度流域(武水流域)和小尺度流域(贞福流域和双溪流域)日径流的分形特征.结果表明:相同时间尺度和不同日径流门限值条件下,相同空间尺度流域间和不同空间尺度流域间日径流均具有显著的分形特征,具有自相似性.随着门限值的增大,不同空间尺度流域间日径流的分形盒维数均逐步减小;当时间尺度在120~150 d时,不同空间尺度流域日径流的分形维数点集均逐渐趋向饱和,当时间尺度大于该值时,就有出现一定门限值径流的可能性.

关键词: 日径流, 空间尺度, 分形理论, 分形维数, 流域, 滨海盐土, 高光谱参数, 土壤水分, 高光谱遥感

Abstract: Based on the fractal theory and the long-term daily discharge records, this paper analyzed the fractal characteristics of daily discharge in mid-scale watershed (Wushui watershed) and small-scale watersheds (Zhenfu and Shuangxi watersheds). Under the same time scales and different threshold values of daily runoff, the fractal characteristics of daily discharge in the watersheds of different spatial scales and of same spatial scales were evident, and existed self-similarity. With the increase of the threshold values of daily runoff, the fractal dimensions of the daily discharge of different space-scale watersheds decreased gradually. The set of fractal dimensions of the daily discharge in different space-scale watersheds tended to be saturated when the time scale was 120-150 days, and the critical threshold values of daily runoff might appear when the time scale exceeded this number of days.  

Key words: daily discharge, spatial scale, fractal theory, fractal dimension, watershed, coastal saline soils, hyperspectral parameters, soil moisture content, hyperspectral remote sensing.