Scholarlink

<p>Hydrological processes, as part of a natural system, are highly complex and chaotic. By analyzing long time series of streamflow data from ~ 4800 hydrologic stations, it is interesting to find out that probability density functions in second order difference (SOD) of the streamflow data are fat-tailed and bell-shaped curves, and their cumulative distribution functions (CDFs) follow an S-shaped curve&#xa0;(S-curve). We found that t-distribution is a good approximation for S-curve, which uses the degree of freedom (DF) to control the tail thickness. We also found that DF of more than 80% of stations are gathered in the range between 5 and 8. Analysis of the S-curves in seven large river basins indicated that the S-curves can vary with time and space, which is regarded as a good indicator for identifying natural and anthropogenic changes. This study provides a symmetrical, identical and concise probability distribution to describe global streamflow under changing environment.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A unified probability distribution of second order difference of global streamflow

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月24日

查看全文
  • Haiting Gu,
  • Weiping Cheng,
  • Hao Chen,
  • Li Liu,
  • Jingkai Xie,
  • Yue-Ping Xu

摘要

Hydrological processes, as part of a natural system, are highly complex and chaotic. By analyzing long time series of streamflow data from ~ 4800 hydrologic stations, it is interesting to find out that probability density functions in second order difference (SOD) of the streamflow data are fat-tailed and bell-shaped curves, and their cumulative distribution functions (CDFs) follow an S-shaped curve (S-curve). We found that t-distribution is a good approximation for S-curve, which uses the degree of freedom (DF) to control the tail thickness. We also found that DF of more than 80% of stations are gathered in the range between 5 and 8. Analysis of the S-curves in seven large river basins indicated that the S-curves can vary with time and space, which is regarded as a good indicator for identifying natural and anthropogenic changes. This study provides a symmetrical, identical and concise probability distribution to describe global streamflow under changing environment.