摘要
这份报纸把小浪分析用于检验变化趋势,多时间规模变化,在上面的红河的 Panlong 盆的推迟的沉积流动(SSF ) 的周期、突然的变化特征,中国。结果显示 SSF 从 1951 ~ 1997 增加了,但是自从 1998,衰退了。SSF 的变化把多时间规模特征和变化在不同时间时期改变了。三周期的时间规模, 4, 7 和 22 年,被决定。22 年的周期的时间规模,是在三次规模之中的最明显的,通过整个研究时期延长了,而第 4-a 7 年的时间规模在某些时间时期仅仅是明显的。分别地有 27 次越过 4 年的时间规模,越过 7 年的时间规模的 16 次和越过 22 年的时间规模的 5 次的突然的变化。根据统计的聚会和气候数据分析,我们断定人的活动是导致了多时间规模的 SSF,而是特征的变化趋势的主要原因,周期、突然的变化被气候变化主要影响。
This paper applied wavelet analysis to examining change tendency, multi-time scale variations, periodic and abrupt change characteristics of suspended sediment flux (SSF) of the Panlong basin in the Upper Red River, China. The results indicated that the SSF had increased from 1951 to 1997, but declined since 1998. The variations of the SSF had multi-time scale characteristics and the fluctuations varied in different time periods. Three periodic time scales, 4, 7 and 22 years, were determined. The 22-year periodic time scale, which was the most obvious one among the three time scales, extended through the whole research period, whereas the 4- and 7-year time scales were obvious only in certain time periods. There were 27 times of abrupt changes across the 4-year time scale, 16 times across the 7-year time scale and 5 times across the 22-year time scale, respectively. On the basis of social statistical and climate data analysis, we concluded that the human activities were the main reason that led to the changing tendency of the SSF, but the characteristics of the multi-time scale, periodic and abrupt change were mainly influenced by climate variations.
作者
DING WenRong~(1,2+) ZHOU Yue~(1,3) L XiXi~4 1 The Faculty of Environment Science and Engineering,Kunming University of Science and Technology,Kunming 650093,China
2 College of Tourism and Geography Science,Yunnan Normal University,Kunming 650092,China
3 Yunnan University of Finance and Economics,Kunming 650221,China
4 Department of Geography,National University of Singapore 119260,Singapore
基金
Supported by the China 973 Program(Grant No.2003CB415105-6)
关键词
河流
中国
红河
微波分析
suspended sediment flux (SSF), sediment variations, wavelet analysis, Longitudinal Range-Gorge Region (LRGR), Red River (HongheRiver)