Cluster analysis for factor classification and riverbank collapse along the desert wide valley reach of the upper Yellow River

被引：0

作者：

Shu, Anping ^{[1
]}

Gao, Jing ^{[1
]}

Duan, Guosheng ^{[1
]}

Zhang, Xin ^{[1
]}

机构：

[1] Key Laboratory for Water and Sediment Sciences of the Ministry of Education, School of Environment, Beijing Normal University, Beijing,100875, China

来源：

Qinghua Daxue Xuebao/Journal of Tsinghua University | 2014年 / 54卷 / 08期

关键词：

Amount of riverbank collapse - Clustering analysis - Factors affecting riverbank collapse - Field investigation - Hydrodynamic conditions - Meteorological data - Reliable evaluation method - Upper yellow rivers;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

An index system was developed using both natural factors and human factors to study riverbank collapse along the desert wide valley reach (Ning-Meng Section) of the upper Yellow River. Remote sensing and field investigation data sets are combined with hydrological, topographic and meteorological data from 2006 to 2010 to identify the factors that influence river bank collapse along the channel with a regression analysis to identify the key factors. The bank collapses along the monitored reaches are classified using a clustering analysis module. The results indicate that the hydrodynamic conditions and slope of river bank are the key factors affecting bank collapse. The clustering results for bank collapse are consistent with the results of the field investigation, so they provide a reliable evaluation method for predicting riverbank collapse along the Ning-Meng Section of the Yellow River. ©, 2014, Press of Tsinghua University. All right reserved.

引用

页码：1044 / 1048