投稿中心

审稿中心

编辑中心

期刊出版

网站地图

友情链接

引用本文:曹子月,姚成,李致家,钟栗,顾玮琪.基于DEM的大别-皖南山区平均洪峰滞时定量分析.湖泊科学,2017,29(3):765-774. DOI:10.18307/2017.0326
CAO Ziyue,YAO Cheng,LI Zhijia,ZHONG Li,GU Weiqi.DEM-based quantitative analysis of average peak time lag of Dabie-South Auhui mountain area. J. Lake Sci.2017,29(3):765-774. DOI:10.18307/2017.0326
【打印本页】   【HTML】   【下载PDF全文】   查看/发表评论  【EndNote】   【RefMan】   【BibTex】
←前一篇|后一篇→ 过刊浏览    高级检索
本文已被:浏览 6909次   下载 3789 本文二维码信息
码上扫一扫!
分享到: 微信 更多
基于DEM的大别-皖南山区平均洪峰滞时定量分析
曹子月1, 姚成1, 李致家1,2, 钟栗1, 顾玮琪1
1.河海大学水文水资源学院 南京 210098;2.河海大学水安全与水科学协同创新中心 南京 210098
摘要:
以皖南山区及大别山区27个中小流域为研究对象,基于数字高程模型DEM提取流域地貌信息,并计算流域平均洪峰滞时.通过建立多元线性回归及通径分析数学模型,探讨地貌因子对流域洪水响应过程的影响.结果表明:在流域系统水平,形状系数、圆度比、流域相对高差、河道分支频率以及森林覆盖率是影响流域平均洪峰滞时的主要指标,其中流域相对高差是相关系数最高的解释变量;各地貌因子间相互作用复杂,其多元线性回归模型对平均洪峰滞时的方差解释量为73.4%,其通径分析模型分别从直接作用及间接作用角度进一步合理阐述各变量对流域平均洪峰滞时的影响.本文可为皖南山区无资料地区分析洪水响应过程提供重要参考,对防洪减灾有显著意义.
关键词:  数字高程模型  洪峰滞时  地貌因子  多元线性回归  通径分析
DOI:10.18307/2017.0326
分类号:
基金项目:国家自然科学基金项目(51679061,41130639);水利部公益项目(201501022);国家重点研发计划项目(2016YFC0402705)
DEM-based quantitative analysis of average peak time lag of Dabie-South Auhui mountain area
CAO Ziyue1, YAO Cheng1, LI Zhijia1,2, ZHONG Li1, GU Weiqi1
1.College of Hydrology and Water Resources, Hohai University, Nanjing 210098, P.R.China;2.National Cooperative Innovation Center for Water Safety & Hydro-Science of Hohai Universtiy, Nanjing 210098, P.R.China
Abstract:
Based on Digital Elevation Model(DEM) in 27 small watersheds of Dabie-South Auhui mountain area, the topographic information was extracted and the average peak time lag was calculated. By establishing the mathematical model of multiple linear regression and path analysis, the influence of the factors on the flood response of the river basin is discussed. The results show the following: At the level of the valley system, shape factor and roundness, valley relative elevation, channel branching frequency and the forest coverage rate affect the basin average peak time lag mainly. And basin relative elevation is the most fundamental explanatory variables; Different geomorphic factors interaction is complex. The multiple linear regression model of average peak time lag has 73.4% explanatory. Further more,the path analysis model respectively describes influence of each variable to the average peak time lag from direct effect and indirect effect. The results can provide important reference to analysis the flood response process of South Anhui mountain area. It is significant for flood control and disaster mitigation.
Key words:  Digital Elevation Model  peak time lag  geomorphology factor  multiple linear regression  path analysis
分享按钮