基于信息熵的河床演变分析  

Analysis of Fluvial Process Based on Information Entropy

作　　者：徐国宾[1] 赵丽娜[1] 

机构地区：[1]天津大学水利工程仿真与安全国家重点实验室,天津300072

出　　处：《天津大学学报》2013年第4期347-353,共7页Journal of Tianjin University(Science and Technology)

基　　金：国家自然科学基金创新研究群体科学基金资助项目(51021004);国家自然科学基金资助项目(50679053)

摘　　要：采用信息熵的理论与方法,引入河床演变的指标信息熵和年份信息熵概念,并给出计算公式定量地分析河床演变.选取黄河下游6个河段作为研究区域,利用每个河段1972—2000年影响因素的实测资料计算了各个影响因素对河床演变影响的客观权重和河段年份信息熵.通过对比研究结果可以看出:能够反映组成河岸与河床物质的相对可动性的宽深比对河床演变的权重最大,并且河床边界条件对河床演变的影响大于来水来沙条件;6个河段的年份信息熵的大小,依次是花—夹河段、夹—高河段、高—孙河段、孙—艾河段、艾—泺河段和泺—利河段,表明年份信息熵越大河型越不稳定,年份信息熵越小河型越稳定有序;同时验证了信息熵越大系统越混乱、信息熵越小系统越有序的结论.By adopting the theory and methods of information entropy, the factor information entropy concept and the year information entropy concept of the fluvial process were proposed, and the formula was provided to quantita- tively analyze the fluvial process. Taking six reaches in the lower Yellow River as study areas, the objective weights of various factors for the fluvial process and the year information entropy of each reach were determined with influ- encing factors of each reach within the year range from 1972 to 2000. The results show that the width to depth ratio which can reflect the relative mobility of the composition of riverbank and riverbed material is the maximum influenc- ing weight for the fluvial process; the influence of river boundary conditions on the fluvial process is greater than that of incoming flow and sediment conditions. The sequence of the year information entropy of the six reaches is Hua-- Jia reach, Jia--Gao reach, Gao--Sun reach, Sun--Ai reach, Ai--Luo reach and Luo--Li reach, which shows that the instability of the river increases with the increase in the value of the year information entropy of a river; it is verified that the chaos of the system increases with the increased value of information entropy of a system.

关 键 词：信息熵 河床演变 权重 黄河下游河段 

分 类 号：TV147[水利工程—水力学及河流动力学]