基于复杂性理论的黄河河川径流序列诊断分析  

Diagnoses on the Yellow River runoff series based on complexity theory

作　　者：佟春生[1] 黄强[1] 刘俊萍[2] 刘涵[1] 席秋义[1] 

机构地区：[1]西安理工大学水利水电学院 [2]浙江工业大学建筑工程学院,浙江杭州310014

出　　处：《系统工程学报》2005年第6期559-563,共5页Journal of Systems Engineering

基　　金：国家自然科学基金资助项目(50079021);国家重点基础研究发展规划资助项目(G1999043608)

摘　　要：水文序列性质的诊断是水文预测的关键问题之一,至今没有得到有效解决.本文通过采用复杂性理论中的复杂性测度,对黄河干流不同水文站的河川径流序列进行诊断分析.结果表明:黄河干流径流序列以随机性为主,确定、随机和混沌成分共存;人类活动的影响总体使得径流变化的随机和混沌增大,且下游的随机成分大于上游,上游的混沌成分大于下游;同时表明复杂性测度具有较灵敏的识别能力,为识别河川径流序列的性质及人类活动的影响提供了一种新的方法.Hydrology series character diagnoses is one of the key problems of hydrology forecasting, which is not yet to be solved. Based on the complexity measure of complexity theory the river nmoff series of different hydrology stations in mainstream of the Yellow River is diagnoses. The results show that the Yellow River runoff series character is focused on is diagnosed randomicity, deterministic and chaos; the human activity effect increases the randomicity and chaos of nmoff variety; and the randomicity in downstream is higher than that in upstream, the chaos in upstream is higher than that in downstream. And it is show that the complexity measure has sensitive identification ability, which offeres a new method to identify river runoff series character and the human activity effects.

关 键 词：河川径流 诊断 随机性 复杂性测度 

分 类 号：P333[天文地球—水文科学]