期刊文献+

河川径流混沌特征分析 被引量:5

Analysis on chaotic characters of river runoff
原文传递
导出
摘要 在对混沌理论及其在径流系统应用的适应性分析的基础上,提出河川径流混沌分析方法;以黄河为研究对象对月径流序列进行相空间重构,并进行混沌特征识别和分析,得到如下结论:天然月径流比实测月径流的饱和关联维数要大,要恰当描述实测月径流序列的变化特征,进行动力系统建模,最少需要4个独立变量,最多需要8个独立变量,要描述天然径流序列则最少需要5~6个,最多需要12个独立变量;同一水文站、同一时期的实测径流序列和天然序列的混沌特征不同;下游的混沌特征要强于上游;从上世纪五十年代到本世纪初黄河干流月径流的混沌特性比上世纪二十年代到上世纪七十年代月径流的混沌特性要稍强;所采用径流时间序列的长、短对混沌特征的识别有影响,序列越长,所表现的混沌特征就越强。黄河径流具有混沌特征,为径流系统的建模和混沌预测提供了依据。 This paper proposes an analysis method of river runoff chaotic character with a discussion on chaos theory and applicability of this method to river runoff system,applies the method to the Yellow River and reconstructs a phase space of its monthly runoff.The conclusions are as follow.Satiable correlation dimension of natural runoff is greater than the measured runoff.For a dynamical model,at least 4 variables and at most 8 variables are needed to depict the variation character of measured runoff,while at least 5-6 and at most 12 for natural runoff.Measured runoff has different chaotic character from that of natural runoff at the same hydrological station in the same time period,and the downstream reach has stronger chaotic character than the upstream.The chaotic character in the period from 1950s to the beginning of this century is somewhat stronger than that of 1920s to 1970s.The chaotic character depends on the length of runoff time series,and longer series has a stronger character.The chaotic character revealed in the present study would be a basis for development of dynamical models and runoff forecast for the Yellow River.
出处 《水力发电学报》 EI CSCD 北大核心 2012年第3期11-17,30,共8页 Journal of Hydroelectric Engineering
基金 国家自然基金重大项目(51190093/E0901) 华北水利水电学院高层次人才科研启动项目(003022) 中国水利水电科学研究院流域水循环模拟与调控国家重点实验室开放基金项目(IWHR-SKL-201113) 河南省高等学校青年骨干教师资助项目(2009GGJS-061) 河南省教育厅自然科学研究资助计划项目(2009A570002 2011A570012)
关键词 水文学及水资源 混沌特征 混沌理论 河川径流 相空间重构 黄河 hydrology and water resources chaotic character chaos theory river runoff phase space reconstruction the Yellow River
  • 相关文献

参考文献14

  • 1张济世;刘立昱;程中山.统计水文学[M]郑州:黄河水利出版社,2006.
  • 2E.N.洛仑兹;刘式达.混沌的本质[M]北京:气象出版社,1997.
  • 3丁晶.洪水混沌分析[J]水资源研究,1992(03):14-18.
  • 4杨思全,陈亚宁,王昂生.基于混沌理论的洪水灾害动力机制(英文)[J].中国科学院研究生院学报,2003,20(4):446-451. 被引量:7
  • 5权先璋,温权,张勇传.混沌预测技术在径流预报中的应用[J].华中理工大学学报,1999,27(12):41-43. 被引量:12
  • 6蒋传文,权先璋,陈实,张士军,张勇传.径流序列的混沌神经网络预测方法[J].水电能源科学,1999,17(2):39-41. 被引量:12
  • 7吕金虎;陆君安;陈士华.混沌时间序列分析及其应用[M]武汉:武汉大学出版社,2001.
  • 8Henon M. A two-dimensional mapping with a strange attractor[J].Communications in Mathematical Physics,1976.69-77.
  • 9Rossler OE. An equation for continuous Chaos[J].Physics Letters,1976,(57).
  • 10Takens F. Detecting strange attractors in turbulence[A].Beilin:Springer-Verlag,1981.366-381.

二级参考文献19

  • 1裴留庆.确定性混沌与信息科学[J].自然杂志,1992,15(9):669-673. 被引量:2
  • 2丁涛,周惠成,黄健辉.混沌水文时间序列区间预测研究[J].水利学报,2004,35(12):15-20. 被引量:31
  • 3王文均,叶敏,陈显维.长江径流时间序列混沌特性的定量分析[J].水科学进展,1994,5(2):87-94. 被引量:44
  • 4林淑真.日径流时间序列之混沌动力探求[J].台湾水利,1996,6.
  • 5林淑真,台湾水利,1996年,44卷,2期,13页
  • 6LORENZ E N.Deterministic Nonperiodic Flow[J].Atmospheric Sci,1963(20):29-34.
  • 7UPMANU L,TAIYE B.Nonlinear dynamics of the Great Salt Lake:nonparametric short-term forecasting[J].Water Resource Research,1996,32(4):975-985.
  • 8PACKARD N H,CRUTCHFIELD J P,FARMER J D,et al.Geometry from a time series[J].Phys Rev Lett,1980,45(9):712-716.
  • 9ROSSLER O E.An Equation for Continuous Chaos[J].Phys Lett,1976(57):13-15.
  • 10LAI Y C,LERNER D.Effective scaling regime for computing the correlating dimension for chaotic time series[J].Physica D,1998(11):10-18.

共引文献44

同被引文献74

引证文献5

二级引证文献67

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部