日径流序列混沌识别中合理长度的确定
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摘要
混沌理论是进行水文时间序列分析的重要手段。为保证分析结果的可靠,主张充分利用现有资料,但目前缺乏时间序列长度对混沌特性识别影响的研究。以长江上游武隆站和北碚站日径流序列(1951年-2012年)为例,通过对二者进行混沌分析,研究了最大Lyapunov指数对序列长度的响应。结果表明,日径流时间序列长度过小时会影响混沌识别结果,使结果缺乏可靠性;并不是样本序列长度越长混沌识别结果越好;当序列长度达到3 000左右时,序列的混沌特性达到稳定,结果可靠并缩短了计算时间。
Chaotic theory is an important means of hydrology time series analysis.In order to get reliable analysis results,it is recommended to make a full use of time series.But the research about how the length of time series affects the identification of chaotic characteristics is rare.In this paper,we carried out a study about the responding effect of the maximum Lyapunov exponent to the length of time series with the use of daily runoff time series of gauged stations named Wulong and Beibei in Yangtze River.The result suggested that short daily runoff time series would affect the result of chaotic identification and make the result unreliable;besides,when the length of daily runoff time series reached 3 000,the chaotic characteristics became stable and reliable,and it saved a lot of computing time at the same time.
Chaotic theory is an important means of hydrology time series analysis.In order to get reliable analysis results,it is recommended to make a full use of time series.But the research about how the length of time series affects the identification of chaotic characteristics is rare.In this paper,we carried out a study about the responding effect of the maximum Lyapunov exponent to the length of time series with the use of daily runoff time series of gauged stations named Wulong and Beibei in Yangtze River.The result suggested that short daily runoff time series would affect the result of chaotic identification and make the result unreliable;besides,when the length of daily runoff time series reached 3 000,the chaotic characteristics became stable and reliable,and it saved a lot of computing time at the same time.
引文
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[13]Lorenz,Edward N.Dimension of weather and climate attractors[J].Nature,1991,353(6341):241-244.
[14]王文,许武成.对水文时间序列混沌特征参数估计问题的讨论[J].水科学进展,2005,16(4):609-616.(WANG Wen,XU Wu-cheng.Some issues on the characteristics of chaotic properties of hydrologic time series[J].Advances in Water Science,2005,16(4):609-616.(in Chinese)
[15]王亦农.浅谈混沌与水文[J].资源环境,2011,3(40):71-72.(WANG Yi-nong.A brief talk about chaotic and hydrology[J].Resources and Environment,2011,3(40):71-72.(in Chinese)
[2]W W Ng,U S Panu,W C Lennox.Chaos based analytical techniques for daily extreme hydrological observations[J].Journal of Hydrology,2007,342:17-41.
[3]李国良.混沌理论及其在水文时间序列中的应用研究[D].哈尔滨:东北农业大学,2007.12.(LI Guo-liang.Studies on chaos theory and its application in hydrology time series[D].Harbin:Northeast Agriculture University,2007.12.(in Chinese)
[4]楼玉.混沌时间序列方法在径流预报中的应用研究[D].杭州:浙江大学,2005.8.18.(LOU Yu.Chaotic time series methods in the study of the application of the runoff forecast[D].Zhejiang Hangzhou Zhejiang University,2005.8.18.(in Chinese)
[5]牟丽琴,林焕新.汀江流域降水时间序列的混沌分析[J].人民珠江,2010(01):27-29,55.(MOU Li-qin,LI Huan-xin.Chaotic analysis of rainfall time series in Tingjiang catchment[J].Pearl River,2010(01):27-29,55.(in Chinese)
[6]袁鹏,李谓新,王文圣,等.月降雨量时间序列中的混沌现象[J].四川大学学报:工程科学版,2002,34(1):16-19.(YUAN Peng,LI Wei-xin,WANG Wen-sheng,et al.Chaos analysis of monthly precipitation time series[J].Journal of Sichuan University:Engineering Science Edition,2002,34(1):16-19.(in Chinese)
[7]周寅康,王腊春,张捷.淮河流域洪涝变化的混沌特征[J].自然灾害学报,1999,8(1):42-47.(ZHOU Yin-kang,WANG Lachun,ZHANG Jie.Some chaotic characteristics of the flood series in Huai River basin[J].Journal of Natural Disasters,1999,8(1),42-47.(in Chinese)
[8]李新杰.河川径流时间序列的非线性特征识别与分析[D].武汉:武汉大学,2013.3.(LI Xin-jie.Nonlinear characteristics identification and analysis for river runoff time series[D].Wuhan:Wuhan University,2013.3.(in Chinese)
[9]陈关荣,吕金虎.Lorenz系统族的动力学分析、控制与同步[M].北京:科学出版社,2003.(CHEN Guan-rong,LYU Jinhu.Dynamics analysis、control and synchronization of Lorenz system[M].Beijing:Science Press,2003.
[10]王文,许武成.混沌时间序列可预报时间长度分析[J].河海大学学报:自然科学版,2004,32(4):367-371.(WANG Wen,XU Wu-cheng.Analysis of length of predictable time of chaotic time series[J].Journal of Hohai University:Natural Sciences,2004,32(4):367-371.(in Chinese)
[11]袁鹏,李谓新,王文圣,等.月降雨量时间序列中的混沌现象[J].四川大学学报:工程科学版,2002,34(1):16-19.(YUAN Peng,LI Wei-xin,WANG Wen-sheng,et al.Chaos analysis of monthly precipitation time series[J].Journal of Sichuan University:Engineering Science Edition,2002,34(1),16-19.(in Chinese)
[12]Alan Wolf,Jack B Swift,Harry L Swinney,et al.Determining Lyapunov exponents from a time series[J].Physica 16D,1985,285-317.
[13]Lorenz,Edward N.Dimension of weather and climate attractors[J].Nature,1991,353(6341):241-244.
[14]王文,许武成.对水文时间序列混沌特征参数估计问题的讨论[J].水科学进展,2005,16(4):609-616.(WANG Wen,XU Wu-cheng.Some issues on the characteristics of chaotic properties of hydrologic time series[J].Advances in Water Science,2005,16(4):609-616.(in Chinese)
[15]王亦农.浅谈混沌与水文[J].资源环境,2011,3(40):71-72.(WANG Yi-nong.A brief talk about chaotic and hydrology[J].Resources and Environment,2011,3(40):71-72.(in Chinese)