水利学报
水利學報
수리학보
2013年
5期
515-520
,共6页
李新杰%胡铁松%郭旭宁%曾祥
李新傑%鬍鐵鬆%郭旭寧%曾祥
리신걸%호철송%곽욱저%증상
径流序列%混沌%时间尺度%0-1测试%关联维数
徑流序列%混沌%時間呎度%0-1測試%關聯維數
경류서렬%혼돈%시간척도%0-1측시%관련유수
runoff series%chaos%timescale%0-1 test%correlation dimension
径流序列的动力行为是在复杂非线性和多尺度现象综合作用下的外在表现.基于混沌理论和相空间重构理论,以金沙江和美国Umpqua河统计的日径流序列为研究对象,对不同时间尺度(日、旬和月)的径流序列,首先利用0-1混沌测试算法计算其渐进增长率,探讨径流序列混沌特性随时间尺度的变化规律,然后重构以上径流序列的相空间,分别计算关联维数、最大Lyapunov指数和Kolmogorov熵.用这3个混沌判别指标分析不同时间尺度下径流序列的混沌特性及其随时间尺度的变化规律.研究结果表明,时间尺度和径流序列非线性特征之间的关系并不明显,渐进增长率随时间尺度的增加并无明显的变化规律,嵌入维数则随时间尺度的增大呈减小趋势,最大lyapunov指数和Kolmogorov熵随着时间尺度的增加逐渐增大.
徑流序列的動力行為是在複雜非線性和多呎度現象綜閤作用下的外在錶現.基于混沌理論和相空間重構理論,以金沙江和美國Umpqua河統計的日徑流序列為研究對象,對不同時間呎度(日、旬和月)的徑流序列,首先利用0-1混沌測試算法計算其漸進增長率,探討徑流序列混沌特性隨時間呎度的變化規律,然後重構以上徑流序列的相空間,分彆計算關聯維數、最大Lyapunov指數和Kolmogorov熵.用這3箇混沌判彆指標分析不同時間呎度下徑流序列的混沌特性及其隨時間呎度的變化規律.研究結果錶明,時間呎度和徑流序列非線性特徵之間的關繫併不明顯,漸進增長率隨時間呎度的增加併無明顯的變化規律,嵌入維數則隨時間呎度的增大呈減小趨勢,最大lyapunov指數和Kolmogorov熵隨著時間呎度的增加逐漸增大.
경류서렬적동역행위시재복잡비선성화다척도현상종합작용하적외재표현.기우혼돈이론화상공간중구이론,이금사강화미국Umpqua하통계적일경류서렬위연구대상,대불동시간척도(일、순화월)적경류서렬,수선이용0-1혼돈측시산법계산기점진증장솔,탐토경류서렬혼돈특성수시간척도적변화규률,연후중구이상경류서렬적상공간,분별계산관련유수、최대Lyapunov지수화Kolmogorov적.용저3개혼돈판별지표분석불동시간척도하경류서렬적혼돈특성급기수시간척도적변화규률.연구결과표명,시간척도화경류서렬비선성특정지간적관계병불명현,점진증장솔수시간척도적증가병무명현적변화규률,감입유수칙수시간척도적증대정감소추세,최대lyapunov지수화Kolmogorov적수착시간척도적증가축점증대.
@@@@Natural runoff dynamics is an outcome of complex nonlinear and multi-scale phenomena,integrated together in some coherent manner. Based on chaos theory and the phase space reconstruction theory,daily runoff series of the Jinsha River in China and the Umpqua River in America are used for this study at different timescales (one day,1/3 month and one month). In this paper,the asymptotic growth rate Kc is calculated by the 0-1 test algorithm and its variation with timescales are explored firstly. Then phase space reconstruction are adopted for the runoff series, and three discrimination indexes are used:correlation dimension;Lyapunov exponent;Kolmogorov entropy. An attempt has been made to identify the existence of chaos and the intensity of nonlinear behavior at three characteristic time scales. A comparison of results reveals that the relationship between the timescales and the intensity of nonlinearity is not so obvious;there is no clear variation of the asymptotic growth rate along with the increase of timescale;and the embedded dimension decreases as the timescales increase. However,the largest Lyapunov exponent and Kolmogorov entropy increase gradually with the increase of the timescale.