Detecting determinism and nonlinearity in riverflow time series

被引:27
|
作者
Porporato, A
Ridolfi, L
机构
[1] Duke Univ, Dept Civil & Environm Engn, Durham, NC 27708 USA
[2] Politecn Torino, Dipartimento Idraul Trasporti & Infrastrutture Ci, I-10129 Turin, Italy
关键词
rainfall-runoff transformation; river-flow forecasting; nonlinear time series analysis; recession curves; entropy;
D O I
10.1623/hysj.48.5.763.51457
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
The temporal evolution of river-flow dynamics is investigated using methods from nonlinear time series analysis. After a discussion on the possible sources of nonlinear deterministic components, different methods for the detection of nonlinear and deterministic components in river flow time series are illustrated and the application to three river-flow time series from basins of different dimensions and characteristics is presented. All the results of different nonlinear techniques show noticeable, evidence of determinism and nonlinearity at high discharge values, while at low discharge values, and especially during recessions, the series seem to be the result of a mostly linear dynamics. The complexity of the dynamics and the degree of nonlinearity are also discussed in relation to the basin dimensions and the kind of hydroclimatic regime.
引用
收藏
页码:763 / 780
页数:18
相关论文
共 50 条
  • [1] The delay vector variance method for detecting determinism and nonlinearity in time series
    Gautama, T
    Mandic, DP
    Van Hulle, MA
    PHYSICA D-NONLINEAR PHENOMENA, 2004, 190 (3-4) : 167 - 176
  • [2] Detecting nonlinearity in multivariate time series
    Palus, M
    PHYSICS LETTERS A, 1996, 213 (3-4) : 138 - 147
  • [3] DETECTING NONLINEARITY IN TIME-SERIES
    DAVIES, N
    PETRUCCELLI, JD
    STATISTICIAN, 1986, 35 (02): : 271 - 280
  • [4] Detecting nonlinearity in multivariate time series
    Palus, M.
    Physics Letters. Section A: General, Atomic and Solid State Physics, 213 (3-4):
  • [5] Detecting determinism in time series: The method of surrogate data
    Small, M
    Tse, CK
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS, 2003, 50 (05): : 663 - 672
  • [6] Application of symbolic techniques in detecting determinism in time series
    Yang, ZJ
    Zhao, GZ
    PROCEEDINGS OF THE 20TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOL 20, PTS 1-6: BIOMEDICAL ENGINEERING TOWARDS THE YEAR 2000 AND BEYOND, 1998, 20 : 2670 - 2673
  • [7] Complexity analysis of riverflow time series
    Asok K. Sen
    Stochastic Environmental Research and Risk Assessment, 2009, 23 : 361 - 366
  • [8] Complexity analysis of riverflow time series
    Sen, Asok K.
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2009, 23 (03) : 361 - 366
  • [9] DETECTING DETERMINISM IN TIME SERIES WITH ORDINAL PATTERNS: A COMPARATIVE STUDY
    Amigo, J. M.
    Zambrano, S.
    Sanjuan, M. A. F.
    INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, 2010, 20 (09): : 2915 - 2924
  • [10] Detecting nonlinearity in time series: Surrogate and bootstrap approaches
    Hinich, M
    Mendes, E
    Stone, L
    STUDIES IN NONLINEAR DYNAMICS AND ECONOMETRICS, 2005, 9 (04):