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Parameter Selection for Phase Space Reconstruction in Hydrological Series and Rationality Analysis of its Chaotic Characteristics

13 pagesPublished: September 20, 2018

Abstract

This study performed a rationality analysis of the delay time and embedding dimension value during phase space reconstruction in hydrological series and the effect on their chaotic characteristics. Using a monthly average runoff time series from the Ayanqian station (upstream) and the Jiangqiao station (midstream) in the Nen River Basin, we reached the following regularity conclusions. 1 Based on the flood season (4 months) in the Nen River Basin, we can deduce that the correlation sequence length for the runoff is 4~5 months, i.e., the delay time =3 or 4 is a reasonable choice. 2 Learn from the predictability experiment results for the monthly rainfall time series, we know that the calculation results of the G-P algorithm for the dimension of runoff series for the Nen River Basin are reasonable, i.e., the embedding dimension is no more than seven. 3 the most suitable parameters for the phase space reconstruction and its chaotic characteristic index in the Nen River Basin are as follows: delay time = 3~4, embedding dimension = 6~7, correlation dimension = 2.90~3.00, maximum Lyapunov index = 0.24~0.32, and the forecast time is 3~4 months.

Keyphrases: chaos theory, delay time, embedding dimension, phase space reconstruction

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 1171-1183.

BibTeX entry
@inproceedings{HIC2018:Parameter_Selection_Phase_Space,
  author    = {Hongyan Li and Shanshan Bao and Yunqing Xuan},
  title     = {Parameter Selection for Phase Space Reconstruction in Hydrological Series and Rationality Analysis of its Chaotic Characteristics},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/2V59},
  doi       = {10.29007/2fb8},
  pages     = {1171-1183},
  year      = {2018}}
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