Application of the Chaos Theory, the Reconstructed Phase Space and Correlation Dimensions in the Suspended Load Transport Patterns as Affected by a Dam: The Case of the Karaj River

Document Type : Research Paper

Authors

Abstract

The sediment load of a river is one of the major parameters in designing a dam, as it not only affect configuration  and construction on its upstream, but also due to its negative consequences resulting from sediment dredging and some environmental issues that arise in its downstream. Therefore, elucidation of sediment transport mechanisms is of utmost importance. As several independent and nonlinear factors affect this phenomenon, its randomness has been accepted by many hydrologists as an axiom. The chaos theory states that many complex systems with random behavior are limited only by the number of parameters, and their behavior is predictable in a short term. The dynamics of sediment transport, and also the influence of a dam on its patterns are studied in this project benefitting from the chaos theory, and the reconstructed phase space and correlation dimensions methods. Results indicate that the sediment time series have low-dimensional chaos, and in a period as short as 10 days, a dam affects the dynamics and converts a chaotic phenomenon in to random ones. However, due to the created information and disconnection that takes place in a chaotic system in longer times, i.e. one month, the above mentioned transformation   disappears an the system resumes a chaotic behavior.
 

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  1. امامی، ا. 1389. انتقال رسوب، انتشارات جهاد دانشگاهی واحد صنعتی امیر کبیر.
  2. شقاقیان، م ر، و ن. طالب بیدختی. 1388. بررسی وجود آشوب در جریان رود در مقیاسهای زمانی گوناگون، مجله مهندسی آب.
  3. فتاحی م ه، ن، طالب بیدختی، غ، رخشنده رو، و ا. شمسایی. 1388. پیش پردازش موجکی و فراکتالی گروه زمانی جریان رودخانه برای شبیه پیش بینی شبکه عصبی. همایش ملی بحران آب. دانشگاه آزاد اسلامی واحد مرودشت، اسفند.
  4. فهیم فرد، س.1392. بررسی وجود الگوهای آشوبناک در سامانه انتقال رسوبات رودخانه (مطالعه موردی: رودخانه کرج).
  5. فهیم فرد، س. ا. شمسایی، م. ه، فتاحی، س. فرزین. 1393. بررسی وجود الگوی آشوبی در گروه زمانی بار بستر رودخانه (مطالعه موردی رودخانه جاجرود). سیزدهمین کنفرانس هیدرولیک ایران، دانشگاه تبریز، تبریز، آبان.
    1. Hang guang, M. A. and H. Chong zho 2006. Selection of embedding dimension and delay time in phase space reconstruction. Front, Electr., Election, Eng, China. 1:111-114.
    2. Lai, Y. and D. Lener 1998. Effective scaling reigme for computing the correlation dimension from chaotic time series. Physica D, 115.
    3. Musielak, Z.E.  and D.E. Musielak, High dimensional chaos in dissipative and driven dynamical systems. Department of Physics the University of Texas at Arlington.
    4. Regonda, S K, B. Sivakumar, and A. Jain. 2004. Temporal scaling in river flow: Can it be chaotic? Hydrol. Sci.– Journal- des Science Hydrologiques. 49.
    5. Saha, L.M. 2011. Measuring chaos: Topological entropy and correlation dimension in discrete map.
    6. Sivakumar, B. 2001. Rainfall dynamics at different temporal scales: A chaotic perspective. Hydrol Earth Sys. Sci. 5: 645-651.
    7. Sivakumar, B, A. W, Jayawardena. 2003. Sediment transport phenomenon in rivers: An alternative perspective, Enviromen Model. Softw. 18:831-838.
    8. Sivakumar, B. 2000.  Chaos theory in hydrology: Important issues and interpretations. J. Hydrol. 227:120.
    9. Sivakumar, B. 2009. Nonlinear dynamics and chaos in hydrological system: Last developments and a look forwards. Stoch Environ Res Risk Access. 23:1027-1036.
    10. Solomatine, D. P., S. Velickov, and J. C. Wust. 2001. Predicting water levels and currents in the North Sea using chaos theory and neural networks Proc. 29 th Iahr Congr. Beijing, China: 1-11.
    11. Stehlik, J. 2003. Deterministic chaos in runoff series. Hydrometeorological Institute, Dept. of Experimental Hydrology, 143, 06 Prague.
    12. Velickov. S. 2006.Nonlinear dynamics and chaos with applications to hydrodynamics and hydrological modeling. Taylor and Francis e-library.
    13. Wang, Y.Z, X, Rong, B. Li, J. Su, and R.Q. Wang, 2010. Chaotic dynamics in ecological time series: 22 year study of a natural population. Int. J. Nonlin. Sciences and Numerical Simul. 11:511-518.