Analysis of River Parameters Using Chaos-Theory Based Indices (Case Study: Zayandehrud River Flow)

Document Type : Technical Note (5 pages)

Authors

1 Professor., Department of Water and Hydraulic Structures, Faculty of Civil Engineering, Semnan University, Semnan, Iran.

2 M.Sc., Department of Water and Hydraulic Structures, Faculty of Civil Engineering, Semnan University, Semnan, Iran.

3 Assistant Professor, Faculty of Civil Engineering, Semnan niversity, Semnan, Iran

Abstract

Analysis of hydrological parameters of rivers in short-term scales and during a long period of time plays a significant role in the study of production and storage of hydro-electrical energy as well as flood and drought control. In this research, by using chaotic indices, the dynamic status of flow time series and effect of time scale on Zayandehrud River flow behavior in 43 years (1971-2013) was evaluated. The data from Eskandari, Ghale Shahrokh, Pole Zamankhan and Pol Kalleh hydrometric stations in Zayandehrud River were investigated at two daily and 10-day time scales. The possibility of chaos in river flow rate was investigated using correlation dimension. Results showed that on a daily scale, the non-integer value of correlation dimension is 3.34, 3.60, 3.77 and 3.84, respectively, for Eskandari, Ghale Shahrokh, Pole Zmankhan and Pol Kalleh. This indicates the chaotic flow rate of these stations. By increasing the time scale to 10 days, the flow rate in all stations becomes random. Using the Lyapunov exponent test, sensitivity of the system to initial conditions was investigated as an attribute of chaotic systems and the forecast horizon was estimated. The largest Lyapunov exponents obtained at each of the four stations in two daily and 10-day time scales were positive. Hurst exponent was used to investigate the random process of data against its non-randomness. Considering the nonlinear dynamic indices, it seems that correlation dimension is more accurate for chaotic detection in nonlinear systems.

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Adab F, Karami H, Mousavi SF, Farzin S (2017) Effect of Ghir barrage on chaotic behavior of discharge in Karun River. Applied Research of Water Sciences 2(1):11-26 (In Persian)
Alami M, Malekani L (2013) Phase space reconstruction and fractal dimension using of delay time and embedding dimension. Journal of Civil and Environmental Engineering 43(1):15-23
Anis Hosseini M, Zaker Moshfegh M (2013) Kashkan river flow analysis and forecasting using chaos theory. Hydraulic Journal 8(3):45-61 (In Persian)
Eslami A, Ghahraman B, Ziaee A, Eslami P (2016) Effect of noise reduction in nonlinear dynamic analysis of maximum daily temperature series in Kerman station. Iran Water Resources Research 12(1):171-185 (In Persian)
Fattahi M, Tarahi M (2017) Chaotic monitoring of river flow using phase space reconstruction method. Iran Water Resources Research 13(2):221-225 (In Persian)
Grassberger P, Procaccia I (1983) Measuring the strangeness of strange attractors. Physica D 9:189-208
Ghorbani MA, Kisi O, Alinezhad M (2010) A prop into the chaotic nature of daily streamflow time series by correlation dimension and largest Lyapunov methods. Applied Mathematical Modeling 34:4050-4057
Hassanzadeh Y, Lotfollahi YM, Shahverdi S, Farzin S, Farzin N (2013) De-noising and prediction of time series based on the wavelet algorithm and chaos theory (Case study: SPI drought monitoring index of Tabriz city). Iran Water Resources Research 8(3):1-13 (In Persian)
Hashemi Golpayegani SMR (2009) Chaos and its applications in engineering. Amirkabir University of Technology, 188 p. (In Persian)
Hurst HE (1951) Long-term storage capacity of reservoirs. Transactions American Society of Civil Engineers 116:770-808
Khatibi R, Sivakumar B, Ghorbani MA, Kisi O, Koçak K, Zadeh DF (2012) Investigating chaos in river stage and discharge time series. Journal of Hydrology 414:108-117
Regonda SK, Sivakumar B, Jain A (2004) Temporal scaling in river flow: can it be chaotic?. Hydrological Sciences Journal 49(3):373-385
Shang P, Li X, Kamae S (2005) Chaotic analysis of traffic time series. Chaos, Solitons and Fractals 25:121-128
Sivakumar B (2001) Rainfall dynamics at different temporal scales: A chaotic perspective. Hydrology and Earth System Sciences 5(4):645-651
Wolff RCL (1992) Local Lyapunov exponents: Looking closely at chaos. Journal of the Royal Statistical Society 54(2):353-371
Yabin S, Chi D (2014) Improving numerical forecast accuracy with Ensemble Kalman Filter and chaos theory. Journal of Hydrology 512:540-548