Multifractal description of streamfow and suspended sediment concentration data from Indian river basin

Adarsh, S.; Dharan, Drisya S.; Nandhu, A. R.; Vishnu, B. Anand; Mohan, Vysakh K.; Wątorek, M.

doi:10.1007/s11600-020-00407-2

Artykuł - szczegóły

Tytuł artykułu

Multifractal description of streamfow and suspended sediment concentration data from Indian river basin

Autorzy

Adarsh S. , Dharan Drisya S. , Nandhu A. R. , Vishnu B. Anand , Mohan Vysakh K. , Wątorek M.

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1007/s11600-020-00407-2

Warianty tytułu

Języki publikacji

Abstrakty

This study investigated the multifractality of streamfow data of 192 stations located in 13 river basins in India using the multifractal detrended fuctuation analysis (MF-DFA). The streamfow datasets of diferent river basins displayed multifractality and long-term persistence with a mean exponent of 0.585. The streamfow records of Krishna basin displayed least persistence and that of Godavari basin displayed strongest multifractality and complexity. Subsequently, the streamfow-sediment links of fve major river basins were evaluated using the novel multifractal cross-correlation analysis (MFCCA) method of cross-correlation studies. The results showed that the joint persistence of streamfow and total suspended sediments (TSS) is approximately the mean of the persistence of individual series. The streamfow displayed higher persistence than TSS in 60% of the stations while in majority of stations of Godavari basin the trend was opposite. The annual cross-correlation is higher than seasonal cross-correlation in majority of stations but at these time scales strength of their association difers with river basin.

Słowa kluczowe

streamflow multifractal sediment persistence correlation

spływ wodny multifraktal osad trwałość korelacja

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2020

Tom

Vol. 68, no. 2

Strony

519--535

Opis fizyczny

Bibliogr. 50 poz.

Twórcy

autor

Adarsh S.

adarsh1982@tkmce.ac.in

TKM College of Engineering, Kollam, Kerala, India

autor

Dharan Drisya S.

TKM College of Engineering, Kollam, Kerala, India

autor

Nandhu A. R.

TKM College of Engineering, Kollam, Kerala, India

autor

Vishnu B. Anand

TKM College of Engineering, Kollam, Kerala, India

autor

Mohan Vysakh K.

TKM College of Engineering, Kollam, Kerala, India

autor

Wątorek M.

Complex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, ul. Radzikowskiego 152, 31-342 Kraków, Poland
Faculty of Computer Science and Telecommunications, Cracow University of Technology, ul. Warszawska 24, 31–155 Kraków, Poland

Bibliografia

1. Adarsh S, Drisya SD, Anuja PK, Aggie S (2018a) Unravelling the scaling characteristics of daily streamflows of Brahmani River Basin, India using Arbitrary order Hilbert spectral and detrended fluctuation analyses. SN Appl Sci 1(2018):58. https://doi.org/10.1007/s42452-018-0056-1
2. Adarsh S, Drisya SD, Anuja PK (2018b) Analyzing the hydrologic variability of Kallada River, India using continuous wavelet transform and fractal theory. Water Conserv Sci Eng. https://doi.org/10.1007/s41101-018-0060-8
3. Adarsh S, Kumar DN, Deepthi B, Gayathri G, Aswathy SS, Bhagyasree S (2019) Multifractal characterization of meteorological drought in India using detrended fluctuation analysis. J Climatol Int. https://doi.org/10.1002/joc.6070
4. Baranowski P, Krzyszczak J, Slawinski C, Hoffmann H, Kozyra J, Nieróbca A, Siwek K, Gluza A (2015) Multifractal analysis of meteorological time series to assess climate impacts. Clim Res 65:39–52
5. Brito AA, Santos FR, de Castro APN, da Cunha Lima AT, Zebende GF, da Cunha Lima IC (2018) Cross-correlation in a turbulent flow: analysis of the velocity field using the σ DCCA coefficient. Europhys Lett 123:20011
6. Dahlstedt K, Jensen H (2005) Fluctuation spectrum and size scaling of river flow and level. Phys A 348:596–610
7. Dey P, Mujumdar PP (2018) Multiscale evolution of persistence of rainfall and streamflow. Adv Water Resour 121:285–303
8. Drożdż S, Oświęcimka P (2015) Detecting and interpreting distortions in hierarchical organization of complex time series. Phys Rev E 91:030902(R)
9. Drożdż S, Minati L, Oświȩcimka P, Stanuszek M, Wątorek M (2019) Signatures of the crypto-currency market decoupling from the Forex. Future Internet 11:154. https://doi.org/10.3390/fi11070154
10. Grech D (2016) Alternative measure of multifractal content and its application in finance. Chaos, Solitons Fractals 88:183–195
11. Hajian S, Movahed MS (2010) Multifractal detrended cross-correlation analysis of sunspot numbers and river flow fluctuations. Phys A 389:4942–4957
12. Hirpa FA, Gebremichael M, Over TM (2010) River flow fluctuation analysis: effect of watershed area. Water Resour Res. https://doi.org/10.1029/2009WR009000
13. Huang YX, Schmitt FG, Hermand JP, Gagne Y, Lu ZM, Liu YM (2011) Arbitrary-order Hilbert spectral analysis for time series possessing scaling statistics: a comparison study with detrended fluctuation analysis and wavelet leaders. Phys Rev E 84:016208. https://doi.org/10.1103/PhysRevE.84.016208
14. Hurst HE (1951) Long-term storage capacity of reservoirs. Trans ASCE 116:770–808
15. Hurst HE, Black RP, Simaika YM (1965) Long-term storage: an experimental study. Constable, London
16. Ihlen EAF (2012) Introduction to multifractal detrended fluctuation analysis in MATLAB. Front Physiol 3:141. https://doi.org/10.3389/fphys.2012.00141
17. Jiang ZQ, Zhou WX (2011) Multifractal detrending moving-average cross-correlation analysis. Phys Rev E 84:016106
18. Jiang ZQ, Wen-Jie X, Zhou WX, Sornette D (2011) Multifractal analysis of financial markets. Quant Finance. http://arxiv.org/abs/1805.04750
19. Kantelhardt JW, Zschiegner SA, Koscielny-Bunde E, Halvin H, Bunde A, Stanley HE (2002) Multifractal detrended fluctuation analysis of non-stationary time series. Phys A 316:87–114
20. Kantelhardt JW, Rybski D, Zschiegner SA, Braun P, Koscielny-Bunde E, Livina V, Havlin S, Bunde A (2003) Multifractality of river runoff and precipitation: comparison of fluctuation analysis and wavelet methods. Phys A 330:240–245
21. Kantelhardt JW, Bunde EK, Rybski D, Barun P, Bunde A, Havlin S (2006) Long-term persistence and multifractality of precipitation and river runoff records. J Geophys Res Atmos 28:1–13
22. Koscielny-Bunde E, Kantelhardt JW, Braun P, Bunde A, Havlin S (2003) Long-term persistence and multifractality of river runoff records: detrended fluctuation studies. J Hydrol 322:120–137
23. Krzyszczak J et al (2019) Multifractal characterization and comparison of meteorological time series from two climatic zones. Theoret Appl Climatol 137:1811–1824
24. Kwapień J, Oświęcimka P, Drożdż S (2015) Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations. Phys Rev E 92:052815
25. Labat D, Masbou J, Beaulieu E, Mangin A (2011) Scaling behavior of the fluctuations in stream flow at the outlet of karstic watersheds, France. J Hydrol 410:162–168
26. Li E, Mu X, Zhao G, Gao P (2015) Multifractal detrended fluctuation analysis of streamflow in Yellow River Basin, China. Water 7:1670–1686
27. Mandelbrot B (1982) The fractal geometry of nature. WH Freeman Publishers, New York
28. Muzy JF, Bacry E, Arneodo A (1991) Wavelets and multifractal formalism for singular signals: application to turbulence data. Phys Rev Lett 67(1991):3515–3518
29. Oświęcimka P, Drożdż S, Kwapień J, Górski A (2013) Effect of detrending on multifractal characteristics. Acta Phys Pol, A 123:597–603
30. Oświȩcimka P, Drożdż S, Forczek M, Jadach S, Kwapień J (2014) Detrended cross-correlation analysis consistently extended to multifractality. Phys Rev E 89:023305
31. Pandey G, Lovejoy S, Schertzer D (1998) Multifractal analysis of daily river flows including extremes for basins five to two million square kilometers, one day to 75 years. J Hydrol 208:62–81
32. Peng CK, Buldyrev SV, Simons M, Stanley HE, Goldberger AL (1994) Mosaic organization of DNA nucleotides. Phys Rev E 49:1685–1689
33. Piao L, Fu Z (2016) Quantifying distinct associations on different temporal scales: comparison of DCCA and Pearson methods. Sci Rep 6:36759
34. Podobnik B, Stanley HE (2008) Detrended cross-correlation analysis: a new method for analyzing two non-stationary time series. Phys Rev Lett 100(8):084102
35. Podobnik B, Grosse I, Horvatic D, Ilic S, Ivanov PCh, Stanley HE (2009a) Quantifying cross-correlations using local and global detrending approaches. Eur Phys J B 71:243–250
36. Podobnik B, Horvatic D, Petersen AM, Stanley HE (2009b) Cross-correlations between volume change and price change. Proc Natl Acad Sci USA 106:22079–22084
37. Podobnik B, Jiang Z-Q, Zhou W-X, Stanley HE (2011) Statistical tests for power-law cross-correlated processes. Phys Rev E 84:066118
38. Rego CRC, Frota HO, Gusmão MS (2013) Multifractality of Brazilian rivers. J Hydrol 495:208–215
39. Shi K (2014) Detrended cross-correlation analysis of temperature, rainfall, PM10 and ambient dioxins in Hong Kong. Atmos Environ 97(2014):130–135
40. Tan X, Gan TW (2017) Multifractality of Canadian precipitation and streamflow. Int J Climatol 37(S1):1221–1236
41. Tessier Y, Lovejoy S, Hubert P, Schertzer D, Pecknold S (1996) Multifractal analysis and modeling of rainfall and river flows and scaling, causal transfer functions. J Geophys Res Atmos 101:26427–26440
42. Vassoler RT, Zebende GF (2012) DCCA cross-correlation coefficient apply in time series of air temperature and air relative humidity. Phys A 391:2438–2443
43. Wątorek M, Drożdż S, Oświęcimka P, Stanuszek M (2019) Multifractal cross-correlations between the world oil and other financial markets in 2012–2017. Energy Econ 81:874–885
44. Wu Y, He Y, Wu M, Lu C, Gao S, Xu Y (2018) Multifractality and cross correlation analysis of streamflow and sediment fluctuation at the apex of the Pearl River Delta. Sci Rep 8:16553. https://doi.org/10.1038/s41598-018-35032-z
45. Yu ZG, Leung Y, Chen YD, Zhang Q, Anh V, Zhou Y (2014) Multifractal analyses of daily rainfall time series in Pearl River basin of China. Phys A 405:193–202
46. Yuan N, Fu Z, Mao J (2010) Different scaling behaviors in daily temperature records over China. Phys A 389(19):4087–4095
47. Zebende GF (2011) DCCA cross-correlation coefficient: quantifying level of cross-correlation. Phys A 390:614–618
48. Zhang Q, Xu CY, Chen DYQ, Gemmer M, Yu ZG (2008) Multifractal detrended fluctuation analysis of streamflow series of the Yangtze river basin, China. Hydrol Process 22:4997–5003
49. Zhang Q, Chong YX, Yu ZG, Liu CL, Chen DYQ (2009) Multifractal analysis of streamflow records of the East River basin (Pearl River), China. Phys A 388:927–934
50. Zhou WX (2008) Multifractal detrended cross-correlation analysis for two non-stationary signals. Phys Rev E 77:066211

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)

Typ dokumentu

Bibliografia

Identyfikator YADDA

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