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Wavelet Transform Based Method for River Stream Flow Time Series Frequency Analysis and Assessment in Tropical Environment

  • Kai Lun Chong
  • Sai Hin LaiEmail author
  • Ahmed El-Shafie
Article
  • 49 Downloads

Abstract

The main aim of this study is to perform a time series frequency analysis and assessment for stream flow over the Johor River using a comparative method between wavelet transform (WT) and Fourier transform (FT). One of the wavelet analyses used was the discrete wavelet transform (DWT), which revealed the periodic wavelet components responsible for the trend detection. Using the FT, the periodicities that governed the trend can be obtained; however, in terms of the time domain analysis, FT seems to be lacking compared to the WT. The conditions for using DWT are discussed, and the selection decisions for such discretization are considered. Besides, using the global wavelet spectrum (GWS) and the continuous wavelet transform (CWT), the dominant periodicity components can be further well described in time frequency characteristic. In addition, the integration of the WT and Mann–Kendall (MK) test allows the determination of possible trends present in the stream flow dataset series. It is shown that the wavelet analysis is more suitable than the Fourier analysis as it exhibits good extraction of the time and frequency characteristics, especially for a nonstationary data series.

Keywords

Wavelet transform Fourier transform Mann-Kendall test Trends Sequential Mann-Kendall test Spearman’ rho test 

Notes

Acknowledgements

The authors would like to appreciate so much the financial support received from the University of Malaya Research Grant (UMRG) coded RP025A-18SUS University of Malaya, Malaysia.

Compliance with Ethical Standards

Conflict of Interest

The authors here declare that we have no conflict of interest with anybody or any institution.

References

  1. Ahmad I, Tang D, Wang T, Wang M, Wagan B (2015) Precipitation trends over time using Mann-Kendall and spearman’s rho tests in swat river basin, Pakistan. Advances in Meteorology, 2015Google Scholar
  2. Amin M, Shaaban A, Ercan A, Ishida K, Kavvas M, Chen Z, Jang S (2017) Future climate change impact assessment of watershed scale hydrologic processes in Peninsular Malaysia by a regional climate model coupled with a physically-based hydrology modelo. Sci Total Environ 575:12–22CrossRefGoogle Scholar
  3. Aminikhanghahi S, Cook DJ (2017) A survey of methods for time series change point detection. Knowl Inf Syst 51(2):339–367CrossRefGoogle Scholar
  4. Bae D-H, Koike T, Awan JA, Lee M-H, Sohn K-H (2015) Climate change impact assessment on water resources and susceptible zones identification in the Asian monsoon region. Water Resour Manag 29(14):5377–5393CrossRefGoogle Scholar
  5. Bayazit M (2015) Nonstationarity of hydrological records and recent trends in trend analysis: a state-of-the-art review. Environmental Processes 2(3):527–542CrossRefGoogle Scholar
  6. de Artigas MZ, Elias AG, de Campra PF (2006) Discrete wavelet analysis to assess long-term trends in geomagnetic activity. Physics and Chemistry of the Earth, Parts A/B/C 31(1-3):77–80Google Scholar
  7. Delgado JM, Apel H, Merz B (2010) Flood trends and variability in the Mekong river. Hydrol Earth Syst Sci 14(3):407–418CrossRefGoogle Scholar
  8. Fathian F, Morid S, Kahya E (2015) Identification of trends in hydrological and climatic variables in Urmia Lake basin, Iran. Theor Appl Climatol 119(3-4):443–464CrossRefGoogle Scholar
  9. GenerPianosi F, Wagener T (2016) Understanding the time-varying importance of different uncertainty sources in hydrological modelling using global sensitivity analysis. Hydrol Process 30(22):3991–4003CrossRefGoogle Scholar
  10. Kendall M (1975) Rank Correlation Methods, Charles Griffin, London. Google ScholarGoogle Scholar
  11. Kundzewicz ZW, Graczyk D, Maurer T, Pińskwar I, Radziejewski M, Svensson C, Szwed M (2005) Trend detection in river flow series: 1. Annual maximum flow/Détection de tendance dans des séries de débit fluvial: 1. Débit maximum annuel. Hydrol Sci J 50(5)Google Scholar
  12. Lehmann E (1975) Nonparametrics: statistical methods based on ranks Holden-Day. Inc., San FranciscoGoogle Scholar
  13. Machiwal D, Jha MK (2009) Time series analysis of hydrologic data for water resources planning and management: a review. Journal of Hydrology and Hydromechanics 54(3):237–257Google Scholar
  14. Mehala N, Dahiya R (2008) A comparative study of FFT, STFT and wavelet techniques for induction machine fault diagnostic analysis. Paper presented at the Proceedings of the 7th WSEAS international conference on computational intelligence, man-machine systems and cybernetics, CairoGoogle Scholar
  15. Mondal A, Kundu S, Mukhopadhyay A (2012) Rainfall trend analysis by Mann-Kendall test: A case study of north-eastern part of Cuttack district, Orissa. International Journal of Geology, Earth and Environmental Sciences 2(1):70–78Google Scholar
  16. Morán-Tejeda E, Ceballos-Barbancho A, Llorente-Pinto JM (2010) Hydrological response of Mediterranean headwaters to climate oscillations and land-cover changes: The mountains of Duero River basin (Central Spain). Glob Planet Chang 72(1-2):39–49CrossRefGoogle Scholar
  17. Nalley D, Adamowski J, Khalil B (2012) Using discrete wavelet transforms to analyze trends in streamflow and precipitation in Quebec and Ontario (1954–2008). J Hydrol 475:204–228CrossRefGoogle Scholar
  18. Nason GP (2006) Stationary and non-stationary time series. Statistics in Volcanology. Special Publications of IAVCEI, vol 1, pp 000–000Google Scholar
  19. Pohlert T (2016). Non-parametric trend tests and change-point detection. CC BY-ND, 4Google Scholar
  20. Sethi R, Pandey BK, Krishan R, Khare D, Nayak P (2015) Performance evaluation and hydrological trend detection of a reservoir under climate change condition. Modeling Earth Systems and Environment 1(4):33CrossRefGoogle Scholar
  21. Shadmani M, Marofi S, Roknian M (2012) Trend analysis in reference evapotranspiration using Mann-Kendall and Spearman’s Rho tests in arid regions of Iran. Water Resour Manag 26(1):211–224CrossRefGoogle Scholar
  22. Sneyers R, Vandiepenbeeck M, Vanilierde R, Demarée G (1990) Climatic changes in Belgium as appearing from the homogenized series of observations made in Brussels–Uccle (1933-1988) In: SCHIETECAT, GD. Contributions à l’etude des changements de climat. Bruxelles: Institut Royal Meteorologique de Belgique, Publications Série 124:17–20Google Scholar
  23. Torrence C, Compo GP (1998) A practical guide to wavelet analysis. Bull Am Meteorol Soc 79(1):61–78CrossRefGoogle Scholar
  24. Wong C, Venneker R, Uhlenbrook S, Jamil A, Zhou Y (2009) Variability of rainfall in Peninsular Malaysia. Hydrol Earth Syst Sci Discuss 6(4):5471–5503CrossRefGoogle Scholar
  25. Wu J, Wei S (1989) Time series analysis. Hunan Science and Technology Press, ChangShaGoogle Scholar
  26. Yue S, Pilon P, Cavadias G (2002) Power of the Mann–Kendall and Spearman's rho tests for detecting monotonic trends in hydrological series. J Hydrol 259(1-4):254–271CrossRefGoogle Scholar
  27. Yue S, Wang C (2004) The Mann-Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resour Manag 18(3):201–218CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Civil Engineering, Faculty of EngineeringUniversity of MalayaKuala LumpurMalaysia

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