| Peer-Reviewed

Influence of the Long-Range Dependence in Rainfall in Modelling Oueme River Basin (Benin, West Africa)

Received: 20 December 2016    Accepted: 29 December 2016    Published: 23 January 2017
Views:       Downloads:
Abstract

Nowadays, there is evidence that hydrological processes exhibit long-range dependence (LRD), i.e. power-type decay of autocorrelation also known as the Hurst phenomenon. This means that the stationarity assumption of hydrological time series, which has been widely used in the past, cannot be further advocated. The objective of this paper is to detect the long-range dependence in rainfall in Oueme River basin and to understand how the Hurst coefficient influences the river discharge dynamics. To this end, this paper formulated the Hurst phenomenon that characterized hydrological and other geophysical time series. Then, the fractional generalization of the triple relationship between the fractional Brownian motion, the corresponding stochastic differential equations (SDE) describing the river basin and the deterministic fractional Fokker-Planck equations (FPE) is analysed for the modelling of the river discharge dynamics. This fractional FPE provides an essential tool for the study of the dynamics of the river discharge in Oueme River basin.

Published in American Journal of Biological and Environmental Statistics (Volume 2, Issue 4)
DOI 10.11648/j.ajbes.20160204.15
Page(s) 50-59
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Hurst Coefficient, Fractional Brownian Motion, Stochastic Differential Equations, Fractional Fokker-Planck Equations, Probability Distribution Function

References
[1] Koutsoyiannis, D. Climate change, the Hurst phenomenon, and hydrological statistics. Hydrological Sciences Journal 2003 N0 48 (1), P. 3-24.
[2] IPCC (Intergovernmental Panel on Climate Change). Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. In: C. B. Field, et al. eds. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change 2014a, Cambridge, UK: Cambridge University Press.
[3] IPCC (Intergovernmental Panel on Climate Change). Climate change 2014: Impacts, adaptation, and vulnerability. Part B: regional aspects. In: V. R. Barros, et al. eds. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change 2014b, Cambridge, UK: Cambridge University Press.
[4] Kindler, J.; Tyszewski, S. On the value of fuzzy concepts in hydrology and water resources management, In “New Uncertainty Concepts in Hydrology and Water Resources” 1995, Ed. Z. Kundzewicz, p. 126-132, Cambridge University Press.
[5] Koutsoyiannis, D. Uncertainty, entropy, scaling and hydrological stochastics, Marginal distributional properties of hydrological processes and state scaling, Hydrological Sciences Journal 2005, 50 (3), 381-404.
[6] Hurst, H. E. Long term storage capacity of reservoirs. Transactions of the American Society of Civil Engineers 1951, 116, 770-808.
[7] Feder, J. Fractals, Plenum 1988, New York.
[8] Lo A. W., 1991. Long-term memory in stock market prices. Econometrica, vol. 59, No. 5, 1279-1313.
[9] Taqqu M. S., Teverovsky V. et Willinger W., 1995. Estimators for Long-Range Dependence: An Empirical Study, Preprint, Boston University.
[10] Stroock, D. W. Markov Processes from K. Ito Perspective, Princeton Univ. Press 2003, Princeton.
[11] Biao, I. E.; Alamou, A. E.; Afouda, A. Improving rainfall-runoff modelling through the control of uncertainties under increasing climate variability in the Oueme River basin (Benin, West Africa). Hydrological Sciences Journal 2016, Vol. 61, No. 16, 2902–2915.
[12] Barthel, R.; Sonneveld, B. G. J. S.; Gotzinger, J.; Keyzer, M. A.; Pande, S.; Printz, A.; Gaiser, T. Integrated assessment of groundwater resources in the Oueme basin, Benin, West Africa. Physics and Chemistry of the Earth 2009, 236-250.
[13] Hurst, H. E. A suggested statistical model for some time series that occur in nature. Nature 1957, 180, 494-495.
[14] Koutsoyiannis, D. Hydrology and change. Hydrological Sciences Journal 2013, 58:6, 1177-1197, DOI: 10.1080/02626667.2013.804626.
[15] Mandelbrot, B. B.; Wallis, J. R. Some Long-Run Properties of Geophysical Records. Water Resources Research 1969, 5, 2, 321-340.
[16] Mandelbrot, B. B. Le problème de la réalité des cycles lents et le syndrome de Joseph. Economie Appliquee 1973, vol. 26, pp. 349-365.
[17] Mandelbrot, B. B.; Taqqu, M. S. Robust R/S Analysis of Long-Run Serial Correlation. Bulletin of the International Statistical Institute 1979, vol. 48, pp 69-104.
[18] Sakalauskiene, G. The Hurst Phenomenon in Hydrology. Environmental Research, Engineering and Management 2003, 3 (25), 16-20.
[19] Mandelbrot, B. B.; Wallis, J. R. Noah, Joseph, and operational hydrology. Water Resour Res 1968, 4 (5), 909-918.
[20] Newey, W. and West, K.., 1987. A simple positive definite, heteroscedasticity and autocorrelation consistent covariance matrix. Econometrica, vol 55, pp. 703-705.
[21] Lo, A., And Mackinlay, C., 1989. The Size and Power of the Variance Ratio Test in Finite Samples: A Monte Carlo Investigation, Journal of Econometrics, 40, 203−238.
[22] Andrews, D., 1991. Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation, Econometrica, vol. 59, pp. 817-858.
[23] Obada, E.; Alamou, A. E; Biao, I. E.; Afouda, A. On the Use of Simple Scaling Stochastic (SSS) Framework to the Daily Hydroclimatic Time Series in the Context of Climate Change. Hydrology 2016. Vol. 4, No. 4, pp. 35-45. doi: 10.11648/j.hyd.20160404.11.
[24] Korvin, G. Fractal Models in the Earth Sciences, Elsevier 1992, New York.
[25] Afouda, A.; Lawin, A. E.; Lebel, T.; Peugeot, C.; Seguis, L. Modèle de transformation pluie-debit basé sur le Principe de Moindre Action. Regional Hydrological Impacts of climatic change. Hydro climatic variability 2005. LAHS Publ. 296, 129-137.
[26] Afouda, A.; Alamou, E. Modèle hydrologique basé sur le principe de moindre action (MODHYPMA). Annales des Sciences Agronomiques du Bénin 2010, 13 (1), 23-45.
[27] Biao, I. E.; Gaba, C.; Alamou, A. E.; Afouda, A. Influence of the uncertainties related to the Random Component of Rainfall Inflow in the Oueme River Basin (Benin, West Africa). International Journal of Current Engineering and Technology 2015. Vol 3, N°3.
[28] Gaba, O. U. C.; Biao, I. E.; Alamou, A. E.; Afouda, A. An Ensemble Approach Modelling to Assess Water Resources in the Mékrou Basin, Benin. Hydrology 2015, vol 3, No 2, pp 22-32, doi: 10.11648/j.hyd.20150302.11.
[29] Duncan, T.; Hu, Y.; Pasik-Duncan, B. Stochastic calculus for fractional Brownian motion I. theory. SIAM J. Control Optim 2000. N0 2, 582–612.
Cite This Article
  • APA Style

    Eliezer Iboukoun Biao, Eric Adechina Alamou. (2017). Influence of the Long-Range Dependence in Rainfall in Modelling Oueme River Basin (Benin, West Africa). American Journal of Biological and Environmental Statistics, 2(4), 50-59. https://doi.org/10.11648/j.ajbes.20160204.15

    Copy | Download

    ACS Style

    Eliezer Iboukoun Biao; Eric Adechina Alamou. Influence of the Long-Range Dependence in Rainfall in Modelling Oueme River Basin (Benin, West Africa). Am. J. Biol. Environ. Stat. 2017, 2(4), 50-59. doi: 10.11648/j.ajbes.20160204.15

    Copy | Download

    AMA Style

    Eliezer Iboukoun Biao, Eric Adechina Alamou. Influence of the Long-Range Dependence in Rainfall in Modelling Oueme River Basin (Benin, West Africa). Am J Biol Environ Stat. 2017;2(4):50-59. doi: 10.11648/j.ajbes.20160204.15

    Copy | Download

  • @article{10.11648/j.ajbes.20160204.15,
      author = {Eliezer Iboukoun Biao and Eric Adechina Alamou},
      title = {Influence of the Long-Range Dependence in Rainfall in Modelling Oueme River Basin (Benin, West Africa)},
      journal = {American Journal of Biological and Environmental Statistics},
      volume = {2},
      number = {4},
      pages = {50-59},
      doi = {10.11648/j.ajbes.20160204.15},
      url = {https://doi.org/10.11648/j.ajbes.20160204.15},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajbes.20160204.15},
      abstract = {Nowadays, there is evidence that hydrological processes exhibit long-range dependence (LRD), i.e. power-type decay of autocorrelation also known as the Hurst phenomenon. This means that the stationarity assumption of hydrological time series, which has been widely used in the past, cannot be further advocated. The objective of this paper is to detect the long-range dependence in rainfall in Oueme River basin and to understand how the Hurst coefficient influences the river discharge dynamics. To this end, this paper formulated the Hurst phenomenon that characterized hydrological and other geophysical time series. Then, the fractional generalization of the triple relationship between the fractional Brownian motion, the corresponding stochastic differential equations (SDE) describing the river basin and the deterministic fractional Fokker-Planck equations (FPE) is analysed for the modelling of the river discharge dynamics. This fractional FPE provides an essential tool for the study of the dynamics of the river discharge in Oueme River basin.},
     year = {2017}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Influence of the Long-Range Dependence in Rainfall in Modelling Oueme River Basin (Benin, West Africa)
    AU  - Eliezer Iboukoun Biao
    AU  - Eric Adechina Alamou
    Y1  - 2017/01/23
    PY  - 2017
    N1  - https://doi.org/10.11648/j.ajbes.20160204.15
    DO  - 10.11648/j.ajbes.20160204.15
    T2  - American Journal of Biological and Environmental Statistics
    JF  - American Journal of Biological and Environmental Statistics
    JO  - American Journal of Biological and Environmental Statistics
    SP  - 50
    EP  - 59
    PB  - Science Publishing Group
    SN  - 2471-979X
    UR  - https://doi.org/10.11648/j.ajbes.20160204.15
    AB  - Nowadays, there is evidence that hydrological processes exhibit long-range dependence (LRD), i.e. power-type decay of autocorrelation also known as the Hurst phenomenon. This means that the stationarity assumption of hydrological time series, which has been widely used in the past, cannot be further advocated. The objective of this paper is to detect the long-range dependence in rainfall in Oueme River basin and to understand how the Hurst coefficient influences the river discharge dynamics. To this end, this paper formulated the Hurst phenomenon that characterized hydrological and other geophysical time series. Then, the fractional generalization of the triple relationship between the fractional Brownian motion, the corresponding stochastic differential equations (SDE) describing the river basin and the deterministic fractional Fokker-Planck equations (FPE) is analysed for the modelling of the river discharge dynamics. This fractional FPE provides an essential tool for the study of the dynamics of the river discharge in Oueme River basin.
    VL  - 2
    IS  - 4
    ER  - 

    Copy | Download

Author Information
  • West African Science Service Center on Climate Change and Adapted Land Use, GRP Water Resources, University of Abomey-Calavi, Abomey-Calavi, Benin

  • Laboratory of Applied Hydrology, National Water Institute, University of Abomey-Calavi, Abomey-Calavi, Benin

  • Sections