Abstract
The multifractal spectrum, f(α), was estimated for hourly rainfall records of 47 gauges located at the tropical Andes of Colombia using five different methodologies. All of these methodologies were applied to binomial measures, which have a well known theoretical multifractal spectrum. From the results, it is possible to conclude the following: (i) all methodologies have satisfactory results in the estimation of f(α) for the synthetic binomial measures (ii) the five methodologies showed different estimations for the rainfall time series spectrum; (iii) the multifractal strength, Δα, showed a wide range of values, varying from 0.66 to 7.4 (iv) the Renyi exponent, T(q), could be represented by a simple two-parameter model, which is based on a generalized version of the multiplicative cascade model; and (v) no clear relationship between the parameters used in this research and elevation was found. Finally, a discussion about the characteristics of the models and problems in the spectrum estimation for hourly time series is presented.
Keywords
References
Adeli, H. & S. L. Hung (1995), Machine learning. Neural networks, genetic algorithms and fuzzy systems, .John Wiley and Sons, Canada.
Agudelo P., P. Arias, & L. Salazar (2001), Caracterización del ciclo diurno de precipitación en los Andes tropicales de Colombia. Región Centro, Tesis Ingeniería Civil, Universidad Nacional de Colombia, Facultad de Minas.
Álvarez, F. & V. Toro (2001), Caracterización del ciclo diurno de precipitación en los Andes tropicales de Colombia. Región Sur, Tesis Ingeniería Civil, Universidad Nacional de Colombia, Facultad de Minas.
Barnsley, M.F. (1993), Fractals Everywhere, 2nd ed., Academic Press, San Diego.
Billingsley, P. (1965), In Ergodic Theory and Information, Wiley, New York.
Braun, E. (1996), Caos, fractales y cosas raras. Fondo de Cultura Económica, México.
Chhabra, A. & R. Jensen (1989), Direct determination of the f singularity spectrum, Physical Review Letters, 62{12), 1372-1330.
Sreenivasan (1989), Direct determination of the f singularity spectrum and its applications to fully developed turbulence, Physical Review A, 40(9), 5284-5294.
Chorin, A. (1994), Vorticity and Turbulence, Springer Verlag, New York.
Courant R. & D. Hilbert (1953), Methods of Mathemat ical Physics, Vol. 1, Interscience Publishers, New York.
de Lima M. l. P & J. Grasman (1999), Multifractal anal ysis of 15-min and daily rainfall from a semi-arid region in Portugal. Journal of Hydrology, 220, 1-11.
Douglas, E. M. & A. P. Barros (2003), Probable maximum precipitation estimation using multifractals: Application in the eastern United States, Journal of Hidrome teorology, 1012-1024.
Flores, C. (2004), Multiplicative casca.de rnodels for rain in hydro-meteorological disasters risk management, ASTINKolloquium, Bergen, Norway.
Grassberger, P., R. Badii, & A. Politi, (1988), Scaling aws for invariant measures on hyperbolic and nonhyper bolic atractors, Physics and Astronomy, 51, 135 -178.
Gupta V. K. & E. Waymire (1993), A statistical analysis of rnesoscale rainfall as a random cascade. Journal of Applied Meteorology, 32, 251-267.
Harris, D., M. Menabde, A. Seed & G. Austin (1996), Multifractal characterization of rain fields with a strong orographic influence, Jo·urnal of Geophysical Research, D21. 101, 405-26.
Kantelhardt, J. W., D. Rybsky, S. Zschiegner, P. Braun, E. Koscielny-Bunde, V. Livina, S. Havlin, & A. Bunde (200:3), Multifractality of river runoff and precipitation: comparison of fluctuation analysis and wavelet rnethods, Physica A, 330, 240-245.
Koscielny-Bunde, E., J. Kantelhardt, P. Braun, A. Bunde, & S. Havlin (2006), Long-term persistence and multifractality of river runoff records: Detrended fluctuation studies, Journal of Hydrology, 322 {1--4), 120-137.
Mandelbrot, B. (1989), Multifractal mea.sures especially for the geophysicist, PAGEOPH, 131(12), 38. Mandelbrot, B. (1990), Negative fractal dimensions and multifractals, Physica A, 163, 10.
Mandelbrot, B. (2003), Multifractal power law distributions: Negative and critica! dimensions and other anomalies, explained by a simple example, Journal of Statistical Physics, 11 O, 739 -77 4.
Mesa O. J.& Poveda G. (1993), The Hurst effect: The scale of fluctuation approach, Water Resources Research, 29, 3995-4002.
Mesa O., G. Poveda & L. Carvajal (1997), Introducción al Clima de Colomb-ia. Universidad Nacional de Colombia, Facultad de Minas.
Montgomery, D. & G. Runger (1996), Probabilidad y estadística aplicadas a la ingeniería, McGraw-Hill, Mexico. p, 1000.
Moreno, H. & G. Poveda (2004), Colas pesadas en el análisis probabilistico de la lluvia y exponente de Hurst durante las fases del ENSO, XVI Seminario Nacional de Hidráulica e Hidrología.
Olsson, J. (1995), Limits and characteristics of the multifractal behavior of a high-resolution rainfall time series, Nonlinear Processes in Geophysics, 2, 23--29.
Olsson, J. & J. Niemczynowicz (1996), Multifractal analysis of daily spatial rainfall distributions, J. Hydrol. 187, 29-43.
Ott, E., W. D. Withers, & J. A. Yorke, (1984), Is the dimension of chaotic attractors invariant under coordinate hanges?, Journal of Statistical Physics, 36, 687-697.
Peitgen, H., H. Jürgens, & D. Saupe (1992), Chaos and Fractals New Frontiers of Science ( Appendix B. Multifractal Measures), Hamilton Printing Co., Ncw York.
Poveda, G., O. Mesa, L. Salazar, P. Arias, H. Moreno, S. Viera, P. Agudelo, V. Toro, & J. Álvarez (2005), Thc diurna! cycle of prccipitation in thc tropical Andes of Colombia, M onthly W eather Review, 133, 228-240.
Schertzer, D. & S. Lovejoy (1996), Notes and correspondence. universal multifractals do exist!: Comments on statistical analysis of mcsoscale rainfall as a random cascadc, Journal of Applied Meteorology 136, 1296-1303.
Schertzer, D., P. Hubert & S. Lovejoy (2003), Scaling, Multifractals and Predictions in Ungaged Basins: Wherc We'vc Been, Where We're Going?, in Prediction of Ungauged Basins, An IAHS Initiative, Eds. P. Hubert et al. , IAHS Press, Wallingford UK.
Schertzer, D., S. Lovejoy, F. Schmitt, Y. Chigirinskaya, & D. Marsan (1997), Multifractal cascade dynamics and turbulent intermittency. Fractals, 5, 427-471.
Seuront, L., F. Schmitt, Y. Lagadeuc, D. Schertzer & S. Lovejoy (1999), Universal Multifractal Analysis as a too! to characterize multiscale intermittent patterns: example of phytoplankton distribution in turbulcnt coastal waters, Journal of Plankton Research, 21, 877-922.
Sivakumar, B. (2001), Is a chaotic multi-fractal approach for rainfall possible?, Hydrological Processes, 15, 943--955.
Svensson, C., J. Olsson & R. Berndtsson (1996), Multifractal properties of daily rainfall in two different climates, Water Resources Research, 32, 2463-2472.
Tessier, Y., S. Lovejoy, & D. Schertzer (1993), Universal multifractals: Theory and observations for rain and clouds, Journal of Applied Meteorology, 223-250.
Vieira S. & H. Moreno (2001), Caracterizaóón del ciclo dforno de precipitación en los Andes tropicales de Colombia. Región Sur, Tesis Ingeniería Civil, Universidad Nacional de Colombia, Facultad de Minas.
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