Abstract
Stochastic characteristics of the Benue River streamflow process are examined under conditions of data austerity. The streamflow process is investigated for trend, non-stationarity and seasonality for a time period of 26 years. Results of trend analyses with Mann-Kendall test show that there is no trend in the annual mean discharges. Monthly flow series examined with seasonal Kendall test indicate the presence of positive change in the trend for some months, especially the months of August, January, and February. For the stationarity test, daily and monthly flow series appear to be stationary whereas at 1%, 5%, and 10% significant levels, the stationarity alternative hypothesis is rejected for the annual flow series. Though monthly flow appears to be stationary going by this test, because of high seasonality, it could be said to exhibit periodic stationarity based on the seasonality analysis. The following conclusions are drawn: (1) There is seasonality in both the mean and variance with unimodal distribution. (2) Days with high mean also have high variance. (3) Skewness coefficients for the months within the dry season period are greater than those of the wet season period, and seasonal autocorrelations for streamflow during dry season are generally larger than those of the wet season. Precisely, they are significantly different for most of the months. (4) The autocorrelation functions estimated “over time” are greater in the absolute value for data that have not been deseasonalised but were initially normalised by logarithmic transformation only, while autocorrelation functions for i = 1, 2, ..., 365 estimated “over realisations” have their coefficients significantly different from other coefficients.
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References
Burn, D. H. and M. A. Hag Elnur, 2002, Detection of hydrologic trends and variability. Hydrology 255: 107–122.
Dickey, D. A. and W. A. Fuller, 1979. Distribution of the estimators for autoregressive time series with a unit root. J. Am. Stat. Assoc. 74: 423–431.
Gimeno, R., B. Manchado and R. Minguez, 1999. Stationarity tests for financial time Series. Physica A 269(1): 72–78.
Hirsch, R. M., J. R. Slack and R. A. Smith, 1982. Techniques of trend analysis for monthly water quality data. Water Resources Research 18(1): 107–121.
Hirsch, R. M. and J. R. Slack, 1984. A non-parametric trend test for seasonal data with serial dependence. Water Resources Research 20(6): 727–732.
Kendall, M. G, 1939. A new measure of rank correlation. Biometrika, 30: 81–93.
Kottegoda, N. T., 1980. Stochastic Water Resources Technology. The Macmillan Press Ltd, London and Basingstoke. Kurt Annen, Unit root DLL (BETA); www.web-reg.de
Lins, H. F. and J. R. Slack, 1999. Streamflow trends in Sweden 1807-2002. Hydrol. Sci. J. 49(1): 69–83.
Mann, H. B, 1945. Non-parametric test against trend. Econometrica, 13: 245–259.
Mitosek, H. T, 2000. On stochastic properties of daily river flow processes. J. Hydrology 228: 188–205.
Papoulis, A., 1965. Probability, Random Variables, and Stochastic Processes. McGraw-Hill. New York.
Salas, J. D., D. C. Boes and R. A. Smith, 1982. Estimation of ARMA Models with Seasonal Parameters. Water Resources Research 18(4): 1 006–1 010.
Said, S. E. and D. Dickey, 1984. Testing for unit roots in autoregressive moving-average models with unknown order. Biometrika, 71: 599–607.
Toro, S. M, 1997. Post construction effects of the Cameroonian Lagdao Dam on the River Benue. J. Chartered Institute, Water Environmental Management,11(2): 109–113.
Von Storch, H., 1995. Misuses of statistical analysis in climate research: In: H. V. Storch and A. Navarra (eds). Analysis of climate: Applications of Statistical Techniques. Springer-Verlag, New York. pp. 11–26.
Wang, W., P. H. A. J. M. van Gelder and J. K. Vrijing, 2005. Detection of changes in Streamflow series in Western Europe over 1901-2000. Water Sci. and Technology, Water Supply 5(6): 289–299.
Zhang, X., K. D. Harvey and R. Uzyk, 2001. Trends in Canadian streamflow. Water Resources Research 37(4): 987–998.
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Supported by the Post Graduate Research Fund from Federal Government of Nigeria under the BEA Scholarship Program (No.CSC2005566002)
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Otache, M.Y., Bakir, M. & Li, Z. Analysis of stochastic characteristics of the Benue River flow process. Chin. J. Ocean. Limnol. 26, 142–151 (2008). https://doi.org/10.1007/s00343-008-0142-0
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DOI: https://doi.org/10.1007/s00343-008-0142-0