Analysis of stochastic characteristics of the Benue River flow process

Martins Y. Otache; Mohammad Bakir; Zhijia Li

doi:10.1007/s00343-008-0142-0

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Analysis of stochastic characteristics of the Benue River flow process

OriginalPaper | Updated：2023-05-16

- Analysis of stochastic characteristics of the Benue River flow process
- Analysis of stochastic characteristics of the Benue River flow process
- 海洋湖沼学报（英文） 2008年26卷第2期页码：142-151
- Affiliations：
  
  State Key Laboratory of Hydrology-Water Resources & Hydraulic Engineering Hohai University
- Author bio：
- Funds：
  
  Supported by the Post Graduate Research Fund from Federal Government of Nigeria under the BEA Scholarship Program (No.CSC2005566002)
- DOI：10.1007/s00343-008-0142-0
  中图分类号：
- 网络首发：2008-05-28，
  
  纸质出版：2008
- Accepted：
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Analysis of stochastic characteristics of the Benue River flow process[J]. 海洋湖沼学报（英文）, 2008,26(2):142-151.

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
Analysis of stochastic characteristics of the Benue River flow process[J]. 海洋湖沼学报（英文）, 2008,26(2):142-151. DOI： 10.1007/s00343-008-0142-0.

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 DOI：

摘要

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%

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

...

365 estimated “over realisations” have their coefficients significantly different from other coefficients.

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references

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