Abstract:
Perturbations in hydrologic time series have recently been witnessed in many parts of
the world and knowledge of their occurrence is of great socio-economic significance.
Various statistical techniques have been used in the past to analyse hydro-climatic
series without revealing important frequency information. The main objective of this
study was to analyse the trend, periodicity and frequency of the hydrometeorological
time series for Nyando River basin. The specific objectives were to: determine trends
investigate periodicity and determine the optimum probability distribution in rainfall
and streamflow time series. Rainfall data of lengths ranging from of 41 - 100 years were
obtained from Water Resources Authority, Kenya Meteorological Department and
Finlay Kenya Limited. Streamflow data of lengths ranging from 45 – 60 years were
obtained from Water Resources Authority. The datasets were first tested for
homogeneity, normality and independence. This study used Wavelet Transform (WT)
method in addition to Mann-Kendall (M-K) and Fourier Transform (FT) to investigate
the rainfall and streamflow trend and periodicity in the basin. In trend detection, M-K
computed the z-statistical values and declared trend or no trend at 95% confidence
interval, while WT detected the peaks and disclosed the time-frequency information for
the trends. Further, FT and WT techniques were used to estimate the power spectrum
and to reveal the periodicities. To obtain the probability distributions, L-moment
diagrams were generated to compare the L-skewness verses L-kurtosis relations of
different distributions. The closest relationships were further confirmed using
goodness-of-fit tests. The M-K results revealed minimal trend in rainfall but showed an
overall increasing trend in streamflow. WT revealed overall increasing trends for both
rainfall and streamflow. The dominant rainfall and streamflow periodicities were
determined at 2-7 years, 2.7-3.3 years, 3.5-4 years, 5.6-6.5 years and 7-8 years. Based
on the results, this study concluded that the Nyando River basin rainfall and streamflow
exhibited increasing trends with periodic cycles over the last thirty years. Further, the
study found that PE3 provides good approximation to the annual maximum floods in
the basin. The study recommends that PE3 could be adopted for estimating the return
periods of floods in the design of hydraulic structures for the Nyando River basin.
Similar studies can be applied in other River basins in Kenya to determine the optimal
probability distributions for the analysis of extreme rainfall and streamflow.
