Forecasting Seasonal Stream Flow in Athi River Basin Using Global and Regional Climate Predictors
Abstract
Extreme weather events are associated with floods and drought which affect
infrastructure, food security, water availability, sanitation and hydro power
generation. The Athi river basin is prone to such extreme weather events. This study
examines the spatial and temporal hydrological characteristics of the Athi river basin, their
teleconnections with EI Nino/Southern Oscillation (ENSO) and the Indian Ocean Dipole
(lOD) and assesses the potential use of derived teleconnections for stream flow
forecasting. The Principal Component analysis (PCA) method was used to design the
minimum rainfall and stream flow networks for the basin. Spatial and temporal PCA
modes were used to study the spatial characteristics of seasonal rainfall and stream flow.
Trends were studied using graphical and Spearman rank correlation methods while
periodicity was investigated using wavelet analysis. PCA and composite analysis were
used to map linkages among extreme seasonal rainfall/stream flow patterns and ENSO
and [00 evolution phases for the 'long' and 'short' rainy seasons. Simple linear
correlation and Canonical Correlation Analysis (CCA) were used to delineate interlinkages
among rainfall, stream flow, ENSO and lOD. The potential of deriving seasonal
rainfall and stream flow forecasts was investigated using the step-wise regression and the
non-parametric seasonal forecasting (NSFM) models. PCA delineated the Athi river basin
into six rainfall and three streamflow homogenous zones. The spatial characteristics of
seasonal rainfall and streamflow showed a strong influence of the Inter Tropical
Convergence Zone (lTCZ), land sea mesoscale circulation system, orography and land use
systems. The PCA based areal rainfall and streamflow indices and communality analysis
were used to determine the best representative stations for the homogenous zones. PCA
(T-mode) delineated most of the wet /high flow and dry/low flow years observed from
historical records including 1997/1984 which are some of the wettest/driest years on
record in the basin. Although, the results showed significant rainfall and stream flow
trends at some locations, it was difficuIt to associate the observed trends to climate
change, due to limited data length. Wavelet analyses showed significant peaks centered at
2-3, 5-7 and 10-12 years which may be associated with Quasi-Biennial Oscillation,
ENSO, solar cycles and decadal variability modes. Linkages between various modes of
ENSO were also delineated including "El Nino Modoki" which is a manifestation
of EI Nino associated with dry instead of the normal wet conditions in the basin.
Strong linkages of seasonal rainfall and stream flow with ENSO and 10D phases with
time lags of 7-9 months and lag correlations of 0.8 - 0.9 were obtained. The composite
results indicated that the wet/high flow and dry/low flow conditions in the basin
could be associated with the evolution of ENSO and IOD phases. CCA method
delineated the major Indian Ocean Sea Surface Temperature (SST) modes, which
are associated with extreme March-May and September-November seasonal rainfall
and streamflow. Regression and NSFM models showed good predictions skills for
low and high flows using ENSO and IOD predictors. The results of this study
provide tools for prediction, early warning of the extremes episodes, management,
planning and operation of water resources systems.