| dc.description.abstract | Unlike any other part of Kenya, the Lake
Victoria Drainage Basin is a complicated area both in
terms of its geography and weather systems. The interplay
of geography and the meso-scale lake-induced
circulation systems, in the presence of the lower tropospheric
flows, gives rise to seasonal rainfall
regimes which have previously been variously defined.
Knowledge of the seasonal rainfall regimes that occur
in the area and some aspects of the characteristics of
rainfall in each seasonal rainfall regime is important
for water resources planning in general and for agriculture
in particular. This study was an attempt to define
and delimit the seasonal rainfall regimes of the Kenyan
part of the Lake Victoria Drainage Basin. On the basls
of the identified seasonal rainfall regimes, a few
sample stations were selected and whose data were used
to study the frequency of occurrence and distribution
of wet and dry spells of various lengths.
The seasonal rainfall regimes were determined
from a 67 x 67 inter-station correlation matrix whlch
was based on the lO-day median rainfall of each station.
The correlation matrix was subjected to Principal Components
Analysis (PCA) the outcome of which was the
extraction of 4 components (based on Kaiser's criterion
of an eigenvalue of 1.0) which explained 89.2% of the
system variance. Only the first two components showed
spatial coherence and meaning; the first and second
Varimax rotated principal components explained 50.8% ~nd
33.1% of the total variance. This led to the identifl.cation
and delineation of the "Kibos" and "Eldoret" seasonal
rainfall re~imes. At the boundaries of each
regime, there were stations that had almost equal loadings
on the first and second Principal Components ~or
seasonal rainfall regimes) These were considered
transitional areas.
An examination of the annual march of the 10-day
or "decade" rainfall for selected stations in each seasonal
rainfall regime revealed that the "Kibos" regime
is mainly bimodal, the rainy periods being March-May
and October-December; for some stations, there is a
third but relatively unimportant peak in August. The
"Eldoret regime" has two rainfall peaks falling within
a single rainy season which extends from April to
September. The transitional zones around Kakamega,
Nandi and Kericho have rainfall almost throughout the
year.
For each seasonal rainfall regime, as well as
for the transitional zones, a few stations were selected
for the study of wet and dry spells. Two criteria were
used to define a wet (and also dry) day i.e. 1.Omm and
S.Omm. The latter limit was chosen because of its
agricultural importance given that potential evapora-
tion in the study area is in the order of 4-6mm day .
For each station, for the common 30-year period (1941-
1970), a count was made with the aid of a computer
programme, of the wet and dry spells of various lengths.
From these data, it was found that the frequency of
both wet and dry spells fell off exponentially from the
shortest duration to the longest. Wet and dry spells
of short duration were more frequent in the "Kibos"
regime. The data further showed that wet spells of
longer durations were more frequent around Kericho and
Tambach. For the 1.Omm criterion, the dry spells were
longer than the wet spells except at Kakamega, Jamji
Estate, Kericho and Sotik. These data help to emphasize
the important nifferences between the main seasonal
rainfall regimes. Near the lake, rainfall tends to fall
in storms lasting anything from some minutes to a few
days, while, particularly in the "Eldoret" regime and
in the transitional areas, rainfall tends to persist
for longer durations.
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For some stations, the wet spells data were
well described by both the Markov chain and Exponential
distribution models according to the X2 goodness-of-fit
test. Only in one case did the observed dry spells
data fit the Exponential distribution model well: in
all other cases, the fit of the dry spells data to the
two models was poor.
From the cumulative frequencies of wet and dry
spells, the percentage of times a period of a given
type of weather (wet or dry) was followed by the same
type of weather was evaluated. It was found that the
probability of a type of weather recurring is higher
the longer that type of weather has persisted.
The Principal Components Analysis (PCA) method
clearly brought out the seasonal rainfall regimes
existing in the study area. The delineation of the
different seasonal rainfall regimes forms a basis for
future planning of a more representative agro- and'
hydro-climatological network in the region. From the
study of the wet and dry spells data, the spatial
contrasts in the pattern of rainfall occurrence
between the different rainfall regions were shown. This
information is important in any consideration of water
resources utilization in general, and in agriculture in
particular. | en |
