Abstract:
Rainfall-run off models have become accepted as important tools in operational
hydrology for estimating information required for water resources planning, design, and
operation. Specifically, rainfall-runoff models are normally useful tools where data are
insufficient by simulating and by extending the time series.
This thesis work presents an appraisal study to compare the performance of four
hydrological models in RVZ- Nyabiraba catchment for Ruvubu river basin and to select
the best candidate model for the catchment response prediction.
In this appr a isal study, to achieve our objective 2 empirical models: Simple Linear
· Model (SLM), Linear Perturbation Model (LPM), and 2 conceptual models: (HBV) and
Soil Moistur e Accounting and Routing (SMAR) were tested in Ruvyironza-Nyabiraba
catchment.
Parameter optimization is carried out by trial and error, ordinary least squares,
Rosenbrok. Simplex and generic algorithm. The parameter set that gave the best
objective function -value over the calibration period in the ranges of the parameters was
used for validation; The visual comparisons were also made for the low and high flow fit
of the hydrographs. The comparison was also made on the basis of the relative errorof
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peak (R E) criteria and the i?dex of volumetric fit (IVF).
From the models comparison performance criteria, it is shown that the Simple line ar
model ( SL M) and HBV are not adequate in modelli ng t�e rainfall runoff transformation.
However , th e RVZ- Nyabiraba catchments exhibit marked seasonal behaviour and good
resul t s was also obtained with Linear Perturbation model (LPM) which involves the
ass u mption o f linearity between the departures from seasonal expectations in input and
out put seri es . Within the range (0.5 - 0 . 9) of the tested models performance, in the RVZ
Nyabiraba c atc hment , out of the four models, SMAR was found to be the best candidate
model th at can sim u late the flows. Hence, SMAR is adequate in modelling the rainfall
runoff tran sformation. Further investigation should be made to generalize the
app lic a bili t y of this model to all Ruvubu river basins.
