Abstract
Abstract. Hydrological models play an important role in water resources management.
These models generally rely on discharge data for calibration. Discharge time
series are normally derived from observed water levels by using a rating
curve. However, this method suffers from many uncertainties due to
insufficient observations, inadequate rating curve fitting procedures, rating
curve extrapolation, and temporal changes in the river geometry.
Unfortunately, this problem is prominent in many African river basins. In
this study, an alternative calibration method is presented using water-level
time series instead of discharge, applied to a semi-distributed rainfall-runoff model for the semi-arid and poorly gauged Mara River basin in Kenya.
The modelled discharges were converted into water levels using the
Strickler–Manning formula. This method produces an additional model output; this is a
“geometric rating curve equation” that relates the modelled discharge to
the observed water level using the Strickler–Manning formula and a calibrated
slope-roughness parameter. This procedure resulted in good and consistent
model results during calibration and validation. The hydrological model was
able to reproduce the water levels for the entire basin as well as for the
Nyangores sub-catchment in the north. The newly derived geometric rating
curves were subsequently compared to the existing rating curves. At the
catchment outlet of the Mara, these differed significantly, most likely due
to uncertainties in the recorded discharge time series. However, at the
“Nyangores” sub-catchment, the geometric and recorded discharge were almost
identical. In conclusion, the results obtained for the Mara River basin
illustrate that with the proposed calibration method, the water-level time
series can be simulated well, and that the discharge-water-level
relation can also be derived, even in catchments with uncertain or lacking rating
curve information.
Subject
General Earth and Planetary Sciences,General Engineering,General Environmental Science
Cited by
9 articles.
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