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Discussion papers | Copyright
https://doi.org/10.5194/hess-2017-661
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Cutting-edge case studies 23 Nov 2017

Cutting-edge case studies | 23 Nov 2017

Review status
This discussion paper is a preprint. A revision of this manuscript was accepted for the journal Hydrology and Earth System Sciences (HESS) and is expected to appear here in due course.

Modelling the Mara River Basin with data uncertainty using water levels for calibration

Petra Hulsman, Thom A. Bogaard, and Hubert H. G. Savenije Petra Hulsman et al.
  • Water Resources Section, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628 CN Delft, the Netherlands

Abstract. Hydrological models play an important role in Water Resources Management. In hydrological modelling, discharge data is generally required for calibration. To obtain continuous time series, water levels are usually converted into discharge by using a rating curve. However with this methodology, uncertainties are introduced in the discharge data due to insufficient observations, inadequate rating curve fitting procedures, extrapolation or temporal changes in the river geometry. Unfortunately, this is often the case in many African river basins. In this study, a semi-distributed rainfall runoff model has been applied to the Mara River Basin for the assessment of the water availability. To reduce the effect of discharge uncertainties in this model, water levels instead of discharge time series were used for calibration. In this model, seven sub-catchments are distinguished and four hydrological response units: forest, shrubs, cropland and grassland. To calibrate the model on water level data, modelled discharges have been converted into water levels using cross-section observations and the Strickler formula. In addition, new geometric rating curves have been obtained based on modelled discharge, observed water level and the Strickler formula. This procedure resulted in good and consistent model results during calibration and validation. The hydrological model was able to reproduce the water depths for the entire basin as well as for the Nyangores sub-catchment in the north. The geometric and recorded (i.e. existing) rating curves were significantly different at Mines, the catchment outlet, probably due to uncertainties in the recorded discharge time series. At Nyangores however, the geometric and recorded discharge were almost identical. In addition, it has been found that the precipitation estimation methodology influenced the model results significantly. Application of a single station for each sub-catchment resulted in flashier responses whereas Thiessen averaged precipitation resulted in more dampened responses. In conclusion, by using water level time series for calibrating the hydrological model of the Mara River Basin promising model results were obtained. For this river basin, the main limitation for obtaining an accurate hydrograph representation was the inadequate knowledge on the spatial distribution of the precipitation.

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Short summary
The prediction of flows for the Mara River in Kenya is challenged due to poor data availability and quality. This concerns precipitation, but also the discharge data which are both crucial for reliable flow predictions. As the water level time series were more reliable, these were used instead of discharge to develop a model that simulates the river flows. Also, the influence of poor precipitation data quality on the flow predictions was assessed for this specific case study.
The prediction of flows for the Mara River in Kenya is challenged due to poor data availability...
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