Flood forecasting using quantitative precipitation forecasts and hydrological modeling in the Sebeya catchment, Rwanda
The absence of a viable flood early warning system for the Sebeya River catchment continues to impede government efforts towards improving community preparedness, the reduction of flood impacts and relief. This paper reports on a recent study that used satellite data, quantitative precipitation fore...
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| Autores principales: | , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
IWA Publishing
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/fc6d8a58e36440c99a51fd1d72a834f6 |
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| Sumario: | The absence of a viable flood early warning system for the Sebeya River catchment continues to impede government efforts towards improving community preparedness, the reduction of flood impacts and relief. This paper reports on a recent study that used satellite data, quantitative precipitation forecasts and the rainfall–runoff model for short-term flood forecasting in the Sebeya catchment. The global precipitation measurement product was used as a satellite rainfall product for model calibration and validation and forecasted European Centre Medium-Range Weather Forecasts (ECMWF) rainfall products were evaluated to forecast flood. Model performance was evaluated by the visual examination of simulated hydrographs, observed hydrographs and a number of performance indicators. The real-time flow forecast assessment was conducted with respect to three different flood warning threshold levels for a 3–24-h lead time. The result for a 3-h lead time showed 72% of hits, 7.5% of false alarms and 9.5% of missed forecasts. The number of hits decreased, as the lead time increased. This study did not consider the uncertainties in observed data, and this can influence the model performance. This work provides a base for future studies to establish a viable flood early warning system in the study area and beyond. HIGHLIGHTS
Potential of the Hydrologiska Byråns Vattenbalansavdelning model for flood forecasting in the Sebeya catchment.;
Evaluation of European Centre Medium-Range Weather Forecasts (ECMWF) rainfall data.;
Graphical evaluation of flood forecasts based on the ECMWF.;
Categorical statistics indicated that the probability of detection was high for a short lead time, showing that a short lead-time forecast gives a higher skill score than forecasts for a longer lead time.; |
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