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Volume 22, issue 1 | Copyright
Hydrol. Earth Syst. Sci., 22, 853-870, 2018
https://doi.org/10.5194/hess-22-853-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 01 Feb 2018

Research article | 01 Feb 2018

Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas

María Carolina Rogelis1 and Micha Werner1,2 María Carolina Rogelis and Micha Werner
  • 1UNESCO-IHE, P.O. Box 3015, 2601 DA Delft, the Netherlands
  • 2Deltares, P.O. Box 177, 2600 MH Delft, the Netherlands

Abstract. Numerical weather prediction (NWP) models are fundamental to extend forecast lead times beyond the concentration time of a watershed. Particularly for flash flood forecasting in tropical mountainous watersheds, forecast precipitation is required to provide timely warnings. This paper aims to assess the potential of NWP for flood early warning purposes, and the possible improvement that bias correction can provide, in a tropical mountainous area. The paper focuses on the comparison of streamflows obtained from the post-processed precipitation forecasts, particularly the comparison of ensemble forecasts and their potential in providing skilful flood forecasts. The Weather Research and Forecasting (WRF) model is used to produce precipitation forecasts that are post-processed and used to drive a hydrologic model. Discharge forecasts obtained from the hydrological model are used to assess the skill of the WRF model. The results show that post-processed WRF precipitation adds value to the flood early warning system when compared to zero-precipitation forecasts, although the precipitation forecast used in this analysis showed little added value when compared to climatology. However, the reduction of biases obtained from the post-processed ensembles show the potential of this method and model to provide usable precipitation forecasts in tropical mountainous watersheds. The need for more detailed evaluation of the WRF model in the study area is highlighted, particularly the identification of the most suitable parameterisation, due to the inability of the model to adequately represent the convective precipitation found in the study area.

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Numerical weather prediction (NWP) models are fundamental for flood early warning, particularly in tropical mountainous watersheds. This paper aims to assess the potential of NWP for flood early warning purposes, and the possible improvement that the post-processing of forecasts can provide, in a tropical mountainous area. The results show the potential of NWP but also the need for more detailed evaluation of the meteorological model in the study area.
Numerical weather prediction (NWP) models are fundamental for flood early warning, particularly...
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