Journal metrics
Journal metrics
IF 4.256
CiteScore 4.10
SNIP 1.412
SJR 2.023
h5-index 58
|
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
1UNESCO-IHE, P.O. Box 3015, 2601 DA Delft, the Netherlands
2Deltares, P.O. Box 177, 2600 MH Delft, the Netherlands
Received: 12 Apr 2017 – Discussion started: 19 Jun 2017
Revised: 04 Dec 2017 – Accepted: 05 Dec 2017 – Published: 01 Feb 2018
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.
Citation: Rogelis, M. C. and Werner, M.: Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas, Hydrol. Earth Syst. Sci., 22, 853-870, https://doi.org/10.5194/hess-22-853-2018, 2018.
2Deltares, P.O. Box 177, 2600 MH Delft, the Netherlands
Citation: Rogelis, M. C. and Werner, M.: Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas, Hydrol. Earth Syst. Sci., 22, 853-870, https://doi.org/10.5194/hess-22-853-2018, 2018.
