COI code: ICSAU05_0346
Paper Language: English
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Authors Evaluation of the precipitation contribution in monitoring the ensemble real time flood forecastingAida Jabbri - Department of Civil & Environmental Engineering, Sejong University, Seoul, South Korea.
Deg-Hyo Bae - Professor, Department of Civil & Environmental Engineering, Sejong University, Seoul, South Korea.
Abstract:This study evaluates the effects of the precipitation of a Numerical Weather Prediction (NWP) model in coupled meteo-hydrological models for real time flood forecasting. The present study includes details concerning the point and catchment analysis of the precipitation in a real time forecast system. The NWP model with a lead time of 72hr, temporal resolution of 10min and spatial resolution of 1km×1km and a rainfall runoff model employed to evaluate the real time flood forecasting on Imjin river which passes through South and North Korea. The skill of the model was relatively higher for the catchment precipitation analysis rather than the point precipitation evaluation as illustrated by lower Root Mean Square Error (RMSE). The results of time series comparison between simulated, observed and forecasted flows indicated that the amplitudes of the peaks are noticeably different in coupled results due to the increased errors.
Keywords:Flood forecasting, Meteo-hydrological model, NWP, Real time, precipitation
COI code: ICSAU05_0346
how to cite to this paper:If you want to refer to this article in your research, you can easily use the following in the resources and references section:
Jabbri, Aida & Deg-Hyo Bae, 2017, Evaluation of the precipitation contribution in monitoring the ensemble real time flood forecasting, 5th international congress of structure, architecture and urban development, تهران, دبيرخانه دايمي كنفرانس, https://www.civilica.com/Paper-ICSAU05-ICSAU05_0346.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Jabbri, Aida & Deg-Hyo Bae, 2017)
Second and more: (Jabbri & Bae, 2017)
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