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Water 2018, 10(1), 56; doi:10.3390/w10010056

High-Resolution Discharge Forecasting for Snowmelt and Rainfall Mixed Events

Department of Geoinformatics, Faculty of Electronics, Telecommunication and Informatics, Gdansk University of Technology, Gabriela Narutowicza 11/12, 80-233 Gdansk, Poland
Author to whom correspondence should be addressed.
Received: 23 November 2017 / Revised: 22 December 2017 / Accepted: 3 January 2018 / Published: 10 January 2018
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Discharge events induced by mixture of snowmelt and rainfall are strongly nonlinear due to consequences of rain-on-snow phenomena and snowmelt dependence on energy balance. However, they received relatively little attention, especially in high-resolution discharge forecasting. In this study, we use Random Forests models for 24 h discharge forecasting in 1 h resolution in a 105.9 km 2 urbanized catchment in NE Poland: Biala River. The forcing data are delivered by Weather Research and Forecasting (WRF) model in 1 h temporal and 4 × 4 km spatial resolutions. The discharge forecasting models are set in two scenarios with snowmelt and rainfall and rainfall only predictors in order to highlight the effect of snowmelt on the results (both scenarios use also pre-forecast discharge based predictors). We show that inclusion of snowmelt decrease the forecast errors for longer forecasts’ lead times. Moreover, importance of discharge based predictors is higher in the rainfall only models then in the snowmelt and rainfall models. We conclude that the role of snowmelt for discharge forecasting in mixed snowmelt and rainfall environments is in accounting for nonlinear physical processes, such as initial wetting and rain on snow, which cannot be properly modelled by rainfall only. View Full-Text
Keywords: discharge forecasting; WRF; numerical weather forecasting; urbanized catchment; snowmelt; rainfall; random forests discharge forecasting; WRF; numerical weather forecasting; urbanized catchment; snowmelt; rainfall; random forests

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Berezowski, T.; Chybicki, A. High-Resolution Discharge Forecasting for Snowmelt and Rainfall Mixed Events. Water 2018, 10, 56.

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