Forecasts of 10-day average inflow into the Ertan hydropower station of the Yalong river basin are needed for seasonal hydropower operation. Medium-range inflow forecasts have usually been obtained by Auto-Regressive-Moving-Average (ARMA) models, which do not utilize any precipitation forecasts. This paper presents a simple GFS-QPFs-based rainfall - runoff model (GRR) using the 10-day accumulated Quantitative Precipitation Forecasts from the Global Forecast System (GFS-QPFs) run at the American National Oceanic and Atmospheric Administration (NOAA). In this study, 10-day accumulated GFS-QPFs over the Yalong river basin are verified by first using a three-category contingency table. Then this paper presents the results from a proposed hydrological model using 10-day accumulated GFS-QPFs. Results show that inflow forecast errors can be reduced considerably, compared with those from the currently used ARMA model by both quantitative and qualitative analysis. Finally, simulations of medium-range hydropower operation are also presented using the historical data and forecasts of 10-day average inflows into the Ertan dam during May to September 2006 to evaluate the efficiency of the proposed hydrological model using the GFS-QPFs. The simulations demonstrate that the use of GFS-QPFs has improved reservoir inflow predictions and hydropower operation of the Ertan hydropower station in the Yalong river basin during the wet season.
Evaluation of precipitation forecasts from NOAA global forecast system in hydropower operation
Huicheng Zhou, Guolei Tang, Ningning Li, Feng Wang, Yajun Wang, Deping Jian; Evaluation of precipitation forecasts from NOAA global forecast system in hydropower operation. Journal of Hydroinformatics 1 January 2011; 13 (1): 81–95. doi: https://doi.org/10.2166/hydro.2010.005
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