个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:水利工程系
学科:水文学及水资源. 工程管理
办公地点:实验3#-435
联系方式:电话:13804245837 QQ:2246578293 微信:dutwaterzhou
电子邮箱:hczhou@dlut.edu.cn
Evaluation of precipitation forecasts from NOAA global forecast system in hydropower operation
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论文类型:期刊论文
发表时间:2011-01-01
发表刊物:JOURNAL OF HYDROINFORMATICS
收录刊物:SCIE、Scopus
卷号:13
期号:1
页面范围:81-95
ISSN号:1464-7141
关键字:global forecast system; hydropower operation; inflow forecasting; quantitative precipitation forecasts
摘要: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.