周惠成

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

扫描关注

论文成果

当前位置: 中文主页 >> 科学研究 >> 论文成果

Evaluation of precipitation forecasts from NOAA global forecast system in hydropower operation

点击次数:

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.