摘要
This paper presents the characteristics of sediment transport by flood in the Lower Yellow River with the reach from Huayuankou to Gaocun, which is regarded as a typical braided pattern. The Artificial Neural Network Model on Water Use for Sediment Transport (WUST) by flood was established based on the measured data from 1980 to 1998. Consequently, simulations of controlling process of sediment transport by flood were made in terms of the control theory under different scenarios. According to the situation of sediment transport by flood in the Lower Yellow River, Open-Loop control system and feedback control system were adopted in system design. In the Open-Loop control system, numerical simulations were made to reveal the relationship between average discharge of flood and the WUST with varying sediment concentrations. The results demonstrate that sediment concentration has significant influence on the controlling process of flood flow to WUST. It is practical and efficient to control WUST if sediment concentration is less than 20 kg/m3. In the feedback control system, controlling processes of sediment concentration and flood discharge for sediment transport were simulated respectively under given conditions, and it was found that sediment transport process could be controlled completely by sediment concentration and discharge at the inlet of the reach from Huayuankou to Gaocun. Using the same method, controlling processes of sediment transport by flood in other reaches in the Lower Yellow River were also simulated. For the case of sediment concentration being 20 kg/m3, the optimized controlling discharge ranges from 2390 to 2900 m3/s in the lower reach of Huayuankou. This study is also of significance to flood control and flushing sediment in the Lower Yellow River with proper operation modes of Xiaolangdi Reservoir.
This paper presents the characteristics of sediment transport by flood in the Lower Yellow River with the reach from Huayuankou to Gaocun, which is regarded as a typical braided pattern. The Artificial Neural Network Model on Water Use for Sediment Transport (WUST) by flood was established based on the measured data from 1980 to 1998. Consequently, simulations of controlling process of sediment transport by flood were made in terms of the control theory under different scenarios. According to the situation of sediment transport by flood in the Lower Yellow River, Open-Loop control system and feedback control system were adopted in system design. In the Open-Loop control system, numerical simulations were made to reveal the relationship between average discharge of flood and the WUST with varying sediment concentrations. The results demonstrate that sediment concentration has significant influence on the controlling process of flood flow to WUST. It is practical and efficient to control WUST if sediment concentration is less than 20 kg/m3. In the feedback control system, controlling processes of sediment concentration and flood discharge for sediment transport were simulated respectively under given conditions, and it was found that sediment transport process could be controlled completely by sediment concentration and discharge at the inlet of the reach from Huayuankou to Gaocun. Using the same method, controlling processes of sediment transport by flood in other reaches in the Lower Yellow River were also simulated. For the case of sediment concentration being 20 kg/m3, the optimized controlling discharge ranges from 2390 to 2900 m3/s in the lower reach of Huayuankou. This study is also of significance to flood control and flushing sediment in the Lower Yellow River with proper operation modes of Xiaolangdi Reservoir.
作者
NI Jinren1, LIU Xiaoyong2, LI Tianhong1, ZHAO Ye’an3 & JIN Ling1 1. Department of Environmental Engineering, Peking University
The Key Laboratory of Water and Sedi- ment Sciences, Ministry of Education, Beijing 100871, China
2. General Institute of Water Resources and Hydropower Planning and Design, Ministry of Water Re- sources, Beijing 100011, China
3. The Yellow River Conservancy Commission, Zhengzhou 450003, China
作者简介
Correspondence should be addressed to Ni Jinren (email: nijinren@iee.pku.edu.cn)
