Generalized Weng Cycle Model of Mid-long Term Prediction of Run-off in Stream
Owing to the impact of various factors (such as climate, topography changes, human activities)on hydrology regime, run-off forecast is a complex subject in the field of the study of hydrology and water resources, gaining lower forecast accuracy as a disappoint result. Therefore, seeking a prediction model which can be used to describe a non-stationary random process of the run-off and be more accurate to analyze the changing discipline of runoff in this field is a hot issue recently. In the context of increasing water crisis, the Generalized Weng Cycle Model is applied to stream flow prediction. Using variable dimension fractal, the model is solved. The applicability of the model is analyzed for its application to stream flow prediction. Then Generalized Weng Cycle Model is employed in stream flow prediction at Guide station on the upper reaches of the Yellow River. Comparing with the WCM and the BP neural network model, the GWCM is more precise and effective in stream flow prediction. Besides, the runoff serials which is obtained by the GWCM has a good homogeneity with the one of natural runoff. Finally, further researches of the GWCM are presented.
generalized cycle Weng model flow prediction fractal method Guide station
Bai Tao Huang Qiang Wei Jing Cao Hui
Xian University of Technology Water Resources Institute, Xian, 710048, China Zhejiang Design Institute of Water Conservancy & Hydro - Electric Power, Hangzhou, 310002, China
国际会议
郑州
英文
1454-1458
2009-10-20（万方平台首次上网日期，不代表论文的发表时间）