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A Multivariate Regression Model for Flood-Peak Level Forecasting on the Lower Yellow River

Author(s): Keyan Xu; Wei Ren; Li Xie

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Keywords: Lower Yellow River; Water level; Factors causing changes; Multivariate regression

Abstract: The lower Yellow River is a wandering channel that goes through periodic water build up. As the channel is scoured and silted at irregular intervals and to different degrees, water level is often an uncertain quantity. Over the past 10 year period the lower channel has gone through intensified shrinkage which has resulted in a diminished flood carrying capacity of the channel and gradually rising water levels. According to statistics, in the year 2000, water level discharge of 3000m3/s in all river stretches downstream of Huayuankou were 2 m higher than those in 1950. Since protection of projects and operation of flood detention areas in lower reaches are closely related with water levels, water levels are an indispensable factor in forecasting. Analyzing the factors that cause changes in water levels in the lower Yellow River, this paper uses multivariate regression to build flood-peak level linear regression forecast models for seven hydrological stations on the lower reaches. All the models exceed 75% in accuracy.

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Year: 2002

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