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The study on Sanmenxia annual flow forecasting in the Yellow River with mix regression model

Science China(Technological Sciences) 2004年第Z1期47卷 118-126页

作者： jiang xiaohui1. liu changming1.2. wang yu3 & wang hongrui1.1. beijing normal university,{1., China 2. Institute of Geographic Science and Natural Resources, Chinese Academy of Sciences, beijing 1.01.1, China 3. Reconnaissance, Planning, Design and Research Institute, YRCC, Zhengzhou 450003, China beijing{1. university Beijing China Institute of Geographic Science and Natural Resources Chinese Academy of Sciences Beijing China Reconnaissance Planning Design and Research Institute YRCC Zhengzhou China

This paper established mix regression model for simulating annual flow, in which annual runoff is auto-regression factor, precipitation, air temperature and water consumption are regression factors; we adopted 9 hypothesis climate change schemes to forecast the change of annual flow of Sanmenxia Station. The results show : (1. When temperature is steady, the average annual runoff will increase by 8.3% if precipitation increases by 1.%; when precipitation decreases by 1.%, the average annual runoff will decrease by 8.2%; when precipitation is steady, the average annual runoff will decrease by 2.4% if temperature increases 1.; if temperature decreases 1., runoff will increase by 1.2%. The mix regression model can well simulate annual runoff. (2) As to 9 different temperature and precipitation scenarios, scenario 9 is the most adverse to the runoff of Sanmenxia Station of Yellow River; i.e. temperature increases 1. and precipitation decreases by 1.%. Under this condition, the simulated average annual runoff decreases by 1..8%. On the contrary, scenario 1.is the best to the enhancement of runoff; i.e. when temperature decreases 1.℃ precipitation will increase by 1.%, which will make the annual runoff of Sanmenxia increase by 1..6%.

关键词： forecast annual flow, mix regression model, Sanmenxia Station

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