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

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Abstract

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 10%; when precipitation decreases by 10%, 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°C; if temperature decreases 1°C, 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°C and precipitation decreases by 10%. Under this condition, the simulated average annual runoff decreases by 10.8%. On the contrary, scenario 1 is the best to the enhancement of runoff; i.e. when temperature decreases 1°C precipitation will increase by 10%, which will make the annual runoff of Sanmenxia increase by 10.6%.

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Correspondence to Jiang Xiaohui.

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Jiang, X., Liu, C., Wang, Y. et al. The study on Sanmenxia annual flow forecasting in the Yellow River with mix regression model. Sci. China Ser. E-Technol. Sci. 47 (Suppl 1), 118–126 (2004). https://doi.org/10.1360/04ez0010

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  • DOI: https://doi.org/10.1360/04ez0010

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