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Artificial neural network model was established between two river flow in two hydrological stations, Yinluoxia Station and Zhamashike Station in upper Heihe River basin. Results indicate very good correlations for the general trend of the flow data at two stations with correlation coefficients of 0.86 and 0.94 for 2004 and 2005, respectively. Major differences between model results and observations occur near the peak flow or flood periods. This indicates that other factors, such as local rainfalls, can be included in future study to further improve the model accuracy. Keywords-artificial neural network; flow; Yinluoxia; Zhamashike; Heihe River

Neural Network Modelling of Flow In Yinluoxia Station Based on Flow in Zhamashike Station in Heihe River, China