Research on Medium and Long Term Runoff Forecast in Yangtze River Basin
Abstract: Yangtze River is one of China’s most economically developed regions, and the quantity of water directly affects the economic and social development in the region, so an accurate medium and long-term forecast is significant for multi-reservoir scheduling, water resources allocation and ra-tional utilization. In this paper, Pingshan, Yichang, Datong and Hankou four stations in the Yangtze River basin were selected as the research objects, based on 75 predictors, including 74 atmospheric circulation index and pre-runoff, using the correlation coefficient method to preliminary select the predictors and stepwise regression method to optimize the predictors, a runoff forecasting model of monthly scale and ten-day scale based on the Support vector machine (SVM) was established. And the applicability of the model in the Yangtze River basin was quantitatively analyzed. In addition, the prediction precision of the model was compared with that of artificial neural network prediction model. The results indicate that the model based on SVM can’t meet the actual application requirements, because the average qualified rates during the test period were only respectively 49.29% and 54.49% in the medium and long-term runoff forecasting of monthly scale and ten-day scale. But the monthly runoff results calculated by ten-day scale are superior to those by monthly scale. The former can provide a reference for the work of the Yangtze River hydrological forecasting. Relatively speaking, the prediction precision of the model based on Support vector machine (SVM) is better than that of artificial neural network model.
文章引用: 贾军伟 , 张利平 , 刘 恋 , 闪丽洁 (2014) 长江干流站中长期径流预报方法研究。 水资源研究， 3， 283-290. doi: 10.12677/JWRR.2014.34035
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