摘要
Abstract
The widely used methods for forecasting river flood flow are the Muskingum flood routing algorithm and the Kalinin Milgakov method. However, these traditional methods are limited by the difficulty in parameter calibration and the flow balancing at confluences of multiple tributaries. In this study, the least square method is proposed to predicting flood flows or flood stages at main river and tributaries using stream gage data. The proposed model, utilizing historical flood data and real-time measurements, predict flood flow and stage by establishing recursive scheme using regression algorithm. The accuracy of the proposed model is independent of other parameters, and the method is simple and easy to be applied to practice. Taking Qigihar stream gage station at Nenjiang River as an example, flood flow in 2013 was forecasted. The results show that the model output is less sensitive to other hydrological parameters, and the forecasting precision is higher than traditional methods with a maximum error less than 5%.关键词
河道洪水/回归分析/流量预测Key words
flood in rivers/regression analysis/flood flow forecasting分类
天文与地球科学
