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河川径流预测是一个十分复杂的问题,生命旋回模型在进行径流趋势预测时具有对资料要求少、计算简单等优点,但由于模型机理的限制,进行预测时得到的序列很难反映径流序列的随机波动变化,且存在预测结果精度不高的缺点。针对这一问题,文中提出了一种新的径流预报模型——生命旋回-Markov组合预测模型。该模型用生命旋回模型预报河川径流的趋势项变化,用周期修正方法反映其径流周期性特征,用Markov模型预报其径流序列随机变化,在此基础上对黄河龙门水文站年径流进行预测时,拟合精度为89.13%,合格率为90.22%,表明该模型精度较高,可为水利工程运行管理提供水文依据。
The runoff prediction of river is a very complex issue. The life cycle model has the advantages of less data requirement and simple calculation in runoff forecasting. However, due to the limitation of model mechanism, the sequence obtained when forecasting is difficult to reflect the randomness of runoff series Fluctuating, and the shortcomings of the prediction accuracy is not high. In response to this problem, a new model of runoff-Markov combination forecasting is proposed. This model predicts the change of trend item of runoff by life cycle model, and uses periodic correction method to reflect the periodic characteristics of runoff. By using Markov model to predict the random variation of runoff series, when predicting annual runoff of Longmen Hydrological Station, The fitting accuracy is 89.13% and the pass rate is 90.22%, which shows that the model has high accuracy and can provide hydrological basis for water project operation and management.