针对生命旋回预测模型不能反映河川径流周期性和波动性变化的特点,将其与权马尔可夫链结合,提出了一种精度较高的预报模型——生命旋回-权马尔可夫链组合模型.该模型用生命旋回模型预报河川径流的趋势项变化,由权马尔可夫链对径流残差序列进行修正,进行预测时采用等维信息方法处理,在此基础上对黄河龙门水文站径流进行预测,拟合精度为86.97%,合格率为86.78%,表明该模型可以用于径流预测.此外,对求解生命旋回模型的方法作出了改进,经研究表明,该方法实用可行. In view of the fact that the life cycle prediction model can not reflect the characteristics of periodic and fluctuant changes of river runoff, this model is combined with Markov chain to propose a new model of life cycle-weight Markov chain combination model This model predicts the change of trend items of runoff by the life cycle model, and corrects the runoff residual sequence by Markov chains, and uses the method of isometric information to predict the runoff. On the basis of this, The prediction accuracy is 86.97% and the pass rate is 86.78%, which indicates that the model can be used for runoff prediction. In addition, the method of solving the life cycle model has been improved. The results show that the method is practical and feasible.