生命旋回- Markov 链模型在径流预测中的应用

摘要

In order to resolve the problem that the life cycle model can not reflect the fluctuation and random characteristics,the life cycle-Markov chain model which combines life cycle model with Markov chain model was built. The characteristic of the model was to predict the trend of runoff series by using life cycle model and amend runoff residual sequence by using Markov chain-model. The runoff prediction of Tangnaihai Hydrological Station in the upper Yellow River shows that the average accuracy of flood period prediction is 81. 93% ,however some months′precision is less ac-curate,which value is less than 80% ;The average accuracy of dry period is 91. 74% ,which qualified rate is 100% .%为了解决生命旋回模型无法反映径流序列随机性的问题，将生命旋回模型与 Markov 链模型结合，建立了生命旋回- Markov 链组合预测模型。该模型的特点是用生命旋回模型模拟预测径流量序列的趋势项，用 Markov 链模型对径流残差序列进行修正。应用该方法对黄河上游唐乃亥水文站的径流量预测结果表明：汛期预测平均相对误差为18.07%，但是有些月份误差较大；枯期预测的平均相对误差为8.26%。