R/S-GM(1,1)组合模型在径流预测中的应用

基于R/S分析法能提供有效的非线性科学预测,河川径流具有灰色禀性,为了提高河流径流预报精度,提出了R/S分析与灰色理论相结合的河川径流预测方法。该方法可以克服径流灰色预测存在的数据波动较大时预测精度降低的缺陷。将该方法应用到黑河莺落峡站和正义峡站的年径流量、汛期和非汛期径流量6个序列进行径流预测验证。结果表明:两站年径流量和汛期径流量序列的预测精度都在90%左右,非汛期径流量序列在80%以上,各径流序列预测结果与Mann-Kendall趋势检验一致,预测结果可靠,为河流径流量的科学预测提供了一种新方法。

Application of R/S-GM(1, 1)model in runoff forecasting

In order to improve accuracy of rivers runoff forecast, a new method combining the rescaled range(R/S)analysis with the grey theory(GM)was proposed, based on that the R/S analysis provides scientific and effective non-linear prediction and rivers runoff has a grey character. This new method using the R/S-GM(1, 1)model can overcome the defects of low prediction accuracy when there is a larger fluctuation in data. Then it was applied in the runoff forecast of the Yingluoxia and the Zhengyixia stations in the Heihe River, with the use of six series of the annual runoff, flood season and non-flood season runoff. It is validated that the prediction accuracy of annual runoff and flood season runoff series are about 90%, and those of non-flood season runoff series are more than 80%, and the forecast results of the runoff series are consistent with the Mann-Kendall trend test results. Hence, the predication result is reliable, providing a new approach for accurate runoff forecast.