改进ARX模型在襄阳站年径流序列预测中的应用

在气候变化和人类活动的影响下,我国部分流域的年径流过程表现出了复杂性波动,常规的统计分析预测模型都有其一定的局限性。多因子自回归模型(ARX模型)可以较高精度地对具有复杂性波动的系统进行模拟。以受人类活动影响和气候变化影响较为显著的汉江流域的襄阳站为研究对象,采用改进后的ARX模型对襄阳站1960~2002的年径流过程进行了模拟,并与多种常用的统计分析方法进行了比较,验证了ARX模型在模拟具有突变性的年径流过程的良好性能。根据所率定模型对襄阳站2003~2012年的年径流进行了预测,预报合格率达到90%,说明了ARX模型在中长期径流预报中较好的适用性。

Application of Improved ARX Model in Predicting Annual Flow at Xiangyang Station

With the impact of climate change and human activities, river flow regime presents complex fluctuation in recent years, which brings limitation to the application of those normal statistical analysis flow forecast model. The multi-factor auto-regression model (ARX) can simulate the complex fluctuation system with higher precision and is improved to simulate and forecast the river flow of a highly impacted river reach -the Xiangyang station from 1960 to 2002. By comparing with some traditional simulation methods, the result proves that the improved RAX model performs the best. Based on the RAX simulation model, annual flow at the Xiangyang station from 2003 to 2012 was forecasted. The reliability rate of forecast is 90%, which indicates the applicability of the RAX model in mid-long term river flow forecast.