农业灌溉用水量混沌预报模型建立与应用

Establishment of chaotic forecasting model and its application in forecasting water consumption of agricultural irrigation

针对当前灌溉用水量预报方法研究现状及预报精度低的问题,提出了混沌预报模型。通过灌溉用水量序列相空间重构在高维空间中恢复演变规律,并进行混沌演变特性识别,建立了基于最大Lyapunov指数的灌溉用水量混沌预报模型。模型用于湖北省举水流域灌溉用水量预报并与不同方法进行对比分析,结果表明模型预报效果好,可以作为农业灌溉用水量预报的一种有效方法。

Based on the analysis of research status and in order to solve the problem of the low precision of irrigation water consumption forecasting, chaotic forecasting model was put forward. The evolvement regulation was resumed in high dimension space with state space reconstruction of irrigation water consumption serials, and the chaotic evolvement characteristic was distinguished. The chaotic forecasting model was established with the maximal Lyapunov index. The model was applied to forecast irrigation water consumption of Jushui River basin in Hubei Province. The comparison of forecasting results which calculated by using chaotic forecasting model with witch calculated by using other methods demonstrated that the proposed model had better forecasting effect, and it could be regard as an effective forecasting method for agricultural irrigation water consumption forecasting.