宁夏青铜峡灌区年退水量时间序列预测模型研究

针对宁夏青铜峡灌区年退水量预测问题，采用时间序列方法分析了灌区年退水量特性，建立了预测模型，结果发现青铜峡灌区年退水量在年际间相互关联，其时间序列是一个非白噪声非平稳时间序列，一阶差分序列是一个非白噪声平稳序列，建立了ARIMA年退水量时间序列模型，模型模拟的平均相对误差为5.66%，预测的相对误差在5%以内，精度较高，可以用于灌区退水量的预测。

Research on time series prediction model of annual return water volume in Qingtongxia irrigation area

In order to address the prediction problem of return water in Qingtongxia irrigation area, this paper analyzed the properties of annual return water volume and built a prediction model by time series method. The research results showed that the return water volume exhibited a correlation pattern between years. Its time series was a non-white noise and non-stationary series, and its first-order differential sequence was a non-white noise and stationary series. As a result, a time series prediction model of annual return water volume had been established with an average relative simulation error of 5.66% and a relative prediction error up to 5%, demonstrating the high simulation and prediction accuracy of this model. Thereby, it could be used for the prediction of annual return water in irrigation area.