基于多变量时间序列CAR模型的地下水埋深预测

为准确估计内蒙古河套灌区地下水埋深的变化规律，根据河套灌区沙壕渠灌域1988－2007年实测的地下水埋深、降雨、蒸发及引水量资料，基于多变量时间序列CAR（Controlled Auto-regressive）模型建立了地下水埋深的预测模型，并对模型进行了验证，并将模型在不同方案条件下进行了地下水埋深预测的应用。结果表明：河套灌区地下水埋深受到气候条件、引水量的影响较大。CAR模型预测效果良好，模型在沙壕渠灌域具有较好的适用性。预测方案显示，当区域蒸发量增加25%，降雨量减少34%，年引水量减少18%时，地下水埋深将达到2.21 m。提出的研究方法和结果可为灌区灌溉用水管理提供参考。

Groundwater depth forecast based on multi-variate time series CAR model

In order to accurately estimate the groundwater depth in Hetao irrigation district, Inner Mongolia, the forecasting model of groundwater depth was established based on multivariate time series CAR model (Controlled auto-regressive)according to the observed data of groundwater depth, precipitation, evaporation and water inflow in Shahaoqu area of Hetao irrigation district from 1988 to 2007. The model was validated and then applied to forecast the groundwater depth under different schemes. The results showed that the changes of groundwater depth in Hetao irrigation district were tremendously influenced by climatic conditions and the irrigation water amount, the multivariate time series CAR model was effective in prediction, and the model had good applicability in Shahao irrigation area. The prediction schemes show that when the evaporation increases by 25%, the rainfall reduces by 34% and the annual water diversion reduces by 18%, and then the groundwater depth would be 2.21 m. Therefore, the research method findings from this paper can provide references for irrigation district in water management.