【摘要】 为了完善中国内地大尺度区域用水量预测模型的研究，为水资源科学利用提供支撑，应用ARMA、灰色GM(1,1)及BP神经网络模型原理，建立省级行政区划、流域、地理大区3种尺度的年用水总量预测模型，对模型优选结果进行统计分析，并应用最优模型对2021-2025年各省级行政区用水总量进行预测。结果表明：对于内地省级行政区划尺度，9个行政区的年用水总量最优预测模型为ARMA模型，6个行政区的最优预测模型为灰色GM(1,1)模型，16个行政区的最优预测模型为BP神经网络模型；对于流域尺度，5个流域的年用水总量最优预测模型为ARMA模型，3个流域的最优预测模型为灰色GM(1,1)模型，长江流域的最优预测模型为BP神经网络模型；对于地理大区尺度，北方6区的年用水总量最优预测模型为BP神经网络模型，南方4区的最优预测模型为灰色GM(1,1)模型；2021-2025年内地各省级行政区的年用水总量总体保持稳定。研究结果可为中国内地用水总量的管理提供依据。更多还原

【Abstract】 In order to improve large-scale water consumption prediction models for mainland China and provide a technical support for the scientific utilization of water resources, the annual total water consumption prediction models of provincial administrative divisions, river basins and geographical regions were established based on the principles of ARMA, gray GM(1,1) and BP neural network model. The optimized results of the models were statistically analyzed, and the selected optimal models were used to predict the total water consumption from 2021 to 2025. The results show that for the provincial administrative division scale, the optimal prediction model of total annual water consumption is ARMA model in nine administrative divisions, gray GM(1,1) model in six administrative divisions, and neural network model in 16 administrative divisions. At the river basin scale, the optimal prediction model is ARMA model in five basins, gray GM(1,1) model in three basins, and neural network model in the Yangtze Basin. For the scale of large geographical regions, the optimal model of the six northern regions is the neural network model, and that of the four southern regions is the gray GM(1,1) model. The water consumption in the next five years will be generally stable. These findings are expected to provide some statistical reference for total water consumption management in China.更多还原