为了提高城市水位监测的准确性及洪涝等灾害的预警能力,提出基于季节性自回归积分滑动平均(Seasonal auto-regressive integral moving average,SARIMA)模型的水位监测预警模型.该模型综合了自回归模型、移动平均模型和季节性差分模型,适用于分析和预测具有季节性和非平稳特征的时间序列数据.结果显示,基于SARIMA预警模型的水位监测系统,对城市周边的水位监测拟合效果较好,可对城市周边水位进行有效监测,提高应对城市内涝灾害的预警效果.
Analysis and Research on the Effect of Water Level Monitoring Based on SARIMA Early Warning Model
In order to improve the accuracy of urban water level monitoring and the early warning ability of floods and other disasters,a water level monitoring and early warning model based on the seasonal autoregressive integral moving average(SARIMA)model was proposed.This model combines autoregressive model,moving average model,and seasonal difference model,suitable for analyzing and predicting time series data with seasonal and non-stationary characteristics.The results show that the water level monitoring system based on the SARIMA warning model has a good fitting effect on the water level monitoring around the city,and can effectively monitor the water level around the city,greatly improving the warning effect of responding to urban waterlogging disasters.
seasonal autoregressive integral moving average modelwater level monitoringwater level warningdata filling
NETL
NSTL
万方数据
维普
