Abstract: Groundwater resources are an important basic resource supporting regional food production. In order to solve the problem of continuous decline in shallow groundwater levels in Hebei Province, taking Cangzhou, a typical plain area in Hebei Province, as an example, based on the observation data of water level monitoring wells from 2007 to 2022, a random combination model of groundwater depth and grey time series is constructed using MATLAB software combined with the principle of grey time series, revealing the variation law of groundwater depth in Cangzhou, which provides a basis for the sustainable development and utilization of groundwater resources in the plain areas of Cangzhou and even Hebei Province. Through relevant simulation methods, it has been confirmed that the model is concise, practical, and has high accuracy. The research results indicate that in the next three years (2023-2025), if the current development trend is followed, the groundwater level in Cangzhou will continue to decline with an average annual decrease of about 1.45m.

Key words: Cangzhou, prediction of groundwater depth, time series, auto correlation

摘要： 地下水资源是支撑区域粮食生产的重要基础资源,为解决河北省浅层地下水水位持续下降问题,以河北省典型平原区沧州市为例,依据2007-2022年水位监测井观测数据,通过MATLAB软件结合灰色时间序列原理搭建地下水埋深灰色时间序列随机组合模型,揭示沧州市地下水埋深变化规律,为沧州市乃至河北省平原区地下水资源可持续开发利用提供依据。通过相关模拟方法证实该模型简洁实用,精度较高。研究结果表明:未来3年(2023-2025年),如果按照目前的发展趋势,沧州市地下水位会继续下降,平均年降幅为1.45m左右。

关键词: 沧州市, 地下水埋深预测, 时间序列, 自相关