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Application of Grey Time Series Random Combination Model in Groundwater Depth Prediction: A Case Study of Cangzhou
HAN Chao, LIU Xiaoyan, LIU Jiajun, HE Yunpeng, WEN Yongfu, LIU Juan
2024, 34(1):
54-60.
DOI: 10.16046/j.cnki.issn2096-5680.2024.01.010
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.
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