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| LSTM-based Groundwater Level Prediction and Anomaly Analysis of Earthquake Precursors |
| LSTM model; timeseries; watertable; earthquake precursors anomalous |
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1. Institute of Disaster Prevention
2. Hebei Province University Smart Emergency Application Technology Research and
Development Center
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Abstract Due to the in?uence of earthquakes, groundwater levels can undergo abnormal changes. The prediction study of
water level change has important theoretical and practical signi?cance for the analysis of possible earthquake precursors
and the mitigation of secondary disasters. In this study, the earthquake selected occurred on April 13, 2015, at 10:28 a.m.,
in Jianshui County, Honghe Hani and Yi Autonomous Prefecture, Yunnan Province. By obtaining groundwater level data
from observation wells in the vicinity of the earthquake, the dataset is divided based on the theoretical concepts of
earthquake active and non-active periods. Subsequently, an LSTM model is employed for training. The di?erences
between the predicted values and the actual values are observed. Experimental results indicate that the model can identify
abnormal changes in groundwater levels caused by earthquakes, providing valuable insights into studying groundwater
level anomalies as earthquake precursors.
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Published: 01 November 2024
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