Study on Spatiotemporal Variation Patterns of Groundwater in the North Shandong Plain and Its Response to Precipitation

Xiaojuan Li ¹ Chaofan Zhou ^1* Huili Gong ¹ Beibei Chen ¹ Xiaodan Gao ¹ Yabin Yang ² Xiaoxiao Sun ²

• ¹ Capital Normal University, Beijing, China
• ² Shandong Provincial Geological and Mineral Exploration and Development Bureau, Ji'nan, China

Precipitation and groundwater are critical components of the hydrological cycle. Understanding their variations and response relationship is vital for water resource management, ecological protection, and flood risk assessment. To explore the spatiotemporal patterns and response relationships of precipitation and groundwater levels in the North Shandong Plain, this study analyzed data from 2012 to 2023, including precipitation records and groundwater level data from various aquifers. Using trend analysis, Independent Component Analysis (ICA), and Cross Wavelet Transform (XWT), the research aimed to identify the spatiotemporal patterns of groundwater and its lagged responses to precipitation. The findings reveal that precipitation in the North Shandong Plain exhibited a non-significant increasing trend from 2012 to 2023. Trend analysis indicates that groundwater levels at 70% of monitoring points were declining, primarily in the central and western regions, forming significant groundwater depression cones. ICA identified three primary spatiotemporal evolution patterns of groundwater levels in the area. The first independent component (IC1) represents the main trend, characterized by a groundwater level decline from 2012 to 2018, followed by a recovery trend aft er 2018. Spatially, areas with high IC1 scores were concentrated in groundwater depression cone centers, particularly in Dezhou City. By integrating XWT analysis, the study explored the lagged response relationships between groundwater levels and precipitation for different aquifer layers. Results indicate distinct differences in lag times: shallow groundwater levels responded more quickly to precipitation, with an average lag of 3.6 months, whereas deep groundwater levels exhibited longer lag times, averaging 8 months, with somdee points reaching up to 12 months. This study combines time series trend analysis and blind source separation techniques to investigate the spatiotemporal evolution patterns and response relationships of groundwater and precipitation. The findings provide new perspectives for regional water cycle research.