Welcome to visit Geoscience!

Geoscience ›› 2025, Vol. 39 ›› Issue (04): 1119-1128.DOI: 10.19657/j.geoscience.1000-8527.2024.141

• Geochemistry • Previous Articles     Next Articles

Analysis of Groundwater Level Dynamics and Influencing Factors in the Chaobai River Basin from 2019 to 2022

ZHANG Tianyu1,2(), XU Congchao1,2, ZHANG Qin3, ZHANG Shuqi4, SHI Bowen1, LIU Di1, YANG Yihong1, CHEN Nan2, LI Rui1,*()   

  1. 1. State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    2. School of Water Resources and Environment, China University of Geosciences (Beijing), Beijing 100083, China
    3. Nuclear and Radiation Safety Center, Ministry of Ecology and Environment, Beijing 100082, China
    4. School of Labor Relations and Human Resources, China University of Labor Relations, Beijing 100048, China
  • Online:2025-08-10 Published:2025-08-27
  • Contact: LI Rui

Abstract:

The Chaobai River Basin is an indispensable water supply area for Beijing. Studying groundwater level dynamics helps identify changes in groundwater levels, which is of great significance for the protection and management of groundwater resources. Based on groundwater level monitoring data of the Chaobai River Basin from 2019 to 2022, this paper analyzes the intra-annual and interannual trends of groundwater levels, as well as the main factors influencing groundwater level dynamics, using GIS technology, SOM clustering analysis, linear trend analysis, principal component analysis (PCA), and multiple linear regression analysis, combined with data on rainfall, extraction, and water consumption.The results show that the groundwater level dynamics of the 27 monitoring wells fall into three categories: strong fluctuation, medium fluctuation, and weak fluctuation, with intra-annual water level changes of 4.2 m, 3.2 m, and 1.5 m, respectively. From 2019 to 2022, the average annual change in groundwater levels ranged from 0.0258 to 0.597 m/a. Principal component analysis extracted two principal components (representing human activity factors and natural factors, respectively) with eigenvalues of 6.21 and 1.59, and a cumulative contribution rate of 89.224%. Multiple linear regression analysis showed that human activities were the main factors affecting groundwater levels, with domestic water use, environmental water use, South-to-North Water Diversion Project replenishment, and ecological water replenishment identified as the primary influencing factors. This study provides a theoretical basis for groundwater management and protection in the Chaobai River Basin.

Key words: Chaobai River Basin, groundwater level dynamics, SOM clustering analysis, principal component analysis, multiple linear regression

CLC Number: