2019—2022年潮白河流域地下水位动态变化及影响因素分析

doi:10.19657/j.geoscience.1000-8527.2024.141

摘要/Abstract

摘要：

潮白河流域是北京市不可或缺的供水区域,开展其地下水位动态研究,对地下水资源保护和管理具有重要意义。本文根据2019—2022年潮白河流域地下水位监测数据,利用GIS技术,采用SOM聚类分析、线性趋势分析、主成分分析和多元线性回归分析等方法,研究潮白河流域地下水位年内动态变化,年际变化趋势。此外,基于降雨量、开采量和用水量等数据,探究了影响地下水位动态变化的主要因素。研究发现:27眼监测井地下水位动态呈强波动性、中波动性和弱波动性三类,年内水位变化分别为4.2、3.2和1.5 m。2019—2022年,地下水位年均变化范围为0.0258~0.597 m。利用主成分分析法提取两个主成分(分别代表人类活动因素和自然因素),特征值分别为6.21和1.59,累积贡献率为89.224%。多元线性回归分析表明人类活动是影响地下水位的主要因素,其中生活用水、环境用水、南水北调补水和生态补水是主要影响因子。

关键词: 潮白河流域, 地下水位动态, SOM聚类分析, 主成分分析, 多元线性回归

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

中图分类号:

P641

张天宇, 徐从超, 张钦, 张姝琪, 石博文, 刘荻, 阳沂洪, 陈男, 李瑞. 2019—2022年潮白河流域地下水位动态变化及影响因素分析[J]. 现代地质, 2025, 39(04): 1119-1128.

ZHANG Tianyu, XU Congchao, ZHANG Qin, ZHANG Shuqi, SHI Bowen, LIU Di, YANG Yihong, CHEN Nan, LI Rui. Analysis of Groundwater Level Dynamics and Influencing Factors in the Chaobai River Basin from 2019 to 2022[J]. Geoscience, 2025, 39(04): 1119-1128.

图/表 9

图1 研究区地下水采样点

Fig.1 Location of groundwater sampling points in the study area

图2 2019—2022年研究区单月降雨量

Fig.2 Monthly rainfall in the study area (2019-2022)

图3 2019—2022年地下水位月均变化量的SOM映射图(a),各簇聚类结果(b)和研究区地下水监测井分组空间分布图(c)

Fig.3 SOM mapping of monthly average changes in groundwater level (2019-2022)(a), clustering results of clusters (b), and spatial distribution of grouped groundwater monitoring wells in the study area (c)

图4 簇 Ⅰ(a)、簇 Ⅱ(b)和簇 Ⅲ 地下水位年内动态(c)

Fig.4 Intra-annual groundwater level dynamics of ClusterⅠ(a), ClusterⅡ(b), and ClusterⅢ (c)

图5 2019年12月(a)和2022年12月(b)地下水位时空分布图

Fig.5 Spatial and temporal distribution map of groundwater level in December 2019 (a) and December 2022 (b)

图6 2019—2022年北京市潮白河地区地下水位变化

Fig.6 Changes of groundwater level in Chaobai River area of Beijing from 2019 to 2022

图7 簇Ⅰ(a)、簇Ⅱ(b)和簇Ⅲ年际变化趋势(c)

Fig.7 Interannual variation trend of ClusterⅠ(a), ClusterⅡ(b), and ClusterⅢ (c)

表1 旋转公因子特征值及贡献率

Table 1 Eigenvalues and contribution rates of rotated common factors

主成分	特征值	贡献率(%)	累积贡献率(%)
F1	6.210	68.996	68.996
F2	1.590	17.668	86.664
F3	0.639	7.103	93.767
F4	0.382	4.242	98.009
F5	0.104	1.160	99.169
F6	0.060	0.670	99.839
F7	0.013	0.145	99.985
F8	0.000	0.015	100.000

表2 旋转公因子特征值对应特征向量

Table 2 Eigenvectors corresponding to rotated common factor eigenvalues

主成分	x₁	x₂	x₃	x₄	x₅	x₆	x₇	x₈	x₉
F1	0.075	-0.070	0.319	0.368	0.307	-0.392	-0.391	0.383	-0.388
F2	0.653	0.711	0.420	0.042	0.283	0.108	-0.117	0.051	0.010

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