Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing, 100124, China.
Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing, 100124, China.
Environ Res. 2022 Sep;212(Pt A):113181. doi: 10.1016/j.envres.2022.113181. Epub 2022 Mar 29.
The arbitrary distribution of groundwater monitoring sites and the redundancy of observation data restrict the ability of monitoring network to provide reliable and effective data information. The purpose of this study is aimed at finding a quantitative method to screen ideal monitoring locations and evaluate the efficiency of the monitoring network. In terms of site selection, we use hydrogeological information, monitoring density and monitoring location to select the suitable site to monitor groundwater quality, understand the temporal trends and identify the abnormal signals of pollution sources. To evaluate the efficiency of monitoring network we used the groundwater quality data for consecutive years to evaluate the groundwater monitoring network based on information entropy and principal component analysis (PCA). The results show that the optimized groundwater monitoring network is comprised of 10 monitoring wells. The efficiency evaluation results of information entropy and PCA are basically consistent. The maximum mutual information (T) and comprehensive index of monitoring site (Laiguangying) were 1.29 and 3.25 respectively, while the minimum T and comprehensive index of monitoring site (Jinzhan) were 1.05 and -0.36 respectively, and the data efficiency was low. This study provides a good example for optimizing a groundwater pollution monitoring network.
地下水监测点的任意分布和观测数据的冗余限制了监测网络提供可靠和有效数据信息的能力。本研究旨在寻找一种定量方法来筛选理想的监测点,并评估监测网络的效率。在选址方面,我们使用水文地质信息、监测密度和监测位置来选择合适的地点来监测地下水质量,了解时间趋势并识别污染源的异常信号。为了评估监测网络的效率,我们使用连续多年的地下水质量数据,基于信息熵和主成分分析(PCA)对地下水监测网络进行评估。结果表明,优化后的地下水监测网络由 10 口监测井组成。信息熵和 PCA 的效率评估结果基本一致。最大互信息(T)和监测点综合指数(来广营)分别为 1.29 和 3.25,而最小 T 和监测点综合指数(金盏)分别为 1.05 和-0.36,数据效率较低。本研究为优化地下水污染监测网络提供了一个很好的范例。