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黄河流域水质评价及时空变化分析

[Water Quality Assessment and Spatial-temporal Variation Analysis in Yellow River Basin].

作者信息

Liu Yan-Long, Zheng Yi-An

机构信息

Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China.

出版信息

Huan Jing Ke Xue. 2022 Mar 8;43(3):1332-1345. doi: 10.13227/j.hjkx.202106111.

Abstract

During the implementation of ecological protection in the Yellow River basin, understanding the water pollution status and spatio-temporal variation of water quality has become the most important thing for water safety in the basin. To analyze the water quality in recent years, the water quality data in the Yellow River basin from 2004 to 2018 were firstly collected from eight typical monitoring stations. Using a combination of multivariate data analysis methods including the Mann-Kendall (M-K) trend test, hierarchical clustering analysis (HCA), principal component analysis (PCA), and modified comprehensive water quality identification index (WQI), the spatio-temporal variation characteristics of the water quality were then explored in the Yellow River basin. The results indicated that in terms of time variation, the HCA from the water quality time series showed that the water quality of the Yellow River basin could be divided into the wet season, normal season, and dry season, being basically consistent with the hydrological period. Combined with the M-K trend test and WQI-based water quality assessment, the water quality of the Yellow River basin was improving gradually, with 2010 as the critical year. The water quality in the wet season was superior to that in the dry season. The pollution indicator NH-N and permanganate index were dominant in both the wet season and dry season. According to the spatial variation analysis, the water quality for all the studied stations improved significantly. Spatial clustering showed that the S6 (Shanxi Yuncheng Hejin Bridge) was obviously different from others, and further comparative study demonstrated that S6 was constantly seriously polluted. The S7 (Henan Jiyuan Xiaolangdi) exhibited different characteristics in the wet and dry season. In all stations, NH-N was considered to be the most common pollution indicator, whereas the permanganate index and DO were also relatively serious for S6. In different hydrological seasons, NH-N and the permanganate index showed different characteristics, and their variety was related to the fact that the former mainly came from domestic and industrial sources, whereas the latter was mainly derived from agricultural sources. The modified WQI showed obvious advantages over single-factor water quality assessment, and the findings from this study can provide scientific evidence for water pollution control and comprehensive water quality management in the Yellow River basin.

摘要

在黄河流域实施生态保护过程中,了解水污染状况及水质的时空变化已成为该流域水安全的重中之重。为分析近年来的水质情况,首先从八个典型监测站收集了2004年至2018年黄河流域的水质数据。运用包括曼-肯德尔(M-K)趋势检验、层次聚类分析(HCA)、主成分分析(PCA)以及改进的综合水质标识指数(WQI)在内的多元数据分析方法相结合的方式,进而探究黄河流域水质的时空变化特征。结果表明,在时间变化方面,水质时间序列的HCA显示黄河流域水质可分为丰水期、平水期和枯水期,基本与水文期一致。结合M-K趋势检验和基于WQI的水质评价,黄河流域水质逐渐改善,2010年为关键年份。丰水期水质优于枯水期。污染指标氨氮(NH-N)和高锰酸盐指数在丰水期和枯水期均占主导地位。根据空间变化分析,所有研究站点的水质均有显著改善。空间聚类表明,S6(山西运城河津大桥)与其他站点明显不同,进一步的对比研究表明S6一直受到严重污染。S7(河南济源小浪底)在丰水期和枯水期表现出不同特征。在所有站点中,氨氮被认为是最常见的污染指标,而高锰酸盐指数和溶解氧(DO)对S6来说也相对严重。在不同水文季节,氨氮和高锰酸盐指数表现出不同特征,其变化与前者主要来自生活和工业源,而后者主要来自农业源这一事实有关。改进后的WQI相较于单因子水质评价具有明显优势,本研究结果可为黄河流域水污染控制和综合水质管理提供科学依据。

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