多元校正分析在水环境地球化学领域中的应用

多元校正分析法应用于水环境地球化学研究,可对复杂的分析数据进行处理和解析,反映水质状况与污染之间的各种关系,建立水质评价和预测模型,从而科学地服务于治理水污染。评述了多元分析方法如主成分分析、偏最小二乘法、人工神经网络等在水环境地球化学研究中的应用、进展和前景。     

Application of multivariate statistical techniques in the assessment of water quality in Sakarya River,Turkey

In this paper, the surface water quality of the Sakarya River in Turkey is assessed by using multivariate statistical techniques. These techniques were applied to the chemical parameters obtained from the five different surface water quality observation stations. Factor and principal component analysis results reveal that the agricultural, anthropogenic and domestic pollution caused differences in terms of water quality. Cluster analysis revealed two different clusters of similarities between the stations, reflecting different chemical properties and pollution levels in the studied river. Surface water quality downstream of the river was different from the water quality upstream. Thus, this study shows the usefulness of multivariate statistical techniques for analysis and interpretation in the surface water quality problem.     

Assessment of water quality and identification of pollution sources of three lakes in Kashmir, India, using multivariate analysis

Multivariate statistical techniques, such as cluster analysis, principal component analysis (PCA) and factor analysis (FA) were applied to evaluate and interpret the water quality data set for 13 parameters at 10 different sites of the three lakes in Kashmir, India. Physicochemical parameters varied significantly (p?<?0.05) among the sampling sites. Hierarchical cluster analysis grouped 10 sampling sites into three clusters of less polluted, moderately polluted and highly polluted sites, based on similarity of water quality characteristics. FA/PCA applied to data sets resulted in three principal components accounting for a cumulative variance of 69.84, 65.05 and 71.76% for Anchar Lake, Khushalsar Lake and Dal Lake, respectively. Factor analysis obtained from principal components (PCs) indicated that factors responsible for accelerated eutrophication of the three lakes are domestic waste waters, agricultural runoff and to some extent catchment geology. This study assesses water quality of three lakes through multivariate statistical analysis of data sets for effective management of these lakes.     

双塔水库水质对人类活动的响应分析

选取1993～2008年瓜州县人类活动数据及双塔水库水质指标年平均值进行主成分分析,去除冗余信息后进行多元线性回归分析,得到四组反映人类活动对水库水环境影响情况的回归方程。说明对双塔水库水质起主要影响作用的是农业活动和因农业活动引起的土地利用变化,农业活动的非点源污染是水库水质的主要污染源,水库水质仍存在富营养化的风险;工业活动对水库水质的影响没有在回归方程中体现出来。在农业活动过程中,耕地面积每增加10 000亩促使pH值上升0.062、溶解氧值下降0.046、高锰酸钾指数上升0.103、COD值上升0.617;而每增加10 000t的氮肥施用量会引起pH值升高1.837;总人口每增加1万人,COD值上升0.798。     

聚类分析在秦淮河水质指标相关性研究中的应用

随着水质监测尺度和监测网络的扩大,传统的水质指标相关性分析的方法已经不能适应于庞大的水质数据。而采用聚类分析法,在对水质指标进行降维处理的同时,可以筛选出水质相关项。利用SPSS软件计算水质指标相关系数矩阵,并绘制聚类分析树形图,对已知水质数据进行相关性分析,结果发现秦淮河东山站水体总有机碳和高锰酸钾指数、总氮和氨氮具有较强相关性。结合线性回归方程的验证,证明R型聚类分析在庞大数据背景下的水质指标相关性研究中具有较好的效果,可以在水污染治理、水质监测评价中发挥较好的作用。     

Geochemical characterization of karst groundwater in the cradle of humankind world heritage site,South Africa

The karst of the Cradle of Humankind World Heritage Site plays a major role in the assimilation or carrying of acid mine drainage, sewage effluent return flow and agricultural run-off. Infiltration of contaminated water has altered the chemical composition of the natural waters of the karst system. A multivariate statistical method in combination with conventional geochemical and spatial analysis was applied on groundwater and surface water quality samples to determine the spatial extent of hydrochemical impacts from different anthropogenic sources. The application of hierarchical cluster analysis of the major ions (148 samples) recognised three distinct hydrochemical regimes. Cluster 1 is moderately mineralized, especially with regard to chloride, nitrate and sulphate, cluster 2 has a low mineralization with all elements well within the recommended drinking water limits of South Africa and cluster 3 represents highly mineralized samples taken in the vicinity of decanting mineshafts. The cluster solution is confirmed by a simple mixing model, indicating varying contributions of three identified end members (acid mine drainage, treated sewage effluents and pristine dolomitic groundwater) to the groundwater quality in the catchment. The combination of statistical, geochemical and spatial methods in conjunction with end-member mixing analysis provides a reliable method to understand the processes responsible for the groundwater quality variations and to assist in the identification of anthropogenic impacts.     

Assessment of surface water quality using multivariate statistical analysis techniques: a case study from Ghrib dam,Algeria

This study explores the water quality status and pollution sources in Ghrib Dam, Algeria. It allows us to obtain more accurate information on water quality by applying a series of multivariate statistical techniques, including principal component analysis (PCA)/factor analysis (FA), hierarchical cluster analysis (CA), and multiple regression analysis (MRA). On 19 physicochemical parameters dataset over 5 years and from 6 different sites located in and around the lake. One-way analysis of variance (ANOVA) was used to investigate the statistically considerable spatial and seasonal differences. The results of ANOVA suggest that there exist a statistically significant temporal variation in the water quality of the dam for all parameters. On the other hand, only organic matter has a statistically significant spatial variation. In the multiple linear models, an association between organic and inorganic parameters was found; their origin comes from the mechanical erosion process of agricultural lands in the watershed. The PCA/FA identifies five dominant factors as responsible of the data structure, explaining more than 94.96% of the total variance in the water quality dataset. This suggests that the variations in water compounds’ concentration are mainly related to the multiple anthropogenic activities, as well as natural processes. The results of cluster analysis demonstrate that the sampling stations were divided in two similar groups, which indicates spatial homogeneity. While seasonal grouping has showed that the source of pollution was related to the level of runoff in the seasons.     

Water quality changes in the Elbe River basin,Czech Republic,in the context of the post-socialist economic transition

This paper analyses the temporal dynamics and spatial trends in water quality changes in the Elbe River basin in the context of the post-socialist economic transition of the Czech Republic (Czechia). During the 1990s, the Czech portion of the Elbe River Basin underwent significant changes in the quality of surface waters. After a long period of massive discharges of pollution, which reached a peak at the end of the 1980s, a reduction in effluent from industrial and municipal sources led to a substantial decrease in the pollution of the Elbe River and its principal tributaries. The scope and speed of such water quality changes was unprecedented in Czechia as well as throughout Europe. The classification of the spatial distribution of water quality trends revealed that the majority of streams in the Czech Elbe River basin displayed improvement of surface water quality. However, the decrease in pollution levels was spatially concentrated mainly in the Elbe River and its main tributaries. Many of the peripheral streams are, on the contrary, experiencing deteriorating water quality, even in regions where water quality improved in the early 1990s because of a decline in local economic activity associated with political changes in the former Eastern Block countries. Further improvements in water quality are thus dependent on measures adopted across the entire river basin, including the numerous minor streams. The current economic revival in a number of regions where decreases in water pollution were not based on systematic pollution reduction measures, but only on the decline of industrial or agricultural production, may result in a return to deteriorating water quality, primarily in the outer regions of the catchment.     

黑河干流浅层地下水与地表水相互转化的水化学特征

通过分析黑河干流地表水与地下水的水化学特征,识别沿黑河干流不同地带地下水与地表水的相互转化关系.研究结果表明:(1)在祁连山区,地下水与地表水的转化以地下水向河流排泄为主.(2)南部盆地,在山前戈壁带,出山河水入渗转化为地下水;溢出带地下水以泉的形式转化为地表水;进入细土平原后,汛期河水补给地下水,非汛期地下水补给河水;在农灌区引河水通过田间入渗补给地下水.(3)北部盆地,在金塔灌区,地下水主要接受引水灌溉入渗补给;在金塔灌区到额济纳旗,河流入渗转化为地下水.     

Spatial characteristics of surface water quality in the Haicheng River (Liao River basin) in Northeast China

Spatial variations of the water quality in the Haicheng River during April and October 2009 were evaluated for the national monitoring program on water pollution control and treatment in China. The spatial autocorrelation analysis with lower Moran’s I values displayed the spatial heterogeneity of the 12 physicochemical parameters among all the sampling sites of the river. The one-way ANOVA showed that all variables at different sampling sites had significant spatial differences (p < 0.01). Based on the similarity of water quality characteristics, cluster analysis grouped the 20 sampling sites into three clusters, related with less polluted, moderately polluted and highly polluted sites. The factor analysis extracted three major factors explaining 76.4 % of the total variance in the water quality data set, i.e., integrated pollution factor, nitrogen pollution factor and physical factor. The results revealed that the river has been severely polluted by organic matter and nitrogen. The major sources leading to water quality deterioration are complex and ascribed to anthropogenic activities, e.g., domestic and industrial wastewater discharges, agricultural runoff, and animal rearing practices.     

基于深度学习的旧金山湾水质预测

传统的水质预测模型计算复杂，且在大对流情况下会引发误差，对于大数据时代下智能化的水质预测问题并不适用。本文针对旧金山湾地表水质研究区的数据资料，利用数据分析、统计检验、深度学习时序模型等技术方法对该研究区的水质进行研究，根据主成分信息构建了长短时记忆（LSTM）循环神经网络模型，对研究区的5个地表水质采样站点进行了水质预测。结果表明：长短时记忆循环神经网络模型通过门控制循环和记忆单元结构，有效控制传入模型的输入特征，从而降低模型的复杂度；双层长短时记忆循环神经网络模型较单层长短时记忆循环神经网络模型的预测精度平均提高5.3%。利用LSTM模型可以对旧金山湾地表水质进行有效评价。     

铁岭南部山区地下水源与补给分析研究

山丘区地下水埋藏情况复杂,结合打井抽水试验方式进行分析研究是一种有效研究方法。通过研究铁岭南部山丘区域气候特性、水文特性、地质和水文地质条件,分析地下水源的补给来源和地表、地下径流的排泄方式。通过浅层地下水取水、浅层和深层混合水取水以及水质状况分析,确定水源的取水方式、取水深度、取用水水质达标状况等等,为满足工农业生产用水和有效保护地下水资源提供科学依据。     

采矿排水对周边水环境影响分析

矿床采选过程中,不可避免地造成一定的外排废水,从而可能影响到周边地表水或地下水水质,为此,本文选取安徽省霍邱县铁矿群为例,应用模糊层次综合评价法以及改进的层次分析法,通过分析沿岗河及其支流采集的水样的水质指标测定结果,对矿区周边地表水的水质进行了评价。评价结果表明:各监测断面的水质均达到Ⅰ类水标准,说明在监测时段内,采矿外排水还未对周边地表水环境产生影响。     

地下水质量影响因素识别与定量评价——以广西桂林会仙湿地为例

近年来,在人类活动强烈的干扰下,湿地地下水环境日益恶化。传统的地下水质量评价方法因未区分天然高背景和人为污染的影响,评价结果不能全面、真实、可靠地表示出水质的实际状态。笔者等选取地下水主要超标指标进行因子分析,并根据各因子的得分和方差贡献率计算各采样点得分,并最终计算因子影响下的综合得分。综合评价结果表明,研究区地下水主要有3个影响因子,因子1主要为天然高背景引起的高铁(TFe),锰(Mn)和铝(Al),因子2为农业及生活污水影响导致的NH⁺₄、高锰酸钾指数(COD_Mn)和NO^-₂超标,因子3为天然与人为复合影响导致的I^-污染。计算得出的综合影响程度与传统的水质评价结果吻合,综合影响程度得分图不仅可以得出地下水质信息,还可根据确定的因子得出天然与人为对地下水质的影响。     

Chemometric approach integrated with capillary electrophoresis for the investigation of public water system sources and quality

A chemometric approach coupled with capillary electrophoresis based on the hierarchical cluster analysis and principal component analysis has been applied for the investigation of the water quality in the Golcuk-Isparta region (Lake District of Turkey). In the research area, Egirdir Lake, Golcuk Lake and surrounding ground and domestic waters have been utilized as drinking water resources. Golcuk Lake is distinctive in terms of high fluoride content (3.50 ± 0.21 mg/mL) which is endemic in volcanic areas where the water flow through volcanic rocks and sediments. Based on the analysis of major anions chloride, sulfate, nitrate and fluoride with capillary electrophoresis, twenty-four drinking water sampling sites in the research area were classified into four classes using the hierarchical cluster and principal component analysis. Combining the research area investigation results of hierarchical cluster and principal component analysis, it was found that fluoride concentration is the major diagnostic variable to determine the quality of drinking waters, and all the other anions are the important classification factors to predict the resources of the drinking water samples, individually. To sum up, this study reveals the potential of the use of capillary electrophoresis in combination with chemometric techniques for the determination of the quality and origin of drinking waters.     

地下水质量影响因素识别与定量评价——以广西桂林会仙湿地为例

近年来,在人类活动强烈的干扰下,湿地地下水环境日益恶化。传统的地下水质量评价方法因未区分天然高背景和人为污染的影响,评价结果不能全面、真实、可靠地表示出水质的实际状态。笔者等选取地下水主要超标指标进行因子分析,并根据各因子的得分和方差贡献率计算各采样点得分,并最终计算因子影响下的综合得分。综合评价结果表明,研究区地下水主要有3个影响因子,因子1主要为天然高背景引起的高铁（TFe）,锰（Mn）和铝（Al）,因子2为农业及生活污水影响导致的NH+4、CODMn和NO-2超标,因子3为天然与人为复合影响导致的I-污染。计算得出的综合影响程度与传统的水质评价结果吻合,综合影响程度得分图不仅可以得出地下水质信息,还可根据确定的因子得出天然与人为对地下水质的影响。     

Evaluation of graphical and multivariate statistical methods for classification of water chemistry data

A robust classification scheme for partitioning water chemistry samples into homogeneous groups is an important tool for the characterization of hydrologic systems. In this paper we test the performance of the many available graphical and statistical methodologies used to classify water samples including: Collins bar diagram, pie diagram, Stiff pattern diagram, Schoeller plot, Piper diagram, Q-mode hierarchical cluster analysis, K-means clustering, principal components analysis, and fuzzy k-means clustering. All the methods are discussed and compared as to their ability to cluster, ease of use, and ease of interpretation. In addition, several issues related to data preparation, database editing, data-gap filling, data screening, and data quality assurance are discussed and a database construction methodology is presented. The use of graphical techniques proved to have limitations compared with the multivariate methods for large data sets. Principal components analysis is useful for data reduction and to assess the continuity/overlap of clusters or clustering/similarities in the data. The most efficient grouping was achieved by statistical clustering techniques. However, these techniques do not provide information on the chemistry of the statistical groups. The combination of graphical and statistical techniques provides a consistent and objective means to classify large numbers of samples while retaining the ease of classic graphical presentations. Electronic Publication     

Research on soil multi-media environmental pollution around a Pb-Zn mining and smelting plant in the karst area of Guangxi Zhuang Autonomous Region,Southwest China

The method of principal component analysis was applied to systematical research on the soil multi-media environment, including soil, surface water, ground water, waterbody sediment and agricultural crops, as well as pollution-inducing wastewater, mullock (or waste ore) and slag in the periphery of a large-sized Pb-Zn mining and smelting plant in a karst area of Guangxi Zhuang Autonomous Region. The results revealed that soils in the area studied have been heavily polluted by Cd, Zn, Pb and Hg, and the levels of these metals in the samples of agricultural crop greatly exceed the standards. The above-mentioned pollutants exist in all soil-multi-media environments. The mullock, slag, wastewater, surface water, ground water, soil, and agricultural crops constitute a composite ecological chain. Therefore, the improper disposal of mullock and slag, and the use of polluted wastewater for agricultural irrigation are the main causes of soil pollution. Heavy metals in the soil have three transition progresses: point (improved soil with slag, ground water inflow plot), linear (river transition) and non-point transition (regional pollution by slag) patterns, and the tailing yard is the most important locus for heavy metals to release into the environment.     

Evaluation of the processes affecting vertical water chemistry in an alluvial aquifer of Mankyeong Watershed, Korea, using multivariate statistical analyses

Vertical variations of redox chemistry and groundwater quality were investigated in an alluvial aquifer beneath an agricultural area, in which deep groundwaters are free of NO₃, Fe, and Mn problems that are frequently encountered during the development of alluvial groundwaters. This study was performed to identify and evaluate vertical chemical processes attenuating these chemical species in the study area. For this study, the processes affecting groundwater chemistry were identified by factor analysis (FA) and the groundwater samples collected from six multilevel samplers were hierarchically classified into three different redox zones by cluster analysis (CA) based on the similarity of geochemical features. FA results indicated three major factors affecting the overall water chemistry: agricultural activities (factor 1), redox reactions (factor 2), and remnant seawater (factor 3). The groundwater quality in the study area was revealed to be controlled by a series of different redox reactions, resulting in different redox zones as a function of depth. It was also revealed that the low Fe and Mn levels in the groundwater of the deeper part are associated with sulfate reduction, which led to precipitation of Fe as iron sulfide and adsorption of Mn on it.     

水质站网规划研究中几个问题的探讨

在进行中国水质站网规划布设合理的性研究中，按河流水系将全国国土分为若干水质站网规划单元分区，然后运用主成分聚类方法进行单元分区类型的划分，作为水质站网规划的基础。在同一类型单元分区内，运用模糊集合聚类方法，将分区内的水质进行分类，以确定水质站的布设密度，并对每一水质参数的采亲频次进行分析研究，以指导确定其采样频次。