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1.
In this study, a methodology for clustering 18 lakes in Alberta, Canada using the data of 19 water quality parameters for a period of 11 years (1988–2002) is presented. The methods consist of (i) principal component analysis (PCA) to determine the dominant water quality parameters, (ii) cluster analysis techniques to develop the characteristics of the clusters, and (iii) pattern‐match lakes to determine the appropriate cluster for each of the lakes. The PCA revealed that three principal components (PCs) were able to explain ～88% of the variability and the dominant water quality parameters were total dissolved solids, total phosphorus, and chlorophyll‐a. We obtained five clusters for the period 1994–1997 by using the dominant parameters with water quality deteriorating as the cluster number increased from 1 to 5. Upon matching cluster patterns with the entire dataset, it was observed that some of the lakes belonged to the same cluster all the time (e.g., cluster 1 for lakes Elkwater, Gregg, and Jarvis; cluster 3 for Sturgeon; cluster 4 for Moonshine; and cluster 5 for Saskatoon), while others changed with time. This methodology could be applied in other regions of the world to identify the most suitable source waters and prioritize their management. It could be helpful to analyze the natural controlling processes, pollution types, impact of seasonal changes and overall quality of source waters. This methodology could be used for monitoring water bodies in a cost effective and efficient way by sampling only less number of dominant parameters instead of using a large set of parameters. 相似文献
2.
This study employed three chemometric data mining techniques (factor analysis (FA), cluster analysis (CA), and discriminant analysis (DA)) to identify the latent structure of a water quality (WQ) dataset pertaining to Kinta River (Malaysia) and to classify eight WQ monitoring stations along the river into groups of similar WQ characteristics. FA identified the WQ parameters responsible for variations in Kinta River's WQ and accentuated the roles of weathering and surface runoff in determining the river's WQ. CA grouped the monitoring locations into a cluster of low levels of water pollution (the two uppermost monitoring stations) and another of relatively high levels of river pollution (the mid-, and down-stream stations). DA confirmed these clusters and produced a discriminant function which can predict the cluster membership of new and/or unknown samples. These chemometric techniques highlight the potential for reasonably reducing the number of WQVs and monitoring stations for long-term monitoring purposes. 相似文献
3.
In the study, multivariate statistical methods including principal component analysis (PCA)/factor analysis (FA) and cluster analysis (CA) were applied to analyze surface water quality data sets obtained from the Huaihe River segment of Bengbu (HRSB) and generated during 2 years (2011–2012) monitoring of 19 parameters at 7 sampling sites. The results of PCA for 7 sampling sites revealed that the first four components of PCA showed 94.89% of the total variance in the data sets of HRSB. The Principal components (Factors) obtained from FA indicated that the parameters for water quality variations were mainly related to heavy metals (Pb, Mn, Zn and Fe) and organic related parameters (COD, PI and DO). The results revealed that the major causes of water quality deterioration were related to inflow of industrial, domestic and agricultural effluents into the Huaihe River. Three significant sampling locations—(sites 2, 3 and 4), (sites 1 and 5) and (sites 6 and 7)—were detected on the basis of similarity of their water quality. Thus, these methods were believed to be valuable to help water resources managers understand complex nature of water quality issues and determine the priorities to improve water quality. 相似文献
4.
Seasonal and spatial variability of water quality parameters in the Port of Genoa, Italy, from 2000 to 2007 总被引：1，自引：0，他引：1
This paper presents the results of the statistical analysis of a set of physico-chemical and biological water quality parameters, monthly collected from 2000 to 2007 in the Genoa Harbour area (Ligurian Sea). We applied multivariate methods, such as principal component analysis (PCA) and dynamic factor analysis (DFA) for investigating the spatial and temporal variability and for providing important background information on pollution problems in the region. PCA evidenced the role of the sewage and river discharges and of the exchanges with the open sea in determining the harbour water quality. DFA was used to estimate underlying common trends in the time series. The DFA results partly show a general improvement of water quality over the 8-years period. However, in other areas, we found inter-annual variations but no significant multi-annual trend. Furthermore, we included meteorological variables in our statistical analyses because of their potential influence on the water quality parameters. These natural forcings explain part of the variability in water quality parameters that are superimposed on the dominating anthropogenic pollution factors. 相似文献
5.
Water Resources - The present study is an attempt to apply principal component analysis (PCA) for spatial assessment of water quality parameters that are responsible for water quality deterioration... 相似文献
6.
The present study demonstrates the usefulness of principal component analysis in condensing and interpreting multivariate time‐series of water quality data. In a case study the water quality system of the lock‐regulated part of the River Neckar (Germany) was analysed, with special emphasis on the oxygen budget. Pooled data of ten water quality parameters and discharge, which had been determined at six stations along a 200 km reach of the river between the years 1993 and 1998, were subjected to principal component analysis. The analysis yielded four stable principal components, explaining 72% of the total variance of the 11 parameters. The four components could be interpreted confidently in terms of underlying processes: biological activity, dilution by high discharge, seasonal effects and the influence of wastewater. From analysing the data of single stations separately, these processes were found to be active throughout the complete reach. Considering the oxygen budget of the river, the variance of biological activity, representing the counteracting processes of primary production and microbial degradation, was found to be most important. This principal component explained 79% of the observed variance of oxygen saturation. In contrast, the analysis of a reduced data set from the 1970s showed that oxygen saturation was then dominated by discharge and temperature variations. The findings indicate that the oxygen budget used to be governed directly by the emission of degradable matter, whereas nowadays eutrophication is most important for extreme oxygen concentrations. Therefore, controlling eutrophication has to be the primary goal, in order to mitigate the rare episodes of pronounced oxygen over‐ and undersaturation in the future. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
7.
Chemometrics data analysis of marine water quality and source identification in Southern Hong Kong 总被引：3，自引：0，他引：3
Various chemometric methods were used to analyze data sets of marine water quality for 19 parameters measured at 16 different sites of southern Hong Kong from 2000 to 2004 (18,240 observations), to determine temporal and spatial variations in marine water quality and identify pollution sources. Hierarchical cluster analysis (CA) grouped the 12 months into three periods (January-April, May-August and September-December) and the 16 sampling sites into two groups (A and B) based on similarities in marine water-quality characteristics. Discriminant analysis (DA) was important in data reduction because it used only eight parameters (TEMP, TURB, Si, NO(3)(-)-N, NH(4)(+)-N, NO(2)(-)-N, DO, and Chl-a) to correctly assign about 86% of the cases, and five parameters (SD, NH(4)(+)-N, TP, NO(2)(-)-N, and BOD(5)) to correctly assign >81.15% of the cases. In addition, principal component analysis (PCA) identified four latent pollution sources for groups A and B: organic/eutrophication pollution, natural pollution, mineral pollution, and nutrient/fecal pollution. Furthermore, during the second and third periods, all sites received more organic/eutrophication pollution and natural pollution than in the first period. SM5, SM6, SM17, SM10, SM11, SM12, and SM13 (second period) were affected by organic and eutrophication pollution, whereas SM3 (third period) and SM9 (second period) were influenced by natural pollution. However, differences between mineral pollution and nutrient/fecal pollution were not significant among the three periods. SM17 and SM10 were affected by mineral pollution, whereas SM4 and SM9 were highly polluted by nitrogenous nutrient/fecal pollution. 相似文献
8.
Abstract A case study is presented for the application of statistical and geostatistical methods to the problem of estimating groundwater quality variables. This methodology has been applied to the investigation of the detrital aquifer of the Bajo Andarax (Almería, Spain). The use of principal components analysis is proposed, as a first step, for identifying relevant types of groundwater and the processes that bring about a change in their quality. As a result of this application, three factors were obtained, which were used as three new variables (VI: sulphate influence; V2: thermal influence; and V3: marine influence). Analysis of their spatial distribution was performed through the calculation of experimental and theoretical variograms, which served as input for geostatistical modelling using ordinary block kriging. This analysis has allowed a probabilistic representation of the data to be obtained by mapping the three variables throughout the aquifer for each sampling point. In this way, one can evaluate the spatial and temporal variation of the principal physico-chemical processes associated with the three variables VI, V2 and V3 implicated in the groundwater quality of the detrital aquifer. 相似文献
9.
Contamination of Hospital Wastewater with Hazardous Compounds as Defined by § 7a WHG In total, 45 samples of hospital wastewater obtained from different origins (total wastewater, nursing, and laboratories) were investigated using chemical analyses as well as biological testing methods. In parallel, the consumption of several product groups relevant to the wastewater has been calculated. The water consumption strongly influenced the quality of the corresponding wastewater. Most of the values of the chemical parameters determined were found within a range as would have been expected for municipal wastewater. The AOX concentrations were distinctly elevated (0.41 mg/L in total wastewater and 0.95 mg/L in nursing wastewater). As could be shown by the calculated consumption of different compounds, the iodoferous X-ray contrast media represented a predominant proportion of the total AOX load of the clinical wastewaters tested. The values of some of the total wastewater samples and the laboratory wastewater samples showed a high toxicity as determined using the daphnia and luminescent bacteria tests. Using Ames and hamster cell tests, 5 out of 23 samples in the clinical area and 7 out of 9 samples from the laboratories turned out to be mutagenic. The origin of this mutagenic potential could not be determined though. 相似文献
10.
运用主成分分离及线性区段等方法 ,使早白垩世样品明显分离出二组磁组分 .叠加剩磁为喜山期重磁化 ,特征剩磁明显偏离现代地磁场方向 ,经倾斜校正后 ,有很好的一致性并通过了倒转检验 ,给出塔里木地块库车坳陷早白垩世巴西盖组古地磁新数据 .综合已有的古地磁结果 ,获得了塔里木地块早白垩世平均剩磁方向及平均古地磁极 ,阐明了塔里木地块早白垩世磁倾角明显偏低这一现象 .分析导致磁倾角偏低的诸多因素 ,认为压实作用可能是导致磁倾角偏低的重要因素之一 . 相似文献
11.
主成分分析方法利用低阶主成分重构航空电磁数据,解决了航空电磁探测中噪声与数据在频谱重叠情况下的噪声压制问题,但是参与重构的低阶主成分仍包含高频空间噪声,影响数据成像精度.本文提出的主成分滤波重构去噪方法,根据自适应窗宽平滑算法,设计了主成分低通滤波器组,对参与重构的低阶主成分进行测线滤波,再将滤波后的低阶主成分重构为电磁信号,不仅可以去除低阶主成分中的高频空间噪声,而且去除了高阶主成分包含的不相关噪声.仿真数据的去噪结果表明,主成分滤波重构获得较高的信噪比,较常规测线滤波与主成分重构分别提高了10.96dB和2.52dB;电导率深度成像结果证明了主成分滤波重构方法能够提高地下深部异常体的识别能力.最后通过实测数据的成像结果进一步验证了本文研究的主成分滤波重构去噪方法的有效性. 相似文献
12.
The spatial and temporal patterns of water quality in Kuwait Bay have been investigated using data from six stations between 2009 and 2011. The results showed that most of water quality parameters such as phosphorus (PO4), nitrate (NO3), dissolved oxygen (DO), and Total Suspended Solids (TSS) fluctuated over time and space. Based on Water Quality Index (WQI) data, six stations were significantly clustered into two main classes using cluster analysis, one group located in western side of the Bay, and other in eastern side. Three principal components are responsible for water quality variations in the Bay. The first component included DO and pH. The second included PO4, TSS and NO3, and the last component contained seawater temperature and turbidity. The spatial and temporal patterns of water quality in Kuwait Bay are mainly controlled by seasonal variations and discharges from point sources of pollution along Kuwait Bay’s coast as well as from Shatt Al-Arab River. 相似文献
13.
时间域航空电磁数据往往在测量过程中受到天然和人文噪声的干扰.如果不能很好滤除这些电磁噪声,那么将会降低资料质量、影响反演的精度,甚至获得错误的解释结果.本文提出了一种基于核主成分分析的去噪方法,通过核主成分分析提取叠加后衰减曲线的主成分,然后使用能量占比方法分离反映地下介质的有效信号和噪声,最后使用反映地下介质的特定成分进行重构.本文所推荐的去噪方法不仅能剔除天然噪声,例如天电产生的尖脉冲或者振荡,而且能有效地抑制人文噪声.分别使用基于核主成分分析的去噪方法,以及AeroTEM软件的处理方法对同样的吊舱式时间域直升机航空电磁勘查系统实测数据进行处理,并比较其结果.处理结果表明：所推荐的去噪方法要优于AeroTEM软件. 相似文献
14.
《Acta Geochimica》2015,(4)
Chemometric techniques and pollution assessment indices were applied to determine the source and intensity of pollution in the Sirsa River, Himachal Pradesh,India. Results show EC, Cr, Fe, Mn, and Ni were above the permissible limit as per the Bureau of Indian Standards.The heavy metal pollution index(HPI) and contamination index(Cd) provided contrasting outcome and poor correlation was observed. A heavy metal evaluation index(HEI)method was developed using a multiple of the mean and correlation coefficient values to provide an alternative pollution classification. The criteria of HEI adopted for reclassification of HPI and Cdproduced comparable results; 40 % samples were labeled as low contamination,50 % as medium contamination, and 10 % as high contamination for all indices. Principal component analysis along with cluster analysis was used to identify the main factors responsible for degradation of water quality,namely discharge of industrial effluent, river bed mining,agricultural runoff, and minor natural or geogenic input.The methods and chemometric study proposed here can be used as effective tools to gather information about water quality and water resource management. 相似文献
15.
Spatial and temporal patterns of the long-range extreme monthly Elbe River flows across Germany are investigated, using various statistical methods, among others, principal component and wavelet analysis. Characteristic time scales are derived for various time series statistics. The wavelet analysis of the raw river discharge data as well as of the major principal component reveal the main oscillatory components and their temporal behavior, namely low frequency oscillations at interannual (6.9 yr) and interdecadal (13.9 yr) scales. The EOFs at ungauged stations are estimated from the principal components of the observed time series sampled over a limited time span whose length equals the major temporal variability scale (≈7 yr). The EOFs (empirical orthogonal functions) obtained in this way are subsequently used to simulate long-range flows at these locations. A comparison of this method with linear interpolation and ordinary kriging of the EOF shows the superiority of the former in representing the distributional properties of the observed time series. The simulated time series preserve also short and long-memory. 相似文献
16.
Jelena S. Kiurski Ivana B. Oros Vesna S. Kecic Ilija M. Kovacevic Snezana M. Aksentijevic 《Stochastic Environmental Research and Risk Assessment (SERRA)》2016,30(4):1289-1300
The paper includes the identification of the main factors responsible for the temporal variations of indoor pollutants during three daily intervals in a photocopying shop. The measurements of concentration levels of total volatile organic compounds, ozone, carbon monoxide, carbon dioxide, nitrogen dioxide, ammonia, perchloroethylene and non-methane hydrocarbons were performed. The individual concentrations of target pollutants were subjected to principal component analysis (PCA) using a software XLSTAT 2014.1.10. Pearson correlation model indicated the relatively weak correlation between the investigated pollutants in a photocopying environment. PCA extracted three principal components (PCs) from the indoor air pollution data set. Obtained PCs explained 56.72 % of the total variance. The summarized biplots showed which pollutants are responsible for photocopying indoor pollution per sampling day/sampling point/time interval/number of measurement. The results pointed out that the main PCs were related to the usage of toners, electrostatic discharge, heating of photocopiers as well as general intensifying of photocopying processes. 相似文献
17.
Spatial distribution of heavy metals in Hong Kong's marine sediments and their human impacts: a GIS-based chemometric approach 总被引：6，自引：0，他引：6
A geographic information system (GIS)-based chemometric approach was applied to investigate the spatial distribution patterns of heavy metals in marine sediments and to identify spatial human impacts on global and local scales. Twelve metals (Zn, V, Ni, Mn, Pb, Cu, Cd, Ba, Hg, Fe, Cr and Al) were surveyed twice annually at 59 sites in Hong Kong from 1998 to 2004. Cluster analysis classified the entire coastal area into three areas on a global scale, representing different pollution levels. Backward discriminant analysis, with 84.5% correct assignments, identified Zn, Pb, Cu, Cd, V, and Fe as significant variables affecting spatial variation on a local scale. Enrichment factors indicated that Cu, Cr, and Zn were derived from human impacts while Al, Ba, Mn, V and Fe originated from rock weathering. Principal component analysis further subdivided human impacts and their affected areas in each area, explaining 87%, 84% and 87% of the total variances, respectively. The primary anthropogenic sources in the three areas were (i) anti-fouling paint and domestic sewage; (ii) surface runoff, wastewater, vehicle emissions and marine transportation; and (iii) ship repainting, dental clinics, electronic/chemical industries and leaded fuel, respectively. Moreover, GIS-based spatial analysis facilitated chemometric methods. 相似文献
18.
Khouloud Gader Ahlem Gara Marnik Vanclooster Slaheddine Khlifi Mohamed Slimani 《水文科学杂志》2020,65(8):1300-1315
ABSTRACT Predicting the impacts of climate change on water resources remains a challenging task and requires a good understanding of the dynamics of the forcing terms in the past. In this study, the variability of precipitation and drought patterns is studied over the Mediterranean catchment of the Medjerda in Tunisia based on an observed rainfall dataset collected at 41 raingauges during the period 1973–2012. The standardized precipitation index and the aridity index were used to characterize drought variability. Multivariate and geostatistical techniques were further employed to identify the spatial variability of annual rainfall. The results show that the Medjerda is marked by a significant spatio-temporal variability of drought, with varying extreme wet and dry events. Four regions with distinct rainfall regimes are identified by utilizing the K-means cluster analysis. A principal component analysis identifies the variables that are responsible for the relationships between precipitation and drought variability. 相似文献
19.
Identification of fuel samples from the Prestige wreckage by pattern recognition methods 总被引：1，自引：0，他引：1
Fernández-Varela R Andrade JM Muniategui S Prada D Ramírez-Villalobos F 《Marine pollution bulletin》2008,56(2):335-347
A set of 34 worldwide crude oils, 12 distilled products (kerosene, gas oils, and fuel oils) and 45 oil samples taken from several Galician beaches (NW Spain) after the wreckage of the Prestige tanker off the Galician coast was studied. Gas chromatography with flame ionization detection was combined with chemometric multivariate pattern recognition methods (principal components analysis, cluster analysis and Kohonen neural networks) to differentiate and characterize the Prestige fuel oil. All multivariate studies differentiated between several groups of crude oils, fuel oils, distilled products, and samples belonging to the Prestige's wreck and samples from other illegal discharges. In addition, a reduced set of 13 n-alkanes out of 36, were statistically selected by Procrustes Rotation to cope with the main patterns in the datasets. These variables retained the most important characteristics of the data set and lead to a fast and cheap analytical screening methodology. 相似文献
20.
Forecasting of Air Quality Index in Delhi Using Neural Network Based on Principal Component Analysis
Forecasting of the air quality index (AQI) is one of the topics of air quality research today as it is useful to assess the effects of air pollutants on human health in urban areas. It has been learned in the last decade that airborne pollution has been a serious and will be a major problem in Delhi in the next few years. The air quality index is a number, based on the comprehensive effect of concentrations of major air pollutants, used by Government agencies to characterize the quality of the air at different locations, which is also used for local and regional air quality management in many metro cities of the world. Thus, the main objective of the present study is to forecast the daily AQI through a neural network based on principal component analysis (PCA). The AQI of criteria air pollutants has been forecasted using the previous day’s AQI and meteorological variables, which have been found to be nearly same for weekends and weekdays. The principal components of a neural network based on PCA (PCA-neural network) have been computed using a correlation matrix of input data. The evaluation of the PCA-neural network model has been made by comparing its results with the results of the neural network and observed values during 2000–2006 in four different seasons through statistical parameters, which reveal that the PCA-neural network is performing better than the neural network in all of the four seasons. 相似文献