Pattern Recognition Techniques for the Evaluation of Spatial and Temporal Variations in Water Quality. A Case Study:

Alberto, Wunderlin Daniel; Pilar, Dı́az Marı́a del; Amé, María Valeria; Fabiana, Pesce Silvia; Cecilia, Hued Andrea; Ángeles, Bistoni Marı́a de los

doi:10.1016/s0043-1354(00)00592-3

Cited by 819 publications

(253 citation statements)

References 13 publications

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“…In previous studies, multivariate statistical techniques, such as cluster analysis (CA), principal component analysis (PCA), factor analysis (FA), discriminant analysis (DA), and multivariate regression analysis (MRA), combined with geographic information system (GIS) tools, were used to interpret large and complex datasets to evaluate temporal-spatial variations, predicate trends, and identify possible impact factors/sources in water quality. For example, Alberto et al (2001) compared the results of CA, FA/PCA, and DA to evaluate both spatial and temporal changes in Suquia River (Argentina) water quality. PCA has been used to extract the factors associated with hydrochemistry variability in the Passaic River (USA) (Bengraı ne and Marhaba 2003) and seasonal correlations of water quality parameters in the lower St. Johns River (USA) (Ouyang et al 2006).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of spatial-temporal variations and trends in surface water quality across a rural-suburban-urban interface

Mei

Liao

Zhu

et al. 2014

Environ Sci Pollut Res

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Water quality degradation is often a severe consequence of rapid economic expansion in developing countries. Methods to assess spatial-temporal patterns and trends in water quality are essential for guiding adaptive management efforts aimed at water quality remediation. Temporal and spatial patterns of surface water quality were investigated for 54 monitoring sites in the Wen-Rui Tang River watershed of eastern China to identify such patterns in water quality occurring across a rural-suburban-urban interface. Twenty physical and chemical water quality parameters were analyzed in surface waters collected once every 4-8 weeks from 2000 to 2010. Temporal and spatial variations among water quality parameters were assessed between seasons (wet/dry) and among major land use zones (urban/suburban/rural). Factor analysis was used to identify parameters that were important in assessing seasonal and spatial variations in water quality. Results revealed that parameters related to organic pollutants (dissolved oxygen (DO), chemical oxygen demand (manganese) (COD Mn ), and 5-day biochemical oxygen demand (BOD 5 )), nutrients (ammonia nitrogen (NH 4 + -N), total nitrogen (TN), total phosphorus (TP)), and salt concentration (electrical conductivity (EC)) were the most important parameters contributing to water quality variation. Collectively, they explained 70.9 % of the total variance. A trend study using the seasonal Kendall test revealed reductions in COD Mn , BOD 5 , NH 4 + -N, petrol, V-phen, and EC concentrations over the 11-year study period. Cluster analysis was employed to evaluate variation among 14 sampling sites representative of dominant land use categories and indicated three, three, and four clusters based on organic, nutrient, and salt water quality characteristics, respectively. Factors that are typically responsible for water quality degradation (including population, topography, and land use) showed no strong correlation with water quality trends implying considerable point source inputs in the watershed. The results of this study help inform ongoing water quality remediation efforts by documenting trends in water quality across various land use zones.

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Section: Introductionmentioning

confidence: 99%

Evaluation of spatial-temporal variations and trends in surface water quality across a rural-suburban-urban interface

Mei

Liao

Zhu

et al. 2014

Environ Sci Pollut Res

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“…Environmetrics have also been applied to characterize and evaluate the surface and freshwater quality as well as verifying spatial variations caused by natural and anthropogenic factors (Helena et al 2000;Singh et al 2005;Juahir et al 2008). Recently, environmetric methods have become an important tool in environmental sciences (Brown et al 1994(Brown et al , 1996 to reveal and evaluate complex relationships in a wide variety of environmental applications (Alberto et al 2001). The most common environmetric methods used for clustering are the hierarchical agglomerative cluster analysis (HACA) and the principal components analysis (PCA) with factor analysis (FA; Kannel et al 2007).…”

Section: Introductionmentioning

confidence: 99%

Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques

Juahir

Zain

Yusoff

et al. 2010

Environ Monit Assess

289

196

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This study investigates the spatial water quality pattern of seven stations located along the main Langat River. Environmetric methods, namely, the hierarchical agglomerative cluster analysis (HACA), the discriminant analysis (DA), the principal component analysis (PCA), and the factor analysis (FA), were used to study the spatial variations of the most significant water quality variables and to determine the origin of pollution sources. Twenty-three water quality parameters were initially selected and analyzed. Three spatial clusters were formed based on HACA. These clusters are designated as downstream of Langat river, middle stream of Langat river, and upstream of Langat River regions. Forward and backward stepwise DA managed to discriminate six and seven water quality variables, respectively, from the original 23 variables. PCA and FA (varimax functionality) were used to investigate the origin of each water quality variable due to land use activities based on the three clustered regions. Seven principal components (PCs) were obtained with 81% total variation for the high-pollution source (HPS) region, while six PCs with 71% and 79% total variances were obtained for the moderatepollution source (MPS) and low-pollution source (LPS) regions, respectively. The pollution sources for the HPS and MPS are of anthropogenic sources (industrial, municipal waste, and agricultural runoff). For the LPS region, the domestic and agricultural runoffs are the main sources of pollution. From this study, we can conclude that the application of environmetric methods can reveal meaningful information on the spatial variability of a large and complex river water quality data.

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“…For example, principal components analysis (PCA), hierarchical cluster analysis (HCA) and discriminant analysis (DA) have been extensively used in environmental hydrogeology to characterize differences in surface water chemistry, including contamination in large watersheds (Cloutier et al, 2008;Farnham et al, 2003;Alberto et al, 2001;Cortecci et al, 2009;Belkhiri et al, 2010). Graphical approaches such as Piper diagrams (Piper, 1944) geochemically classify surface water quality into hydro-geochemical facies of water (Back, 1966;Frey et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Using integrated multivariate statistics to assess the hydrochemistry of surface water quality, Lake Taihu basin, China

Brower

Siegel

et al. 2014

J Limnol

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We investigated the hydrochemical setting of Lake Taihu (eastern China) Key words: Principal component analysis, discriminant analysis, hierarchical cluster analysis, geographical information system (gis), Key words: Principal component analysis, discriminant analysis, hierarchical cluster analysis, geographical information system (gis), N o n -c o m m e r c i a lThe demand for freshwater needed for increasing crop The demand for freshwater needed for increasing crop production and industrialization occurs almost everywhere production and industrialization occurs almost everywhere in China and these conflicting needs have led to widespread in China and these conflicting needs have led to widespread water contamination. Taihu Lake (eastern China) notably water contamination. Taihu Lake (eastern China) notably suffers periodic hyper-eutrophication and drinking water suffers periodic hyper-eutrophication and drinking water deterioration, from heavy nutrient loadings from all of these deterioration, from heavy nutrient loadings from all of these sources This pollution has led to shortages of freshwater sources This pollution has led to shortages of freshwater for the City of Wuxi and other nearby cities. Taihu Lake, for the City of Wuxi and other nearby cities. Taihu Lake, for the City of Wuxi and other nearby cities. Taihu Lake, water contamination. Taihu Lake (eastern China) notably water contamination. Taihu Lake (eastern China) notably water contamination. Taihu Lake (eastern China) notably N o n water contamination. Taihu Lake (eastern China) notably water contamination. Taihu Lake (eastern China) notably water contamination. Taihu Lake (eastern China) notably N o n water contamination. Taihu Lake (eastern China) notably N o n water contamination. Taihu Lake (eastern China) notably suffers periodic hyper-eutrophication and drinking water suffers periodic hyper-eutrophication and drinking water suffers periodic hyper-eutrophication and drinking water N o n suffers periodic hyper-eutrophication and drinking water suffers periodic hyper-eutrophication and drinking water suffers periodic hyper-eutrophication and drinking water suffers periodic hyper-eutrophication and drinking water suffers periodic hyper-eutrophication and drinking water suffers periodic hyper-eutrophication and drinking water N o n suffers periodic hyper-eutrophication and drinking water suffers periodic hyper-eutrophication and drinking water suffers periodic hyper-eutrophication and drinking water suffers periodic hyper-eutrophication and drinking water N o n suffers periodic hyper-eutrophication and drinking water deterioration, from heavy nutrient loadings from all of these deterioration, from heavy nutrient loadings from all of these deterioration, from heavy nutrient loadings from all of these N o n deterioration, from heavy nutrient loadings from all of these deterioration, from heavy nutrient loadings from all of these deterioration, from heavy nutrient loadings from all of these deterioration, from heavy nutrient loadings f...

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Pattern Recognition Techniques for the Evaluation of Spatial and Temporal Variations in Water Quality. A Case Study:

Cited by 819 publications

References 13 publications

Evaluation of spatial-temporal variations and trends in surface water quality across a rural-suburban-urban interface

Evaluation of spatial-temporal variations and trends in surface water quality across a rural-suburban-urban interface

Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques

Using integrated multivariate statistics to assess the hydrochemistry of surface water quality, Lake Taihu basin, China

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