Avaliação da qualidade das águas superficiais na circunscrição hidrográfica do rio Piranga utilizando análise estatística multivariada e não-paramétrica

No estado de Minas Gerais, as campanhas de coleta e análise da qualidade da água nos corpos hídricos contemplam até 51 variáveis, o que dificulta a análise e interpretação desse conjunto de dados e a identificação das variáveis determinantes para a qualidade da água. Diante disso, o objetivo deste trabalho foi identificar as principais fontes de poluição, bem como o comportamento da qualidade da água ao longo do tempo de monitoramento, por meio de diferentes análises estatísticas na circunscrição hidrográfica do rio Piranga. Pelos resultados obtidos, a análise fatorial/análise de componentes principais apontou a alta susceptibilidade que a bacia apresenta à erosão do solo, a contaminação pelo lançamento de efluentes domésticos e a variabilidade da qualidade das águas em virtude dos metais pesados. As variáveis Escherichia coli, ferro dissolvido, fósforo total e manganês total apresentaram os valores de violação da classe de enquadramento mais críticos. A análise de tendência mostrou padrões diferentes para o índice de qualidade da água e para as variáveis mais relevantes para a qualidade da água. Dentre as variáveis que compõe o índice, destacam-se as tendências de aumento de nitrato em todas as estações analisadas. De maneira geral, os resultados mostraram que a qualidade da água na área de estudo varia em função da erosão do solo, do alto grau de contaminação por efluentes domésticos, da poluição difusa advinda das áreas agrícolas e dos metais pesados, sendo as variáveis de qualidade da água vinculadas a estes fatores as mais importantes. Surface water quality assessment in the hydrographic region of the Piranga River using multivariate and non-parametric statistical analysis ABSTRACTIn the state of Minas Gerais, campaigns to collect and analyze water quality in water bodies include up to 51 variables, which makes it difficult to analyze and interpret this data set and to identify the determining variables for water quality. Therefore, the objective of this work was to identify the main sources of pollution, as well as the behavior of water quality over the monitoring time, through different statistical analyzes in the hydrographic region of the Piranga River. Based on the results obtained, the factor analysis/principal component analysis out the high susceptibility that the hydrographic region presents to soil erosion, contamination by the release of domestic effluents and the variability of water quality due to heavy metals. The variables Escherichia coli, dissolved iron, total phosphorus and total manganese presented the most critical values of violation of the framework class. The trend analysis showed different patterns for the water quality index and for the most relevant variables for water quality. Among the variables that make up the index, the trends of nitrate increase in all analyzed stations stand out. In general, the results showed that the water quality in the unit varies depending on soil erosion, the high degree of contamination by domestic effluents, the diffuse pollution from agricultural areas and heavy metals, with water quality variables being linked to these factors the most important.Keywords: environmental analysis, Minas Gerais, water pollution, water resources.

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Application of multivariate statistical techniques in the water quality assessment of Danube river, Serbia

Archives of Environmental Protection ◽

10.1515/aep-2015-0044 ◽

2015 ◽

Vol 41 (4) ◽

pp. 96-103 ◽

Cited By ~ 11

Author(s):

Danijela Voza ◽

Milovan Vukovic ◽

Ljiljana Takic ◽

Djordje Nikolic ◽

Ivana Mladenovic-Ranisavljevic

Keyword(s):

Water Quality ◽

Water Quality Management ◽

Surface Water Quality ◽

Principal Component ◽

Water Quality Assessment ◽

Water Quality Monitoring ◽

Danube River ◽

Multivariate Techniques ◽

Data Set ◽

Political Issue

AbstractThe aim of this article is to evaluate the quality of the Danube River in its course through Serbia as well as to demonstrate the possibilities for using three statistical methods: Principal Component Analysis (PCA), Factor Analysis (FA) and Cluster Analysis (CA) in the surface water quality management. Given that the Danube is an important trans-boundary river, thorough water quality monitoring by sampling at different distances during shorter and longer periods of time is not only ecological, but also a political issue. Monitoring was carried out at monthly intervals from January to December 2011, at 17 sampling sites. The obtained data set was treated by multivariate techniques in order, firstly, to identify the similarities and differences between sampling periods and locations, secondly, to recognize variables that affect the temporal and spatial water quality changes and thirdly, to present the anthropogenic impact on water quality parameters.

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Surface-water-quality assessment of the lower Kansas River basin, Kansas and Nebraska; dissolved oxygen and Escherichia coli bacteria in streams during low flow, July 1988 through July 1989

10.3133/wri944077 ◽

1995 ◽

Keyword(s):

Escherichia Coli ◽

Water Quality ◽

Surface Water ◽

Dissolved Oxygen ◽

Quality Assessment ◽

Surface Water Quality ◽

Water Quality Assessment ◽

Low Flow ◽

Kansas River ◽

Escherichia Coli Bacteria

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MIMR Criterion Application: Entropy Approach to Select the Optimal Quality Parameter Set Responsible for River Pollution

Sustainability ◽

10.3390/su12052078 ◽

2020 ◽

Vol 12 (5) ◽

pp. 2078

Author(s):

Domenica Mirauda ◽

Marco Ostoich

Keyword(s):

Water Quality ◽

Low Cost ◽

Surface Water Quality ◽

Principal Component ◽

Water Quality Assessment ◽

River Pollution ◽

Mitigation Measures ◽

Quality Level ◽

Maximum Information ◽

Optimal Quality

Surface water quality has a vital role when defining the sustainability of the ecological environment, public health, and the social and economic development of whole countries. Unfortunately, the rapid growth of the worldwide population together with the current climate change have mostly determined fluvial pollution. Therefore, the employment of effective methodologies, able to rapidly and easily obtain reliable information on the quality of rivers, is becoming fundamental for an efficient use of the resource and for the implementation of mitigation measures and actions. The Water Quality Index (WQI) is among the most widely used methods to provide a clear and complete picture of the contamination status of a river stressed by point and diffuse sources of natural and anthropic origin, leading the policy makers and end-users towards a more and more correct and sustainable management of the water resource. The parameter choice is one of the most important and complex phases and recent statistical techniques do not seem to show great objectivity and accuracy in the identification of the real water quality status. The present paper offers a new approach, based on entropy theory and known as the Maximum Information Minimum Redundancy (MIMR) criterion, to define the optimal subset of chemical, physical, and biological parameters, describing the variation of the river quality level in space and time and thus identifying its pollution sources. An algorithm was implemented for the MIMR criterion and applied to a sample basin of Northeast Italy in order to verify its reliability and accuracy. A comparison with the Principal Component Analysis (PCA) showed how the MIMR is more suitable and objective to obtain the optimal quality parameters set, especially when the amount of investigated variables is small, and can thus be a useful tool for fast and low-cost water quality assessment in rivers.

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Water Quality Assessment using Environmetrics and Pollution Indices in a Tropical River, Kerala, SW Coast of India

Current World Environment ◽

10.12944/cwe.15.1.04 ◽

2020 ◽

Vol 15 (1) ◽

pp. 11-23

Author(s):

S Sukanya ◽

Sabu Joseph

Keyword(s):

Water Quality ◽

Surface Water ◽

Pearson Correlation ◽

Pollution Index ◽

Surface Water Quality ◽

Principal Component ◽

Water Quality Assessment ◽

Organic Pollution ◽

Pollution Indices ◽

Heavy Load

Envirometrics and pollution indices are proxies to assess water quality of a wetland ecosystem. Hence, the present study is focused on establishing water quality and elucidating the pollution status of Karamana River (KR) in Kerala, SW coast of India. The Karamana River Basin – KRB (n=6th; L= 68 km, A=695 km2), is the main source of water for domestic and drinking purpose in Thiruvananthapuram city. The Killi River (n= 5th; L= 24 km, A= 102 km2), the largest tributary of KR, carry heavy load of pollutants mainly from city and joins KR towards its downstream side. For this study, about 12 sampling stations were selected along the KR from upstream to downstream (interval= ~3km), and water samples (n=12x2= 24) were collected during non-monsoon (NON) and monsoon (MON) of 2015 to assess the variability and sourcing of key hydrochemical variables. Environmetric methods, viz., Pearson Correlation and Principal Component Analysis (PCA) were applied for apportionment of pollution sources significantly responsible for the surface water quality. It was found that sewage effluents and seawater intrusion were the primary factors deteriorating water quality in downstream. Further, the results of water quality analyses and Pollution Indices, viz., Organic Pollution Index (OPI), Eutrophication Index (EI) and Comprehensive Pollution Index (CPI) indicate that lower reaches (L= ~4 km) of KR is seriously polluted. A distinct Zone of Pollution Influence (ZPI) has been delineated based on the indices and this attempt is first of its kind in KR. The present study provides several noteworthy contributions to the existing knowledge on the factors influencing surface water quality and serves as a baseline data for watershed managers and administrators.

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Multivariate statistical evaluation of dissolved heavy metals and a water quality assessment in the Lake Aha watershed, Southwest China

PeerJ ◽

10.7717/peerj.9660 ◽

2020 ◽

Vol 8 ◽

pp. e9660

Author(s):

Shilin Gao ◽

Zhuhong Wang ◽

Qixin Wu ◽

Jie Zeng

Keyword(s):

Heavy Metals ◽

Water Quality ◽

Risk Assessment ◽

Mine Drainage ◽

Principal Component ◽

Water Quality Assessment ◽

Multivariate Statistical ◽

Small Watersheds ◽

Dissolved Heavy Metals ◽

The Impact

Heavy metals are of public concern in aquatic ecosystems due to their growing release from industries and mining activities. This study investigated the sources, temporal-spatial distributions and water quality of dissolved heavy metals (Mn, Co, Al, Ni, Ba, V, Sb, Fe, Sr) in the Lake Aha watershed, an area under the influence of sewage and acid mining drainage. These heavy metals displayed significant spatial and temporal variabilities. The water quality index results (WQI values ranged from 3.21 to 15.64) and health risk assessment (all hazard indexes are below 1) indicated that dissolved heavy metals in this study pose a low risk for human health. Correlation analysis and principal component analysis indicated that Fe and Sr mainly presented a natural geological feature in the study area, and Mn, Co, Al and Ni were influenced by the acid coal mine drainage, whereas Ba, V and Sb were under the impact of local industrial or medical activities. This study provides new insights into the risk assessment of heavy metals in small watersheds.

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Water quality assessment of the Tano Basin in Ghana: a multivariate statistical approach

Applied Water Science ◽

10.1007/s13201-021-01374-9 ◽

2021 ◽

Vol 11 (2) ◽

Cited By ~ 1

Author(s):

Samuel Obiri ◽

Gloria Addico ◽

Saada Mohammed ◽

Wilson William Anku ◽

Humphry Darko ◽

...

Keyword(s):

Water Quality ◽

Electrical Conductivity ◽

Water Samples ◽

Anthropogenic Activities ◽

Principal Component ◽

Water Quality Assessment ◽

Total Variance ◽

Total Alkalinity ◽

Multivariate Statistical ◽

Data Set

AbstractMultivariate statistical techniques including principal component and factor analyses were applied in this study to assess the quality of surface water from Tano basin in Ghana. The water samples were obtained from three monitoring stations from January to October 2016. The obtained data set was analysed using multivariate statistical methods. The results obtained from Rho Spearman's correlation revealed that at P < 0.05 two-tailed, a positive correlation between pH and total dissolved solids, pH and alkalinity, pH and electrical conductivity, pH and major anions and cations such as SO4, F, Ca, K, Na and Mg was established. However, negative correlation existed between pH-colour, pH-turbidity and total suspended solids. The results of the principal component analysis show that the five principal components explain more than 91.57% of the total variance and hence can be relied upon for identification of the main sources of variation in the physicochemical properties of the water samples. Principal component 1 embodies about 54.26% of the variance and possesses a high loading for electrical conductivity, Na, Ca, K, Mg. Principal component 2, which also explains 33.94% of the total variance, holds high loadings for pH, SO4, HCO3, and total alkalinity. Component 3 also shows high loadings for TDS, TSS and conductivity, which account for 3.378% of the variation in the hydrochemistry. Components 4 and 5 show a joint influence of anthropogenic activities and partial ecological recovery system of the river and its basin which influence the overall water quality within the basin.

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Multivariate Water Quality Assessment of Renowned Pilgrim Spot, Gujarat, India: A Statistical Approach

Current World Environment ◽

10.12944/cwe.12.3.10 ◽

2017 ◽

Vol 12 (3) ◽

pp. 584-597

Author(s):

Sheju Thomas ◽

Hiren Soni ◽

Ashok Saxena

Keyword(s):

Water Quality ◽

Statistical Tests ◽

Sampling Site ◽

Surface Water Quality ◽

Principal Component ◽

Water Quality Assessment ◽

Quality Parameters ◽

Sodium Absorption ◽

Cross Sectional ◽

Base Exchange

Gomti Palustrine Habitat is one of the renowned pilgrimage ponds of Central Gujarat, India. In the present research, different statistical tests were applied to 21 water quality parameters to trace and delineate the status of water quality. The present study was undertaken for one year (December, 2012 to November, 2013) with monthly sampling covering three successive seasons (winter, summer, monsoon). Three permanent sampling stations (V1, V2, V3) were selected to cover the cross-sectional and diagonal regime of wetland. Ionic Signatures (IS) confirmed the wetland to be dominated with Ca and HCO3-, indicating leaching of minerals from drainage basins. Index of Base Exchange (IBE) supported the enrichment of Na+ ions in the water regime owing to clay horizons. Exchangeable Sodium Ratio (ESR) (1.416 meq/l) and Sodium Absorption Ratio (SAR) (1.367 meq/l) found to be minimal referring to leaching and dissolution of salts during precipitation. Surface water quality is exhibited by low Salinity and low Sodicity zone, can be used for irrigation purpose. Principal Component Analysis (PCA) identified a reduced number of mean of 3 varifactors indicating that 93.35% of temporal and spatial changes affect the water quality drastically. First factor from the factor analysis explained a total of 74.44% among TH, HCO3-, Mg, Cl, salinity and K+. One way ANOVA revealed that Sampling Site 2 is maximally loaded with aquatic pollutants, followed by Sampling Site 3 and Sampling Site 1 (Site description is given in the later section of the paper). These outcomes manifested prime necessity to restore the physical, chemical and biological integrity of water quality to revert the ecological balance of an aquatic ecosystem.

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