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

2015 ◽  
Vol 41 (4) ◽  
pp. 96-103 ◽  
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.

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

2021 ◽  
Vol 14 (2) ◽  
pp. 694
Author(s):  
Micael De Souza Fraga ◽  
Laura Thebit de Almeida ◽  
Marcel Carvalho Abreu ◽  
Felipe Bernardes Silva ◽  
Guilherme Barbosa Reis ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Heavy Metals ◽  
Water Quality ◽  
Soil Erosion ◽  
Surface Water Quality ◽  
Principal Component ◽  
Water Quality Assessment ◽  
Minas Gerais ◽  
Data Set ◽  
Domestic Effluents

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.

scholarly journals Danube water quality and assessment on ecotourism in the biosphere reserve ‘Bačko Podunavlje’ in Serbia

2020 ◽  
Vol 20 (4) ◽  
pp. 1215-1228
Author(s):  
Sanja Obradović ◽  
Milana Pantelić ◽  
Vladimir Stojanović ◽  
Aleksandra Tešin ◽  
Dragan Dolinaj
Keyword(s):  
Water Quality ◽  
Ecological Status ◽  
Biosphere Reserve ◽  
Surface Water Quality ◽  
Principal Component ◽  
Quality Parameters ◽  
Danube River ◽  
Multivariate Statistical ◽  
Limit Values ◽  
Starting Point

Abstract ‘Bačko Podunavlje’ represents one of the largest and the best-preserved wetland areas of the upper Danube. Water quality is crucial for nature in protected areas and ecotourism. The paper is based on data for the period 1992–2016. Using multivariate statistical analysis, water quality was defined. One-factor analysis of variations is the starting point for the analysis of time variables (annual and monthly analysis). The principal component analysis (PCA) of the ten quality parameters is in the three factors that determine the greatest impact on the change in water quality. Results revealed the satisfactory ecological status of the Danube River in these sections (Bezdan and Bogojevo) and there is no threat that the biodiversity of this area is endangered by poor water quality, which fully justifies the possibilities for intensive development of ecotourism in the biosphere reserve. Suspended solids are the only parameter that exceeds the allowed limit values in a larger number of measurements, especially in the summer period of the year. Other analyzed water quality parameters range within the allowed limit values for the second class of surface water quality based on the Law on Waters (Republic of Serbia) and in accordance with the Water Quality Classification Criteria of ICPDR.

scholarly journals A Multivariate and Spatiotemporal Analysis of Water Quality in Code River, Indonesia

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Mochamad A. Pratama ◽  
Yan D. Immanuel ◽  
Dwinanti R. Marthanty
Keyword(s):  
Water Quality ◽  
Land Cover ◽  
Agricultural Land ◽  
Water Quality Management ◽  
Temporal Trends ◽  
Oxygen Demand ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Quality Data ◽  
Water Quality Data

The efficacy of a water quality management strategy highly depends on the analysis of water quality data, which must be intensively analyzed from both spatial and temporal perspectives. This study aims to analyze spatial and temporal trends in water quality in Code River in Indonesia and correlate these with land use and land cover changes over a particular period. Water quality data consisting of 15 parameters and Landsat image data taken from 2011 to 2017 were collected and analyzed. We found that the concentrations of total dissolved solid, nitrite, nitrate, and zinc had increasing trends from upstream to downstream over time, whereas concentrations of parameter biological oxygen demand, cuprum, and fecal coliform consistently undermined water quality standards. This study also found that the proportion of natural vegetation land cover had a positive correlation with the quality of Code River’s water, whereas agricultural land and built-up areas were the most sensitive to water pollution in the river. Moreover, the principal component analysis of water quality data suggested that organic matter, metals, and domestic wastewater were the most important factors for explaining the total variability of water quality in Code River. This study demonstrates the application of a GIS-based multivariate analysis to the interpretation of water quality monitoring data, which could aid watershed stakeholders in developing data-driven intervention strategies for improving the water quality in rivers and streams.

scholarly journals Temporal and Spatial Water Quality Assessment for Rivers in Metropolitan Areas Using Multivariate Statistics and Water Quality Indices: A Case Study of the Geumho River, Korea

2021 ◽  
Author(s):  
Chang Dae Jo ◽  
Jung Min Kim ◽  
Seong Min Kim ◽  
Heon Gak Kwon
Keyword(s):  
Water Quality ◽  
Multivariate Statistics ◽  
Water Quality Management ◽  
Principal Component ◽  
Water Quality Assessment ◽  
Principal Factor ◽  
Economic Activities ◽  
Management Interventions ◽  
Industrial Complexes

Abstract The Geumho River in South Korea passes through a metropolitan area with a high population density and multiple industrial complexes and, therefore, the water quality of this river is of significance for human health and economic activities. This study aims to assess the water quality of the Geumho River to inform river water quality management and improve pollution control using multivariate statistics and the Korean Water Quality Index (KWQI). Principal component and factor analysis identified those factors related to organic pollutants and metabolism (principal factor 1), and phosphorus and fecal coliform content (principal factor 2). In a cluster analysis, time was considered by distinguishing between seasons (spring, summer, autumn, and winter) and space was considered based on upstream (US), midstream (MS), and downstream (DS) river sections. Seven temporal variables and six spatial variables were extracted from the discriminant analysis (DA) results; the most important water quality variables were high during the spring and summer seasons and in the MS and DS regions. Temporally, the KWQI was highest in winter (70.9) and lowest in spring (59.2), whereas spatially, KWQI values were highest in the US (67.5) and lowest in the MS (56.4) sections. These results indicate that to be most effective, water management interventions in the Geumho River should focus on the urban midstream section and spring seasons.

scholarly journals Assessment of river water quality in the South Baltic coast by multivariate techniques

2011 ◽  
Vol 9 (2) ◽  
pp. 265-274 ◽  
Author(s):  
Monika Cieszynska ◽  
Marek Wesolowski ◽  
Maria Bartoszewicz ◽  
Malgorzata Michalska
Keyword(s):  
Water Quality ◽  
Temporal Trends ◽  
Monitoring Program ◽  
Oxygen Demand ◽  
Large Data ◽  
Water Quality Monitoring ◽  
Multivariate Techniques ◽  
Data Set ◽  
Water Properties ◽  
Physicochemical Composition

AbstractThe paper presents an example of using multivariate techniques to interpret a large data set obtained during a 4-year water quality monitoring program in the Gdansk Municipality region, on the southern coast of the Baltic Sea. From 2004 to 2007, 11 physicochemical water parameters were analyzed monthly at 15 sites within eight watercourses. Principal-components analysis and cluster analysis were used to explore the data. Spatio-temporal trends in water quality were evaluated, the variables that determined the data set’s structure and the factors that affected the water’s physicochemical composition identified, with the goal of helping to optimize future monitoring. To reduce the number of analyzed variables, relationships between the analyzed parameters were also identified. The results revealed that the differences in physicochemical water properties among stations were generally smaller than those between the warmer and cooler seasons. It was determined that seasonal intrusions of brackish water from the Gulf of Gdansk can modify the water properties of some watercourses in the study area, but that dissolved oxygen, chemical oxygen demand, and total phosphorus were the main parameters responsible for the overall variation in the observed data. These parameters are related to pollution of anthropogenic origin.

scholarly journals EVALUATING SURFACE WATER QUALITY AND WATER MONITORING PARAMETERS IN THE TIEN RIVER, VIETNAMESE MEKONG DELTA

2021 ◽  
Vol 83 (3) ◽  
pp. 29-36
Author(s):  
Thanh Giao Nguyen ◽  
Vo Quang Minh
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Monitoring Program ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Water Monitoring ◽  
Water Quality Parameters

The study aimed to evaluate the surface water quality of the Tien River and identify water quality parameters to be monitored using the water quality monitoring data in the period of 2011 - 2019. The water samples were collected at five locations from Tan Chau to Cho Moi districts, An Giang province for three times per year (i.e., in March, June, and September). Water quality parameters included temperature (oC), pH, dissolved oxygen (DO), total suspended solids (TSS), nitrate (NO3--N), orthophosphate (PO43--P), biological oxygen demand (BOD), and coliforms. These parameter results were compared with the national technical regulation on surface water quality QCVN 08-MT: 2015/BTNMT, column A1. Principal component analysis (PCA) was used to identify the sources of pollution and the main factors affecting water quality. The results of this study showed that DO concentration was lower and TSS, BOD, PO43--P, coliforms concentrations in the Tien river exceeded QCVN 08-MT: 2015/BTNMT, column A1. pH, temperature, and NO3--N values were in accordance with the permitted regulation. The water monitoring parameters were seasonally fluctuated. DO, BOD, TSS, and coliforms concentrations were higher in the rainy season whereas NO3--N and PO43--P were higher in the dry season. The PCA results illustrated that pH, TSS, DO, BOD, PO43--P and coliforms should be included in the monitoring program. Other indicators such as temperature and NO3--N could be considered excluded from the program to save costs. 

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

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.

Development of a surface water quality assessment system in Hungary

1994 ◽  
Vol 30 (5) ◽  
pp. 97-110
Author(s):  
Pál Varga ◽  
Sándor Kisgyörgy
Keyword(s):  
Water Quality ◽  
Surface Waters ◽  
Surface Water Quality ◽  
Water Quality Assessment ◽  
Water Quality Monitoring ◽  
Assessment System ◽  
Sampling Points ◽  
Quality Categories ◽  
Water Uses ◽  
New System

Recent Hungarian water quality monitoring system uses 300 sampling points to classify surface waters into three quality categories that are mainly reflecting the viewpoints of different water uses. The suggested new system halved the number of the sampling points, while sampling frequency increased. The new system also includes metals, microbiological indices and organic micropollutants. The almost 70 constituents of the system are grouped into five water quality categories. The assessment is based on the value of 90 % relative frequency. The suggested new system is going to be introduced in practice from 1995 on.

scholarly journals Long-Term Assessment of Surface Water Quality in a Highly Managed Estuary Basin

2021 ◽  
Vol 18 (17) ◽  
pp. 9417
Author(s):  
Angelica M. Moncada ◽  
Assefa M. Melesse ◽  
Jagath Vithanage ◽  
René M. Price
Keyword(s):  
Water Quality ◽  
Water Quality Management ◽  
Surface Water Quality ◽  
Principal Component ◽  
Nutrient Concentrations ◽  
Trend Test ◽  
Lake Okeechobee ◽  
Row Crops ◽  
Long Time

Anthropogenic developments in coastal watersheds cause significant ecological changes to estuaries. Since estuaries respond to inputs on relatively long time scales, robust analyses of long-term data should be employed to account for seasonality, internal cycling, and climatological cycles. This study characterizes the water quality of a highly managed coastal basin, the St. Lucie Estuary Basin, FL, USA, from 1999 to 2019 to detect spatiotemporal differences in the estuary’s water quality and its tributaries. The estuary is artificially connected to Lake Okeechobee, so it receives fresh water from an external basin. Monthly water samples collected from November 1999 to October 2019 were assessed using principal component analysis, correlation analysis, and the Seasonal Kendall trend test. Nitrogen, phosphorus, color, total suspended solids, and turbidity concentrations varied seasonally and spatially. Inflows from Lake Okeechobee were characterized by high turbidity, while higher phosphorus concentrations characterized inflows from tributaries within the basin. Differences among tributaries within the basin may be attributed to flow regimes (e.g., significant releases vs. steady flow) and land use (e.g., pasture vs. row crops). Decreasing trends for orthophosphate, total phosphorus, and color and increasing trends for dissolved oxygen were found over the long term. Decreases in nutrient concentrations over time could be due to local mitigation efforts. Understanding the differences in water quality between the tributaries of the St. Lucie Estuary is essential for the overall water quality management of the estuary.

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

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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