Assessment of Water Quality for Aquaculture in Hau River, Mekong Delta, Vietnam Using Multivariate Statistical Analysis

The deterioration signs of water quality in the Hau River are apparent. The present study analyzed the surface water quality of the Hau River using multivariate statistical techniques, including principal component analysis (PCA) and Cluster Analysis (CA). Eleven water quality parameters were analyzed at 19 different sites in An Giang and Can Tho Provinces for 12 months from January to December 2019. The findings show high levels of Biological Oxygen Demand (BOD), Total Soluble Solids (TSS), and total coliform, all year round. The PCA revealed that all the water quality parameters influenced the water quality of the Hau River, hence the relevance for water sample scrutiny. The dendrogram of similarity between sampling sites showed a maximum similarity of 95.6%. The Accumulation Factor (AF) trend showed that the concentrations/values of TSS, BOD, and phosphate (PO43−) in the downstream were 1.29, 1.53, and 1.52 times, respectively, greater than the upstream levels. Despite most of the parameters analyzed supporting aquaculture production, caution is needed in the regulation of pollution point sources to undertake sustainable aquaculture production.

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Statistical Assessment of Water Quality Parameters for Pollution Source Identification in Sukhnag Stream: An Inflow Stream of Lake Wular (Ramsar Site), Kashmir Himalaya

Journal of Ecosystems ◽

10.1155/2014/898054 ◽

2014 ◽

Vol 2014 ◽

pp. 1-18 ◽

Cited By ~ 33

Author(s):

Salim Aijaz Bhat ◽

Gowhar Meraj ◽

Sayar Yaseen ◽

Ashok K. Pandit

Keyword(s):

Water Quality ◽

Cluster Analysis ◽

Principal Component ◽

Pollution Source ◽

Quality Parameters ◽

Water Quality Parameters ◽

Accumulation Factor ◽

Kashmir Himalaya ◽

And Cluster Analysis ◽

Maximum Similarity

The precursors of deterioration of immaculate Kashmir Himalaya water bodies are apparent. This study statistically analyzes the deteriorating water quality of the Sukhnag stream, one of the major inflow stream of Lake Wular. Statistical techniques, such as principal component analysis (PCA), regression analysis, and cluster analysis, were applied to 26 water quality parameters. PCA identified a reduced number of mean 2 varifactors, indicating that 96% of temporal and spatial changes affect the water quality in this stream. First factor from factor analysis explained 66% of the total variance between velocity, total-P, NO3–N, Ca2+, Na+, TS, TSS, and TDS. Bray-Curtis cluster analysis showed a similarity of 96% between sites IV and V and 94% between sites II and III. The dendrogram of seasonal similarity showed a maximum similarity of 97% between spring and autumn and 82% between winter and summer clusters. For nitrate, nitrite, and chloride, the trend in accumulation factor (AF) showed that the downstream concentrations were about 2.0, 2.0, and 2.9, times respectively, greater than upstream concentrations.

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Evaluation of Water Quality of Kaveri River in Tiruchirappalli District, Tamil Nadu by Principal Component Analysis

Current World Environment ◽

10.12944/cwe.11.1.12 ◽

2016 ◽

Vol 11 (1) ◽

pp. 89-95 ◽

Cited By ~ 1

Author(s):

Monikandon Sukumaran ◽

Kesavan Devarayan

Keyword(s):

Water Quality ◽

Principal Component Analysis ◽

Tamil Nadu ◽

Oxygen Demand ◽

Principal Component ◽

Component Analysis ◽

Quality Parameters ◽

Water Quality Parameters ◽

Linear Relationships

Principal component analysis is a unique technique for reducing the dimensionality of the data. In this study, ten water quality parameters of the river Kaveri observed at five different stations of Tiruchirappalli for six years were collected and subjected to principal component analysis. A computational program was prepared in order to process and understand the data as a cluster. At first necessary data for compiling the program were listed and then fed to the program. Then the outputs were analyzed and possible linear and non-linear relationships between the water quality parameters and the timeline. It is understood that biological oxygen demand and fecal coli had a linear relationship. Further, the results suggested for group of factors that influence the water quality in a particular year.

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Spatial and temporal variation of water quality of a segment of Marikina River using multivariate statistical methods

Water Science & Technology ◽

10.2166/wst.2017.279 ◽

2017 ◽

Vol 76 (6) ◽

pp. 1510-1522 ◽

Cited By ~ 9

Author(s):

Vanseng Chounlamany ◽

Maria Antonia Tanchuling ◽

Takanobu Inoue

Keyword(s):

Water Quality ◽

Oxygen Demand ◽

Quality Parameters ◽

Point Sources ◽

Spatial And Temporal Variation ◽

Wet Season ◽

Multivariate Statistical ◽

Data Set ◽

Monitoring Stations

Payatas landfill in Quezon City, Philippines, releases leachate to the Marikina River through a creek. Multivariate statistical techniques were applied to study temporal and spatial variations in water quality of a segment of the Marikina River. The data set included 12 physico-chemical parameters for five monitoring stations over a year. Cluster analysis grouped the monitoring stations into four clusters and identified January–May as dry season and June–September as wet season. Principal components analysis showed that three latent factors are responsible for the data set explaining 83% of its total variance. The chemical oxygen demand, biochemical oxygen demand, total dissolved solids, Cl− and PO43− are influenced by anthropogenic impact/eutrophication pollution from point sources. Total suspended solids, turbidity and SO42− are influenced by rain and soil erosion. The highest state of pollution is at the Payatas creek outfall from March to May, whereas at downstream stations it is in May. The current study indicates that the river monitoring requires only four stations, nine water quality parameters and testing over three specific months of the year. The findings of this study imply that Payatas landfill requires a proper leachate collection and treatment system to reduce its impact on the Marikina River.

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Classification and Prediction of Goldfish Population and Water Quality Using a Potentiometric E-Tongue

Transactions of the ASABE ◽

10.13031/trans.9488 ◽

2017 ◽

Vol 60 (4) ◽

pp. 1037-1044

Author(s):

Zhenbo Wei ◽

Yu Zhao ◽

Jun Wang

Keyword(s):

Neural Network ◽

Water Quality ◽

Pattern Recognition ◽

Comprehensive Evaluation ◽

Back Propagation ◽

Correlation Coefficients ◽

Principal Component ◽

Quality Parameters ◽

Water Quality Parameters ◽

Pattern Recognition Methods

Abstract. In this study, a potentiometric E-tongue was employed for comprehensive evaluation of water quality and goldfish population with the help of pattern recognition methods. Four water quality parameters, i.e., pH and concentrations of dissolved oxygen (DO), nitrite (NO2-N), and ammonium (NH3-N), were tested by conventional analysis methods. The differences in water quality parameters between samples were revealed by two-way analysis of variance (ANOVA). The cultivation days and goldfish population were classified well by principal component analysis (PCA) and canonical discriminant analysis (CDA), and the distribution of each sample was clearer in CDA score plots than in PCA score plots. The cultivation days, goldfish population, and water parameters were predicted by a T-S fuzzy neural network (TSFNN) and back-propagation artificial neural network (BPANN). BPANN performed better than TSFNN in the prediction, and all fitting correlation coefficients were >0.90. The results indicated that the potentiometric E-tongue coupled with pattern recognition methods could be applied as a rapid method for the determination and evaluation of water quality and goldfish population. Keywords: Classify, E-tongue, Goldfish water, Prediction.

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Investigating the Impact of Anthropogenic and Natural Sources of Pollution on Quality of Water in Upper Indus Basin (UIB) by Using Multivariate Statistical Analysis

Journal of Chemistry ◽

10.1155/2019/4307251 ◽

2019 ◽

Vol 2019 ◽

pp. 1-13 ◽

Cited By ~ 2

Author(s):

Mansoor A. Baluch ◽

Hashim Nisar Hashmi

Keyword(s):

Water Quality ◽

Statistical Analysis ◽

Multivariate Statistical Analysis ◽

Quality Parameters ◽

Anthropogenic Source ◽

Indus River ◽

Multivariate Statistical ◽

Quality Of Water ◽

The Impact

Water quality of the Indus River around the upper basin and the main river was evaluated with the help of statistical analysis. In order to analyze the similarities and dissimilarities for identifying the spatial variations in water quality of the Indus River and sources of contamination, multivariate statistical analysis, i.e., principle component analysis (PCA), cluster analysis, and descriptive analysis, was done. Data of 8 physicochemical quality parameters from 64 sampling stations belonging to 6 regions (labeled as M1, M2, M3, M4, M5, and M6) were used for analysis. The parameters used for assessing the water quality were pH, dissolved oxygen (DO), oxygen reducing potential (ORP), electrical conductivity (EC), total dissolved solids (TDS), salinity (%), and concentration of arsenic (As) and lead (Pb), respectively. PCA assisted in extracting and recognizing the responsible variation factors of water quality over the region, and the results showed three underlying factors including anthropogenic source pollution along with runoff due to rain and soil erosion were responsible for explaining the 93.87% of total variance. The parameters which were significantly influenced by anthropogenic impact are DO, EC, TDS (negative), and concentration of Pb (positive), while the concentration of As, % salinity, and ORP are affected by erosion and runoff due to rain. The worst pollution situation for regions M1 and M6 was due to the concentration of As which was approximately 400 μg/l (i.e., 40 times higher than minimum WHO recommendation). Furthermore, the results also indicated that, in the Indus River, three monitoring stations and five quality parameters are sufficient to have a reasonable confidence about the quality of water in this most important reserve of Pakistan.

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Groundwater quality assessment of Shahdadkot, Qubo Saeed Khan and Sijawal Junejo Talukas of District Qambar Shahdadkot, Sindh

Applied Water Science ◽

10.1007/s13201-019-1098-2 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 3

Author(s):

Muhammad Farooque Lanjwani ◽

Muhammad Yar Khuhawar ◽

Taj Muhammad Jahangir Khuhawar

Keyword(s):

Water Quality ◽

Principal Component ◽

Quality Parameters ◽

World Health ◽

Coefficient Of Determination ◽

High Concentration ◽

Permissible Limits ◽

Groundwater Samples ◽

Health Organization

AbstractThe study examines the water quality of Shahdadkot, Qubo Saeed Khan and Sijawal Junejo talukas of Qambar Shahdadkot District, less affected by industrial contamination. A total of 38 groundwater samples were collected and analysed for 28 parameters. The results indicated that 57.89% samples were not suitable for drinking purpose with total dissolved solids above than maximum permissible limit of World Health Organization (WHO) (1000 mg/L). The pH, total phosphate, orthophosphate and nitrite were within WHO limits. The concentration of essential metals more than half samples, fluoride in 60.52% and heavy metals 0–50% were contaminated higher than permissible limits of WHO. The statistical analysis of water quality parameters was also carried out to evaluate coefficient of determination among the parameters, cluster analysis and principal component analysis. Water quality determined for irrigation based on Kelly index (KI), sodium percentage (Na%), chloride–sulphate ratio, sodium adsorption ratio, permeability index (PI), chloroalkaline indices 1 (CAI-1), residual sodium carbonate and chloride bicarbonate ratio indicated that samples (55 to 100%) could be used for irrigation purposes. The consumption of water with high concentration of salts and fluoride above the permissible limits may be a cause of a number of diseases in the area.

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Investigation of surface water quality of the Buriganga river in Bangladesh: Laboratory and spatial analysis approaches

Dhaka University Journal of Biological Sciences ◽

10.3329/dujbs.v28i2.46501 ◽

2019 ◽

Vol 28 (2) ◽

pp. 147-158

Author(s):

Mohammad Saiful Islam ◽

Romana Afroz ◽

Md Bodruddoza Mia

Keyword(s):

Heavy Metals ◽

Water Quality ◽

Quality Standard ◽

Quality Parameters ◽

Average Concentration ◽

Water Quality Parameters ◽

Economic Implications ◽

Permissible Limits ◽

Buriganga River

This work has been conducted to evaluate the water quality of the Buriganga river. In situ water quality parameters and water samples were collected from 10 locations in January 2016 and analyzed later in laboratory for water quality parameters such as pH, Eh, EC, TDS, cations (Na+, K+, Ca2+, Mg2, As3+), anions (Cl-, HCO3-, NO2-, NO3-, SO42-, F-, Br-, PO43-), heavy metals (Cr2+, Pb2+, Zn2+, Cd+2, Fe2+, Mn2+) to see whether or not the level of these parameters are within the permissible limits. The average values of pH, Eh, EC and temperature were 7.31, –214.9 mV, 928.9 μs/cm and 21.4°C, respectively; the average concentration of Na+, K+, Ca2+, Mg2+, and As3+ were 109.62, 13.38, 46.78, 13.98 and 0.018 mg/l, respectively, while the concentrations of Cl-,HCO3-, PO43-, SO42-, NO3-, NO2-, F and Br -were 79, 331.06, 2.22, 84.32, 0.0254, 0.058, 0.224 and 0.073 mg/l, respectively; and the concentration of heavy metals Pb2+, Zn2+, Fe2+ and Mn2+were 0.28, 0.053, 0.17 and 0.23 mg/l, respectively. The study indicates that most of the parameters are within the permissible limits set by Bangladesh water quality standard. The concentrations of K+, Mn2+, and Pb2+ were beyond the permissible limits meaning that that the water of Buriganga is not safe for drinking. The people living beside Buriganga river should be more cautious about using the polluted/contaminated river water. The concerned authorities should take urgent necessary steps to improve the degraded water quality of the river considering the ecological, environmental and economic implications associated with it. Dhaka Univ. J. Biol. Sci. 28(2): 147-158, 2019 (July)

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

Water Science & Technology Water Supply ◽

10.2166/ws.2020.036 ◽

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.

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A Spatial Analysis to Define Data Requirements for Hydrological and Water Quality Models in Data-Limited Regions

Water ◽

10.3390/w11020267 ◽

2019 ◽

Vol 11 (2) ◽

pp. 267 ◽

Cited By ~ 4

Author(s):

Ersilia D’Ambrosio ◽

Anna De Girolamo ◽

Marinella Spanò ◽

Vera Corbelli ◽

Gennaro Capasso ◽

...

Keyword(s):

Water Quality ◽

Spatial Analysis ◽

Surface Water ◽

Source Parameters ◽

Quality Parameters ◽

Point Sources ◽

Water Quality Parameters ◽

Limited Area ◽

Climatic Data ◽

Basin Scale

The objective of the present work is a spatial analysis aimed at supporting hydrological and water quality model applications in the Canale d’Aiedda basin (Puglia, Italy), a data-limited area. The basin is part of the sensitive environmental area of Taranto that requires remediation of the soil, subsoil, surface water, and groundwater. A monitoring plan was defined to record the streamflow and water quality parameters needed for calibrating and validating models, and a database archived in a GIS environment was built, which includes climatic data, soil hydraulic parameters, groundwater data, surface water quality parameters, point-source parameters, and information on agricultural practices. Based on a one-year monitoring of activities, the average annual loads of N-NO3 and P-PO4 delivered to the Mar Piccolo amounted to about 42 t year−1, and 2 t year−1, respectively. Knowledge uncertainty in monthly load estimation was found to be up to 25% for N-NO3 and 40% for P-PO4. The contributions of point sources in terms of N-NO3 and P-PO4 were estimated at 45% and 77%, respectively. This study defines a procedure for supporting modelling activities at the basin scale for data-limited regions.

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