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

2017 ◽  
Vol 76 (6) ◽  
pp. 1510-1522 ◽  
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.

Multivariate statistical techniques for the assessment of surface water quality of Fuji River Basin, Japan

2006 ◽  
Vol 6 (5) ◽  
pp. 59-67 ◽  
Author(s):  
S. Shrestha ◽  
F. Kazama
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
River Basin ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Organic Pollution ◽  
Quality Parameters ◽  
Point Sources ◽  
Discharge Temperature

Different multivariate statistical techniques were used to evaluate temporal and spatial variations of surface water-quality of Fuji river basin using data sets of 8 years monitoring at 13 different sites. The hierarchical cluster analysis grouped thirteen sampling sites into three clusters i.e. relatively less polluted (LP), medium polluted (MP) and highly polluted (HP) sites based on the similarity of water quality characteristics. The principal component analysis/factor analysis indicated that the parameters responsible for water quality variations are mainly related to discharge and temperature (natural), organic pollution (point sources) in LP areas; organic pollution (point sources) and nutrients (non point sources) in MP areas; and organic pollution and nutrients (point sources) in HP areas. The discriminant analysis showed that six water quality parameters (discharge, temperature, dissolved oxygen, biochemical oxygen demand, electrical conductivity and nitrate nitrogen) account for most of the expected temporal variations whereas seven water quality parameters (discharge, temperature, biochemical oxygen demand, pH, electrical conductivity, nitrate nitrogen and ammonical nitrogen) account for most of the expected spatial variations in surface water quality of Fuji river basin.

scholarly journals Application of Multivariate Statistical Analysis in Evaluation of Surface River Water Quality of a Tropical River

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Teck-Yee Ling ◽  
Chen-Lin Soo ◽  
Jing-Jing Liew ◽  
Lee Nyanti ◽  
Siong-Fong Sim ◽  
...  
Keyword(s):  
Water Quality ◽  
Suspended Solids ◽  
Anthropogenic Activities ◽  
Oxygen Demand ◽  
Domestic Wastewater ◽  
Total Suspended Solids ◽  
Tropical River ◽  
Multivariate Statistical ◽  
Data Set

The present study evaluated the spatial variations of surface water quality in a tropical river using multivariate statistical techniques, including cluster analysis (CA) and principal component analysis (PCA). Twenty physicochemical parameters were measured at 30 stations along the Batang Baram and its tributaries. The water quality of the Batang Baram was categorized as “slightly polluted” where the chemical oxygen demand and total suspended solids were the most deteriorated parameters. The CA grouped the 30 stations into four clusters which shared similar characteristics within the same cluster, representing the upstream, middle, and downstream regions of the main river and the tributaries from the middle to downstream regions of the river. The PCA has determined a reduced number of six principal components that explained 83.6% of the data set variance. The first PC indicated that the total suspended solids, turbidity, and hydrogen sulphide were the dominant polluting factors which is attributed to the logging activities, followed by the five-day biochemical oxygen demand, total phosphorus, organic nitrogen, and nitrate-nitrogen in the second PC which are related to the discharges from domestic wastewater. The components also imply that logging activities are the major anthropogenic activities responsible for water quality variations in the Batang Baram when compared to the domestic wastewater discharge.

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

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3307
Author(s):  
Fridah Gacheri Mutea ◽  
Howard Kasigwa Nelson ◽  
Hoa Van Au ◽  
Truong Giang Huynh ◽  
Ut Ngoc Vu
Keyword(s):  
Water Quality ◽  
Principal Component ◽  
Quality Parameters ◽  
Point Sources ◽  
Water Quality Parameters ◽  
Soluble Solids ◽  
Accumulation Factor ◽  
Multivariate Statistical ◽  
Aquaculture Production

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.

The Chao Phraya River Basin: water quality and anthropogenic influences

2018 ◽  
Vol 19 (5) ◽  
pp. 1287-1294 ◽  
Author(s):  
Nuanchan Singkran ◽  
Pitchaya Anantawong ◽  
Naree Intharawichian ◽  
Karika Kunta
Keyword(s):  
Water Quality ◽  
Land Use ◽  
River Basin ◽  
River Mouth ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
Paddy Fields ◽  
Coliform Bacteria ◽  
Wet Season ◽  
Chao Phraya River

Abstract Land use influences and trends in water quality parameters were determined for the Chao Phraya River, Thailand. Dissolved oxygen (DO), biochemical oxygen demand (BOD), and nitrate-nitrogen (NO3-N) showed significant trends (R2 ≥ 0.5) across the year, while total phosphorus (TP) and faecal coliform bacteria (FCB) showed significant trends only in the wet season. DO increased, but BOD, NO3-N, and TP decreased, from the lower section (river kilometres (rkm) 7–58 from the river mouth) through the middle section (rkm 58–143) to the upper section (rkm 143–379) of the river. Lead and mercury showed weak/no trends (R2 < 0.5). Based on the river section, major land use groups were a combination of urban and built-up areas (43%) and aquaculture (21%) in the lower river basin, paddy fields (56%) and urban and built-up areas (21%) in the middle river basin, and paddy fields (44%) and other agricultural areas (34%) in the upper river basin. Most water quality and land use attributes had significantly positive or negative correlations (at P ≤ 0.05) among each other. The river was in crisis because of high FCB concentrations. Serious measures are suggested to manage FCB and relevant human activities in the river basin.

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

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
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.

scholarly journals Evaluation of Water Quality of the Titas River Using NSF Water Quality Index

2010 ◽  
Vol 3 (1) ◽  
pp. 151 ◽  
Author(s):  
S. Islam ◽  
T. Rasul ◽  
J. Bin Alam ◽  
M. A. Haque
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Laboratory Tests ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
Huge Amount ◽  
Water Quality Status ◽  
Quality Status

The Titas River, a trans-boundary river of Bangladesh flows almost the entire Brahmanbaria district, consumes a huge amount of sewage, agricultural discharges and runoff, waste produced from human excreta, discharges of two oil mills and contaminants from other minor sources. A study is conducted to find the water quality status of the river during the period from July 2008 to June 2009 and by using National Sanitation Foundation (NSF) water quality index, the probable use of this water is predicted. This work consists of laboratory tests for the evaluation of some water quality parameters of the Titas and to identify its probable use in various purposes. The results of the laboratory tests and NSF water quality index suggest that the water can be used for recreation, pisciculture and irrigation purposes but requires treatment before using for drinking.Keywords: Water pollution; Faecal coliform; Dissolved oxygen (DO); Biochemical oxygen demand (BOD).© 2011 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved.doi:10.3329/jsr.v3i1.6170                 J. Sci. Res. 3 (1), 151-159 (2011)

scholarly journals Trend Of Water Quality Status In Kelantan River Downstream, Peninsular Malaysia

2020 ◽  
Vol 16 (3) ◽  
pp. 178
Author(s):  
Arniza Fitri ◽  
Khairul Nizam Abdul Maulud ◽  
Dian Pratiwi ◽  
Arlina Phelia ◽  
Farli Rossi ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Water Samples ◽  
Human Activities ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
Peninsular Malaysia ◽  
Water Quality Status ◽  
Quality Status

The issues of freshwater pollutions and the high demand of clean freshwater for daily human activities have forced developing countries such as Malaysia to continuously monitor the quality of the freshwater. The present study objective is to present the trend of water quality status in the Kelantan River downstream, Peninsular Malaysia from 2005 to 2018. Water samples were collected during dry and monsoon seasons from a sampling station located at downstream of the Kelantan River. Water quality parameters such as temperature, pH and dissolved oxygen (DO) were measured in situ while other parameters were analysed in the laboratory based on retrieved water samples. Water quality status was determined based on National Water Quality Standard (NWQS) for River in Malaysia by calculating the water quality index (WQI) according to the concentration of six water quality parameters involving pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (TSS) and Ammonia Nitrogen (AN). The results showed that Kelantan River had good water quality during the dry season classified in Class II at 2005. The water quality was found to be slightly lower during the monsoon season in year 2006. In addition, increasing the number of construction, human activities in the land use areas, land use changes and the sewage water from domestic, industrial, wet market and food outlets in the Kelantan State have declined the water quality in Kelantan River from Class II (in 2005) to Class III (in 2010 and 2011) and to become Class IV in 2017 to 2018. The results of the present study are expected to give valuable information for the water managers in order to deal with better strategies in controlling the quality of freshwater at the Kelantan River and minimize the incidence of pollution-oriented problems, thus the water can be utilized for various water uses with appropriate quality.

scholarly journals Assessment of Surface Water Quality using Indices and Geographic Information System in the Sebou River Basin, Morocco

2021 ◽  
Vol 17 (10) ◽  
Author(s):  
Kanga Idé Soumaila ◽  
Naimi Mustapha ◽  
Chikhaoui Mohamed
Keyword(s):  
Water Quality ◽  
River Water ◽  
Oxygen Demand ◽  
Water Quality Monitoring ◽  
Dry Season ◽  
River Water Quality ◽  
Wet Season ◽  
Water Quality Variation ◽  
Quality Variation ◽  
Monitoring Stations

The aim of this study is to access the quality of monitored rivers and to map the polluted river sections in the Sebou basin using Geographic Information System (GIS). The potential causes of water quality variation will also be added for suitable measures to be taken. A Water Quality Index (WQI) which developed in Morocco was applied to 17 river water quality monitoring stations with data on 6 parameters (Dissolved oxygen (DO), ammonium ion (NH4 + ), 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), fecal coliforms (FC) and total phosphorus (TP)) collected twice during the wet and dry season over 1990-2017 period. The result shows that river water quality is classified as bad, very bad and medium at 59% of the monitoring stations, while 41% are considered as good to excellent. Interpolation of mean values of overall WQI of the 17 river water quality monitoring stations, revealed evidence of quality degradation along several kilometers of most river sections in the Sebou basin. The correlation matrix between the sub-indices of water quality parameters and the overall WQI showed high positive correlation coefficients and highlights the contribution to water quality degradation as follows: TP (𝑟 = +0.96 ) ≥ NH4 + (𝑟 = +0.96 ) > BOD5 (𝑟 = +0.94) > COD (𝑟 = +0.86) > FC (𝑟 = +0.83) > DO (𝑟 = +0.79). The sections of Fès, Innaounene Rivers, and an extended stretch of Tizguit River must no longer be used for irrigation. River water quality is overall of better quality in the wet season compared to the dry season. Simple linear regressions between the seasonal water quality variation and the overall WQI showed higher coefficients of determination R 2 (0.67 and 0.60) between dry season WQI and the overall WQI and between wet season WQI and the overall WQI respectively. It is clear that discharges of industrial and domestic wastewater during the dry season and agricultural activities are most likely to be the causes of the degradation of river water quality.

scholarly journals Implementation of Long-Short Term Memory Neural Network (LSTM) for Predicting The Water Quality Parameters in Sungai Selangor

2021 ◽  
Vol 6 (4) ◽  
pp. 40-49
Author(s):  
Nur Natasya Mohd Anuar ◽  
Nur Fatihah Fauzi ◽  
Huda Zuhrah Ab Halim ◽  
Nur Izzati Khairudin ◽  
Nurizatul Syarfinas Ahmad Bakhtiar ◽  
...  
Keyword(s):  
Water Quality ◽  
Short Term Memory ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Short Term ◽  
Term Memory ◽  
Quality Of Water ◽  
Long Short Term Memory

Predictions of future events must be factored into decision-making. Predictions of water quality are critical to assist authorities in making operational, management, and strategic decisions to keep the quality of water supply monitored under specific criteria. Taking advantage of the good performance of long short-term memory (LSTM) deep neural networks in time-series prediction, the purpose of this paper is to develop and train a Long-Short Term Memory (LSTM) Neural Network to predict water quality parameters in the Selangor River. The primary goal of this study is to predict five (5) water quality parameters in the Selangor River, namely Biochemical Oxygen Demand (BOD), Ammonia Nitrogen (NH3-N), Chemical Oxygen Demand (COD), pH, and Dissolved Oxygen (DO), using secondary data from different monitoring stations along the river basin. The accuracy of this method was then measured using RMSE as the forecast measure. The results show that by using the Power of Hydrogen (pH), the dataset yielded the lowest RMSE value, with a minimum of 0.2106 at station 004 and a maximum of 1.2587 at station 001. The results of the study indicate that the predicted values of the model and the actual values were in good agreement and revealed the future developing trend of water quality parameters, showing the feasibility and effectiveness of using LSTM deep neural networks to predict the quality of water parameters.

scholarly journals Multivariate Statistical Analysis of Water Quality and Trophic State in an Artificial Dam Reservoir

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 186
Author(s):  
Md Mamun ◽  
Ji Yoon Kim ◽  
Kwang-Guk An
Keyword(s):  
Water Quality ◽  
Trophic State ◽  
Suspended Solids ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Trophic State Index ◽  
Multivariate Statistical ◽  
Chl A ◽  
State Index

Paldang Reservoir, located in the Han River basin in South Korea, is used for drinking water, fishing, irrigation, recreation, and hydroelectric power. Therefore, the water quality of the reservoir is of great importance. The main objectives of this study were to evaluate spatial and seasonal variations of surface water quality in the reservoir using multivariate statistical techniques (MSTs) along with the Trophic State Index (TSI) and Trophic State Index deviation (TSID). The empirical relationships among nutrients (total phosphorus, TP; total nitrogen, TN), chlorophyll-a (CHL-a), and annual variations of water quality parameters were also determined. To this end, 12 water quality parameters were monitored monthly at five sites along the reservoir from 1996 to 2019. Most of the parameters (all except pH, dissolved oxygen (DO), and total coliform bacteria (TCB)) showed significant spatial variations, indicating an influence of anthropogenic activities. Principal component analysis combined with factor analysis (PCA/FA) suggested that the parameters responsible for water quality variations were primarily correlated with nutrients and organic matter (anthropogenic), suspended solids (both natural and anthropogenic), and ionic concentrations (both natural and anthropogenic). Stepwise spatial discriminant analysis (DA) identified water temperature (WT), DO, electrical conductivity (EC), chemical oxygen demand (COD), the ratio of biological oxygen demand (BOD) to COD (BOD/COD), TN, TN:TP, and TCB as the parameters responsible for variations among sites, and seasonal stepwise DA identified WT, BOD, and total suspended solids (TSS) as the parameters responsible for variations among seasons. COD has increased (R2 = 0.63, p < 0.01) in the reservoir since 1996, suggesting that nonbiodegradable organic loading to the water body is rising. The empirical regression models of CHL-a-TP (R2 = 0.45) and CHL-a-TN (R2 = 0.27) indicated that TP better explained algal growth than TN. The mean TSI values for TP, CHL-a, and Secchi depth (SD) indicated a eutrophic state of the reservoir for all seasons and sites. Analysis of TSID suggested that blue-green algae dominated the algal community in the reservoir. The present results show that a significant increase in algal chlorophyll occurs during spring in the reservoir. Our findings may facilitate the management of Paldang Reservoir.

Sign in / Sign up

Export Citation Format

Share Document