scholarly journals Spatiotemporal Analysis of Surface Water Quality in Dong Thap Province, Vietnam Using Water Quality Index and Statistical Approaches

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 336
Author(s):  
Nguyen Thanh Giao ◽  
Phan Kim Anh ◽  
Huynh Thi Hong Nhien
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
E Coli

The study was conducted to spatiotemporally analyze the quality, location and critical water variables influencing water quality using water monitoring data from the Department of Environment and Natural Resources, Dong Thap province in 2019. The water quality parameters including turbidity, pH, temperature, dissolved oxygen (DO), total suspended solids (TSS), biological oxygen demand (BOD), chemical oxygen demand (COD), nitrite (N-NO2−), nitrate (N-NO3−), ammonium (N-NH4+), total nitrogen (TN), orthophosphate (P-PO43−), chloride (Cl−), oil and grease, sulfate (SO42−), coliforms, and Escherichia coli (E. coli) were collected at 58 locations with the frequency of four times per year (February, May, August, and November). These parameters were compared with national technical regulation on surface water quality—QCVN 08-MT: 2015/BTNMT. Water quality index (WQI) was calculated and spatially presented by geographical information system (GIS) tool. Pearson correlation analysis, cluster analysis (CA), and principal component analysis (PCA) were used to evaluate the correlation among water quality parameters, group and reduce the sampling sites, and identify key parameters and potential water pollution sources. The results showed that TSS, BOD, COD, N-NH4+, P-PO43−, coliforms, and E. coli were the significant concerns impairing the water quality. Water quality was assessed from poor to medium levels by WQI analysis. CA suggested that the current monitoring locations could be reduced from 58 sites to 43 sites which can be saved the total monitoring budget up to 25.85%. PCA showed that temperature, pH, TSS, DO, BOD, COD, N-NH4+, N-NO2−, TN, P-PO43−, coliforms, and E. coli were the key water parameters influencing water quality in Dong Thap province’s canals and rivers; thus, these parameters should be monitored annually. The water pollution sources were possibly hydrological conditions, water runoff, riverbank erosion, domestic and urban activities, and industrial and agricultural discharges. Significantly, the municipal and agricultural wastes could be decisive factors to the change of surface water quality in the study area. Further studies need to focus on identifying sources of water pollution for implementing appropriate water management strategies.

scholarly journals Assessment of coastal surface water quality for irrigation purpose

2020 ◽  
Vol 15 (4) ◽  
pp. 960-972
Author(s):  
M. F. Serder ◽  
M. S. Islam ◽  
M. R. Hasan ◽  
M. S. Yeasmin ◽  
M. G. Mostafa
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Water Type ◽  
Post Monsoon ◽  
Irrigation Purpose

Abstract The study aimed to assess the coastal surface water quality for irrigation purposes through the analysis of the water samples of some selected estuaries, rivers, and ponds. The analysis results showed that the mean value of typical water quality parameters like electrical conductivity (EC), total dissolved solids (TDS), sodium (Na+), and chloride (Cl−) ions exceeded the permissible limit of the Department of Environment (DoE), Bangladesh 2010, and FAO, 1985 for the pre- and post-monsoon seasons. The Piper diagram indicated a Na-Cl water type, especially during the pre- and post-monsoon seasons. The water quality parameters in the areas showed a higher amount than the standard permissible limits, indicating that the quality is deteriorating. The water quality index values for domestic uses showed very poorly to unsuitable in most of the surface waters except pond water, especially during the pre- and post-monsoon periods. The surface water quality index for irrigation purpose usages was found to be high and/ or severely restricted (score: 0–55) during the pre- and post-monsoon seasons. The study observed that due to saline water intrusion, the water quality deterioration started from post-monsoon and reached its highest level during the pre-monsoon season, which gradually depreciates the water quality in coastal watersheds of Bangladesh.

scholarly journals Surface Water Pollution Risk From Vietnam Water Quality Index (VN-WQI) in the Ca Mau City, Mekong Delta

2021 ◽  
Vol 20 (4) ◽  
Author(s):  
Nguyen Ngan Ha ◽  
Tran Thi Thu Huong ◽  
Pham The Vinh ◽  
Tran Thi Van
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Sentinel 2

This paper presents the study of integrating the remote sensing technology with in-situ ground observation for assessing the status of water quality in Ca Mau city through the Vietnam Water Quality Index (VN-WQI). The Sentinel-2 image and in-situ surface water samples were collected on 20 February 2020 for this study. The sample results were then specified by samples’ coordination. Besides, Sentinel-2 imaging was processed by radiometric and atmospheric correction, geometric registration, and extracted pixel spectral values from the sample locations. The multiple linear regressions of seven water quality parameters including BOD5, COD, NH4, PO4, TSS, pH, Coliform with surface water’s pixel spectral values from the satellite images were calculated and used to simulate water quality parameters on the satellite image. They were integrated into the VN-WQI to estimate, classify, and evaluate the general surface water quality of the Ca Mau city. The results show that there is a regressive correlation between measured data and image spectral values, and the simulation also well fits with the data with an acceptable error. The surface water quality of Ca Mau city is heavily polluted with almost all water quality parameters recognized at B1 to above B2 level according to the QCVN08-MT:2015/BTNMT. In terms of VN-WQI, the results also illustrate the low quality of surface water and heavy pollution only used for water transportation, not for domestic use. This approach can be a powerful method in spatially monitoring water quality and supporting environment management.

scholarly journals Assessment of Surface Water Quality of Danube River in Terms of Usual Parameters and Correlation Analyses

2019 ◽  
Vol 70 (2) ◽  
pp. 398-406
Author(s):  
Romana Drasovean ◽  
Gabriel Murariu ◽  
Gigi Constantinescu ◽  
Adrian Circiumaru
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Pearson Correlation ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Danube River ◽  
Index Method

In order to determine the water quality of Danube River, in the Galati area, the Water Quality Index was calculated. Water Quality Index is a useful number of overall qualities of water. Galati is a Danube port city located in south-eastern of Romania. Samples were taken from 9 places along the Danube starting with the place where the Siret flows into the Danube to the Profiland Steel Plant. Profiland Steel is a company in Galai whose main activities are: sheet and zinc strips; treatment and coating of metals. The monitoring period was one year, from November 2016 to December 2017. Every month, thirty physical - chemical parameters were investigated. In this study the assessment of surface water quality was determined on the basis of various indicators such as: potassium and calcium ions, nitrites, nitrates, total nitrogen, ammonium, chlorides, total phosphorus, sulphates, cadmium, chrome, copper, lead, iron, zinc, density, dissolved oxygen, chemical oxygen demand (CCO-Cr), biochemical oxygen demand (CBO5), electrical conductivity, the density of the conductivity, resistivity, pH, salinity, total dissolved solids. The water quality index (WQI) has been calculated by using Weighted Arithmetic Water Quality Index Method. Two types of correlations were developed: Pearson correlation matrix and Spearman correlation.

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 Investigation of Water Quality Index of River Noyyal and Its Connected Ponds Coimbatore Tamilnadu India

2019 ◽  
Vol 35 (3) ◽  
pp. 1125-1131
Author(s):  
M. Jeyaraj ◽  
A. Indhuleka ◽  
C. Arunpaul
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Biological Parameters ◽  
Sampling Locations ◽  
Physico Chemical ◽  
Coimbatore District

This investigation deals with the determination of various physico-chemical and biological parameters of surface water quality of river Noyyal and its connected ponds at Coimbatore, India. Based on their significance, the sampling locations were selected. There are five sampling locations were selected like river Noyyal at sorce (S1), Perur Lake, (S2), Ukkadam Pond (S3), Singanallur Lake (S4) and Sulur Pond (S5), and samples were collected from each locations at river Noyyal basin in and around Coimbatore district. The surface water quality index determination is prerequisite and essential. In this present work, from different methods of water quality determination, the most commonly used index of National Sanitation Foundation water quality index (NSF-WQI) has been followed. The physico-chemical and biological parameters such as dissolved oxygen, faecal coliforms counts, pH, biochemical oxygen demand, phosphate, nitrates, turbidity, and total dissolved solids were investigated. Except in Noyyal river at source (S1) all the measured parameters are showed to be very high compared to limits suggested by WHO particularly during summer season and thereby it is not suitable for public use.

scholarly journals Assessment of surface water quality in relation to water quality index of tropical lentic environment, Central Gujarat, India

2014 ◽  
Vol 3 (1) ◽  
pp. 168-176 ◽  
Author(s):  
Hiren B Soni ◽  
Sheju Thomas
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Management Strategies ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Total Alkalinity ◽  
Total Hardness ◽  
Human Consumption

The present study involved the determination of surface water quality index of tropical sacred wetland viz. Dakor Pilgrimage Wetland (DPW), Central Gujarat, India. The main aim of the study was to evaluate various water quality parameters to draw-out the water quality index for an assessment of a tropical aquatic body. The monthly values of pH, Dissolved Oxygen (DO), Total Suspended Solids (TSS), Total Dissolved Solids (TDS), Total alkalinity (TA), Total Hardness (TH), Calcium Hardness (Ca), Magnesium Hardness (Mg), Chloride, Sulphate, Phosphate, Sodium, and Potassium, were analyzed to compute water quality index (WQI). The results manifest that WQI at site 1 (D1) was maximum (161.74), followed by D2 (159.96), and minimum at site 3 (D3) (157.19). The values clearly depicts that quality of water is completely unfit for human consumption unless and until strict and mandatory steps are taken to rejuvenate it. The suggestive measures to improve the overall health of an aquatic body is also discussed herewith alongwith conservation measures and management strategies. DOI: http://dx.doi.org/10.3126/ije.v3i1.9952 International Journal of Environment Vol.3(1) 2014: 168-176

scholarly journals Water Quality Assessment of Surface and Groundwater Sources Using a Water Quality Index Method: A Case Study of a Peri-Urban Town in Southwest, Nigeria

Environments ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 23 ◽  
Author(s):  
Samuel Olasoji ◽  
Nather Oyewole ◽  
Bayode Abiola ◽  
Joshua Edokpayi
Keyword(s):  
Water Quality ◽  
Water Samples ◽  
Water Quality Index ◽  
Quality Index ◽  
Quality Parameters ◽  
Faecal Coliform ◽  
Water Quality Parameters ◽  
Treated Water ◽  
E Coli

Sustainable access to safe drinking water remains a global problem as more people in the world still consume water from unimproved sources. This study was carried out to evaluate the quality of 12 different water sources and 2 treated water used by a peri-urban town in the Southwest region of Nigeria to assess their suitability for drinking and domestic use. Water quality parameters studied include pH, temperature, acidity, total alkalinity, chloride content and total CO2. A Flame Atomic Absorption spectrophotometer was used to determine the concentrations of Ca, Mg, Cu, Cr, and Pb in the water samples. The total coliform was determined using the most probable number technique while a qualitative method was used to detect the presence of faecal coliform and E. coli in the water samples. All the physicochemical water quality parameters complied with regulatory standards. Similarly, most of the heavy metals also complied except for some sites. Faecal coliform and E. coli tested positive for all the samples except one of the tap water sample. Majority of the water samples (86%) were rated as excellent based on the physicochemical parameters. One sample each was rated as having poor and good water quality, respectively. All the samples tested positive for faecal coliform bacteria and E. coli except one (treated water). It is recommended that Microbial water quality parameters be included in all Water Quality Index (WQI) analyses in order to give the true status of the quality of a water resource.

scholarly journals Quality Characterization of Surface Water Sources Using Water Quality Index in Urban Areas of Solan District of Himachal Pradesh

2020 ◽  
pp. 1-12
Author(s):  
Jyotsana Pandit ◽  
S. K. Bhardwaj
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Urban Areas ◽  
Quality Index ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Water Sources ◽  
Anthropogenic Pressure

The studies of surface water quality of urban areas has become a major environmental challenge. In effect these aquatic ecosystems are increasingly under strong anthropogenic pressure. This fact causes the deteriorations of their quality and biodiversity. That seems the cases of the surface water of Solan District. Known the importance of these ecosystems in socio-economic activities of this district, it is important to lead studies for water qualities assessment. So, the surface water quality of urban areas of Solan District was assessed using the water quality index (WQI).To realize this objective, water samples were collected from five urban areas (Arki, Baddi, Nalagarh, Parwanoo, Solan) during the summer and winter seasons and were analyzed for major physicochemical parameters, viz. pH, EC, turbidity, TDS, BOD, COD, DO,As, Cr, Zn, Pb, Cd, to determine its suitability for drinking and domestic purposes. In surface water pH, EC, turbidity, TDS, BOD, COD, DO were found in the range of 6.74-7.55, 0.294-0.506 dS m-1,3.71-7.79 NTU, 105.51-253.26 mg l-1, 1.51-3.14 mg l-1,101.79-166.88 mg l-1, 4.16-6.58 mg l-1 consequently. Trace elements Pb, Cr, Zn, As, Cd, were found in the range of 0.04-0.28 mg l-1, 0.034-0.063 mg l-1, 0.22-0.46 mg l-1, 0.004-0.020 mg l-1 and 0.002-0.008 mg l-1 respectively. All water quality parameters except Pb, Cr, Cd were within the permissible limits. Out of all urban areas WQI of Arki (33) and Solan (46) was categorized as good. Whereas WQI of Parwanoo, Baddi and Nalagarh was 69, 62, 57 respectively and was categorized as poor, indicating negative impacts o urbanization and industrialization. The study indicated that urbanization in the district has started impacting surface water sources, therefore bregular quality monitoring is required and for sustainable urbanization the implementation of stringent rules and guidelines are needed to enhance health and preserve them for future generations.

Application of Artificial Neural Network to Predict the Water Quality Index of Brahmani River Basin Odisha, India

2018 ◽  
Vol 6 (8) ◽  
pp. 205
Author(s):  
Binayini Bhagat ◽  
D. P. Satapathy
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Artificial Neural Network ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
Physico Chemical ◽  
Artificial Neural

Water is one of the prime elements responsible for subsistence on the earth. The scarcity of potable water is gradually increasing with the increase in population. The surface water quality is a very crucial and sensitive issue and is also a great environmental concern worldwide. Surface water pollution by physical, chemical, radiological and biological contaminants can be considered as an epidemic at times, all over the world. The present research work aims at assessing the water quality index (WQI) in the surface water of Brahmani river basin in Odisha by monitoring five sampling locations. The surface water samples data were subjected to comprehensive physico-chemical analysis besides general parameters. The monthly water quality parameters were collected and analyzed from five selected gauging stations of Odisha during the months of January to December from 2011 to 2016. Eleven physical, chemical and biological water quality parameters viz. pH, Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Electrical Conductivity(EC), Nitrogen as nitrate (Nitrate-N), Total Coli-form Bacteria(TC), Fecal Coli-form Bacteria(FC), Chemical Oxygen Demand (COD), Nitrogen as ammonia (NH4-N), Total Alkalinity (TA) as CaCO3, Total Hardness (TH) as CaCO3 were selected for the analysis. Analysis of water quality for Brahmani River is done by Water Quality Index (WQI). Prediction of water quality index is done by using Artificial Neural Network (ANN).  It is apparent from WQI values that Talcher and Panposh recorded the water quality as moderate to poor and nearly unsuitable during the years 2011-2016 indicating water as not safe for domestic purposes and needs treatment, the WQI values of Kamalanga ranged from good to poor and the WQI values of Aul and Pottamundai ranged from good to moderate. Eleven physico-chemical parameters were involved in this analysis as input variables and water quality index as output variable. Two models were proposed to identify the most effective model in an attempt to predict the WQI.  Correlation between the parameters was carried out to find out the significant parameters affecting WQI. The ANN developed was trained and tested successfully using the available data sets and the performance of ANN models were determined by coefficient of determination (R2) and Root Mean Square Error (RMSE). Results show that ANN-1 gives the higher value of R2 in summer, monsoon and winter season (0.989, 0.976 and 0.959) and low RMSE (2.1865, 2.0768 and1.9657) as compared to that of the second model (ANN-2) which gives R2 value as 0.933, 0.945 and 0.943 and RMSE value as 2.8765, 2.5456 and 1.2745 for summer, monsoon and winter seasons respectively. Hence this study triggered the use of Artificial Neural Network to predict the Water Quality Index (WQI) rather than using the traditional WQI equation.

Seasonal and Temporal Assessment of Surface Water Quality in Saguling Reservoir Indonesia Using Water Quality Index

2020 ◽  
Author(s):  
Mariana Marselina ◽  
Arwin Sabar ◽  
Nurul Fahimah
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Fecal Coliform ◽  
Quality Index ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Distribution Analysis ◽  
Wet Season ◽  
Reservoir Water

Abstract In recent years, developments in agriculture, industry, and urban activities, especially around rivers and reservoirs have caused significant changes to the quality and quantity of water resources. This includes the Saguling Reservoir, which is located in Citarum basin, Indonesia. A review of previous studies reveals that Water Quality Index (WQI) is efficient for the identification of pollution sources as well as for the understanding of temporal and spatial variations in reservoir water quality. The National Sanitation Foundation – Water Quality Index (NSFWQI), which is a commonly used indicator of surface water quality, is based on turbidity, temperature, phosphate, nitrate, fecal coliform, pH, DO, TS, and BOD parameters. Using the results from the correlation matrix, we show that the two water quality parameters that influence the NSFWQI value the most are turbidity and fecal coliform. The average index of NSFWQI was determined to be 48.42 during the dry season, 43.97 during the normal season, and 45.82 during the wet season. A calculation of the WQI classified the water quality in the Saguling Reservoir as “bad” in condition. This study reveals that the strongest and most significant correlation between the concentration parameters and the WQI score is the turbidity concentration fecal coli, which is usable to determine the required parameters for the calculation of WQI with reduced parameters, if needed. This research also conducted nitrate concentration distribution analysis around Saguling Reservoir using the Inverse Distance Weighted method.

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