Estimation of surface water quality in a Yazoo River tributary using the duration curve and recurrence interval approach

2013 ◽  
Vol 13 (2) ◽  
pp. 515-523 ◽  
Author(s):  
Ying Ouyang ◽  
Prem B. Parajuli ◽  
Daniel A. Marion
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Temperature ◽  
Interval Analysis ◽  
Specific Conductivity ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Recurrence Interval ◽  
Analysis Techniques ◽  
Deer Creek

Pollution of surface water with harmful chemicals and eutrophication of rivers and lakes with excess nutrients are serious environmental concerns. This study estimated surface water quality in a stream within the Yazoo River Basin (YRB), Mississippi, USA, using the duration curve and recurrence interval analysis techniques. Data from the US Geological Survey (USGS) surface water monitoring station located in Deer Creek east of Leland from the YRB were selected for the analysis. Results showed that the water quality constituents, namely water temperature, specific conductivity (SC) and dissolved oxygen (DO), in this stream were found not to be the major concerns as the percentages of the time when these constituents did not meet their criteria were very low. Our results further revealed that the water temperature and SC increased as time elapsed, indicating the potential global warming and contamination impacts in this stream. In contrast, the DO and pH decreased as time elapsed, postulating a potential increase in biochemical oxygen demand and an acidic trend in this stream. Over the last decade, the average recurrence intervals when the water temperature, SC, and DO did not meet their criteria or minimum conditions were around 1 year. Using a target DO value of 429 kg d−1 proposed by the Mississippi Department of Environmental Quality, results from this study showed that there was about 25% of the time when the DO load did not meet the target value. This study suggests that the duration curve and recurrence interval analysis techniques are useful statistical tools for water quality trend estimation.

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 Assessment of Water Quality in the Lakes Along Colentina River

2015 ◽  
Vol 13 ◽  
pp. 194-199
Author(s):  
Petra Ionescu ◽  
Violeta Monica Radu ◽  
Elena Diacu ◽  
Ecaterina Marcu
Keyword(s):  
Water Quality ◽  
Electrical Conductivity ◽  
Surface Water ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Ammonium Nitrogen ◽  
Entry And Exit ◽  
Quality Classification ◽  
Water Quality Classification ◽  
Calcium Magnesium

The purpose of this study is to evaluate the water quality in the lakes along Colentina River according to Romanian regulations referring to the norms on surface water quality classification, MO 161/2006. To achieve this goal, two sampling sections (entry and exit points) for each lake have been established, and the following indicators have been determined: pH, water temperature, dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, nitrites, nitrates and ammonium nitrogen, total nitrogen, orthophosphates, total phosphorus, electrical conductivity, filterable residue, chlorides, sulphates, calcium, magnesium and sodium. Following this study, the variation of the concentrations of determined indicators in the two sampling sections for each lake has been assessed, as well as the classification into quality classes according to the before mentioned order.

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.

Analysis of Water Environmental Quality Using BP Artificial Neural Network in Weihe River Baoji Segment

2013 ◽  
Vol 401-403 ◽  
pp. 2147-2150 ◽  
Author(s):  
Heng Xing Xie
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Artificial Neural Network ◽  
Surface Water ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Bp Artificial Neural Network ◽  
Weihe River ◽  
Artificial Neural ◽  
Water Environmental Quality

The BP artificial neural network model in type 7-5-5 was constructed with the surface water quality standard (GB3838-2002) and the surface water quality items such as BOD5 (5 day biochemical oxygen demand), COD (chemical oxygen demand), permanganate index, fluoride, NH3-N, TP (total phosphorus) and TN (total nitrogen), and the water environmental quality evaluation was conducted using the trained BP artificial neural network with the water contamination concentration data in 6 sections of Weihe river Baoji segment in year 2009. Results showed that the water quality were GradeIand GradeII in Lin Jia Cun section and Sheng Li Qiao section, and Grade III in the rest section (Wo Long Si Bridge, Guo Zhen Bridge, Cai Jia Po Bridge and Chang Xing Bridge).

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 Variations of surface water quality in selected tidal creeks of Sagar Island, Indian Sundarban eco-region: a multivariate approach

2021 ◽  
Vol 11 (3) ◽  
Author(s):  
Sanghamitra Basu ◽  
Subarna Bhattacharyya ◽  
Pranab Gogoi ◽  
Suryasis Dasgupta ◽  
Sanjoy Kumar Das
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Dissolved Oxygen ◽  
Water Temperature ◽  
Surface Water Quality ◽  
Tidal Creeks ◽  
Water Parameters ◽  
Indian Sundarbans ◽  
Sagar Island ◽  
Annual Range

AbstractSagar Island in Indian Sundarbans is bestowed with numerous tidal creeks providing a suitable home to its inherent aquatic biota. The present study investigated the variation in the surface water quality in selected tidal creeks of Sagar Island, Indian Sundarbans to understand the present status of water quality for wildlife propagation and fisheries. Ten water parameters were taken into consideration for analysis on monthly basis from four stations (tidal creeks) from September 2015 to August 2016. One-way ANOVA showed five parameters (water temperature, salinity, dissolved oxygen, turbidity and chemical oxygen demand) varied significantly between seasons (p ≤ 0.05). Factor analysis exhibited four factors explaining 53.21% total variance in the observed data. Salinity and turbidity showed a maximum annual range of variations followed by dissolved oxygen. The fluctuations of physicochemical parameters throughout the year hinted toward the ever-changing nature of the estuarine ecosystem with possible human-induced impacts. Pronounced variation in turbidity seemed to be the effect of ferrying/transportation, monsoonal runoff and other human-induced activities. In the present study, water parameters viz., water temperature, dissolved oxygen and turbidity were the deterministic parameters influencing the variables in the system. The other important parameters were found to be COD, BOD3 and nitrate concentrations during the study period. The study shall provide baseline information in formulating the management measures in terms of water quality in wildlife propagation and fisheries.

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 Surveying causes of surface water pollution at Sao River, Binh Thuy district, Can Tho city, Vietnam

2021 ◽  
Vol 9 (2) ◽  
pp. 103-110
Author(s):  
Nguyen Thanh Giao
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Surface Water ◽  
Solid Waste ◽  
Biological Activities ◽  
Water Environment ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Domestic Wastewater ◽  
Wastewater Management

Surface water sources play an important role in human and biological activities and the socio-economic development of the region. Therefore, the assessment of water quality and determination of the causes of water pollution in Sao river is essential for good management of the surface water environment. The study was conducted from July to December 2020. Water samples were collected at the time of low tide to evaluate the water quality indicators of temperature, pH, conductivity (EC), dissolved oxygen (DO), biological oxygen demand (BOD), total suspended solids (TSS), ammonium (N-NH4+), orthophosphate (P-PO43-) and coliform. The source of pollution was determined by direct interviews with households living near Sao river. The results showed that surface water quality in Sao river had signs of organic pollution and microbiological pollution due to BOD, TSS, N-NH4+, P-PO43-, coliform exceeded the allowable limits of National Technical regulation on surface water quality (QCVN 08-MT:2015/BTNMT, column A1). The results of the interview revealed that 70% of respondents said that water was seriously polluted and the main sources of pollution were domestic solid waste and domestic wastewater. Therefore, to improve surface water quality in Sao river, solid waste and wastewater management is urgently required. It is necessary to promote the monitoring and management of water quality with the participation of local authorities and communities.

scholarly journals ASSESSMENT OF SURFACE WATER QUALITY FOR IRRIGATION PURPOSES IN JEMBER DISTRICT, INDONESIA

2015 ◽  
Vol 2 (1) ◽  
pp. 260 ◽  
Author(s):  
Retno Wimbaningrum ◽  
Endang Arisoesilaningsih ◽  
Catur Retnaningdyah ◽  
Serafinah Indriyani
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Temperature ◽  
Irrigation Water ◽  
Surface Water Quality ◽  
Quality Standard ◽  
Irrigated Agriculture ◽  
Irrigation Water Quality ◽  
Water Quality Standard ◽  
The Republic

<p>Irrigated agriculture is dependent on an adequate water supply of usable quality. The analysis of physico­chemical parameters of surface water inJember District was done for the criteria of irrigation water quality. Surface water comprises spring water, falls, rivers, and tertiary irrigation channels. For this purpose, three sectors or locations were chosen to take twenty seven water samples in the summer season (September to October, 2013). DO, electrical conductivity (ECw), pH, and water temperature values were measured directly in the field,while analyses of nitrate (NH3-N), orthophosphate, total dissolved solids (TDS), and bicarbonate (HCO3-) was conducted in a laboratory. The results indicated that ECw, TDS, pH, water temperature,NH3-N, and orthophosphate were under the limits set out by the Rules of the Republic of Indonesia Government (PP RI) No. 82, 2001, for water quality standard and FAO for irrigation water quality standard. Thus, the surface water of Jember District was considered to be suitable for irrigation at the sampled location.</p><p><br /><strong>Keywords</strong>: Surface water quality; irrigation; physico-chemical parameter; Jember District.</p>

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