scholarly journals Environmental status of Manahara River, Kathmandu, Nepal

1970 ◽  
Vol 10 ◽  
pp. 21-32 ◽  
Author(s):  
Ramita Bajracharya ◽  
Naresh Kazi Tamrakar
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Anthropogenic Activities ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Coliform Bacteria ◽  
Pollution Level ◽  
Buffer Zones ◽  
Landuse Change ◽  
Environmental Status

The Manahara River located in northeast part of the Kathmandu Valley has been disturbed for last one decade by several anthropogenic activities and natural causes thereby deteriorating its recreational functions and stream habitat. To obtain an existing environmental condition and disturbances of the river, the river was surveyed for its habitat, pollution level and surface water quality. Among the five representative segments of the river, the downstream segment (Sano Thimi) was scored into intermediate category showing more pollution and environmental deterioration compared to the upstream segments. Turbidity, electrical conductivity, chemical oxygen demand, biological oxygen demand and ammonia increase, whereas dissolved oxygen decreases from upstream to downstream with exponential functions. Aquatic lives like Garra sp. (Buduna), Schizothorax sp. (Asala), Channa sp. (Hiele) and Heteropneustes sp. (Singe) were observed except in downstream of the Jadibuti Bridge situated downstream from Sano Thimi stretch. Fish species were rare from the Jadibuti area most probably due to reduced dissoved oxygen (5 mg/l). Coliform bacteria ranged from 3000 to 4000 in the Manahara River showing high amount of bacterial contamination. Major disturbances, which affect river habitat and surface water quality of the Manahara River were destruction of riparian buffer zones, excavation excessive amount of sand from the river, encroachment of floodplains and bars, solid waste and sewer effluent, and tendency of landuse change. To retard environmental degradation of the Manahara River from the human-induced activities, local government needs to take immediate action.   doi: 10.3126/bdg.v10i0.1417 Bulletin of the Department of Geology, Tribhuvan University, Kathmandu, Nepal, Vol. 10, 2007, pp. 21-32

scholarly journals Correlation between Spatial-Temporal Variation in Landscape Patterns and Surface Water Quality: A Case Study in the Yi River Watershed, China

2019 ◽  
Vol 9 (6) ◽  
pp. 1053
Author(s):  
Ziqi Bian ◽  
Lyuyi Liu ◽  
Shengyan Ding
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Sampling Site ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Ammonia Nitrogen ◽  
Landscape Composition ◽  
Landscape Patterns ◽  
Buffer Zones ◽  
River Watershed

The evidence for a correlation between landscape patterns and surface water quality is still weak. We chose the Yi River watershed in China as a study area. We selected and determined the chemical oxygen demand, ammonia nitrogen, total phosphorus, dissolved oxygen, and electric conductivity to represent the surface water quality. We analyzed the spatial distribution of the surface water quality. Buffer zones with five different radii were built around each sampling site to analyze landscape patterns on different scales. A correlation analysis was completed to examine the influencing rules and the response mechanisms between landscape patterns and surface water quality indicators. The results show that: (1) Different landscape composition types impact the surface water quality differently and increasing the area of forest land can effectively reduce non-point source pollution, (2) an increase in urban area may threaten the surface water quality, and (3) landscape compositional change has a greater influence on surface water quality compared to landscape configurational change. This study provides a scientific foundation for the spatial development of watersheds and outlines a strategy for improving the sustainability of surface water quality and the surrounding environment.

scholarly journals Assessment of Anthropogenic Impact of Surface Water Quality, South Africa

2018 ◽  
Vol 6 (2) ◽  
pp. 12
Author(s):  
Dipitseng Manamela ◽  
Omotayo Awofolu
Keyword(s):  
South Africa ◽  
Water Quality ◽  
Surface Water ◽  
Anthropogenic Activities ◽  
Treatment Plant ◽  
Surface Water Quality ◽  
Total Coliform ◽  
Mean Values ◽  
Physico Chemical ◽  
The Impact

This article investigates the impact of anthropogenic activities on an important surface water from physico-chemical, chemical and microbial perspectives. The surface water, referred to as Blesbokspruit is in the West Rand District of South Africa. Potential impactors include wastewater treatment plant, mines, farmlands and informal settlements. Water samples were collected from nine purposively selected sampling points and analysed in 2014. The mean values of analysed variables across sampling sites and periods ranged from pH: 7.4-8.4; EC: 93.0 - 146.6 mS/m; TSS: 11.3 – 39.0 mg/L; TDS: 590.3 - 1020.3 mg/L; COD: 15.6- 34.8 mg/L. Those for anions varied from NO3-: 0.2- 2.1 (mg/L) N; PO43- : 0.4-0.9 mg/L and SO42-: 118.6 - 379.5 mg/L. The metallic variables ranged from As: 0.01-0.06 mg/L; Cd: 0.02-0.06 mg/L; Fe: 0.04-0.73 mg/L; Cu: 0.02 – 0.05 mg/L and Zn: 0.05 – 0.15 mg/L. The Faecal coliform varied from 15.9-16878.5 cfu/100 ml; Total coliform: 92.9-430294 cfu/100 ml and HPC from 4322.5-39776 cfu/1ml. Detection of toxic metals and pathogenic organisms above target safety limits indicate unsuitability of the water for domestic use with impact on the health of aquatic ecosystem. The study generally revealed the impact of anthropogenic activities on the surface water quality.

scholarly journals Multivariate Monitoring of Surface Water Quality: Physico-Chemical, Microbiological and 3D Fluorescence Characterization

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1673
Author(s):  
Claude Daou ◽  
Mervat El Hoz ◽  
Amine Kassouf ◽  
Bernard Legube
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Anthropogenic Activities ◽  
Surface Water Quality ◽  
Principal Component ◽  
Specific Weight ◽  
Quality Parameters ◽  
Primary Objective ◽  
Fluorescence Excitation ◽  
Fluorescence Characteristics

The primary objective of this study is to explore a water quality database on two Mediterranean rivers (the Kadisha-Abou Ali and El Jaouz rivers—located in north Lebanon), considering their physicochemical, microbiological and fluorescence characteristics. Principal Component Analysis (PCA) was applied to the matrix gathering physicochemical and microbiological data while the Common Components and Specific Weight Analysis (CCSWA) or ComDim was used for fluorescence excitation-emission matrices (EEMs). This approach provided complementary and valuable information regarding water quality in such complex ecosystem. As highlighted by the PCA and ComDim scores, the Kadisha-Abou Ali River is highly influenced by anthropogenic activities because its watershed districts are intensively populated. This influence reveals the implication of organic and bacteriological parameters. To the contrary, the El Jaouz watershed is less inhabited and is characterized by mineral parameters, which determines its water quality. This work highlighted the relationship between fluorescence EEMs and major water quality parameters, enabling the selection of reliable water quality indicators for the studied rivers. The proposed methodology can surely be generalized to the monitoring of surface water quality in other rivers. Each customized water quality fingerprint should constantly be inspected in order to account for any emerging pollution.

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 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. 

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