scholarly journals Benthic Community and Assessment of Water Quality Using Biological Index in RAMSAR, Ninh Binh

2021 ◽  
Author(s):  
Do Van Nhuong ◽  
Tran Nam Hai ◽  
Nguyen Thi Nga ◽  
Tran Duc Hau
Keyword(s):  
Water Quality ◽  
Species Composition ◽  
Water Quality Assessment ◽  
Biological Indicators ◽  
Aquatic Environments ◽  
Biological Index ◽  
Northern Vietnam ◽  
Freshwater Bodies ◽  
Assess Quality

Van Long, the largest wetland RAMSAR in delta areas of northern Vietnam, is a famous destination for tourists, which might influence on water quality and biodiversity. Two surveys in September 2019 and May 2020 aimed to determine species composition of macrozoobenthos and build biological indicators to assess the water quality for biodiversity conservation. Present findings report a list of 41 species in 27 genera, 14 families of macrozoobenthos (Gastropoda, Bivalvia, Crustacea - Decapoda) in Van Long. Of which, Gastropoda is the most abundant, accounting for 58.5% of the total number of species, followed by Crustacean (26.8%) and Bivalvia (14.6%). Both Shannon-Weiner biodiversity (H') and Margalef indices “d” in rainy season are higher than those in dry season (H '= 2.565 vs. 2.466 and d = 4.987 vs. 3.286, respectively). For water quality assessment, based on TCVN 7220-2: 2002, the water in Van Long RAMSAR is in low level of pollution. According to ASPT index on average (3.42), this parameter was under medium to heavily polluted. The results recommend utilizing family taxon of macrozoobenthos with the recorded scales to assess quality of aquatic environments of freshwater bodies in northern Vietnam.

Water quality assessment and apportionment source of pollution from neighbouring rivers in the Tapeng Lagoon (Taiwan) using multivariate analysis: a case study

2006 ◽  
Vol 54 (11-12) ◽  
pp. 47-55 ◽  
Author(s):  
S.-W. Liao ◽  
J.-Y. Sheu ◽  
J.-J. Chen ◽  
C.-G. Lee
Keyword(s):  
Water Quality ◽  
Water Resource Management ◽  
Pollution Prevention ◽  
Water Quality Assessment ◽  
Stream Pollution ◽  
Effect Factor ◽  
Habitat Recovery ◽  
Quality Of Water ◽  
Source Of Pollution

Factor analysis was conducted to explain the characteristics and variation in the quality of water during the disassembly of oyster frames and fishery boxes. The result shows that the most important latent factors in the Tapeng Lagoon are the ocean factor, the primary productivity factor, and the fishery pollution factor. Canonical discriminant analysis is applied to identify the source of pollution in neighbouring rivers outside the Tapeng Lagoon. The two constructed discriminant functions (CDFs) showed a marked contribution to all the discriminant variables, and that total nitrogen, algae, dissolved oxygen, and total phosphate combined in the nutrient effect factor. The recognition capacities in these two CDFs were 95.6% and 4.4%, respectively. The water quality in the Kaoping river most strongly affected the water quality in the Tapeng Lagoon. Disassembling the oyster frames and fishery boxes improved the water quality markedly. However, environmental topographic conditions indicate that strengthening stream pollution prevention and constructing another entrance to the ocean are the best approaches for improving the quality of water in the Tapeng Lagoon by reducing eutrophication. These approaches and results yield useful information concerning habitat recovery and water resource management.

scholarly journals Modelling the hydrology and water quality of 3S river system (Sekong, Sesan and Srepok)

2016 ◽  
Vol 19 (2) ◽  
pp. 107-117
Author(s):  
Trang Thi Thuy Nguyen ◽  
Khoi Nguyen Dao
Keyword(s):  
Water Quality ◽  
Swat Model ◽  
Model Performance ◽  
River System ◽  
Water Quality Assessment ◽  
River Basin Management ◽  
Analysis Tool ◽  
Nitrogen And Phosphorus ◽  
Model Soil

The objective of this study was to simulate the hydrologic characteristic and water quality of 3S rivers system (Sekong, Sesan and Srepok) using SWAT model (Soil and Water Analysis Tool). Agriculture and forest are the main land use types in this basin accounting for more than 80 % of the total area. Therfore, nitrogen and phosphorus were selected to be parameters for water quality assessment. SWAT-CUP model was applied to calibrate the model for stream flow and water quality based on SUFI-2 (Sequential Uncertainty Fitting version 2) method. The model performance has been assessed by three statistical indices, including coefficient corellation (R2), Nash-Sutcliffe efficient coefficience (NSE) and percentage Bias (PBIAS). The results showed that SWAT model was well calibrated for simulating the streamflow and water quality with the values of R2 greater than 0.5 except for the Attapeu and Kontum stations, and of PBIAS less than 10 % and 35 % for streamflow and water quality, respectively. The well-calibrated SWAT model can be applied in predicting the hydrology and water quality for other application. Furthermore, it is a tool supporting the policy makers to offer a suitable decisions regarding the sustainable river basin management.

scholarly journals SEASONAL BIOLOGICAL WATER QUALITY ASSESSMENT OF RIVER KSHIPRA USING BENTHIC MACRO-INVERTEBRATES

2015 ◽  
Vol 3 (9SE) ◽  
pp. 1-7
Author(s):  
Akhand Archna ◽  
Shrivastava Sharad ◽  
Akhand Pratibha
Keyword(s):  
Water Quality ◽  
River Water ◽  
Benthic Fauna ◽  
Water Quality Assessment ◽  
Seasonal Abundance ◽  
Dominant Group ◽  
Biological Water ◽  
Water Quality Status ◽  
Biological Water Quality

The water quality of River Kshipra in stretch of 195 km was studied for water quality status using benthic macro invertebrates for all three seasons’ monsoon, winter and summer. The River water quality is subject to severe domestic and industrial pollution at compete stretch of River. In the present investigation a total of 13 Orders of macrobenthic fauna i.e. Ephemeroptera, Trichoptera, Placoptera, Coleoptera, Hemiptera, Odonata, Crustacea, Diptera, Pulmonata, Operculata, Pulmonata, Oligochaeta and Hirudinea belong to 3 Phylum’s Arthropoda, Mollusca and Annelida were reported. Arthropoda was the most dominant group in all seasons. On seasonal comparison of benthic fauna is observe that abundance were decreasing order were, Winter > Monsoon > summer. To monitor the water quality samples from two years (2010-12) from different stations were collected monthly. The works highlighted the condition of the River water in various seasons with respect of the seasonal abundance of the benthic macro-invertebrates organisms mentioned above.

scholarly journals Rain water quality assessment as air quality indicator in Pakistan

2019 ◽  
Vol 54 (2) ◽  
pp. 161-168
Author(s):  
G Yaqub ◽  
A Hamid ◽  
S Asghar
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Air Quality ◽  
Water Quality Assessment ◽  
Rain Water ◽  
Domestic Water ◽  
Indirect Evaluation ◽  
Potential Use ◽  
Insight Into

Rain is an effective way for removing pollutants from the atmosphere. The present study was initiated to determine rain water quality for its safe use as potable water, as well as a tool for indirect evaluation of air quality of different study areas. A total of 20 rain water samples were collected from areas including Kasur, Sheikhupura, Gujranwala and Lahore. The pH (5.49 + 0.323), turbidity (12.267 + 5.933NTU), Cl- (4785 + 1458.32ppm) and F- (16.44 + 4.52ppm) contents of samples are not in compliance with drinking water quality limits (Pakistan, WHO). Average sulphate (1.396 + 0.384 ppm) and NO3 − concentrations (52.35 + 12.11ppm) varied between 1.005-2.05ppm and 36.79-81.3ppm, respectively. Heavy metals analysis showed presence of Cu, Co, Mn and Zn concentrations below WHO limits while Cd and Pb concentrations exceeded WHO limits with values ranging between 0.005ppm-0.017ppm and 19ppm-254ppm, respectively . Findings indicate that rain water can provide an insight into the air quality of an area and its potential use as an alternative to drinking water, especially in areas of short domestic water supply. Bangladesh J. Sci. Ind. Res.54(2), 161-168, 2019

scholarly journals Water Quality Assessment of Sirsiya River

2013 ◽  
Vol 13 (2) ◽  
pp. 141-146 ◽  
Author(s):  
Binod Prasad Shah ◽  
Bhoj R Pant
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
River Water ◽  
Water Samples ◽  
Industrial Effluent ◽  
Water Quality Assessment ◽  
Chemical Characteristic ◽  
Oil And Grease ◽  
Industrial Corridor

The parameters such as temperature, PH, TSS, TDS, ammonia, phenol, cyanide, sulfide, oil and grease, chloride, DO, COD and BOD were taken to assess the water quality of Sirsiya river, central southern Nepal. Water samples were collected from upstream to downstream from the point receiving industrial effluent to Sirsiya river. It receives wastewater burden of more than 250 industries along Bara/Parsa industrial corridor. All the parameters except oil and grease were found within the generic standard. The study revealed that the physic-chemical characteristic of the river water was changing as a result of the discharge of untreated effluents from different industries. This may impact on water quality of Sirsiya river and also pose human health problems. Nepal Journal of Science and Technology Vol. 13, No. 2 (2012) 141-146 DOI: http://dx.doi.org/10.3126/njst.v13i2.7727

Grey Correlation Model Based on Diatom Indices Evaluating Water Quality of Longjiang River

2013 ◽  
Vol 448-453 ◽  
pp. 43-47 ◽  
Author(s):  
Xin Tang ◽  
De Suo Cai ◽  
Wen Ting Yao
Keyword(s):  
Water Quality ◽  
Water Quality Assessment ◽  
Quality Standard ◽  
Relational Model ◽  
Water Quality Standard ◽  
Diatom Index ◽  
Model Based ◽  
Diatom Indices ◽  
Grey Relational

In order to evaluate the water quality of Longjiang river comprehensively, diatoms of 15 sampling sites are collected to establish the Grey Relational Model based on three diatom indexesIPS, IBD and IDG. From the Cluster analysis of sampling sites and the box plot of diatom index, IBD is the best, then the IPS, the diatom index weights on water quality assessment are 0.637 for IBD, 0.2583 for IPS, 0.1074 for IDG respectively. Finally, by comparing the water quality standard level based on Grey Relational Model, it can be known that the water quality of most sampling sites is fine except that site No.1 and No.3 belong to III water quality standard. The result shows that it is more comprehensive and reasonable to use the Grey Relational Model based on diatom index rather than individual diatom index to assess water quality.

scholarly journals Water quality assessment of a temperate urban lagoon using physico-chemical and biological indicators

2019 ◽  
Vol 1 (5) ◽  
Author(s):  
Diamela Gianello ◽  
Elizabeth Ávila-Hernández ◽  
Irene Aguer ◽  
Melina Celeste Crettaz-Minaglia
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Water Quality Assessment ◽  
Biological Indicators ◽  
Physico Chemical

Seasonal Dynamics of Algal Biodiversity and Water Quality Assessment of Jiangsu Shilianghe Reservoir in China

2013 ◽  
Vol 807-809 ◽  
pp. 61-65
Author(s):  
Yuan Gao
Keyword(s):  
Water Quality ◽  
Species Diversity ◽  
Cell Density ◽  
Seasonal Dynamics ◽  
Algal Cell ◽  
Water Quality Assessment ◽  
Wiener Index ◽  
Biological Indicators ◽  
Sand Mining ◽  
Rivers And Lakes

Analysis of 4 sampling surveys on Jiangsu Shilianghe reservoir in May, July and October of 2011 and January of 2012, 109 species of algae belonging to 7 divisions were totally identified. The green algae and diatoms were the main species while Euglena and Cryptomonas were rare. The algal cell density in each season was compared as follows: summer (63.77 × 1000000 / L) > autumn (61.87 ×1000000 / L) > spring (43.31 ×1000000 / L) > winter (37.922 ×1000000 / L). Algae Shannon-Wiener index and Pielou indexes of each season were compared and described as follows: summer (2.71, 0.41) > winter (2.09, 0.32) > autumn (2.05, 0.31) > spring (1.85, 0.28). The Margalef indexes of each season were compared as follows: summer (1.51) > spring (1.38) > autumn (1.19) > winter (0.86). The water quality was assessed as α-medium pollution according to biological indicators. Sand mining, cages and obstruction between rivers and lakes may be the main reasons that lead to high algal cell density and low index of species diversity.

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