scholarly journals Changes of Benthic Macroinvertebrates in Thi Vai River and Cai Mep Estuaries Under Polluted Conditions with Industrial Wastewater

2017 ◽  
Vol 63 (2) ◽  
pp. 19-25
Author(s):  
Nguyen Thi Thanh Huong ◽  
Pham Anh Duc ◽  
Pham Van Mien
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Total Nitrogen ◽  
Total Phosphorus ◽  
Benthic Macroinvertebrates ◽  
Industrial Wastewater ◽  
Water Quality Assessment ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Left Bank

Abstract The pollution on the Thi Vai River has been spreading out rapidly over the two lasted decades caused by the wastewater from the industrial parks in the left bank of Thi Vai River and Cai Mep Estuaries. The evaluation of the benthic macroinvertebrate changes was very necessary to identify the consequences of the industrial wastewater on water quality and aquatic ecosystem of Thi Vai River and Cai Mep Estuaries. In this study, the variables of benthic macroinvertebrates and water quality were investigated in Thi Vai River and Cai Mep Estuaries, Southern Vietnam. The monitoring data of benthic macroinvertebrates and water quality parameters covered the period from 1989 to 2015 at 6 sampling sites in Thi Vai River and Cai Mep Estuaries. The basic water quality parameters were also tested including pH, dissolved oxygen (DO), total nitrogen, and total phosphorus. The biodiversity indices of benthic macroinvertebrates were applied for water quality assessment. The results showed that pH ranged from 6.4 – 7.6 during the monitoring. The DO concentrations were in between 0.20 - 6.70 mg/L. The concentrations of total nitrogen and total phosphorous ranged from 0.03 - 5.70 mg/L 0.024 - 1.380 mg/L respectively. Macroinvertebrate community in the study area consisted of 36 species of polychaeta, gastropoda, bivalvia, and crustacea, of which, species of polychaeta were dominant in species number. The benthic macroinvertebartes density ranged from 0 - 2.746 individuals/m−1 with the main dominant species of Neanthes caudata, Prionospio malmgreni, Paraprionospio pinnata, Trichochaeta carica, Maldane sarsi, Capitella capitata, Terebellides stroemi, Euditylia polymorpha, Grandidierella lignorum, Apseudes vietnamensis. The biodiversity index values during the monitoring characterized for aquatic environmental conditions of mesotrophic to polytrophic. Besides, species richness positively correlated with DO, total nitrogen, and total phosphorus. The results confirmed the advantage of using benthic macroinvertebrates and their indices for water quality assessment.

scholarly journals Water Quality Assessment of the Godavari River

1970 ◽  
Vol 5 ◽  
pp. 31-34 ◽  
Author(s):  
Ajay D. Chavan ◽  
M P Sharma ◽  
Renu Bhargava
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Pollution Control ◽  
Water Quality Management ◽  
Water Quality Assessment ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Control Board ◽  
Godavari River ◽  
The Usa

The Godavari River is a second largest river in India originating from Trimbakeswar, Nasik, Maharashtra, India. It fl ows through the states of Madhya Pradesh, Karnataka, Orissa and Andhra Pradesh. The river, passing through Nasik City, is 82% polluted by domestic pollution and 18% by industries. The study covers about 65 km of the river starting from Kushawart Trimbakeswar to Saikheda Village, from where it enters the city. Ten locations were selected for collection of water samples from the river and the samples were analyzed for water quality parameters in the Environmental Laboratory of the Maharashtra Pollution Control Board (MPCB), Nasik. These data as well as data from the Central Pollution Control Board (CPCB) were used to compute the National Sanitation Foundation Water Quality Index (NSFWQI), mostly applicable in the USA and India. The results of NSFWQI of Godavari River indicates its water quality as ‘bad' (26-50) or ‘medium' (51-70) over the study stretch. The NSFWQI of December 2007 and February 2008 indicate an improvement in water quality at all locations over earlier data from 2002-07. Based upon the results, the existing conservation measures have been reviewed and additional measures are suggested. The study concludes that major stressor is sewage pollution.Key words: Water quality parameters; Water quality assessment; Water quality management; Conservation measuresDOI: 10.3126/hn.v5i0.2483Hydro Nepal Vol. 5, July 2009 Page:31-34 

scholarly journals Identifying the Underlying Relationship Between Water Quality Parameters of the Groundwater Samples using Association and Clustering Algorithms in Coimbatore District

2019 ◽  
Vol 8 (2) ◽  
pp. 177-185
Keyword(s):  
Data Mining ◽  
Water Quality ◽  
Quality Assessment ◽  
Ground Water ◽  
Clustering Algorithms ◽  
Water Quality Assessment ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Coimbatore District ◽  
Soft Computing Techniques

Water is a highly complex environmental system; its protection cannot be met by traditional methods. As a part of the process, it is mandatory to evaluate the parameters of ground water so as to pursue suitable treatment. These days’ data mining algorithms have been developed to handle various data-rich environmental problems. In data mining, several techniques such as complex non-linear science, soft computing techniques, clustering and association have been applied in the domain of ground water quality assessment and evaluation in and around Coimbatore District. In this work, the statistical cluster analysis methods and association rule mining techniques were used to identify the spatial distribution of different cluster of wells having similar characteristics and determine the relationship between different water quality variables. The water quality assessment in Coimbatore was done using 13 parameters, namely NO3 - , TDS, Mg2+, Ca2+, Na+ , Cl- , F- , SO4 2- , EC, pH and Hardness including location in different sites. The main objective of the present study is to assess the performance of various clustering algorithms of WEKA and identify the most suitable algorithm for clustering water quality samples. K-Mean algorithm and centroid method of Hierarchical clustering performed in the similar manner in clustering. In addition to that, this study focused on identifying the water quality parameters exceeding permissible limits that occur together (TDS, Mg2+, SO4 2- , EC, hardness) in the given samples using Association Algorithms. The performance and efficiency of different association algorithms like Apriori and Frequent Pattern Growth algorithm was evaluated by factors like support, confidence, lift, leverage and conviction values

scholarly journals Water Quality Assessment and Monitoring for River Malaprabha using the Internet of Things(IoT) system

2019 ◽  
Vol 8 (2) ◽  
pp. 3839-3844
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Real Time ◽  
Agricultural Waste ◽  
Water Quality Assessment ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Data ◽  
Time Interval ◽  
Water Quality Data

Water Technology is a new approach for assessing water quality. Water technology is the method by which the water quality can be improved so as to accept the water for a specific use. In this paper, an IoT based water quality assessment has been carried out. The IoT system consists of electronic devices and associated sensors to capture water quality. Experimental samples for water quality check were chosen from, river Malaprabha. The water samples are collected from a water quality monitoring station near Khanapur town, Belagavi district, in the state of Karnataka, India. The water quality parameters assessed here are temperature, pH, Dissolved Oxygen (DO), Total Dissolved Solids (TDS), Biological Oxygen Demand (BOD), Conductivity and Nitrate (NO3). The proposed IoT system collects the real-time water quality data at every regular time interval. The need for real-time assessment is because, in recent years the water is getting polluted at an alarming level, due to urbanization and industrialization, that results in pollutions like an Urban waste, industrial waste, and agricultural waste, etc... disposed into water. Thus making, the use of water even harder for day-to-day anthropogenic activities. The IoT system developed can be used to monitor and assess the water quality parameters.

scholarly journals Economic evaluation of the impacts of water quality on fishery production in the Estuary Complex of Santos, São Vicente and Bertioga cities, in southeastern coast of Brazil

2020 ◽  
Vol 56 (1) ◽  
pp. 99-110
Author(s):  
Victor Carrozza Barcellini ◽  
Ângela Tavares Paes ◽  
Simone Georges El Khouri Miraglia
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Total Phosphorus ◽  
Linear Models ◽  
Quality Parameters ◽  
Sao Paulo ◽  
Water Quality Parameters ◽  
São Paulo ◽  
Fishing Activity ◽  
Monetary Loss

The present study proposes a diagnosis of water quality and fishery production in the Estuarine Complex of Santos, São Vicente, and Bertioga Cities as a requirement for economic valuation of water pollution impacts on fishing production. In the study period (2009–2014), three water quality parameters were identified (dissolved oxygen, total phosphorus, and nitrate), which occurred more frequently in non-conformity with Brazilian water standards, according to reports released by the Environmental Company of São Paulo State (Companhia Ambiental do Estado de São Paulo — CETESB). For data collection of fishery production, data from the monitoring of Institute of Fisheries of Santos City (Instituto de Pesca de Santos) were used, and 15 species were identified with higher occurrence in the study area. The relation between water quality parameters and fishery production was analyzed with mixed linear models, in which significant values for dissolved oxygen parameters, total phosphorus (positive relation), and nitrate (negative relation) were found. Environmental valuation considered only the direct use values (DUV) component of the valuation of fishery production variation in relation to water quality variation. For this purpose, the Marginal Productivity Method (MPM) of the dose-response function was used, which resulted in a range of monetary loss between US$ 24,760,550.22 and US$ 60,635,978.78. The obtained values represent only a portion of the valuation of economic and environmental loss in the fishing activity (part of DUV). Therefore, economic value calculated is conservative, and although it did not reached the total amount corresponding to all the impacts caused by poor water quality, given the limitations of methods and study period, the obtained values represent the minimum environmental monetary loss.

scholarly journals Study on water and soil quality parameters of shrimp and prawn farming in the southwest region of Bangladesh

2016 ◽  
Vol 13 (1) ◽  
pp. 153-160 ◽  
Author(s):  
MA Zafar ◽  
MM Haque ◽  
MSB Aziz ◽  
MM Alam
Keyword(s):  
Water Quality ◽  
Organic Carbon ◽  
Soil Quality ◽  
Total Nitrogen ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Wet Season ◽  
Ammonia Content ◽  
Phosphorous Content ◽  
Shrimp Farms

Water and soil quality parameters play a vital role for sustainable shrimp and prawn production which together is the leading exportable seafood product in Bangladesh contributing to a significant amount of foreign currency earnings. However, this sector is often negatively criticized by the consumers of importing countries for farm (locally called gher in Bengali) environment. In this context, an investigation was carried out to assess water and soil quality parameters of shrimp and prawn farms in southwest Bangladesh. This study was conducted at Dumuria and Paickgacha Upazila of Khulna district during dry and wet season in 2012. The data were collected from 9 shrimp and prawn farms and they were categorized in three different groups (as treatments) including 3 prawn (T1), 3 shrimp & prawn (T2) and 3 shrimp farms (T3). Water temperature, dissolved oxygen, pH, ammonia, nitrate, nitrite, alkalinity, salinity, total phosphorous and total hardness were measured using portable advanced HACH water quality test kit in both dry and wet season. Farm soil (sediment) quality parameters including pH, organic carbon, total nitrogen and available phosphorus were measured in the laboratory in wet season. It was found that most of the water quality parameters were in suitable range in both seasons for prawn, shrimp & prawn and shrimp farming. However, the ammonia content was 0.009 to 0.45 ppm and 0.2 to 0.6 ppm in shrimp farm during dry and wet season, respectively which was higher than the other category of farms. The higher ammonia content in shrimp farm might be due to the decomposition of aquatic weeds, organic matter, uneaten feed etc. creating stress to shrimp. Different co-relationships found between the water quality parameters in all the farming systems in the both seasons. In terms of soil quality parameters such as pH, organic carbon and total nitrogen, there was no significant difference between the farm categories. However, available phosphorous content was significantly higher in shrimp & prawn farm. Phosphorous content was found negatively correlated with pH and organic carbon content of farm sediment (soil). From the present study, it could be argued that ammonia is the main problem for shrimp farms that may cause severe disease outbreak which need to be addressed from the view point of research and development towards sustainable seafood production in Bangladesh.J. Bangladesh Agril. Univ. 13(1): 153-160, June 2015

scholarly journals Multivariate statistical approaches to benthic macroinvertebrates and water quality for farming impact assessment in Selangor River, Malaysia

2021 ◽  
Author(s):  
Nadeesha Dilani Hettige ◽  
Rohasliney Binti Hashim ◽  
Zulfa Hanan Ash’aari ◽  
Ahmad Abas Kutty ◽  
Nor Rohaizah Jamil
Keyword(s):  
Water Quality ◽  
Benthic Macroinvertebrates ◽  
Oxygen Demand ◽  
Fish Farming ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Ammoniacal Nitrogen ◽  
Fish Farms ◽  
Organic Contamination ◽  
Multivariate Statistical

Abstract This study examined the influence of fish farming activities on water quality and benthic macroinvertebrates at the Rawang sub-basin of Selangor River. Multivariate statistical techniques were used to determine major influencing water quality parameters causing organic contamination and the dominant pollution-tolerant benthic macroinvertebrates. Sampling was conducted at Guntong River (SR1), Guntong River’s tributary (SR2, the control site), Kuang River (SR3 and SR6), Gong River (SR4), and Serendah River (SR5) using random sampling techniques based on accessibility and proximity to fish farms. Benthic macroinvertebrates and water samples were collected from April 2019 to March 2020. Based on the principal components analysis (PCA), electrical conductivity (EC), dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), ammoniacal-nitrogen, and total suspended solids (TSS) were major water quality parameters influenced by fish farming activities. The Canonical Correspondence Analysis (CCA) revealed that several taxa of benthic macroinvertebrates (Chironomidae, Naididae, Lumbriculidae, Tubificidae, unidentified Oligochaeta, Leeches (Helobdella sp.), Planorbidae, and some Odonata) were moderately or highly sensitive to TSS, BOD, COD, turbidity, ammoniacal-nitrogen, and EC. These taxa were dominant in the sampling sites, which were close to fish farms. Findings in this study showed that fish farming activities impacted the water quality and benthic macroinvertebrates in this sub-basin.

scholarly journals A Custom Sensor Network for Autonomous Water Quality Assessment in Fish Farms

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2192
Author(s):  
Juan Francisco Fuentes-Pérez ◽  
Francisco Javier Sanz-Ronda
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Sensor Network ◽  
Low Cost ◽  
Water Quality Assessment ◽  
Quality Parameters ◽  
Fish Farms ◽  
Management Platform ◽  
Machine Learning Applications ◽  
Online Management

The control of water quality is crucial to ensure the survival of fish in aquaculture production facilities. Today, the combination of sensors with communication technologies permits to monitor these crucial parameters in real-time, allowing to take fast management decisions. However, out-of-the-box solutions are expensive, due to the small market and the industrial nature of sensors, besides being little customizable. To solve this, the present work describes a low-cost hardware and software architecture developed to achieve the autonomous water quality assessment and management on a remote facility for fish conservation aquaculture within the framework of the Smart Comunidad Rural Digital (smartCRD) project. The developed sensor network has been working uninterruptedly since its installation (20 April 2021). It is based on open source technology and includes a central gateway for on-site data monitoring of water quality nodes as well as an online management platform for data visualization and sensor network configuration. Likewise, the system can detect autonomously water quality parameters outside configurable thresholds and deliver management alarms. The described architecture, besides low-cost, is highly customizable, compatible with other sensor network projects, machine-learning applications, and is capable of edge computing. Thus, it contributes to making open sensorization more accessible to real-world applications.

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