scholarly journals State of spring phytoplankton and quality of the Kenozero waters in 2018

2019 ◽  
Vol 19 (1) ◽  
pp. 43-48
Author(s):  
Natalia Otchenasch ◽  
Gennadii Dvoryankin ◽  
Ekaterina Imant
Keyword(s):  
Water Quality ◽  
National Parks ◽  
Ecological Status ◽  
Surface Water Quality ◽  
Water Bodies ◽  
Quality Classification ◽  
Water Quality Classification ◽  
Environmental Measures ◽  
Nature Preservation

Phytoplankton constitutes a key part of all aquatic ecosystems. It produces organic matter, thus forming the first level of food chains in water bodies. In addition, phytoplankton plays a major role in the water quality formation. The studies of algocoenosis always remain relevant, since the obtained data provides important information on the ecological status of water bodies. This information can subsequently be used for planning and implementing environmental measures, which are particularly significant for water bodies located in specially protected areas. National parks existing for the purposes of nature preservation, education and research are also designed for tourism, which makes their ecosystems more vulnerable. Population residing in such territories and its economic activity may also carry some environmental risks, which necessitates regular complex observations. This paper covers the state of spring phytoplankton community of Lake Kenozero in 2018, its qualitative and quantitative characteristics (species composition, abundance and biomass). In the course of research, we identified 70 phytoplankton taxa belonging to seven divisions: Bacillariophyta, Dinophyta, Chlorophyta, Cyanophyta, Chrysophyta, Xanthophyta and Euglenophyta. The dominant species complex included diatoms (Asterionellaformosa, Melosiragranulata, Tabellariafenestrata), representatives of Dinophyta (Gymnodinium sp.), as well as small euglenoids. Species diversity was estimated using the Shannon-Weaver index. Aquatic environment contamination was assessed, i.e. the saprobity index was calculated and the class of surface water quality was determined. According to the water quality classification of water bodies and watercourses by hydrobiological indicators, Lake Kenozero was assigned the second class of water quality (moderately polluted).

Surface water quality classification using data mining approaches: Irrigation along the Aladag River*

2021 ◽  
Author(s):  
Mohammad Taghi Sattari ◽  
Hajar Feizi ◽  
Muslume Sevba Colak ◽  
Ahmet Ozturk ◽  
Fazli Ozturk ◽  
...  
Keyword(s):  
Data Mining ◽  
Water Quality ◽  
Surface Water ◽  
Surface Water Quality ◽  
Quality Classification ◽  
Water Quality Classification ◽  
Using Data

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.

scholarly journals Interpretation of the results of surface water quality applying multivariate analysis

2015 ◽  
Vol 69 (1) ◽  
pp. 29-36 ◽  
Author(s):  
Borko Matijevic ◽  
Djendji Vastag ◽  
Milena Becelic-Tomin ◽  
Bozo Dalmacija ◽  
Suzana Apostolov
Keyword(s):  
Water Quality ◽  
Statistical Analysis ◽  
Surface Water ◽  
Ecological Status ◽  
Surface Water Quality ◽  
Water Bodies ◽  
Chemical Parameters ◽  
Multivariate Statistical ◽  
Surface Water Bodies ◽  
The Given

Monitoring of surface water, through the analysis of physical-chemical and chemical parameters is a very important factor in the control of water quality and the health of living beings. Surface water quality is largely determined by the nature (atmospherics) and anthropogenic processes (discharge of municipal and industrial waste water). The results of monitoring of surface water are usually too expensive and difficult for correct interpreting, due to the spatial and temporal variations in water quality. By applying Multivariate statistical analysis can achieve significant reductions of the ampleness of the available data and the better interpretation of the obtained results about the quality and ecological status/potential of water. In this paper, were analyzed selected results of the analysis of surface water in AP Vojvodina in 2011 year by using multivariate statistical analysis (cluster analysis and principal components analysis). These techniques allow the interpretation of the results of the monitoring program of investigated surface water bodies and simultaneous identification of registered influence and potential sources of pollution on the quality of the given water bodies. With both methods applied and the division of water bodies tested in the same manner at the origin (natural and artificial) and on the basis of territorial belonging monitoring stations (Banat and Backa). Individual variations are discussed in corresponding differences in individual measuring stations in relation to others. Application of the given method, a grouping of the examined indicators of water quality in the following factors: hydro-chemical factor, ecological factor, the factor point pollution and diffusion. The obtained results confirm the initial hypothesis that the use of different statistical methods can identify the main factors that have an impact on the ecological status and ecological potential of water bodies and to improve the existing monitoring. In addition, analysis of the extracted surface water bodies where it is necessary to implement simultaneous monitoring of the biological quality elements to determine whether chemical parameters ensure the functioning of ecosystems.

scholarly journals ECOLOGICAL ASSESSMENT OF SURFACE WATER QUALITY OF ROSTAVYTSIA RIVER

2020 ◽  
pp. 86-92
Author(s):  
Pavlo Smilii ◽  
Mykhailo Melniychuk
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Quality Indicators ◽  
Environmental Assessment ◽  
Surface Waters ◽  
Ecological Status ◽  
Surface Water Quality ◽  
Ecological Assessment ◽  
Salt Composition

Purpose – perform ecological assessment of the surface waters of the Rostavytsia river within the Zhytomyr region. Method. Environmental assessment of the surface water of the Rostavytsia river was carried out using the system of classification of standards for the assessment of surface water quality of Ukraine. On the basis of common environmental criteria, the methodology makes it possible to compare the quality of water at different sites of water bodies, in water bodies of different regions. The calculation of the ecological assessment of water quality was carried out within three blocks: block of salt composition (І1), block of trophic-saprobiological (ecological-sanitary) indicators (І2) and block of indicators of content of specific substances of toxic action (І3). The results are presented in the form of a combined environmental assessment based on the final conclusions of the three blocks and based on the calculation of the integrated environmental index (IE). Results. Omprehensive studies on changing the water quality of the Rostavytsia river were conducted within the Zhytomyr region during 2016-2017. The water quality of the river according to the final values of the integral indicators of water quality of the three blocks varies within the II and III quality classes. The total environmental indices (IE) for the mean and worst indices are 3,2 and 3,3 respectively. In general, the water quality along the main channel of the Rostavytsia river within the Zhytomyr region corresponds to the second class, 3 categories, 3 subcategories according to the average quality indicators and 3(4) subcategories by worst performance. The total values of the integral surface water quality indicators of the Rostavytsia river indicate their contamination by trophic-saprobiological components. Scientific novelty. For the first time, on the basis of analytical studies and stock materials, an ecological assessment of the surface waters of the Rostavytsia river within the Zhytomyr region was carried out by three blocks of indicators: salt composition, trophic-saprobiological indicators and specific toxic substances. The integral ecological index is determined. The trends of pollutants accumulation in the surface waters of the Rostavytsia river have been established. Practical significance. The conducted researches allowed to analyze and evaluate the ecological status of the surface waters of the Rostavytsia river within the Zhytomyr region, which will allow to establish ecological standards of water quality and on this basis to determine the main directions for improvement of water resources and to substantiate the system of recommendations aimed at improving the ecological status of the studied basin.

scholarly journals Comparative analysis of decision tree algorithms on quality of water contaminated with soil

2015 ◽  
Vol 45 (2) ◽  
pp. 267-273 ◽  
Author(s):  
Mara Andrea Dota ◽  
Carlos Eduardo Cugnasca ◽  
Domingos Sávio Barbosa
Keyword(s):  
Water Quality ◽  
Comparative Analysis ◽  
Urban Areas ◽  
Contaminated Water ◽  
Quality Of Water ◽  
Water Classification ◽  
Quality Classification ◽  
Water Quality Classification ◽  
Tree Algorithms

Agriculture, roads, animal farms and other land uses may modify the water quality from rivers, dams and other surface freshwaters. In the control of the ecological process and for environmental management, it is necessary to quickly and accurately identify surface water contamination (in areas such as rivers and dams) with contaminated runoff waters coming, for example, from cultivation and urban areas. This paper presents a comparative analysis of different classification algorithms applied to the data collected from a sample of soil-contaminated water aiming to identify if the water quality classification proposed in this research agrees with reality. The sample was part of a laboratory experiment, which began with a sample of treated water added with increasing fractions of soil. The results show that the proposed classification for water quality in this scenario is coherent, because different algorithms indicated a strong statistic relationship between the classes and their instances, that is, in the classes that qualify the water sample and the values which describe each class. The proposed water classification varies from excelling to very awful (12 classes)

scholarly journals WATER QUALITY CLASSIFICATION BY ARTIFICIAL NEURAL NETWORK - A CASE STUDY OF DONG NAI RIVER, VIETNAM

2018 ◽  
Vol 55 (4C) ◽  
pp. 297
Author(s):  
Nguyen Hien Than
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Artificial Neural Network ◽  
Urban Areas ◽  
Fuzzy Comprehensive Evaluation ◽  
Neural Network Models ◽  
Quality Classification ◽  
Water Quality Classification ◽  
Artificial Neural

The Dong Nai River is the main source of supplied water for Ho Chi Minh City, Dong Nai, Binh Duong province and other areas. However, the water quality state of the Dong Nai River has been heavily pressured by discharged sources from urban areas, industrial zones, agricultural, domestic activities, etc. In this paper, the authors employed the artificial neural network model (ANNs) to classify water quality of Dong Nai River that apply a new tool to assess water quality in Vietnam. The monitoring data were used for eight years from 2007 to 2014 with 23 monitoring stations. Two neural network models including a multi-layer perceptron (MLPNN) and a generalized regression network (GRNN) were employed to classify water quality of the Dong Nai River. The results of the study showed that GRNN and MLPNN classified excellently water quality. Optimal structure of the MLPNN was H8I4O1 with model error about 0.1268 while the GRNN was error about 0.00001615. Comparing the result of water quality classification between the ANNs and the fuzzy comprehensive evaluation indicated that they were in close agreement with the respective values (the accurate rate of GRNN 100% and 98,5 % of MLPNN).

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