scholarly journals Research on assessment of surface water quality of Hau river in An Giang province on the basis of physicochemical parameters and zooplankton system

2021 ◽  
Vol 9 (12) ◽  
pp. 54-75
Author(s):  
Phu Huynh ◽  
Ngoc Thao Nguyen Ly ◽  
Ngoc Han Huynh Thi ◽  
Ngoc Nu Tran
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Physicochemical Parameters ◽  
Surface Water Quality

scholarly journals Dynamics of changes in surface water quality indicators of the Western Bug River basin within Ukraine using GIS technologies

2019 ◽  
Vol 42 (1) ◽  
pp. 67-75 ◽  
Author(s):  
Igor Gopchak ◽  
Tetiana Basiuk ◽  
Ihor Bialyk ◽  
Oleg Pinchuk ◽  
Ievgenii Gerasimov
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Environmental Assessment ◽  
Land Surface ◽  
Surface Water Quality ◽  
Ecological Condition ◽  
Toxic Substances ◽  
Ecological Index ◽  
Gis Technologies

Abstract The environmental assessment of the surface water quality of the Western Bug River has been made using the system of classification quality of land surface water of Ukraine in accordance with the approved methodology, which allows comparing water quality of separate areas of water objects of different regions. The calculation of the environmental assessment of water quality has been carried according to three blocks: block of salt composition, block of trophic and saprobic (ecological and sanitary) indicators and block of indicators of content of specific toxic substances. The results are presented in the form of a combined environmental assessment, based on the final conclusions of the three blocks and consists in calculating the integral ecological index. Comprehensive studies of changes in the water quality of the Western Bug River have been conducted within the territory of Ukraine for a long-term period. The water quality of the river on the final values of the integral indicators of the ecological condition corresponded mainly to 4nd category of the 3rd class – the water is “satisfactory” by condition and “little polluted” by degree of purity (except for points of observation that located within the Volyn region, where the water quality corresponded to 3rd category and the 2nd class. It is “good” by condition and “fairly clean” by the degree of purity). Visualization and part of the analysis are performed using GIS technologies in the software of the ArcGIS 10.3.

Impacts of pollutant loading, climate variability and site management on the surface water quality of a lowland raised bog, Thorne Moors, E. England, UK

2004 ◽  
Vol 19 (3) ◽  
pp. 413-422 ◽  
Author(s):  
Simon Bottrell ◽  
Jonathan Coulson ◽  
Michael Spence ◽  
Peter Roworth ◽  
Martin Novak ◽  
...  
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Climate Variability ◽  
Surface Water Quality ◽  
Site Management ◽  
Raised Bog ◽  
Pollutant Loading

scholarly journals Application of artificial neural network (ANN) for water quality index (WQI) prediction for the river Warta, Poland

2021 ◽  
Vol 2130 (1) ◽  
pp. 012028
Author(s):  
M Kulisz ◽  
J Kujawska
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Artificial Neural Network ◽  
Surface Water ◽  
Water Quality Index ◽  
Physicochemical Parameters ◽  
Quality Index ◽  
Surface Water Quality ◽  
Network Modelling ◽  
Neural Network Modelling

Abstract The aim of this paper is to present the potential of using neural network modelling for the prediction of the surface water quality index (WQI). An artificial neural network modelling has been performed using the physicochemical parameters (TDS, chloride, TH, nitrate, and manganese) as an input layer to the model, and the WQI as an output layer. The physicochemical parameters have been taken from five measuring stations of the river Warta in the years 2014-2018 via the Chief Inspectorate of Environmental Protection (GIOŚ). The best results of modelling were obtained for networks with 5 neurons in the hidden layer. A high correlation coefficient (general and within subsets) 0.9792, low level of MSE in each subset (training, test, validation), as well as RMSE at a level of 0.624507639 serve as a confirmation. Additionally, the maximum percentage of an error for WQI value did not exceed 4%, which confirms a high level of conformity of real data in comparison to those obtained during prediction. The aforementioned results clearly present that the ANN models are effective for the prediction of the value of the Surface water quality index and may be regarded as adequate for application in simulation by units monitoring condition of the environment.

scholarly journals Continuous and Periodic Monitoring System of Surface Water Quality of an Impounding Reservoir: Sulejow Reservoir, Poland

2019 ◽  
Vol 16 (3) ◽  
pp. 301
Author(s):  
Aleksandra Ziemińska-Stolarska ◽  
Mirosław Imbierowicz ◽  
Marcin Jaskulski ◽  
Aleksander Szmidt ◽  
Ireneusz Zbiciński
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Monitoring System ◽  
Online Monitoring ◽  
Surface Water Quality ◽  
Dam Reservoir ◽  
Reservoir Water ◽  
Periodic Monitoring

Keywords: online monitoring; dam reservoir; water quality; multi-parameter probe; eutrophication

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