scholarly journals Seasonal and Temporal Assessment of Surface Water Quality in Saguling Reservoir Indonesia Using Water Quality Index

2020 ◽  
Author(s):  
Mariana Marselina ◽  
Arwin Sabar ◽  
Nurul Fahimah
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Surface Water Quality ◽  
Distribution Analysis ◽  
Wet Season ◽  
Reservoir Water ◽  
Agriculture Industry ◽  
Reduced Parameters

Abstract Developments in agriculture, industry, and urban activities have caused deterioration of water resources such as rivers and reservoirs in terms of quality and also quantity. This includes the Saguling Reservoir, which is located in Citarum basin, Indonesia. A review of previous studies reveals that Water Quality Index (WQI) is efficient for the identification of pollution sources as well as for the understanding of temporal and spatial variations in reservoir water quality. The NSFWQI (The National Sanitation Foundation Water Quality Index) is one of the calculation methods of WQI. NSFWQI is commonly used as an indicator of surface water quality is based on Nitrate, Phosphate, Turbidity, Temperature, Fecal coliform, pH, DO, TSS, and BOD parameters. The average index of NSFWQI was determined to be 48.42 during the dry season, 43.97 during the normal season, and 45.82 during the wet season. A calculation of the WQI classified the water quality in the Saguling Reservoir as “bad” in condition. This study reveals that the strongest and most significant correlation between the concentration parameters and the WQI score is the turbidity concentration fecal coli, which is used to determine the required parameters for the calculation of WQI with reduced parameters if needed. This research also conducted nitrate concentration distribution analysis around Saguling Reservoir using the Inverse Distance Weighted method.

Seasonal and Temporal Assessment of Surface Water Quality in Saguling Reservoir Indonesia Using Water Quality Index

2020 ◽  
Author(s):  
Mariana Marselina ◽  
Arwin Sabar ◽  
Nurul Fahimah
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Fecal Coliform ◽  
Quality Index ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Distribution Analysis ◽  
Wet Season ◽  
Reservoir Water

Abstract In recent years, developments in agriculture, industry, and urban activities, especially around rivers and reservoirs have caused significant changes to the quality and quantity of water resources. This includes the Saguling Reservoir, which is located in Citarum basin, Indonesia. A review of previous studies reveals that Water Quality Index (WQI) is efficient for the identification of pollution sources as well as for the understanding of temporal and spatial variations in reservoir water quality. The National Sanitation Foundation – Water Quality Index (NSFWQI), which is a commonly used indicator of surface water quality, is based on turbidity, temperature, phosphate, nitrate, fecal coliform, pH, DO, TS, and BOD parameters. Using the results from the correlation matrix, we show that the two water quality parameters that influence the NSFWQI value the most are turbidity and fecal coliform. The average index of NSFWQI was determined to be 48.42 during the dry season, 43.97 during the normal season, and 45.82 during the wet season. A calculation of the WQI classified the water quality in the Saguling Reservoir as “bad” in condition. This study reveals that the strongest and most significant correlation between the concentration parameters and the WQI score is the turbidity concentration fecal coli, which is usable to determine the required parameters for the calculation of WQI with reduced parameters, if needed. This research also conducted nitrate concentration distribution analysis around Saguling Reservoir using the Inverse Distance Weighted method.

scholarly journals THE ASSESSMENT OF SURFACE WATER QUALITY IN THE LEPENC RIVER BASIN USING WATER QUALITY INDEX (WQI) METHODOLOGY

2018 ◽  
Vol 11 (2) ◽  
pp. 653-660 ◽  
Author(s):  
P. S.Bytyçi1 ◽  
H. S. Çadraku ◽  
F. N. Zhushi Etemi ◽  
M. A. Ismaili ◽  
O. B. Fetoshi ◽  
...  
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
River Basin ◽  
Water Quality Index ◽  
Quality Index ◽  
Surface Water Quality

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.

Evaluating the surface Water quality index fuzzy and its influence on water treatment

2019 ◽  
Vol 32 ◽  
pp. 100890 ◽  
Author(s):  
Mariângela Dutra de Oliveira ◽  
Oscar Luiz Teixeira de Rezende ◽  
Juliana Freitas Ramos de Fonseca ◽  
Marcelo Libânio
Keyword(s):  
Water Quality ◽  
Water Treatment ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Surface Water Quality

scholarly journals Assessment of coastal surface water quality for irrigation purpose

2020 ◽  
Vol 15 (4) ◽  
pp. 960-972
Author(s):  
M. F. Serder ◽  
M. S. Islam ◽  
M. R. Hasan ◽  
M. S. Yeasmin ◽  
M. G. Mostafa
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Water Type ◽  
Post Monsoon ◽  
Irrigation Purpose

Abstract The study aimed to assess the coastal surface water quality for irrigation purposes through the analysis of the water samples of some selected estuaries, rivers, and ponds. The analysis results showed that the mean value of typical water quality parameters like electrical conductivity (EC), total dissolved solids (TDS), sodium (Na+), and chloride (Cl−) ions exceeded the permissible limit of the Department of Environment (DoE), Bangladesh 2010, and FAO, 1985 for the pre- and post-monsoon seasons. The Piper diagram indicated a Na-Cl water type, especially during the pre- and post-monsoon seasons. The water quality parameters in the areas showed a higher amount than the standard permissible limits, indicating that the quality is deteriorating. The water quality index values for domestic uses showed very poorly to unsuitable in most of the surface waters except pond water, especially during the pre- and post-monsoon periods. The surface water quality index for irrigation purpose usages was found to be high and/ or severely restricted (score: 0–55) during the pre- and post-monsoon seasons. The study observed that due to saline water intrusion, the water quality deterioration started from post-monsoon and reached its highest level during the pre-monsoon season, which gradually depreciates the water quality in coastal watersheds of Bangladesh.

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