Wszystkie pola: water quality index (WQI) - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: A Multivariate Technique to Develop Hybrid Water Quality Index of the Bengawan Solo River, Indonesia
Autorzy:: Lusiana, Evellin Dewi
Mahmudi, Mohammad
Hutahaean, Sarah Mega
Darmawan, Arief
Buwono, Nanik Retno
Arsad, Sulastri
Musa, Muhammad
Powiązania:: https://bibliotekanauki.pl/articles/2026733.pdf
Data publikacji:: 2022
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: principal component analysis
WQI
water quality index
variable selection
water quality assessment
Opis:: Surface water resource, such as river, is constantly contaminated by domestic and industrial pollutants. In order to properly manage the water resource, a composite index for water quality assessment, such as water quality index (WQI), has been designed to monitor and evaluate the properties of surface water. However, this index is quite subjective in terms of determination of relative weights. A principal component analysis (PCA) can be used to reduce the dimension and subjectivity of water quality variables. The purpose of this study was to implement the use of hybrid PCA and WQI methods to assess and monitor the water quality of the Bengawan Solo River, which is located in Java Island, Indonesia. The result suggested that COD, BOD, TSS, TDS, nitrate, nitrite, and ammonia were the main factors that determine water quality of the Bengawan Solo River. Furthermore, it was revealed that most samples from the river showed water quality status as slightly polluted. In addition to this, the seasonal variation of the PCWI values indicated a significant increase of water pollution in the Bengawan Solo River per year.
Źródło:: Journal of Ecological Engineering; 2022, 23, 2; 123-131
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Water Quality Assessment of the Morava e Binçës River Based on the Physicochemical Parameters and Water Quality Index
Autorzy:: Musliu, M.
Bilalli, A.
Durmishi, B.
Ismaili, M.
Ibrahimi, H.
Powiązania:: https://bibliotekanauki.pl/articles/124003.pdf
Data publikacji:: 2018
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: physicochemical parameter
river waters
Water Quality
WQI
Morava e Binçës
Opis:: The quality of surface waters is being impacted by the anthropogenic and natural pollution, thus limiting the usage of this water for drinking, industry, agriculture, recreation and other purposes. The water quality indices are intended to provide a single value for the water quality of a source or a stream that reduces the large amount of parameters in a simpler expression and enables an easy interpretation of the monitoring data. During 2017, seventeen physicochemical parameters were measured in spring, summer, autumn and winter, in five locations along the Morava e Binçës River in Kosovo. For the assessment we employed the Water Quality Index (WQI) which uses the physicochemical parameters for the evaluation of the water quality. The findings of this study ascertain that MB1 station had the best quality with a value of WQI 88 and is classified in the Good Category, whereas the lowest quality of water was found on in MB4 station with a value of WQI 65 and it is thus classified in the Fair Category. Finally, the average WQI was calculated for the entire measurement period and it resulted in a value of 77.60 indicating that the Morava e Binçës River waters belong to the Fair Category.
Źródło:: Journal of Ecological Engineering; 2018, 19, 6; 104-112
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Water Quality Classification by Integration of Attribute-Realization and Support Vector Machine for the Chao Phraya River
Autorzy:: Sillberg, Chalisa Veesommai
Kullavanijaya, Pratin
Chavalparit, Orathai
Powiązania:: https://bibliotekanauki.pl/articles/1955579.pdf
Data publikacji:: 2021
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: environmental data analysis
machine learning
SVM
support vector machine
water quality index
WQI
Opis:: The water quality index (WQI) is an essential indicator to manage water usage properly. This study aimed at applying a machine learning-based approach integrating attribute-realization (AR) and support vector machine (SVM) algorithm to classify the Chao Phraya River’s water quality. The historical monitoring dataset during 2008-2019 including biological oxygen demand (BOD), conductivity (Cond), dissolved oxygen (DO), faecal coliform bacteria (FCB), total coliform bacteria (TCB), ammonia (NH3-N), nitrate (NO3-N), salinity (Sal), suspended solids (SS), total nitrogen (TN), total dissolved solids (TDS), and turbidity (Turb), were processed via four studied steps: data pre-processing by means substituting method, contributing parameter evaluation by recognition pattern study, examination of the mathematic functions for quality classification, and validation of obtained approach. The results showed that NH3-N, TCB, FCB, BOD, DO, and Sal were the main attributes contributing orderly to water quality classification with confidence values of 0.80, 0.79, 0.78, 0.76, 0.69, and 0.64, respectively. Linear regression was the most suitable function to river water data classification than Sigmoid, Radial basis and Polynomial. The different number of attributes and mathematic functions promoted the different classification performance and accuracy. The validation confirmed that AR-SVM was a potent approach application to classify river water’s quality with 0.86-0.95 accuracy when applied three to six attributes.
Źródło:: Journal of Ecological Engineering; 2021, 22, 9; 70-86
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Application of Water Quality Index and Multivariate Statistical Techniques to Assess and Predict of Groundwater Quality with Aid of Geographic Information System
Autorzy:: Dawood, Ammar S.
Jabbar, Mushtak T.
Al-Tameemi, Hayfaa H.
Baer, Eric M.
Powiązania:: https://bibliotekanauki.pl/articles/2105290.pdf
Data publikacji:: 2022
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: cluster analysis
water quality
groundwater
factor analysis
WQI
GIS
multi-layer perceptron
Opis:: In this study, the groundwater quality and spatial distribution of the Basra province in the south of Iraq was assessed and mapped for drinking and irrigation purposes. Groundwater samples (n = 41) were collected from deep wells in the study area to demonstrate, estimate and model the Water Quality Index (WQI). The analysis of water samples integrated with GIS-based IDW technique was used to express the spatial variation in the study area with consideration of WQI. The physicochemical parameters, including pH, sodium (Na+), electrical conductivity (EC), chloride (Cl-), total dissolved solids (TDS), calcium (Ca2+), nitrate (NO3-), sulfate (SO42-), magnesium (Mg2+), and bicarbonate (HCO3-) were identified for groundwater quality assessment. The results of calculated WQI classify groundwater into three sorts. The results of WQI showed that 2.5%, 2.5% and 95% of the groundwater samples were classified as poor/very poor/unsuitable for drinking, respectively. The GIS tools integrated with statistical techniques are utilized for spatial distribution and description of water quality. Correlation analysis of groundwater data revealed that some parameters have actually a relationship that is strong with the other parameters and they share a common source of origin. Multivariate statistical techniques, especially cluster analysis (CA) and factor analysis (FA), were applied for the evaluation of spatial variations of forty-one selected groundwater samples. Cluster analysis confirmed that some different locations of wells have comparable sourced elements of water pollution, whereas factor analysis yielded three factors which are accountable for groundwater quality variations, clarifying more than 72% of the total variance of the data and permitted to group the preferred water quality. MultiLayer Perceptron (MLP) models were applied in modeling the water quality index. Comparing different result values of the MLP network suggested that the values of MSE and r for the selected model are 0.1940 and 0.9998, respectively. Finally, it can be revealed that the MLP network precisely predicted the output, i.e. the WQI values.
Źródło:: Journal of Ecological Engineering; 2022, 23, 6; 189--204
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Assessment Water Quality Indices of Surface Water for Drinking and Irrigation Applications – A Comparison Review
Autorzy:: Al Yousif, Mustafa A.
Chabuk, Ali
Powiązania:: https://bibliotekanauki.pl/articles/24201763.pdf
Data publikacji:: 2023
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: WQI
water quality index
drinking use
irrigation use
index
WQR
water quality rating
Opis:: Water is one of the most important natural resources for all living organisms, including humans. Water consumption is increasing over the years as a result of the increase in the number of people, and at the same time, the causes of pollution of surface water sources increase. Water pollution is one of the most important causes of diseases and the transmission of infection to the organisms that use it. Also, the quality of agricultural crops is linked to the quality of the water used for irrigation. As a result, there was a need to monitor and evaluate the main water sources to maintain the quality of their water suitable for use by humans and other organisms. As is well known, it is difficult to evaluate the water quality of large samples with concentrations of many parameters using traditional methods, which depend on comparing experimentally determined parameter values with current standards. As a result, over the past century and the present, many methods of assessing water quality have emerged. This research aims to introduce the most important indices of water quality used at present to assess the quality of surface water for drinking and irrigation purposes, as well as the history of these methods and their development over time and their most important advantages, in addition to a group of the most important research that used these methods during the past few years.
Źródło:: Journal of Ecological Engineering; 2023, 24, 5; 40--55
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Analysis of Surface Water Quality of Four Rivers in Jayapura Regency, Indonesia: CCME-WQI Approach
Autorzy:: Tanjung, Rosye Hefmi Rechnelty
Yonas, Marcelino Novryanto
Suwito, -
Maury, Hendra Kurniawan
Sarungu, Yulius
Hamuna, Baigo
Powiązania:: https://bibliotekanauki.pl/articles/2025813.pdf
Data publikacji:: 2021
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: CCME-WQI
water quality index
physicochemical
heavy metal
microbiological
Jayapura Regency
Opis:: In Indonesia, the river water quality has been determined based on Government Regulation of the Republic of Indonesia No. 22 of 2021. This study aimed to determine the quality of surface water from the Damsari, Jabawi, Kleblow, and Komba Rivers in Jayapura Regency based on the monitoring data from 2016 to 2019. The CCME-WQI method is used to determine the status of rivers based on river water quality standards (class 1 to class 4). The results of the study showed that the parameters of water temperature, TDS, pH, $NH_3, NO_3^-, SO_4^-2$, surfactant, oil/grease, Cr-(IV), Mn, Fe, Fecal Coliform, and Total Coliform were still in accordance with the quality standard. Meanwhile, TSS, COD, BOD, Total Phosphate, Hg, and Ni have exceeded the water quality standard, where the dominant pollutant source is an anthropogenic waste. On the basis of the WQI average value, the four rivers are not suitable as a source of drinking water (Poor-Marginal; 41.33 – 58.25). The Jabawi River can be used as a recreational facility, but it must be under special management (Fair; 69.75), while the other three rivers are not suitable (Marginal; 52.00 – 61.67). The Jabawi and Komba Rivers are in the Fair category (75.50 and 69.33) to support aquatic life, while the Damsari and Kleblow Rivers are in the Marginal category (59.00 and 61.25). The water quality of the four rivers is very good and suitable to be used as a water source for irrigation (Good category; 80.00 – 88.00). The strategies for controlling river water pollution and increasing the role of the government, stakeholders, and the community are needed.
Źródło:: Journal of Ecological Engineering; 2022, 23, 1; 73-82
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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