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Wyszukujesz frazę "Al Saad, Zainb A.A." wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
Evaluation of water treatment plants quality in Basrah Province, by factor and cluster analysis
Autorzy:
Al Saad, Zainb A.A.
Hamdan, Ahmed N.A.
Powiązania:
https://bibliotekanauki.pl/articles/293213.pdf
Data publikacji:
2020
Wydawca:
Instytut Technologiczno-Przyrodniczy
Tematy:
cluster analysis (CA)
factor analysis (FA)
multivariate statistics
the Shatt Al Arab River
water quality
water treatment plant
Opis:
The Shatt Al Arab River (SAAR) is a major source of raw water for most water treatment plants (WTP’s) located along with it in Basrah province. This study aims to determine the effects of different variables on water quality of the SAAR, using multivariate statistical analysis. Seventeen variables were measured in nine WTP’s during 2017, these sites are Al Hussain (1), Awaissan (2), Al Abass (3), Al Garma (4), Mhaigran (5), Al Asmaee (6), Al Jubaila (7), Al Baradia (8), Al Lebani (9). The dataset is treated using principal component analysis (PCA) / factor analysis (FA), cluster analysis (CA) to the most important factors affecting water quality, sources of contamination and the suitability of water for drinking and irrigation. Three factors are responsible for the data structure representing 88.86% of the total variance in the dataset. CA shows three different groups of similarity between the sampling stations, in which station 5 (Mhaigran) is more contaminated than others, while station 3 (Al Abass) and 6 (Al Asmaee) are less contaminated. Electrical conductivity (EC) and sodium adsorption ratio (SAR) are plotted on Richard diagram. It is shown that the samples of water of Mhaigran are located in the class of C4-S3 of very high salinity and sodium, water samples of Al Abass station, are located in the class of C3-S1 of high salinity and low sodium, and others are located in the class of C4-S2 of high salinity and medium sodium. Generally, the results of most water quality parameters reveal that SAAR is not within the permissible levels of drinking and irrigation.
Źródło:
Journal of Water and Land Development; 2020, 46; 10-19
1429-7426
2083-4535
Pojawia się w:
Journal of Water and Land Development
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy system modelling to assess water quality for irrigation purposes
Autorzy:
Hamdan, Ahmed Naseh Ahmed
Al Saad, Zainb A. A.
Abu-Alhail, Saad
Powiązania:
https://bibliotekanauki.pl/articles/1841962.pdf
Data publikacji:
2021
Wydawca:
Instytut Technologiczno-Przyrodniczy
Tematy:
Fuzzy Inference System
irrigation water quality
Richard diagram
sodium adsorption ratio
Opis:
This study attempts to find a fuzzy logic system for assessing the quality of water in water treatment plants (WTPs) providing water for irrigation purposes in the Basrah Governorate (South of Iraq). Each month, samples are taken in each of six major WTPs to measure electrical conductivity (EC), and the content of sodium, magnesium and calcium. The calculated value which is the sodium adsorption ratio (SAR) is plotted with EC on the Richard diagram. SAR and EC values are combined together in a fuzzy inference system (FIS) to find out a quality number called the fuzzy irrigation water quality index number (FIWQI) which ranges from zero to one. The higher the value of the index, the better water quality. The Richard diagram, which helps to classify irrigation water, is used to adjust FIS components. Results show that the FIWQI for all WTPs changes depending on location and season. It ranges between 0.114–0.170, 0.120–0.190, 0.114–0.170, 0.114–0.202, 0.118–0.500 and 0.46–0.500 for Al-Bradhaia 1, Al-Jubaila 1, Shatt Al-Arab, Garmmah 1, Al-Rebat, and Old Shauaibah WTPs, respectively. The results indicate that WTPs effluent drawn from the Shatt Al-Arab River has poor water quality for irrigation purposes, except for an Old Shauaibah which receives water from another source called a sweet water canal. FIS results are compared with values obtained from the Richard diagram and 96% degree of compatibility between the two methods is attained. This indicates that FIS is an acceptable method for water quality classification.
Źródło:
Journal of Water and Land Development; 2021, 50; 98-107
1429-7426
2083-4535
Pojawia się w:
Journal of Water and Land Development
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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