A comparison between weighted arithmetic and Canadian methods for a drinking water quality index at selected locations in shatt al-kufa

kizar, Fatima Mohsen

doi:10.1088/1757-899x/433/1/012026

Cited by 14 publications

(5 citation statements)

References 2 publications

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“…The thirteen (13) significant parameters selected for the determination of the WQI were EC, TDS, pH, TA, TH, Mn, Fe, Ca 2+ , Mg 2+ , Cl − , F − , NO 3− , and SO 4 2− . Equation (1) ([ 49 , 50 ];, 2020; [ [19] , [20] , [21] , [22] ]) was used to calculate the weighted arithmetic water quality index based on Ghana Standard Authority (GSA) water quality requirements for the different parameters.

Where W i denotes the unit weight for every parameter, q i is the 0–100 subindex rating for each variable, and n is the number of consolidated subindices.…”

Section: Methodsmentioning

confidence: 99%

Application of machine learning techniques to predict groundwater quality in the Nabogo Basin, Northern Ghana

Apogba,

Anornu,

Koon

et al. 2024

Heliyon

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Where W i denotes the unit weight for every parameter, q i is the 0–100 subindex rating for each variable, and n is the number of consolidated subindices.…”

Section: Methodsmentioning

confidence: 99%

Application of machine learning techniques to predict groundwater quality in the Nabogo Basin, Northern Ghana

Apogba,

Anornu,

Koon

et al. 2024

Heliyon

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“…A Water Quality Index (WQI) is a numerical summarization of water quality data in a simple and consistent manner so as to be understandable and useable by the general public (Adelagun et al, 2021;Bhat et al, 2022). Suitable parameters were used to compare the water quality to WHO and Indian standard values (Kizar, 2018; BIS, 2012) to construct the water quality index using a slightly modi ed version of Weighted Arithmetic Index method (Table 1) (Deshpande et al, 2021). Modi cation made to the method consist of the unit weight calculated from a constant being changed in favour of relative weight calculated from assigned weights obtained from studies conducted.…”

Section: Water Quality Indexmentioning

confidence: 99%

Effect of Faults and Fractures on Springwater Quality and Discharge of West Phaileng, Mizoram

Sailo,

Vanlalhruaia

2024

Preprint

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The North Eastern part of India compromises of hilly slopes and ridges. The main source of water is of river, streams, rainfall and springs. Due to change in environmental variables, many springs and streams are drying up as discharge decreases. A lithological study shows the area to consist of clay, silt, shale, siltstone and sandstone where porosity is low leading to low yielding capacity. Hydrogeological and geochemical composition studied represents the water within this region as immature and major ions composition shows Na+>Mg2+>Ca2+>Mn2+>Fe2+>K+ in cations and anoins HCO3->Cl->SO42->NO3->PO43-. The mineral saturation indices constructed using PHREEQC showed supersaturation with dolomite, siderite and vivianite. The hydrogeochemical formation mechanism using Gibbs Diagram and Piper diagram suggested rock weathering type. Principal Component Analysis (PCA) was performed as a multivariate analysis to determine the correlation between different components of hydrogeochemistry. The assessment of springwater quality using water quality index (WQI) shows good quality for most of the samples. A conceptual recharge model was the constructed anticipating mountain front recharge as major recharge of spring water. The springwater hydrograph was modelled using Maillets. It was observed that two types of flow, firstly the initial larget slope corresponding to conduit flow and secondly smaller slope to the diffuse flow was system. Thus the main mechanism of recharge in the hilly regions of West Phaileng was attributed to the mountain front recharge which is influenced by faults and fractures.

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“…However, instead of dealing with a large number of water quality data, analyzing the quality of water by applying specific indices that help minimizing the data size into a single value is recommended (Eassa and Mahmood, 2012). The water quality index (WQI) is a simple and effective way for rating the water appropriateness for drinking or other purposes mathematically, which turn the multiple number of water quality data to a unique value (UNEP GEMS, 2007;Alobaidy et al, 2010a;Akter et al, 2016;Kizar, 2018). This index was firstly interpreted and used by Horton.…”

Section: Introductionmentioning

confidence: 99%

A New Modeled Equation of the Water Quality Index for Examination of the Water Quality of Treatment Plants in Basra City (Iraq)

Faroon

Yaseen

Saad

2023

EREM

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Monitoring the pollution degree of water treatment plants (WTPs) or any water sources requires routine and continuous water quality measurements, which is considered a challenging task. For this reason, applying a statistical tool to deal with a single value instead of a huge number of water quality values is very useful for a decision maker in this field. This work aimed to evaluate the characteristics of the purified water that is supplied from the most important water purification stations in Basra governorate for drinking use. Additionally, the study aimed at using the water quality index (WQI) for examination of the water quality, and obtaining a new equation of the WQI for water treatment plants based on the weighted arithmetic index. In this consent, 96 treated water samples were collected, regularly, from eight water purification plants in Basra city over a period of 12 months in 2021, for measuring the main physicochemical properties. Results showed that the studied units supplied treated water with the WQI varying between 50 and 72, and only the water supplied from Al-Asmaee unit could be classified as good water for drinking. The new developed formula of the WQI was valuable and applicable to examine the water quality of any water treatment unit in Basra city. It is recommended to use ridge linear regression (RLR) as the best statistic approach. The coefficient of R2 founded by RLR method was 96.1369. This method is helpful to be applied for a decision maker for monitoring different resources of water in case of the availability of enough data.

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A comparison between weighted arithmetic and Canadian methods for a drinking water quality index at selected locations in shatt al-kufa

Cited by 14 publications

References 2 publications

Application of machine learning techniques to predict groundwater quality in the Nabogo Basin, Northern Ghana

Application of machine learning techniques to predict groundwater quality in the Nabogo Basin, Northern Ghana

Effect of Faults and Fractures on Springwater Quality and Discharge of West Phaileng, Mizoram

A New Modeled Equation of the Water Quality Index for Examination of the Water Quality of Treatment Plants in Basra City (Iraq)

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