NDLI: Classification of Drinking Water Quality Index and Identification of Significant Factors

Content Provider	Springer Nature Link
Author	Nazir, Hafiza Mamona Hussain, Ijaz Zafar, Mazhar Iqbal Ali, Zulifqar AbdEl Salam, Nasser M.
Copyright Year	2016
Abstract	Water pipes are considered to be one of responsible sources for the water pollution. Among these sources of water supply, the water pipes are the only source of carrying out fresh or processed water into lakes, ponds and streams etc. In Pakistan, knowledge on the condition of water pipes is scarce as deterioration of water pipes are hardly inspected due to high cost. The aim of the current research was to examine the quality of water pipelines of eight districts of South-Punjab, namely, Mianwali, Khushab, Layyah, Bhakkar, Dera Ghazi Khan, Muzaffargarh, Rajanpur and Rahim Yar Khan. Selected sampling stations were analyzed for physio-chemical parameters such as pH, Total Dissolve Solids (TDS), Sulfate (SO$_{4}$), Chlorine (Cl), Calcium (Ca), Magnesium (Mg), Hardness, Nitrate (NO$_{3}$), Fluoride (F) and Iron (Fe). The data pertaining water monitoring contain different parameters and seem difficult work for the interpretation of water quality by managing different parameters separately. For this purpose, National Sanitation Foundation Water Quality Index (NSF-WQI) was determined to communicate the quality of water in a simple form. Besides this, groups comprising of similar sampling sites based on water quality characteristics were identified using unsupervised technique. Factor Analysis (FA) has been performed for extracting the latent pollution sources that may cause the more variance in large and complex data. The calculated values of WQI from 1600 sampling stations ranging from 20.73 to 223.74 are divided into five groups; Excellent to Unsuitable class of waters with the average value 62.09 described as good limit for drinking water. Further sampling stations are divided into five optimal clusters selected with suitable k value obtained from Silhouette coefficient. Results of k-means clustering are also verified with natural groups made by WQI. Analysis of multivariate techniques showed several factors to be responsible for the water quality deterioration. It is found out from the FA that three latent factors such as organic pollution, agriculture run-off and urban land use caused 83.30 % of the total variation. Hence, water quality management and control of these latent factors are strongly recommended.
Starting Page	4233
Ending Page	4246
Page Count	14
File Format	PDF
ISSN	09204741
Journal	Water Resources Management
Volume Number	30
Issue Number	12
e-ISSN	15731650
Language	English
Publisher	Springer Netherlands
Publisher Date	2016-07-21
Publisher Institution	European Water Resources Association (EWRA)
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Classification Factor analysis K-mean clustering Water pipelines Water quality index Hydrogeology Hydrology/Water Resources Geotechnical Engineering & Applied Earth Sciences Atmospheric Sciences Civil Engineering Environment
Content Type	Text
Resource Type	Article
Subject	Water Science and Technology Civil and Structural Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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