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1 Ul Hassan, M.; Ali, Z.. 2002. Potential for blue-gray water trade-offs for irrigation in small towns of Pakistan: A case study of farmers’ costs and benefits in Haroonabad. The Pakistan Development Review, 41(2):161-177.
Irrigated farming ; Costs ; Wastewater ; Land use ; Employment ; Family labor ; Tenancy ; Fertilizers ; Policy / Pakistan / Haroonabad
(Location: IWMI-HQ Call no: IWMI 631.7.4 G730 ULH Record No: H032306)
2 Nazir, H. M.; Hussain, I.; Zafar, M. I.; Ali, Z.; AbdEl-Salam, N. M. 2016. Classification of drinking water quality index and identification of significant factors. Water Resources Management, 30(12):4233-4246. [doi: https://doi.org/10.1007/s11269-016-1417-4]
Drinking water ; Water quality ; Water pollution ; Chemicophysical properties ; Factor analysis ; Pipes ; Cluster sampling / Pakistan / South Punjab / Mianwali / Khushab / Layyah / Bhakkar / Dera Ghazi Khan / Muzaffargarh / Rajanpur / Rahim Yar Khan
(Location: IWMI HQ Call no: e-copy only Record No: H047692)
(0.57 MB)
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 (SO4), Chlorine (Cl), Calcium (Ca), Magnesium (Mg), Hardness, Nitrate (NO3), 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.
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