A survey was conducted in the Chaj Doab (the area between the rivers Chenab and Jhelum) to characterize the skimming wells used to extract freshwater layer. The survey revealed a drastic increase in the number of skimming wells installed during the drought period from 2000 to 2002. About 36% of skimming wells were found to pump water of EC greater than 2.0 dS/m. The number of strainers varied from 2 to 20 and the size varied from 5 to15 cm. The prevailing depth to the water table in the area ranged from 2 to 10 m, whereas the strainers of the wells were usually at 18 m depth. The spatial and temporal variability of groundwater quality was very high. Based on pumping test results and analysis, it is suggested that skimming wells of about 28 lps discharge should not be installed within a radius of 350 m. Six strainers of 7.5 cm diameter are recommended for installation within a depth of 20 m to pump about 28 lps of water. The skimming wells may be operated continuously for 4 to 12 hours/day, depending on the source of recharge, without having adverse effect on groundwater and pumped water quality. Copyright © 2011 John Wiley & Sons, Ltd.
Water quality modeling has been shown to be a useful tool in strategic water quality management. In this study, HEC-RAS model was employed to assess the water quality of Soan River. The model was calibrated and validated successfully by evaluation through NSE and R2 values. The simulated BOD and DO values were found to be in agreement with the measured values. Furthermore, the findings revealed that the Soan River was polluted downstream of the Kaak Bridge due to industrialization and urbanization along the River’s banks. The HEC-RAS model is a useful tool for managing water quality and making decisions. Furthermore, many situations were investigated in order to provide appropriate options for River water quality management. Sewage effluents, agricultural runoff and industrial effluents were found to be responsible for the high nutrient levels in the River which in turn reduced DO levels and increased BOD. The requirement for comprehensive integrated models that can be used to make defensible decisions is now important for the long-term management of aquatic ecosystems. The uncertainty surrounding the outcomes of integrated modelling studies makes it difficult for water resource managers to execute them.
Evaluating the quality of river water is a critical process due to pollution and variations of natural or anthropogenic origin. For the Soan River (Pakistan), seven sampling sites were selected in the urban area of Rawalpindi/Islamabad, and 18 major chemical parameters were examined over two seasons, i.e., premonsoon and postmonsoon 2019. Multivariate statistical approaches such as the Spearman correlation coefficient, cluster analysis (CA), and principal component analysis (PCA) were used to evaluate the water quality of the Soan River based on temporal and spatial patterns. Analytical results obtained by PCA show that 92.46% of the total variation in the premonsoon season and 93.11% in the postmonsoon season were observed by only two loading factors in both seasons. The PCA and CA made it possible to extract and recognize the origins of the factors responsible for water quality variations during the year 2019. The sampling stations were grouped into specific clusters on the basis of the spatiotemporal pattern of water quality data. The parameters dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), turbidity, and total suspended solids (TSS) are among the prominent contributing variations in water quality, indicating that the water quality of the Soan River deteriorates gradually as it passes through the urban areas, receiving domestic and industrial wastewater from the outfalls. This study indicates that the adopted methodology can be utilized effectively for effective river water quality management.
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