Complex Linkage between Watershed Attributes and Surface Water Quality: Gaining Insight via Path Analysis
Author(s): |
Afed Ullah Khan
Hafiz Ur Rahman Liaqat Ali Muhammad Ijaz Khan Humayun Mehmood Khan Afnan Ullah Khan Fayaz Ahmad Khan Jehanzeb Khan Liaqat Ali Shah Kashif Haleem Asim Abbas Izaz Ahmad |
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Medium: | journal article |
Language(s): | English |
Published in: | Civil Engineering Journal, 1 April 2021, n. 4, v. 7 |
Page(s): | 701-712 |
DOI: | 10.28991/cej-2021-03091683 |
Abstract: |
Understanding the influence of various variables on surface water quality is extremely important for protecting ecosystem health. The principal aim of this study is to assess the direct (DE), indirect (IE) and total effects (TE) of socio-economic, terrestrial and hydrological factors on surface water quality via path analysis through the lens of 15 sub-basins located on Indus basin, Pakistan. Four path models were selected based on Comparative Fit Index (CFI) = 0.999 value. First path model showed that rangelands having low population density decline river runoff which decreases instream Electrical Conductivity (EC) because of lower anthropogenic activities. Second path model depicted that croplands having higher population density enhance river runoff due to irrigation tail water discharge which decline instream EC because of dilution. Third path model showed that croplands with higher population density enhance river runoff which increases instream NO3 concentration because of unscientific application of irrigation water. Fourth path model unveiled that croplands enhance Gross Domestic Product (GDP) which enhance river runoff and instream NO3 concentration. To protect ecosystem health, Best Management Practices (BMPs), precision farming and modern irrigation techniques should be adopted to reduce irrigation tail water discharges containing pollutants entry in Indus River. |
Copyright: | © 2021 Afed Ullah Khan, Hafiz Ur Rahman, Liaqat Ali, Muhammad Ijaz Khan, Humayun Mehmood Khan, Afnan Ullah Khan, Fayaz Ahmad Khan, Jehanzeb Khan, Liaqat Ali Shah, Kashif Haleem, Asim Abbas, Izaz Ahmad |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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10603656 - Published on:
17/04/2021 - Last updated on:
02/06/2021