- All Journals
- Al-Qadisiyah University
- Basrah University
- Kirkuk University
- Mosul University
- The Iraqi Borad for Medical Specialization
- University of Anbar
- University of Technology
- Al Mustafa University
- Al-Zahraa University for Women
- Alnoor University
- Kunooz University
- Misan University
- Ninevah University
- Tikrit University
- University of Al-Hamdaniya
- University of Kerbala
Water Quality Assessment of Al-Gharraf River, South of Iraq Using Multivariate Statistical Techniques | ||
| Journal of Al-Nahrain University - Science | ||
| Article 1, Volume 20, Issue 2, 2017, Pages 114-122 | ||
| Authors | ||
| Salwan Ali Abed; Salam Hussein Ewaid | ||
| Abstract | ||
| The multivariate statistical methods (principal component analysis "PCA" and hierarchical cluster analysis "CA"), were used to evaluate the water quality of Al-Gharraf River, the largest branch of Tigris River, south of Iraq. Water quality parameters were calculated monthly at each of the ten stations along the river during the year 2014-2015, to investigate the potential pollution sources and samples were analyzed for 18 physicochemical and biological parameters. The PCA supported in extracting and recognizing the factors that are responsible for river water quality variance over the year. Four factors identified that are responsible for 70% of the total variance in water quality of the river. The first factor is a multi-source factor that explains 31.6% of the total variation. The second factor is organic source factor that explains 14.6% of the total variance. The third factor is soil erosion source factor that explains 12.8% of the total variance. The fourth factor is caused by sulfates and calcium and explains 11% of the total variance. The hierarchical CA classified the 10 monitoring sites into three differentiated groups showed similar water quality features. The natural hydro-geochemical and anthropogenic activities such as domestic wastewater influents were the significant factors affect the water quality. The results of this work can be used to decrease the number of samples analyzed in both space and time to help the decision makers in recognizing priorities to improve water quality. | ||
| Keywords | ||
| Gharraf River; Water quality; multivariate statistical methods | ||
|
Statistics Article View: 145 PDF Download: 31 |
||