The impact of spatial and temporal shifts on Orontes River water quality parameters

Document Type : Original Article

Authors

1 Department of Environmental and Sanitary Engineering, Faculty of Civil Engineering, Damascus University, Damascus, Syria

2 Department of Horticultural Sciences, Faculty of Agricultural Engineering, Al-Baath University, Homs, Syria

3 Department of Horticultural Sciences, University College of Agriculture and Natural Resources, University of Tehran, Iran

10.30493/das.2023.364393

Abstract

Orontes River is one of the most important rivers in Syria and a major source of water for drinking, irrigating, and industrial purposes. This research aims to study the effect of temporal and spatial changes on the water quality of the Orontes River and to assess its suitability for different uses. Seasonal water quality monitoring data for the period between 2010 and 2020 consisting of  21 quality parameters (EC, COD, BOD, TUR, DO, pH, NH4, Cl, Na, T, TSS, TDS, SS, FC, NO3-, PO4-3, K, Ca, Mg, SAR, TH) at 11 stations along the river basin were used. The data were analyzed using statistical analysis techniques to study the correlation between these indicators and to determine the least number of variables that affect water quality. MANOVA analysis was applied to the dataset to study the linear relationship between independent variables (seasons and stations) and dependent variables (quality parameters). The results showed that 9 and 14 water quality parameters were influenced by seasonal and spatial changes, respectively. Additionally, the combined effect of seasonal and spatial changes influenced EC, DO, COD, PO4-3, NO3-. Therefore, these water parameters can be considered useful in determining pollution severity and evaluating water management policies in the studied area.

Keywords


Conflict of interest statement

The authors declared no conflict of interest.

Funding statement

The authors declared that no funding was received in relation to this manuscript.

Data availability statement

The authors declared that the used dataset can be obtained from the corresponding author upon reasonable request.

  1. Mfonka Z, Kpoumié A, Ngouh AN, Mouncherou OF, Nsangou D, Rakotondrabe F, Takounjou AF, Zammouri M, Ngoupayou JR, Ndjigui PD. Water Quality Assessment in the Bamoun Plateau, Western-Cameroon: Hydrogeochemical Modelling and Multivariate Statistical Analysis Approach. J. water resource prot. 2021;13(2):112-38. DOI
  2. Wang J, Lautz LS, Nolte TM, Posthuma L, Koopman KR, Leuven RS, Hendriks AJ. Towards a systematic method for assessing the impact of chemical pollution on ecosystem services of water systems. J. Environ. Manage. 2021;281. DOI
  3. Rabee AM, Abdul-Kareem BM, Al-Dhamin AS. Seasonal variations of some ecological parameters in Tigris River water at Baghdad Region, Iraq. J. water resource prot. 2011;3(4):262. DOI
  4. Rahman K, Barua S, Ahammad F, Alam A. Assessment of pollution and sources of heavy metals in the sediments of the Shitalakhya river, Bangladesh. Int. J. Adv. Geosci. 2020;8:89-94. DOI
  5. Manoj K, Ghosh S, Padhy PK. Characterization and classification of hydrochemistry using multivariate graphical and hydrostatistical techniques. Res. J. Chem. Sci. 2013;5(3):32-42.
  6. Kilic E, Yucel N. Determination of Spatial and Temporal Changes in Water Quality at Asi River Using Multivariate Statistical Techniques. Turkish J. Fish. Aquat. Sci.2018;19(9),727-37. DOI
  7. Fraga MDS, Reis GB, da Silva, DD, Guedes HAS, Elesbon AAA. Use of multivariate statistical methods to analyze the monitoring of surface water quality in the Doce River basin, Minas Gerais, Brazil. Environ. Sci. Pollut. Res. 2020;27(28):35303-18. DOI
  8. Rajesh Kumar M, Vijay Kumar R, Sreejani TP, Sravya PV, Srinivasa Rao GV. Multivariate statistical analysis of water quality of Godavari River at Polavaram for irrigation purposes. In Water Resources and Environmental Engineering II: Climate and Environment. Springer Singapore 2019:115-24. DOI
  9. Ganiyu SA, Badmus BS, Olurin OT, Ojekunle ZO. Evaluation of seasonal variation of water quality using multivariate statistical analysis and irrigation parameter indices in Ajakanga area, Ibadan, Nigeria. Appl. Water Sci. 2018;8(35):1-15. DOI
  10. Ali Z, Bhaskar SB. Basic statistical tools in research and data analysis. Indian J. Anaesth. 2016;60(9):662–9. DOI
  11. Cosgrove WJ, Loucks DP. Water management: Current and future challenges and research directions. Water Resour. Res. 2015;51(6):4823-39. DOI
  12. Yousef D. The Orontes Water Pollution Patterning—Syria—By Means of Geographic Information System GIS. J. Res. Sci. Stud. Eng. 2009;31:139-59.
  13. UN-ESCWA. Chapter 7: Orontes river basin. In Inventory of shared water resources in western Asia. Beirut: UN-ESCWA. 2013.
  14. Sun X, Zhang H, Zhong M, Wang Z, Liang X, Huang T, Huang H. Analyses on the temporal and spatial characteristics of water quality in a seagoing river using multivariate statistical techniques: A case study in the Duliujian River, China. Int. J. Environ. Res. 2019; 16(6),1020. DOI
  15. Tavakol M, Arjmandi R, Shayeghi M, Monavari SM, Karbassi A. Application of multivariate statistical methods to optimize water quality monitoring network with emphasis on the pollution caused by fish farms. Iran. J. Public Health. 2017;46(1):83-92.
  16. Ruždjak D. Evaluation of river water quality variations using multivariate statistical techniques: Sava River (Croatia): a case study. Environ. Monit. Assess. 2015;187(4):215. DOI
  17. Banda TD, Kumarasamy M. Application of multivariate statistical analysis in the development of a surrogate water quality index (WQI) for South African watersheds. Water. 2020;12(6):1584. DOI
  18. Costa D, Azevedo DJ, Santos M, Assumpcao R. Water quality assessment based on multivariate statistics and water quality index of a strategic river in the Brazilian Atlantic Forest. Sci. Rep. 2020;10(22038). DOI
  19. Guide to Assessment of Water Bodies and Watercourses in Syria. The Syrian Ministry of Local Administration and Environment. 2014.
  20. Chen X, Liu X, Li B, Peng W, Dong F, Huang A, Wang W, Cao F. Water quality assessment and spatial–temporal variation analysis in Erhai lake, southwest China. Open Geosci. 2021;13:1643-55. DOI
  21. Khouri L, Al-Moufti MB. Selection of Suitable Aggregation Function for Estimation of Water Quality Index for the Orontes River. Ecol. Indic. 2022;142,1-12. DOI

Articles in Press, Accepted Manuscript
Available Online from 25 February 2023
  • Receive Date: 03 October 2022
  • Revise Date: 08 December 2022
  • Accept Date: 15 February 2023
  • First Publish Date: 25 February 2023