Assessment of surface water quality using statistical analysis methods: Orontes River (Case study)

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Lina Khouri
https://orcid.org/0000-0001-6482-5173
Muhammad Bashar Al-Mufti

Abstract

The study investigates the water quality of the Orontes River, which is considered one of the important water recourses in Syria, as it is used for drinking, irrigation, swimming and industrial needs. A database of 660 measurements for 13 parameters concentrations used, were taken from 11 monitoring points distributed along the Orontes River for a period of five years from 2015-2019, and to study the correlation between parameters and their impact on water quality, statistical analysis was applied using (SPSS) program. Cluster analysis was applied in order to classify the pollution areas along the river, and two groups were given: (low pollution - high pollution), where the areas were classified according to the sources of pollution to which they are exposed. This indicates the importance of cluster analysis in studying movement of the pollutants and reducing the number of sampling points. Factor analysis gave 5 main factors responsible for explaining 92.86% of the total variance, with 78.2% measurement quality, it includes 7 basic parameters: (EC, TUR, NO3, Na, pH, NH4, COD). This study showed the ability of factor analysis in determining the most important parameters that effect on the water quality, which helps in reducing the number of parameters needed for sampling.

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Khouri L, Al-Mufti MB. Assessment of surface water quality using statistical analysis methods: Orontes River (Case study) . Baghdad Sci.J [Internet]. 2022 Oct. 1 [cited 2022 Nov. 30];19(5):0981. Available from: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/6262
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References

Ma X, Wang L, Yang H, Li N, Gong C. Spatiotemporal Analysis of Water Quality Using Multivariate Statistical Techniques and the Water Quality Identification Index for the Qinhuai River Basin, East China. Water. 2020; 12(10): 2764. DOI.org/10.3390/w12102764.

Ocheje J, Obeta M, Jennifer E, Ogunka H, Elekwachi W. Seasonal Variations in Imabolo Stream Water Quality in Ankpa Urban Area of Kogi State, Nigeria. Int J Environ Clim. Chang. 2019; 9(4): 229-241. DOI:10.9734/IJECC/2019/v9i430110.

Ali Z, Bhaskar B S. Basic statistical tools in research and data analysis. Indian J Anaesth. 2016; 60(9): 662–669. DOI: 10.4103/0019-5049.190623.

Kangabam RD, Bhoominathan SD, Kanagaraj S, Munisamy G. Development of a water quality index (WQI) for the Loktak Lake in India. Appl Water Sci. 2017 June; 8(27): 3-14. DOI:10.1007/s13201-017-0579-4.

Rashad S, Moneem MA, El- Chaghaby G. Seasonal variation and correlation between the physical, chemical and microbiological parameters of Nile water in selected area in Egypt (Case study). Baghdad Sci J. 2020 Dec 1; 17(4): 1160-1168. DOI: http://dx.doi.org/10.21123/bsj.2020.17.4.1160.

Al-Salim H T, Shehab M Z. Assessments of Water Quality index (WQI) For Tigris River in Mosul City/North of Iraq. Int. j. res. 2016 August; 2(8): 82-93. https://www.academia.edu/28424199/Assessments of Water Quality index WQI for Tigris River in Mosul City North of Iraq.

Sapkal RS, Valunjkar SS. development and sensitivity analysis of water quality index for evaluation of surface water for drinking purpose. Int J Civ Eng. 2013; 4(4): 119-134. (www.iaeme.com/ijciet.asp).

Arief S, Nitin M, Abdullah Y, Perera BC. Development of River Water Quality Indices - a review. Environ Monit Assess. 2016; 188: 58. DOI 10.1007/s10661-015-5050-0.

Ighalo J, Adeniyi AG, Marques G. Artificial intelligence for surface water quality monitoring and assessment: a systematic literature analysis. Model Earth Syst Environ. 2021; 7(2): 3. DOI:10.1007/s40808-020-01041-z.

Hashim K, Al-Araji Y. Evaluation of Physical Chemical and Biological Characteristics of Underground Wells in Badra City, Iraq. Baghdad Sci J. 2019; 16(3): 560-570. DOI:10.21123/bsj.2019.16.3.0560

Wang J, Lautz LS, Nolte TM, Posthuma L, Koopman K, Leuven R, et al. Towards a systematic method for assessing the impact of chemical pollution on ecosystem services of water systems. J Environ Manage. 2021; 281: 111-873. DOI: 10.1016/j.jenvman.2020.111873.

Singh KP, Malik A, Sinha S, Mohan D. Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)-a case study. Water Res. 2004; 38: 3980–3992. DOI: 10.1007/s10653-005-9001-5

Muangthong S, Shrestha S. Assessment of surface water quality using multivariate statistical techniques: case study of the Nampong River and Songkhram River, Thailand. Environ Monit Assess. 2015; 187(9):4774. DOI:10.1007/s10661-015-4774-1

Ghosh S, Manoj K, Padhy PK. haracterization and Classification of Hydrochemistry Using Multivariate graphical and Hydro Statistical Techniques. Res J Chem Sci. 2013; 5 (3): 32 – 42. (www.isca.in)

Yousef D. The Orontes Water Pollution Patterning By Means of Geographic Information System GIS - Syria. J. Res. Sci. Stud. Eng. 2009; 31 (1): 4-15. (https://www.researchgate.net/publication/266558749 Using GIS to Improve Monitoring of Water Quality in El-Assi River).

Ahmad A. Evaluation of Groundwater Quality Index for drinking purpose from some villages around Darbandikhan district, Kurdistan Region–Iraq. J Agric Vet Sci. 2014; 7(9):34-41. (www.iosrjournals.org).

Azhar SC, Aris AZ, Yusoff MK, Ramlia MF, Juahir H. Classification of River Water Quality Using Multivariate Analysis. Proc Env Sci. 2015; 30: 79-84. DOI.org/10.1016/j.proenv.2015.10.014.

Ibrahim A, Juahir H, Toriman ME, Kamarudin MKA, Isiyaka HA. Assessment of Surface Water Quality Using Multivariate Statistical Techniques in the Terengganu River Basin. Mal J Anal Sci. 2015; 19 (2):338–348 .(https://www.researchgate.net/publication/281927411 Assessment_of_surface water quality using multivariate statistical techniques in the terengganu river basin ).

Shekha Y, Ali LA, Toma JJ. Assessment of Water Quality and Trophic Status of Duhok Lake Dam. Baghdad Sci J. 2017; 14(2): 335-342. DOI:10.21123/bsj.2017.14.2.0335

Oliveira J, Maia K, Castro N, Oliveir S. Spatial-temporal analysis of the surface water quality of the Pará River Basin through statistical techniques. Rev. Ambient. Água. 2019 Feb; 14(1): 1-14. DOI.org/10.4136/ambi-agua.2322.

Adejoro CO, Ogwueleka FN. Users Perception of Social Media Opportunities and Challenges. Int J Sci Res. 2020; 8(4): 93. DOI:10.29333/ojcmt/2451.

Chen T, Zhang H, Sun C, Li H, Gao Y. Multivariate statistical approaches to identify the major factors governing groundwater quality. Appl water Sci. 2018; 8, 215: 1-6. DOI:10.1007/s13201-018-0837-0

Mathuram T, Chandran M, Dinakaran K. Study On Physicochemical Parameters Of Surface Water Of Vaigai River Near Madurai City, Tamil Nadu, India. Int J Creat Res Thoughts. 2017; 5(4): 1-24. (www.ijcrt.org).

Ewaid SH, Abed SA, Kadhum SA. Predicting the Tigris River water quality within Baghdad, Iraq by using water quality index and regression analysis. Environ Technol Innov. 2018; 11:390-398. DOI.org/10.1016/j.eti.2018.06.013

Hossain G, Reza S, Nessa L, Ahmed SS. Factor and cluster analysis of water quality data of the groundwater wells of Kushtia, Bangladesh: Implication for arsenic enrichment and mobilization. J Geol Soc India. 2013 March; 81: 377-384. DOI: 10.1007/s12594-013-0048-0.

Rahman K, Barua S, Alam S, Aalm A. Ecological Risk Assessment of Heavy Metals concentration in Sediment of the Shitalakhya River. Int Multidiscip Res J. 2020 june; 6 (6): 15-20. (https://www.researchgate.net/publication /343975536 Ecological Risk Assessment of Heavy Metals concentration in Sediment of the Shitalakhya River).