Evaluation of Water quality in the Tigris River within Baghdad, Iraq using Multivariate Statistical Techniques

Document identifier: oai:DiVA.org:ltu-76502
Access full text here:10.1088/1742-6596/1294/7/072025
Keyword: Engineering and Technology, Teknik och teknologier, Civil Engineering, Geotechnical Engineering, Samhällsbyggnadsteknik, Geoteknik, Multivariate statistical techniques, Water quality, Tigris River, Iraq, Vattenteknik, Water Resources Engineering, Soil Mechanics
Publication year: 2019
Relevant Sustainable Development Goals (SDGs):
SDG 11 Sustainable cities and communitiesSDG 6 Clean water and sanitationSDG 2 Zero hunger
The SDG label(s) above have been assigned by OSDG.ai


This research concentrated on the Tigris River water quality monitoring information. Some multivariate statistical techniques were applied like basic Ingredient (PC) test, discriminant analysis (DA), multiple linear regression analysis (MLRA) to evaluate important parameters affecting water quality during year 2017-2018. The study included 25 water quality parameters, viz., Temperature (T), Potential of Hydrogen (pH), Turbidity (Tur), Total Alkaline (TA), Full rigidity (TH), Calcium (Ca+2), Chloride (Cl-1), Magnesium (Mg+2), Electrical Conductivity (EC), Sulfate (SO4-2), Total Solids (TS), Suspended Solids (SS), Iron (Fe+2), Fluoride (F-1), Aluminum (Al+3), Nitrite (NO2-1), Nitrate (NO3-1), Silica (SiO2), Phosphate (PO4-3), Ammonia (NH3), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD5), Chemical Oxygen Demand (COD), Sodium (Na+1), and Total Dissolved Solids (TDS). Generally, all the parameters were within the standards except Tur, TA, Ca+2, EC, SO4-2. The levels of Tur and EC are of critical factors influence upon the Tigris water quality. The PCA identified six principal components responsible for 78.12% of the variation caused by the industrial, domestic, municipal and agricultural runoff pollution sources. DA results produced the eight parameters; T, BOD5, EC, Mg+2, DO, Tur, Na+1, and COD as the most significant parameters differentiating the two parts of the year (the cold and warm seasons). The result of MLRA showed that BOD5, Na+1, T, DO, and PO4-3 are the important dependable factors for predicting the COD value as an indicator of organic and nonorganic pollution. This research demonstrated success importance utilizing Multivariate statistical methods like valuable instrument of administration, control, and preserve the water of the river.


Salwan Ali Abed

Department of Environment, College of Science, University of Al-Qadisiyah, Iraq
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Salam Hussein Ewaid

Technical Institute of Shatra, Southern Technical University, Iraq
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Nadhir Al-Ansari

Luleå tekniska universitet; Geoteknologi
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