Hydrogeochemical Study and Geospatial Analysis of Water Quality Using GIS based Water Index and Multivariate Statistics in Kombolcha City, Ethiopia

• Published in: Water, air, and soil pollution air, and soil pollution, 2024-10, Vol.235 (10), p.637, Article 637
• Main Authors: Adamu, Anteneh Yayeh, Nigussie, Asmare Belay, Amognehegn, Asnake Enawgaw
• Format: Article
• Language: English
• Subjects: Anions; Anthropogenic factors; Atmospheric Protection/Air Quality Control/Air Pollution; Cadmium; Calcium carbonate; Calcium ions; Calcium sulfate; Carbonates; Cation exchange; Cation exchanging; Cations; Chromium; Climate Change/Climate Change Impacts; Correlation; Correlation analysis; Data analysis; Earth and Environmental Science; Effluents; Environment; Geochemistry; Geographic information systems; Geographical information systems; Groundwater; Groundwater pollution; Groundwater quality; Heavy metals; Hydrogeochemistry; Hydrogeology; Industrial pollution; Industrial sites; Iron; Lead; Magnesium; Manganese; Mineralization; Multivariate analysis; Pollution; Pollution index; Pollution levels; Pollution sources; Principal components analysis; Silicates; Soil Science & Conservation; Spatial analysis; Spatial data; Statistical analysis; Sulfur dioxide; Surface water; Surface-groundwater relations; Trace metals; Urbanization; Waste disposal; Water analysis; Water pollution; Water quality; Water Quality/Water Pollution; Water sampling
• ISSN: 0049-6979; 1573-2932
• DOI: 10.1007/s11270-024-07438-1

The study was carried out to evaluate hydro geochemistry and the risk of groundwater and surface water pollution in the Kombolcha area. To achieve this, hydrogeochemical analysis, water heavy metal, geospatial data analysis, correlation matrix, principal component analysis, Heavy metal Pollution Index (HPI), and Water Quality Index (WQI) methodologies were employed. A total of 36 samples (both water and effluent samples) had been collected and assessed for major physicochemical variables and heavy metals. Hydrogeochemical methods showed groundwater mineralization due to (1) silicate weathering, (2) cation exchange processes, and (3) anthropogenic sources (i.e., contaminated discharge of sulphate, carbonate, and trace metal effluents). The study result revealed that major ions dominating the area are Ca 2+  > Na +  > Mg 2+  > K + , HCO3 −  > SO 2−  > Cl −  > NO3 − , and Fe > Mn > Pb > Cr > Cd for cations, anions and trace metals respectively with all heavy netals had mean concentrations above the WHO recommended limits. Calculated Pollution indices revealed 50.7% of the sample belongs to a low level of pollution, while 35% and 14.3% belong to a medium and high level of pollution respectively which consequently translating the area into high groundwater pollution zones. The correlation matrix revealed that no significant correlation exists between the water quality variables (Cl and NO3 − with Fe, Pb, Cr, Mn, and Cd). PCA was applied on the data set to identify the spatial sources of pollution in groundwater and in the first principal component analysis, Mn, Fe, Cr, Pb, and Cd (in descending order) were found in amounts greater than 0.5, confirming that these metals were from anthropogenic sources. The combined assessments based on WQI and HPI, the study showed that water samples in the proximity of industrial sites are polluted by factories effluent and uncontrolled waste disposal due to urbanization.