Comparative Analysis of Groundwater Quality Index for Bhavani River Basin Using Remote Sensing and Statistical Analysis
Autor(en): |
Rahul Ravichandran
Raviraj Ayyavoo Lalitha Rajangam Nagarajan Madasamy Basker Murugaiyan Sumathi Shanmugam |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Jordan Journal of Civil Engineering, 1 Januar 2023, n. 1, v. 17 |
Seite(n): | 58-70 |
DOI: | 10.14525/jjce.v17i1.06 |
Abstrakt: |
This research was conducted to examine the drinking (WQI1) and irrigation (WQI2) water quality for the Bhavani river basin using statistical methodologies. The study area geographically covers up to 4207 km². For evaluating the Water Quality Index (WQI), fourteen groundwater parameters were employed and the data was gathered for two decades (1972–1990 & 2010–2019). The groundwater parameters include TDS, pH, EC, TH, Ca2+, Mg2+, Na+, K+, CO3 2-, HCO3 - , NO3 - , Cl- , F- and SO4 2-. The weightage arithmetic approach was utilized to compute the WQI1 and all the parameters were spatially represented using Arc GIS 10.3 software. To compute the WQI2, the Sodium Absorption Ratio (SAR), Sodium Percentage (%Na), Residual Sodium Carbonate (RSC), Magnesium Hazard Ratio (MHR), Kelly's Ratio (KR), Permeability Index (PI) and Potential Salinity (PI) are employed. The hydro-geochemical features are statistically examined using the Piper trilinear diagram, Gibbs plot, correlation matrix and PCA biplot. The study results suggest that irrigation-and drinking-water quality is worsening from 2% to 44% of the studied region. Statistical analysis also yields satisfactory findings for both decades. According to the geochemical study, the anion and cation ranking for the 1972 decade is Mg2+> Ca+> Na+> K+=Cl- >HCO3 - ->CO3 2->SO4 2-, while the ranking for the 2019 decade is Na+> Mg2+> Ca+> K+=HCO3 - >Cl- >SO4 2->CO3 2->F- . The research indicates viable locations for drinking and irrigation reasons, while the low groundwater quality areas need effective treatment procedures before groundwater utilization. KEYWORDS: Groundwater, Hydro-geochemistry, Remote sensing, Statistical analysis, Water quality index. |
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Datenseite - Reference-ID
10715740 - Veröffentlicht am:
21.03.2023 - Geändert am:
21.03.2023