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Fig. 4. Durov diagram plot for groundwater samples in Owerri metropolis

Figure 4 Durov diagram plot for groundwater samples in Owerri metropolis

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Table 1. Showing the stratigraphic succession within the study area [28] and [30]
Table 1. Showing the stratigraphic succession within the study area [28] and [30]
horizons [42,43]. The heavy rainfall coupled with deep water drawing nature of the trees in the soi contributes to the high infiltration of rainwater Variations in soil bulk density, soil total porosity and gravimetric moisture content are attributed tc different agronomic practices in the different lanc use types [11]. Due to clay movement, there is downward increase in clay content with well-developed argillic horizon in soils derived from coastal plain sand, while there is kandic horizon in soils derived from Ameki Shale [3]. Soils developed from the different parent materials have varying colours. Reddish brown to reddish orange and
horizons [42,43]. The heavy rainfall coupled with deep water drawing nature of the trees in the soi contributes to the high infiltration of rainwater Variations in soil bulk density, soil total porosity and gravimetric moisture content are attributed tc different agronomic practices in the different lanc use types [11]. Due to clay movement, there is downward increase in clay content with well-developed argillic horizon in soils derived from coastal plain sand, while there is kandic horizon in soils derived from Ameki Shale [3]. Soils developed from the different parent materials have varying colours. Reddish brown to reddish orange and
The correlation matrix presented in Table 4 indicates a strong positive relationship as the values tend close to 1 and a strong negative relationship as values tend close to -1. Unity (1) in the matrix implies the parameters are same and no quantitative or qualitative difference exists while zero (0) implies there is no correlation at all. The pH of water is strongly negatively correlated with magnesium ion. A strong positive correlation exists between EC and TDS, similar to the correlation between EC and TSS, plus EC and bicarbonate. By implication, when bicarbonate ion concentration, TDS, and TSS _ also increases in the groundwater, EC also increases. TDS, TSS and bicarbonate ion are strongly positively correlated to each other; increase in bicarbonate ion implies increase in TDS and TSS. It is important to mention that bicarbonate ions have the strongest influence on the EC and TDS of the groundwater in the study area. As expected, TSS retains a strong positive correlation between potassium ions and zinc ions. Magnesium ions and sodium ions, sodium ions and sulphate ions are strongly positively correlated. Increase in chloride ions in groundwater implies a strong reduction in the amount of bicarbonate ions, TDS and TSS while it strongly favours manganese ions. Nitrate ions are strongly positively correlated to sulphate ions, and sodium ions also. Increase in ferrous ions indicates a strong decrease in magnesium ions, sodium ions and sulphate ions. Generally, the statistical analysis of the entire study area (Table 5) shows that the Pb™ parameter exhibits the highest measure of dispersion with a range of 0.0005 and a CV% of 47.14. This implies that the Pb” constituent of the groundwater varies spatially over the study area more than any other constituent. Cr2*, Mn", K*, TSS, Zn**, Mg** and Cu** parameters follow this spatial variation trend in a descending order. Low values of CV% observed for temperature, Na’, pH, and Cl implies that the spatial distribution of these parameters across the study area are even. The relative abundance of majority of the cations in meq/| follows this sequence - Na* > Ca** > K* > Mg”, while that of the anions follows this sequence - HCO; > CI > Fig. 2. lon balance diagram for all sampling locations
The correlation matrix presented in Table 4 indicates a strong positive relationship as the values tend close to 1 and a strong negative relationship as values tend close to -1. Unity (1) in the matrix implies the parameters are same and no quantitative or qualitative difference exists while zero (0) implies there is no correlation at all. The pH of water is strongly negatively correlated with magnesium ion. A strong positive correlation exists between EC and TDS, similar to the correlation between EC and TSS, plus EC and bicarbonate. By implication, when bicarbonate ion concentration, TDS, and TSS _ also increases in the groundwater, EC also increases. TDS, TSS and bicarbonate ion are strongly positively correlated to each other; increase in bicarbonate ion implies increase in TDS and TSS. It is important to mention that bicarbonate ions have the strongest influence on the EC and TDS of the groundwater in the study area. As expected, TSS retains a strong positive correlation between potassium ions and zinc ions. Magnesium ions and sodium ions, sodium ions and sulphate ions are strongly positively correlated. Increase in chloride ions in groundwater implies a strong reduction in the amount of bicarbonate ions, TDS and TSS while it strongly favours manganese ions. Nitrate ions are strongly positively correlated to sulphate ions, and sodium ions also. Increase in ferrous ions indicates a strong decrease in magnesium ions, sodium ions and sulphate ions. Generally, the statistical analysis of the entire study area (Table 5) shows that the Pb™ parameter exhibits the highest measure of dispersion with a range of 0.0005 and a CV% of 47.14. This implies that the Pb” constituent of the groundwater varies spatially over the study area more than any other constituent. Cr2*, Mn", K*, TSS, Zn**, Mg** and Cu** parameters follow this spatial variation trend in a descending order. Low values of CV% observed for temperature, Na’, pH, and Cl implies that the spatial distribution of these parameters across the study area are even. The relative abundance of majority of the cations in meq/| follows this sequence - Na* > Ca** > K* > Mg”, while that of the anions follows this sequence - HCO; > CI > Fig. 2. lon balance diagram for all sampling locations
SD — Standard Deviation; CV% - Percent Coefficient of Variation Table 3. Standard deviation and percent coefficient of variation of samples collected in each sampling location in Owerri
SD — Standard Deviation; CV% - Percent Coefficient of Variation Table 3. Standard deviation and percent coefficient of variation of samples collected in each sampling location in Owerri
Table 4. Quality Assurance/Quality Control: Reliability analysis for the measured parameters
Table 4. Quality Assurance/Quality Control: Reliability analysis for the measured parameters
Table 5. Measures of central tendency and dispersion for groundwater samples in Owerri
Table 5. Measures of central tendency and dispersion for groundwater samples in Owerri
Table 6. Correlation matrix of some measured parameters
Table 6. Correlation matrix of some measured parameters
Table 7. Water classification by TDS level [59] Using the Piper diagram classification scheme presented by Ravikumar et al. [60], three hydrogeochemical facies were _ identified among the five samples. Samples from Orji, kenegbu and Obinze are classified into the Na*—CI water type, the sample from Orogwe alls into the Mixed Ca**-Na*-HCO; water type class while the sample from Naze lies in between he Na’—CI water type and the Mixed Ca’- Mg**-HCO; water type. In the cations triangle, every other sample is classified into the Na” + K” ype while the sample from Naze lies at the border between the Na* + K* type and the no- dominant type. In the anions triangle, the sample rom Orogwe is classified into the HCO; type
Table 7. Water classification by TDS level [59] Using the Piper diagram classification scheme presented by Ravikumar et al. [60], three hydrogeochemical facies were _ identified among the five samples. Samples from Orji, kenegbu and Obinze are classified into the Na*—CI water type, the sample from Orogwe alls into the Mixed Ca**-Na*-HCO; water type class while the sample from Naze lies in between he Na’—CI water type and the Mixed Ca’- Mg**-HCO; water type. In the cations triangle, every other sample is classified into the Na” + K” ype while the sample from Naze lies at the border between the Na* + K* type and the no- dominant type. In the anions triangle, the sample rom Orogwe is classified into the HCO; type
Table 8. Showing the classification of water by hardness [61] 4.3 Sodium Absorption Ratio (SAR)
Table 8. Showing the classification of water by hardness [61] 4.3 Sodium Absorption Ratio (SAR)
Fig. 6. Wilcox Diagram plot showing the viability of the samples for irrigation purposes
Fig. 6. Wilcox Diagram plot showing the viability of the samples for irrigation purposes
Fig. 7. Schoeller diagram for majority of heavy metals in the study area
Fig. 7. Schoeller diagram for majority of heavy metals in the study area
Fig. 9. Giggenbach triangle plot showing the water-rock equilibrium level of Owerri groundwater samples. Sqr(Mg) in the plot, is VMg
Fig. 9. Giggenbach triangle plot showing the water-rock equilibrium level of Owerri groundwater samples. Sqr(Mg) in the plot, is VMg
Related topics:
Environmental ScienceEnvironmental RemediationWater and wastewater treatmentGroundwater ContaminationEnergy and EnvironmentSoil and Water EngineeringEnvironmental SustainabilityInterpolation (Geostatistics)Remote sensing and GISIrrigation water use efficiency
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