Page 168 - AJWEP-22-6

Yadav, et al.

be attributed to the interaction of NH with minerals the robustness of the regression model in predicting
3
in the water (such as calcium and magnesium) or its total alkalinity based on NH concentration.
3
influence on the solubility of carbonate minerals, which
contribute to TH. The small maximum deviation (0.115) 3.3.5.9. Conductivity versus total alkalinity
further confirms the robustness of the regression model. The regression line equation y = 0.876x + 0.119
(maximum deviation = 0.0370, r = 0.983) was obtained
2
3.3.5.6. TH versus total alkalinity by plotting conductivity against total alkalinity, as
The regression line equation y = 1.10x − 0.0963 depicted in Figure S8. The regression analysis revealed
(maximum deviation = 0.0440, r = 0.974) was obtained a very strong positive linear relationship, as indicated
2
by plotting TH against total alkalinity, as shown in by the high coefficient of determination (r = 0.983).
2
Figure S5. The high r² value (0.974) indicates a very This equation suggests that for every unit increase in
strong positive relationship. Moreover, this r value is total alkalinity, conductivity increases by 0.876 units.
2
higher than for TH versus NH 0.905), free CO 0.942), This relationship is consistent with the expected
2 (
3 (
conductivity (0.925), and TDS (0.700), suggesting that behavior, as total alkalinity is primarily influenced by
total alkalinity is the strongest predictor of TH among CO and HCO , which are conductive and contribute
2−
−
3
3
the variables analyzed. This difference may be due to to the overall ion concentration in water. The very
the direct relationship between total alkalinity and the small maximum deviation (0.0370) further confirms the
carbonate minerals that contribute to TH. robustness of the regression model.
The r value for total alkalinity versus conductivity
2
3.3.5.7. Total alkalinity versus chloride (0.983) is higher than those for total alkalinity versus Cl
−
The regression line equation y = 0.664x + 0.331 (0.902), NH (0.899), and TH (0.974). This suggests that

3
(maximum deviation = 0.196, r = 0.902) was total alkalinity is the strongest predictor of conductivity
2
obtained by plotting total alkalinity against Cl , among the variables analyzed.
−
as shown in Figure S6. The r value of 0.902
2
indicates a strong positive linear relationship. This 3.3.5.10. Free carbon dioxide versus ammonia
equation implies that for every unit increase in Cl The regression line equation y = 0.906x + 0.103
−
concentration, total alkalinity increases by 0.664 (maximum deviation = 0.0898, r = 0.951) was obtained
2
units. This relationship may be attributed to the by plotting free CO against NH , as depicted in
2
3
coexistence of Cl ions with other ions (such as Figure S9. The regression analysis revealed a very strong
−
sodium, Ca , or Mg ) that contribute to alkalinity, or positive linear relationship, as indicated by the high
2+
2+
it may reflect indirect geochemical processes linking value of r (0.951). This equation suggests that for every
2
Cl and alkalinity. The relatively small maximum unit increase in NH concentration, free CO increases
−
3
2
deviation (0.196) further supports the reliability of by 0.906 units. This relationship may be attributed to the
the regression model in predicting total alkalinity reaction of NH with water to form NH and hydroxide
+
4
3
based on Cl concentration. ions, which can influence the equilibrium of CO in
−
2
water and shift it toward the formation of more free
3.3.5.8. Total alkalinity versus ammonia CO . The small maximum deviation (0.0898) further
2
The regression line equation y = 1.11x − 0.0804 supports the robustness of the regression model.
(maximum deviation = 0.0909, r = 0.899) was
2
obtained by plotting total alkalinity against NH , as 3.3.5.11. Escherichia coli versus total dissolved solids
3
shown in Figure S7. The regression analysis revealed The regression line equation y = 1.18xm − 0.187
a strong positive linear relationship, as indicated by (maximum deviation = 0.280, r = 0.953) was obtained
2
the high coefficient of determination (r = 0.899). This by plotting E. coli against TDS, as shown in Figure S10.
2
equation suggests that for every unit increase in NH 3 The regression analysis revealed a very strong positive
concentration, total alkalinity increases by 1.11 units. linear relationship, indicated by the high r value. This
2
This relationship may be attributed to the reaction of equation suggests that for every unit increase in TDS,
NH with water to form NH , which can influence the E. coli concentration increases by 1.18 units. This
+
4
3
buffering capacity of water and contribute to alkalinity. relationship may be attributed to the fact that higher
In addition, NH may coexist with other ions (such as TDS levels often indicate the presence of organic
3
CO or HCO ) that directly contribute to alkalinity. matter, nutrients, or other dissolved substances that
−
2−
3
3
The small maximum deviation (0.0909) further confirms support the growth and survival of E. coli and other
Volume 22 Issue 6 (2025) 162 doi: 10.36922/AJWEP025120083