*Promising Techniques for Wastewater Treatment and Water Quality Assessment*


#### **Table 4.**

*Spearman rank correlation coefficients.*


**Table 5.** *Intermediate results for the Spearman correlation.* *Water Quality Parameters and Monitoring Soft Surface Water Quality Using Statistical… DOI: http://dx.doi.org/10.5772/intechopen.97372*

Spearman coefficients between the WQI and the water quality indicators that were measured.

**Table 4** shows the high values obtained for WQI are associated with the high values obtained for chlorides, nitrates, nitrites, ammonium, total nitrogen, sulphates, lead, cadmium, iron, zinc. The association between these variables would be considered statistically significant.

**Table 5** exemplifies such a calculation for the correlation coefficient between WQI and CCO-Cr.

For chlorides, nitrates, nitrites, ammonium, sulphates, lead, cadmium, iron, zinc, total nitrogen, the values of p coefficient are less than 0.001 (i.e., highly significant with confidence greater than 99.99%). For pH and DO, p < 0.01 means the statistical links are significant and the confidence is 99%.

Once the correlations between pollutants and WQI are identified, the sources of pollution can be established or the related process.

#### **4. Conclusions**

This chapter highlighted the importance of using statistical methods to display the water quality condition, using WQI evaluation and Pearson and Spearman correlations.

In order to exemplify the statistical methods, we have used a series of data from our previous work, consisting of 13 parameters measured for water samples taken from the Danube River, from Galati City area, Romania. Statistical correlations were made between quality parameters and Water Quality Index; thus, it was possible to identify which are the pollutants that determined an advanced degree of water pollution. The excessive pollution which occurred during the time interval November 2016–June 2017 is due to the presence of high concentrations of chlorides, nitrates, nitrites, ammonium, sulphates, lead, cadmium, iron and zinc. In recent times there are many statistical software for water quality analysis. If we do not have, for various reasons such programs, the statistical approach can be done classically. Water Quality Index (WQI) provides information on the overall quality of the water, while the correlation coefficients may indicate the parameters that influenced the changes in water quality.

#### **Acknowledgements**

This study was funded by the main author's personal resources.

*Promising Techniques for Wastewater Treatment and Water Quality Assessment*
