## 11 Scatter Plot
### Cluster Analysis  
Cluster analysis is a collection of multivariate approaches to identify true data clusters or stations [92]. Hierarchical cluster analysis (HCA) is a useful tool for evaluating geochemical data and has been used to classify groundwater samples to develop geochemical models [93; 94]. The basic goal of HCA is to classify things into statistically distinct groups or clusters so that objects within one cluster are similar, but different, from those in another [95]. After normalizing the data set to the Z scale, the hydrogeochemical characteristics of 40 groundwater samples were used in hierarchical cluster analysis (HCA) using [PERSON]'s linkage approach [96]. Standardization increases the influence of factors with low variance and reduces the influence of variables with high variance. This also makes the data dimensionless by removing the influence of multiple measures. Figure 13a shows the dendrogram of the site pattern resulting from the cluster analysis plot (CA) for January 2020, and Figure 13b shows the dendrogram for January 2021. \begin{table}
\begin{tabular}{l r r r r r r} \hline \hline \multirow{2}{*}{**Parameters**} & \multicolumn{3}{c}{**January 2020**} & \multicolumn{3}{c}{**January 2021**} \\ \cline{2-7}  & **F\_1** & **F\_2** & **F\_1** & **F\_2** & **F\_3** & **F\_4** \\ \hline
**pH** & 0.10 & \(-\)_0.86_ & 0.11 & 0.04 & \(-\)0.15 & 0.93 \\
**EC** & _0.94_ & 0.31 & _0.87_ & 0.44 & \(-\)0.08 & 0.05 \\
**TDS** & _0.94_ & 0.31 & _0.75_ & _0.63_ & 0.16 & 0.01 \\
**Ca\({}^{2+}\)** & _0.96_ & 0.03 & _0.93_ & \(-\)0.15 & 0.06 & \(-\)0.03 \\
**Mg\({}^{2+}\)** & _0.96_ & 0.02 & _0.91_ & 0.09 & \(-\)0.01 & 0.14 \\
**Na\({}^{+}\)** & _0.84_ & _0.46_ & 0.07 & _0.98_ & \(-\)0.03 & \(-\)0.02 \\
**K\({}^{+}\)** & _0.78_ & _0.50_ & 0.03 & _0.96_ & \(-\)0.02 & 0.05 \\
**Cl\({}^{-}\)** & _0.89_ & _0.39_ & 0.44 & _0.60_ & 0.48 & \(-\)0.02 \\
**HCO\({}_{3}\)\({}^{-}\)** & _0.73_ & \(-\)0.12 & _0.80_ & 0.03 & \(-\)0.33 & 0.16 \\
**SO\({}_{4}\)\({}^{2-}\)** & _0.89_ & 0.08 & 0.26 & 0.51 & \(-\)0.62 & \(-\)0.36 \\
**NO\({}_{3}\)\({}^{-}\)** & _0.84_ & 0.21 & \(-\)0.12 & 0.09 & 0.79 & \(-\)0.27 \\
**F\({}^{-}\)** & 0.18 & _0.49_ & 0.49 & 0.27 & \(-\)0.21 & \(-\)0.17 \\
**Total** & 7.80 & 1.86 & 4.19 & 3.22 & 1.45 & 1.15 \\
**\% of Variance** & 64.99 & 15.50 & 34.93 & 26.85 & 12.11 & 9.55 \\
**Cumulative \%** & 64.99 & 80.48 & 34.93 & 61.78 & 73.88 & 83.43 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Principal component analysis for the analytical results. Figure 13: Dendrogram showing the spatial clustering of samples for (**a**) January 2020 and (**b**) January 2021. The dendrogram was divided into several groups, each of which had several subgroups and singletons. In January 2020, the groundwater stations were divided into two main clusters (Figure 13a). Cluster 1, with sampling sites 4 through 9, 11, 13, 14, 17, 18, 20 through 25, 27 through 35, and 38 through 40, was characterized by the weathering and regeneration ion exchange processes. The mean EC of the samples present in cluster 1 was 862.5 \(\upmu\)S/cm and HCO\({}_{3}\)\({}^{-}\) (147.4 mg/L) was the dominant ion, followed by Cl\({}^{-}\) (111.4 mg/L) and Na\({}^{+}\) (110.9 mg/L), in terms of mean concentrations. Cluster 1 included the uncontaminated groundwater. Cluster 2, with samples 1, 2, 3, 10, 12, 15, 16, 19, 26, 36, and 37, could be classified as a mixture of seawater intrusion and salinization based on the salts formed in relation to their hydrogeochemistry. The mean EC of this second cluster group was 4850 \(\upmu\)S/cm and the predominant ion in these samples was Cl\({}^{-}\) (1205.5 mg/L), followed by Na\({}^{+}\) (581.8 mg/L), and HCO\({}_{3}\)\({}^{-}\) (404.7 mg/L), which shows strong pollution of groundwater based on the mean values. In contrast, the stations in January 2021 were divided into three cluster groups (Figure 13b). Cluster 1, which included samples 1, 3, 4, 11 through 17, 22, 23, 29, 32, 34, 35, 37, 39, and 40, was moderately polluted due to the mixing of anthropogenic runoff and seawater.