PCA was used to extract the most important parameters explaining the quality of the water and determining the latent factors affecting the water quality. PCA (after varimax rotation) of analysed variables in the pre- and post-monsoon season extracts three principal components (PC1, PC2, and PC2), accounting for 97.759 and 99.123% of the cumulative variables of the dataset (eigen value >1), respectively and are shown in Table 6. In pre-monsoon season, the first principal component (PC1) exhibits higher loadings for pH, TA, DO, BOD, COD, Cl−, 
, Fe. This component can be linked to anthropogenic activity and exogenic contributions. The second principal component (PC2) accounts for EC, TDS, and TH; which can be attributed to geogenic factors such as soil erosion and mineral dissolution in the lake watershed. PC 3 shows higher loadings for TN, TP, and Chl-a, which infers lake water chemistry is influenced by trophic parameters due to excess nutrient loading in the lake water system. While during the post-monsoon season, the PC1 reveals higher loadings for pH, EC, TDS, TN, and Fe, which may occur due to the combined influence of anthropogenic contributions and temporal factors (such as precipitation and mineral dissolution). The PC2 accounts for TP and Chl-a; which is an indicative of eutrophic condition and excess nutrient in lake water. PC3 shows higher loadings for TSS, 
, Cl−, which can be linked with lithogenic and exogenic factors.
Varimax rotated PCA loadings matrix of Mirik lake water parameters
| Variables | Component (pre-monsoon) | Component (post-monsoon) | ||||
|---|---|---|---|---|---|---|
| PC1 | PC2 | PC3 | PC1 | PC2 | PC3 | |
| pH | .864 | .425 | .252 | .873 | .373 | .290 |
| EC | .594 | .758 | .251 | .739 | .429 | .496 |
| TSS | .018 | .642 | .645 | .197 | .336 | .896 |
| TDS | .590 | .767 | .240 | .739 | .436 | .498 |
| TA | .970 | .100 | .099 | .603 | .637 | .469 |
| TH | .550 | .706 | .421 | .628 | .651 | .381 |
| DO | .706 | .555 | .421 | .678 | .583 | .411 |
| BOD | .711 | .646 | .273 | .683 | .504 | .511 |
| COD | .742 | .589 | .303 | .654 | .588 | .458 |
| Cl− | .861 | .469 | .148 | .591 | .406 | .655 |
 | .837 | .295 | .442 | .549 | .195 | .806 |
 | .143 | .198 | .934 | .277 | .871 | .395 |
 | .403 | .170 | .824 | .887 | .320 | .325 |
| Chl-a | .336 | .577 | .602 | .667 | .679 | .113 |
| Fe | .735 | .488 | .468 | .849 | .324 | .409 |
| Variables | Component (pre-monsoon) | Component (post-monsoon) | ||||
|---|---|---|---|---|---|---|
| PC1 | PC2 | PC3 | PC1 | PC2 | PC3 | |
| pH | .864 | .425 | .252 | .873 | .373 | .290 |
| EC | .594 | .758 | .251 | .739 | .429 | .496 |
| TSS | .018 | .642 | .645 | .197 | .336 | .896 |
| TDS | .590 | .767 | .240 | .739 | .436 | .498 |
| TA | .970 | .100 | .099 | .603 | .637 | .469 |
| TH | .550 | .706 | .421 | .628 | .651 | .381 |
| DO | .706 | .555 | .421 | .678 | .583 | .411 |
| BOD | .711 | .646 | .273 | .683 | .504 | .511 |
| COD | .742 | .589 | .303 | .654 | .588 | .458 |
| Cl− | .861 | .469 | .148 | .591 | .406 | .655 |
| | .837 | .295 | .442 | .549 | .195 | .806 |
| | .143 | .198 | .934 | .277 | .871 | .395 |
| | .403 | .170 | .824 | .887 | .320 | .325 |
| Chl-a | .336 | .577 | .602 | .667 | .679 | .113 |
| Fe | .735 | .488 | .468 | .849 | .324 | .409 |
Extraction method: principal component analysis; Rotation method: Varimax with Kaiser normalization.
Rotation converged in nine iterations. Values highlighted in bold represent higher loading and show larger correlations with extracted PC.