Research Article
Prediction of the Impact of Land Usage Changes on Water Pollution in Public Space Planning with Machine Learning
Table 3
Determination coefficients of regression models of surface water pollution indicators at different spatial scales.
| Season | Water quality index | 50 m | 100 m | 200 m | 300 m | 400 m | 500 m | 600 m | Watershed |
| Wet season | TN | 0.640 | 0.704 | 0.786 | 0.835 | 0.839 | 0.853 | 0.871 | 0.902 | NH3-N | 0.594 | 0.674 | 0.777 | 0.829 | 0.839 | 0.860 | 0.876 | 0.899 | CODMn | 0.565 | 0.625 | 0.682 | 0.711 | 0.720 | 0.736 | 0.759 | 0.818 | DO | 0.197 | 0.237 | 0.349 | 0.433 | 0.464 | 0.488 | 0.475 | 0.485 |
| Dry season | TN | 0.639 | 0.684 | 0.749 | 0.786 | 0.798 | 0.810 | 0.824 | 0.869 | NH3-N | 0.667 | 0.741 | 0.829 | 0.879 | 0.882 | 0.894 | 0.906 | 0.928 | CODMn | 0.525 | 0.583 | 0.588 | 0.592 | 0.573 | 0.577 | 0.601 | 0.587 | DO | 0.583 | 0.607 | 0.662 | 0.670 | 0.652 | 0.658 | 0.637 | 0.62 |
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