Environment and Ecology Research Vol. 14(1), pp. 71 - 90
DOI: 10.13189/eer.2026.140107
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Modeling the Water Quality Index (CCME WQI) of Six Pasig River Main Line Monitoring Stations and Forecasting Using Machine Learning Models

P. S. O. David , A. J. G. Moreno , J. E. D. D. Soriano ^*, M. A. S. Tamayo
School of Civil, Environmental, & Geological Engineering, Mapúa University, Philippines

ABSTRACT

This study evaluated the water quality of the Pasig River Main Line by applying the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) and implemented machine learning models to forecast future trends. Water quality data from six monitoring stations spanning 2010 to 2024 were consolidated and translated into annual WQI scores. Three predictive models: Artificial Neural Networks (ANN), Gradient Boosted Regression (GBR), and Long Short Term Memory (LSTM), were used and assessed using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and coefficient of determination (R²). Among the models evaluated, the LSTM model exhibited the most consistent performance, achieving the lowest RMSE in four out of six stations and the lowest MAE in three. It demonstrated stable training behavior without signs of overfitting and effectively captured directional trends in water quality. However, generalizability remained limited, as only one station achieved a high R² value, likely due to the small dataset. Forecasts from 2025 to 2030 using the LSTM model indicated minimal, decimal-level changes in WQI scores, suggesting that the Pasig River is unlikely to exhibit significant improvement or deterioration within the forecast period. These results show the utility of machine learning in environmental forecasting and the necessity of implementing targeted, data-informed interventions in river rehabilitation programs.

KEYWORDS
Pasig River, CCME WQI, Water Quality, Machine Learning

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] P. S. O. David , A. J. G. Moreno , J. E. D. D. Soriano , M. A. S. Tamayo , "Modeling the Water Quality Index (CCME WQI) of Six Pasig River Main Line Monitoring Stations and Forecasting Using Machine Learning Models," Environment and Ecology Research, Vol. 14, No. 1, pp. 71 - 90, 2026. DOI: 10.13189/eer.2026.140107.

(b). APA Format:
P. S. O. David , A. J. G. Moreno , J. E. D. D. Soriano , M. A. S. Tamayo (2026). Modeling the Water Quality Index (CCME WQI) of Six Pasig River Main Line Monitoring Stations and Forecasting Using Machine Learning Models. Environment and Ecology Research, 14(1), 71 - 90. DOI: 10.13189/eer.2026.140107.