Predictive Modeling of Gravity Filtration Performance for Potabilization of Variable Surface Waters: Application to Lake Kabongo Data and Perspectives for the Future Plant

Context: Increasing climatic variability threatens the efficacy of conventional water treatment lines, particularly gravity filtration, a robust and economically accessible process in resource-limited contexts. Lake Kabongo, a major supply source, exhibits significant quality fluctuations (turbidity, organic matter, algal blooms) likely to alter filter performance.  Objective: To develop a hybrid (mechanistic–statistical) predictive model of gravity filtration performance (effluent turbidity, head loss, cycle duration) based on raw water quality, to shift from empirical operation to anticipatory management.  Methodology: A systematic meta-analysis of over twenty historical trials conducted between May and June 2025 on Lake Kabongo water was performed. A hybrid model combining fundamental equations of porous media filtration and multivariate polynomial regressions calibrated on experimental data was developed. Validation is based on data partitioning (70/30), comprehensive statistical analysis (coefficients with 95% CI, residual analysis) and simulation of extreme climatic scenarios.  Key Results: Initial turbidity, Total Organic Carbon (TOC) concentration and UV275 absorbance explain over 85% of the performance variance. The final model shows coefficients of determination of 0.89 for effluent turbidity, 0.86 for TOC and 0.83 for UV275. Sensitivity analysis identifies activated carbon height (Hc) as the second most influential parameter after initial turbidity. Simulations reveal critical thresholds (e.g., turbidity > 100 NTU) beyond which filtration efficiency drops sharply.  Conclusion / Scope: The developed tool allows for optimization of the future Katebi containerized plant operation by anticipating at-risk periods and adjusting operational parameters. This approach is transferable to other gravity filtration systems subject to hydro-climatic variability and contributes to securing drinking water production in a context of global change.