Abstract
This study aimed to develop a comprehensive Ain El Houtz Wastewater Treatment Plant (WWTP) model that represents its biological nutrient removal process to simulate its performance and assess the model's predictability. Operational data was collected and analyzed over three years (2020 to 2023), to characterize the water quality of influent and effluent discharged from the plant. Physicochemical parameters such as Total Suspended Solids (TSS), Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD5), Ammonium-Nitrogen (NH4), Nitrite-Nitrogen (N-NO2−), Nitrate-Nitrogen (N-NO3−), and Phosphate ions (PO4-3) were considered. Using the GPS-X software modeling platform, a process flow diagram was developed to integrate the ASM2d model for biological nutrient removal. Through the sensitivity analysis of kinetic and stoichiometric parameters, the research identified the key parameters that impacted the nutrient removal efficiency, which in turn further guided the calibration process. The calibration adjustments focused primarily on parameters associated with denitrification, autotrophic growth, and oxygen saturation coefficients. Statistical measures such as Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) were used to evaluate the model’s performance in both steady-state and dynamic-state validation scenarios. Results indicated that for the steady state the MAE and RMSE were the same, NH4 (6.06) N-NO2−& N-NO3− (1.36), and PO4-3 (3.167), while for dynamic-state we noticed a difference between the MAE and RMSE for the concentration, indicating the complexity of modeling nutrient removal processes. It was observed that PO4−3 concentration was not affected by the sensitivity analysis, possibly due to the lack of availability of specific process for the phosphorus removal in the treatment plant, further studies are needed to be carried out to address this issue in detail.