Modeling Biological Nutrients Removal for Waste Water Treatment Plant Management: Case Study Ain El Houtz WWTP

Abstract

In recent years, it has become more important for wastewater treatment plants (WWTPs) to monitor nutrient concentrations in their effluents in order to protect the environment and human health. This study focuses on the Ain El Houtz WWTP and aims to develop a comprehensive model that accurately represents its biological nutrient removal process. The goal is to simulate its performance and assess the model's predictability. Operational data was collected and analyzed over a period of three years, from 2020 to 2022, to characterize the water quality of influent and effluent. 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 (PO4-3) were evaluated. Using the GPS-X modeling platform, the study developed a process flow diagram that integrates the ASM2d model for biological nutrient removal. Through sensitivity analysis, the research identified the key parameters that have an impact on nutrient removal efficiency, which in turn guided the calibration process. The focus of the calibration adjustments primarily lies 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 utilized to evaluate the model's performance in both steady state and dynamic validation scenarios. Results indicated differences between simulated and observed concentrations for ammonium, nitrite, nitrate, and phosphate, underscoring the complexity of accurately modeling nutrient removal processes.