Uncertainty assessment of a membrane bioreactor model using the GLUE methodology

A mathematical model for the simulation of physical-biological organic removal by means of a membrane bioreactor (MBR) has been previously developed and tested. This paper presents an analysis of the uncertainty of the MBR model. Particularly, the research explores the applicability of the Generalised Likelihood Uncertainty Estimation (GLUE) methodology that is one of the most widely used methods for investigating the uncertainties in the hydrology and that now on is spreading in other research field. For the application of the GLUE methodology, several Monte Carlo simulations have been run varying the all model influential parameters simultaneously. The model was applied to an MBR pilot plant located at the Acqua dei Corsari WWTP (Palermo, IT) where water quality data were gathered. In particular, the MBR pilot plant consists of a lab-scale hollow fibre membrane module in submerged configuration. The GLUE methodology enabled us to gain useful insight about the robustness of the model approach. Particularly, the results showed that the biological process is influenced mainly by the parameters characterising the formation and degradation of Soluble Microbial Products, whereas the fouling phenomenon is mainly influenced by the backwashing efficiency. The application of the GLUE methodology shows that the model considered for the MBR simulation is somehow too simple in order to predict plants performances. Indeed, GLUE enabled us to identify the main model components that needs to be improved and where much attention has to be paid both in terms of model algorithms and quality data to be gathered. This studies confirmed the suitability of the GLUE methodology as a powerful tool for simplified screening methodology to assess the uncertainty also in the field of wastewater treatment.