6533b823fe1ef96bd127e251

RESEARCH PRODUCT

Micropollutants throughout an integrated urban drainage model: Sensitivity and uncertainty analysis

Giorgio ManninaAlida CosenzaGaspare Viviani

subject

HydrologyMathematical modellingSettore ICAR/03 - Ingegneria Sanitaria-Ambientale0208 environmental biotechnologyContaminants of emerging concerns; Mathematical modelling; Monte Carlo simulations; Sensitivity analysis; Urban water quality; Water Science and TechnologyUrban water qualityEnvironmental engineering02 engineering and technologySorption coefficient010501 environmental sciences01 natural sciencesContaminants of emerging concern020801 environmental engineeringKey factorsWater bodySensitivity analysiEnvironmental scienceSewage treatmentSensitivity (control systems)DrainageMonte Carlo simulationUncertainty analysisUncertainty reduction theory0105 earth and related environmental sciencesWater Science and Technology

description

Abstract The paper presents the sensitivity and uncertainty analysis of an integrated urban drainage model which includes micropollutants. Specifically, a bespoke integrated model developed in previous studies has been modified in order to include the micropollutant assessment (namely, sulfamethoxazole – SMX). The model takes into account also the interactions between the three components of the system: sewer system (SS), wastewater treatment plant (WWTP) and receiving water body (RWB). The analysis has been applied to an experimental catchment nearby Palermo (Italy): the Nocella catchment. Overall, five scenarios, each characterized by different uncertainty combinations of sub-systems (i.e., SS, WWTP and RWB), have been considered applying, for the sensitivity analysis, the Extended-FAST method in order to select the key factors affecting the RWB quality and to design a reliable/useful experimental campaign. Results have demonstrated that sensitivity analysis is a powerful tool for increasing operator confidence in the modelling results. The approach adopted here can be used for blocking some non-identifiable factors, thus wisely modifying the structure of the model and reducing the related uncertainty. The model factors related to the SS have been found to be the most relevant factors affecting the SMX modeling in the RWB when all model factors (scenario 1) or model factors of SS (scenarios 2 and 3) are varied. If the only factors related to the WWTP are changed (scenarios 4 and 5), the SMX concentration in the RWB is mainly influenced (till to 95% influence of the total variance for S SMX,max ) by the aerobic sorption coefficient. A progressive uncertainty reduction from the upstream to downstream was found for the soluble fraction of SMX in the RWB.

https://doi.org/10.1016/j.jhydrol.2017.09.026