TY - CONF

T1 - Relative importance of secondary settling tank models in WWTP simulations

T2 - A global sensitivity analysis using BSM2

A1 - Ramin,Elham

A1 - Flores-Alsina,Xavier

A1 - Sin,Gürkan

A1 - Gernaey,Krist

A1 - Jeppsson,Ulf

A1 - Mikkelsen,Peter Steen

A1 - Plósz,Benedek

AU - Ramin,Elham

AU - Flores-Alsina,Xavier

AU - Sin,Gürkan

AU - Gernaey,Krist

AU - Jeppsson,Ulf

AU - Mikkelsen,Peter Steen

AU - Plósz,Benedek

PY - 2012

Y1 - 2012

N2 - Results obtained in a study using the Benchmark Simulation Model No. 1 (BSM1) show that a one-dimensional secondary settling tank (1-D SST) model structure and its parameters are among the most significant sources of uncertainty in wastewater treatment plant (WWTP) simulations [Ramin et al., 2011]. The sensitivity results consistently indicate that the prediction of sludge production is most sensitive to the variation of the settling parameters. In the present study, we use the Benchmark Simulation Model No. 2 (BSM2), a plant-wide benchmark, that combines the Activated Sludge Model No. 1 (ASM1) with the Anaerobic Digestion Model No. 1 (ADM1). We use BSM2 as a vehicle to compare two different 1-D SST models, and to assess the relative significance of their performance on WWTP simulation model outputs. The two 1-D SST models assessed include the firstorder model by Takács et al. [1991] and the second-order convection-dispersion<br/>tool [Plósz et al., 2007]. Additionally, we assess the impact of two operational strategies for excess activated sludge wastage on simulation performance. A global sensitivity analysis (GSA) on BSM2 was carried out using two methods: (a) linear regression of Monte Carlo simulations (SRC method); and (b) Morris screening. The overall objective of assessing the 1-D SST model selection and<br/>parameters in GSA is to provide a parameter sensitivity ranking for WWTP calibration exercises, aiming at predicting key plant performance criteria, including methane production and effluent water quality index. Results obtained in this study show that, 1-D SST model parameters strongly influence biogas production via anaerobic digestion and the plant’s effluent water quality, but they have limited<br/>effect on estimating the quality of nitrogen rich returns from the digester.

AB - Results obtained in a study using the Benchmark Simulation Model No. 1 (BSM1) show that a one-dimensional secondary settling tank (1-D SST) model structure and its parameters are among the most significant sources of uncertainty in wastewater treatment plant (WWTP) simulations [Ramin et al., 2011]. The sensitivity results consistently indicate that the prediction of sludge production is most sensitive to the variation of the settling parameters. In the present study, we use the Benchmark Simulation Model No. 2 (BSM2), a plant-wide benchmark, that combines the Activated Sludge Model No. 1 (ASM1) with the Anaerobic Digestion Model No. 1 (ADM1). We use BSM2 as a vehicle to compare two different 1-D SST models, and to assess the relative significance of their performance on WWTP simulation model outputs. The two 1-D SST models assessed include the firstorder model by Takács et al. [1991] and the second-order convection-dispersion<br/>tool [Plósz et al., 2007]. Additionally, we assess the impact of two operational strategies for excess activated sludge wastage on simulation performance. A global sensitivity analysis (GSA) on BSM2 was carried out using two methods: (a) linear regression of Monte Carlo simulations (SRC method); and (b) Morris screening. The overall objective of assessing the 1-D SST model selection and<br/>parameters in GSA is to provide a parameter sensitivity ranking for WWTP calibration exercises, aiming at predicting key plant performance criteria, including methane production and effluent water quality index. Results obtained in this study show that, 1-D SST model parameters strongly influence biogas production via anaerobic digestion and the plant’s effluent water quality, but they have limited<br/>effect on estimating the quality of nitrogen rich returns from the digester.

KW - Modelling

KW - ASM

KW - BSM

KW - Water quality

KW - Simulators

KW - Uncertainty

KW - Good modelling practice

KW - Sensitivity analysis

UR - http://www.iemss.org/society/index.php/iemss-2012-proceedings

ER -