Keywords

Dynamic models, global sensitivity analysis, Bayesian methods, multi-objective functions, uncertainty propagation

Start Date

16-9-2020 3:40 PM

End Date

16-9-2020 4:00 PM

Abstract

Integrated urban drainage models (IUDM) are useful tools for protect and forecast the receiving water body’s quality state. IUDMs are generally made up by a cascade of sub-models (simulating the sewer system, wastewater treatment plant and receiving water body). The sub-models are connected together and the output of one sub-model becomes the input of the following one. The uncertainty produced in one sub-model propagates to the following ones in a manner dependent on the model structure, the estimation of parameters and the availability and uncertainty of measurements in the different parts of the system. Uncertainty basically propagates throughout a chain of models in which the simulation output from upstream models is transferred to the downstream ones as input. This study presents a summary of the results and insights gained in the last 15-years on sensitivity and uncertainty analysis in integrated urban drainage modelling. Specifically, several sensitivity and uncertainty methods were applied to multiple water-quality models. Advantage and dis-vantage of methods and modelling approaches will be presented with the final aims to draw future perspectives and challenges. The variance decomposition approach is applied in combination with sensitivity analysis to pin down the sub-models characterized by higher uncertainty. A balance in terms of uncertainty among the different sub-models was proposed to contain data and numerical efforts.

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Sep 16th, 3:40 PM Sep 16th, 4:00 PM

Sensitivity and uncertainty analysis in integrated Urban Drainage Modelling: where do we stand?

Integrated urban drainage models (IUDM) are useful tools for protect and forecast the receiving water body’s quality state. IUDMs are generally made up by a cascade of sub-models (simulating the sewer system, wastewater treatment plant and receiving water body). The sub-models are connected together and the output of one sub-model becomes the input of the following one. The uncertainty produced in one sub-model propagates to the following ones in a manner dependent on the model structure, the estimation of parameters and the availability and uncertainty of measurements in the different parts of the system. Uncertainty basically propagates throughout a chain of models in which the simulation output from upstream models is transferred to the downstream ones as input. This study presents a summary of the results and insights gained in the last 15-years on sensitivity and uncertainty analysis in integrated urban drainage modelling. Specifically, several sensitivity and uncertainty methods were applied to multiple water-quality models. Advantage and dis-vantage of methods and modelling approaches will be presented with the final aims to draw future perspectives and challenges. The variance decomposition approach is applied in combination with sensitivity analysis to pin down the sub-models characterized by higher uncertainty. A balance in terms of uncertainty among the different sub-models was proposed to contain data and numerical efforts.