Identification of behavioural model input data sets for WWTP uncertainty analysis

Uncertainty analysis is important for wastewater treatment plant (WWTP) model applications. An important aspect of uncertainty analysis is the identification and proper quantification of sources of uncertainty. In this contribution, a methodology to identify an ensemble of behavioural model representations (combinations of input data, model structure and parameter values) is presented and evaluated. The outcome is a multivariate conditional distribution of input data that is used for generating samples of likely inputs (such as Monte Carlo input samples) to perform WWTP model uncertainty analysis. This article presents an approach to verify uncertainty distributions of input data (otherwise often assumed) by using historical observations and actual plant data.

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Last updated: 2021-05-17

IVL Swedish Environmental Research Institute

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IVL Swedish Environmental Research Institute has a wide environmental profile. We combine applied research and development with close collaboration between industry and the public sphere. Our consultancy is evidence-based, and our research is characterized by interdisciplinary science and system thinking.


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