Uncertainty Propagation in Integrated Urban Water Quality Modelling

Giorgio Mannina, Giorgio Mannina

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Sensitivity and uncertainty assessment of integrated urban drainagewater quality models are crucial steps in the evaluation of the reliability ofmodel results. Indeed, the assessment of the reliability of the results of complexwater quality models is crucial in understanding their significance. In the case ofintegrated urban drainage water quality models, due to the fact that integratedapproaches are basically a cascade of sub-models (simulating the sewer system,wastewater treatment plant and receiving water body), uncertainty produced inone sub-model propagates to the following ones in a manner dependent on themodel structure, the estimation of parameters and the availability and uncertainty of measurements in the different parts of the system. Uncertainty basicallypropagates throughout a chain of models in which the simulation output fromupstream models is transferred to the downstream ones as input. The paperpresents the uncertainty assessment of an integrated urban drainage modeldeveloped in previous studies by means of the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. A straightforward approach based onthe analysis of the coefficient of variation (Rxy). Rxy is defined as the ratiobetween the standard deviation (a) and the average (l) value of the model outputof reference taken into account. The analysis has been applied to an experimental catchment in Bologna (Italy) which consists of a part of the Bolognasewer network and a reach of the Savena river. The results showed that themethod can be a useful tool for uncertainty analysis and for guiding the operatorin the choice of the modelling approach.
Lingua originaleEnglish
Titolo della pubblicazione ospiteSpringer Nature Switzerland AG 2019 G. Mannina (Ed.): UDM 2018, GREEN
Numero di pagine8
Stato di pubblicazionePublished - 2019

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology
  • Management, Monitoring, Policy and Law
  • Industrial and Manufacturing Engineering

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