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Published on: June 1, 2022
Probabilistic modelling of combined sewer overflow using the First Order Reliability Method
S Thorndahl1, K Schaarup-Jensen, J B Jensen
1Department of Civil Engineering, Aalborg University, Sohngaardsholmsvej 57, 9000 Aalborg, Denmark. st@civil.aau.dk
This study introduces a new probabilistic method for analyzing urban drainage systems and predicting combined sewer overflows. It quantizes uncertainties in rainfall and system parameters to assess overflow risks.
Area of Science:
- Environmental Engineering
- Hydrology
- Water Resource Management
Background:
- Urban drainage systems face challenges in predicting combined sewer overflows (CSOs).
- Accurate hydrodynamical analysis requires accounting for input and parameter uncertainties.
- Existing methods may not fully capture the probabilistic nature of CSO events.
Purpose of the Study:
- To present a novel probabilistic hydrodynamical analysis method for urban drainage systems.
- To specifically improve the prediction of combined sewer overflow events.
- To integrate input and parameter uncertainties into drainage system analysis.
Main Methods:
- Developed a probabilistic shell to incorporate uncertainties.
- Applied the First Order Reliability Method (FORM) with the MOUSE urban drainage model.
- Utilized statistical analysis of several years of rainfall data for parameterization.
Main Results:
- Successfully implemented a probabilistic approach for hydrodynamical analysis.
- Enabled the quantification of uncertainties in rainfall input and model parameters.
- Derived failure probabilities and return periods for combined sewer overflows.
Conclusions:
- The proposed probabilistic method offers an effective alternative for analyzing urban drainage systems.
- This approach enhances the prediction accuracy of combined sewer overflows.
- It provides valuable insights into the risks associated with CSO events to receiving waters.
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