Risk-Informed Framework for Sewerage System Rehabilitation Management

The increasing storm frequency and severity due to climate change, and sewer system degradation due to aging and corrosion impose a greater risk of failure and overflooding to drainage systems. This paper proposes a new risk-informed framework in order to identify optimal strategies for drainage system rehabilitation under limited rehabilitation budgets. The proposed Hydraulics and Risk Combined Model (HRCM) dynamically couples the Storm Water Management Model (SWMM) and a risk model through a multiobjective optimization to maximize hydraulic performance while minimizing the risk of failure of the sewer system. The sensitivity analysis shows that with a small population size in a genetic algorithm the HRCM is capable of solving complex test cases. In addition, with increasing population size, the Pareto front converges with several rehabilitation strategies having the same objective function values. The model is examined in the context of several simple and complex scenarios, and the results demonstrate the model's validity and robustness. The results also show that the proposed model is capable of identifying satisfactory rehabilitation strategies that can inform the optimal drainage system rehabilitation.

Automated summary

The study introduces a risk-informed approach for drainage system rehabilitation, optimizing hydraulic performance while minimizing failure risk. The proposed model is validated across various scenarios, demonstrating its effectiveness and robustness.