Storm sewer pipe renewal planning considering deterioration, climate change, and urbanization: a dynamic Bayesian network and GIS framework

ABSTRACT

Risk-based renewal planning is essential for the reliable and continuous functioning of infrastructure systems. In this paper, we propose a risk assessment framework for storm sewer networks considering both hydraulic capacity and asset deterioration. The method is designed for a city-scale analysis and can provide an insightful result even when there is incomplete information. The objective is to assign a relative risk score to each pipe to inform replacement priorities. Moreover, we adopt a dynamic framework to proactively assess risk in different time horizons to investigate the impact of climate change and urbanization. A Dynamic Bayesian Network (DBN) model is used to capture dependencies among indicators, quantify uncertainty, and update belief when new information becomes available. Geographic information system (GIS) applications are used to collect and process model input data as well as visualize analysis results. Finally, the method is demonstrated on a storm sewer network in the city of Vernon, Canada.

KEYWORDS:

• Storm sewer
• renewal planning
• risk assessment
• urbanization
• climate change

Acknowledgments

This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC), Alexander Graham Bell Canada Graduate Scholarship - Doctoral. We also thank the City of Vernon’s Infrastructure Management Department for providing data and support for the project.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data Availability Statement

Some data, models, or code used during the study were provided by a third party. Direct requests for these materials may be made to the provider, as indicated in the Acknowledgements. Some or all data, models, or code generated or used during the study are available from the corresponding author by request.

Additional information

Notes on contributors

Yekenalem Abebe

Yekenalem Abebe is a Ph.D. candidate at the University of British Columbia and NSERC CGD-D award holder. His research focuses on developing frameworks, methods, and metrics to support decision-makers in municipal infrastructures management, urban disaster resilience, and risk assessment.

Solomon Tesfamariam

Solomon Tesfamariam PhD is a Professor in School of Engineering at University of British Columbia. Tesfamariam’s current research interest entails: developing multi hazard risk-based decision support tools for infrastructure management (earthquake, wind, etc.); hybrid building design; risk management of civil infrastructure system; and vulnerability assessment of spatially distributed network systems.