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UBC Theses and Dissertations

Development of a spatiotemporal decision support framework for managing urban stormwater infrastructures : focusing on risk assessment, climate change and funding strategies Abebe, Yekenalem

Abstract

This dissertation proposes a comprehensive stormwater infrastructure management framework, considering climate change and urbanization. It starts by presenting a Bayesian Network (BN) model to investigate food vulnerability and storm sewer renewal complexity. The methodology is used to quantify uncertainty and capture the causal nexus between the various factors considered in the study. This helps us understand the social, economic, and physical vulnerabilities in relation to urban flooding and storm sewer failure. Then a Dynamic Bayesian Network (DBN) model is developed to assess the risk of storm sewer failure. By considering both asset deterioration and capacity failure, the method provides a way to investigate climate change and urbanization impacts in the asset replacement and renewal prioritization process. Based on the output from the food vulnerability and failure risk assessment, critical areas are identified for further analysis. For these areas, a risk-based cost-benefit analysis is presented to investigate possible adaptation alternatives. Lastly, a System Dynamics (SD) approach is proposed to investigate sustainable funding strategies for stormwater infrastructure management. The full implementation of the proposed models in a Geographic Information System (GIS) platform provides a spatiotemporal framework to guide stormwater infrastructure management decisions. The research outcome is vital in improving current practices in asset management and climate change adaptation. The framework enables strategic decision making and aids in implementing proactive asset management programs. In addition, it helps in allocating scarce public resources and prioritizing investment decisions effectively.

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Rights

Attribution-NonCommercial-NoDerivatives 4.0 International