Stochastic Flood Risk Assessment under Climate Change Scenarios for Toronto, Canada Using CAPRA

Abstract

Amongst all natural disasters, floods have the greatest economic and social impacts worldwide, and their frequency is expected to increase due to climate change. Therefore, improved flood risk assessment is important for implementing flood mitigation measures in urban areas. The increasing need for quantifying the impacts of flooding have resulted in the development of methods for flood risk assessment. The aim of this study was to quantify flood risk under climate change scenarios in the Rockcliffe area within the Humber River watershed in Toronto, Canada, by using the Comprehensive Approach to Probabilistic Risk Assessment (CAPRA) method. CAPRA is a platform for stochastic disaster risk assessment that allows for the characterization of uncertainty in the underlying numerical models. The risk was obtained by integrating the (i) flood hazard, which considered future rainfall based on the Representative Concentration Pathways (RCPs 2.6, 4.5, 6.0, and 8.5) for three time periods (short-term: 2020–2049, medium-term: 2040–2069, and long-term: 2070–2099); (ii) exposed assets within a flood-prone region; (iii) vulnerability functions, which quantified the damage to an asset at different hazard levels. The results revealed that rainfall intensities are likely to increase during the 21st century in the study area, leading to an increase in flood hazards, higher economic costs, and social impacts for the majority of the scenarios. The highest impacts were found for the climate scenario RCP 8.5 for the long-term period and the lowest for RCP 4.5 for the short-term period. The results from this modeling approach can be used for planning purposes in a floodplain management study. The modeling approach identifies critical areas that need to be protected to mitigate future flood risks. Higher resolution climate change and field data are needed to obtain detailed results required for a final design that will mitigate these risks.

Keywords

• flood risk
• climate change
• exposure
• vulnerability
• Toronto
• stochastic analysis