Spatiotemporal Dynamics and Climate-Driven Risk of Compound Flood Events in the Great Lakes Basin

Floods are among the most frequent and economically significant natural hazards affecting communities worldwide. Understanding their mechanisms, spatiotemporal patterns and projected changes is crucial to develop effective strategies for risk mitigation. This study analyzes three types of climate-driven flood events in the Great Lakes basin, driven by Rain-on-Snow (ROS), Saturation Excess flooding (SEF), and Successive Rainfall (SR), in the historical period (1985-2014) and the future period (2071-2100). Assessments are based on WRF-Hydro simulations forced by RDRS observations and eight downscaled and bias-adjusted General Circulation Models (GCMs) under SSP5-8.5 emission scenario. Based on the model outputs, the characteristics of extreme events including intensity, frequency, and seasonality, are evaluated and their contributions to the heavy runoff are investigated. Furthermore, flood risk is characterized by integrating the intensity and frequency of events with exposure and vulnerability for the Great Lakes basin. Overall, snow-related events are projected to decrease, while rain-related events are expected to increase. Single rainfall extreme events are projected to dominate future surface runoff generation, while single snowmelt events are more sensitive to climate change in the northern sub-basin. The contribution of ROS is less pronounced and is expected to decrease, whereas the SEF events show a higher contribution with an increasing impact in the future period. In addition, flood temporal and spatial correlation analyses show that future floods are likely to occur earlier, with increasing spring floods across the region. The spatial correlation between floods in the Lake Erie and Lake Michigan Basins is stronger and projected to increase, suggesting greater influence from large-scale atmospheric drivers. The seasonal shifts underscore the need for adaptive, season-specific flood management policies in the Great Lakes region. These results emphasize that the study of compound extreme events should move beyond individual event characteristics and place greater emphasis on hydroclimatic interactions and their associated impacts.

Name thesis:degree_name

M Eng Sci

Discipline thesis:degree_discipline

Civil and Environmental Engineering

Grantor dc:publisher

The University of Western Ontario

Year dc:date.issued

2025

Author dc:creator

• Wang, Yuxuan

Advisor dc:contributor.advisor

• Najafi, M. Reza

• Great Lakes Basin
• Flooding
• Compound Inland Flood
• Risk Assessment
• Seasonality
• Spatiotemporal Clustering

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/20.500.14721/38586

OAI identifier oai:identifier

oai:uwo.scholaris.ca:20.500.14721/38586