Analysis of Lagged Compound Droughts and Floods in the Great Lakes Basin: Historical Patterns and Future Projections under Climate Change
Abstract
Floods and droughts, as two extremes of the hydrologic cycle, can exert adverse environmental, economic, and societal impacts. Understanding their spatial and temporal patterns and changes under climate change and their interplay and compounding effects is critical to developing sustainable and resilient strategies. This study investigates the complex interactions between these opposing extremes, lagged compound droughts and floods (LCDF). We employed a streamflow-based analysis of LCDF over Canada (1963-2012) and proposed a magnitude index based on daily streamflow. The LCDF characteristics were calculated and the potential effect of teleconnections on these LCDFs was assessed based on the Bayesian quantile regression. We then bias-corrected/downscaled precipitation, maximum and minimum temperature, and near-surface wind in eastward and northward from eight CMIP6 GCMs under SSP2-4.5 and SSP5-8.5 scenarios using the Multivariate Bias-Correction algorithm (MBCn) over the Great Lakes and St. Lawrence River basin (GLB) and calculated the characteristics of LCDF events under a warming-related scenario naming it successive warm/dry-warm/wet (SWDWW) and successive warm/wet-warm/dry (SWWWD) events. Next, the WRF-Hydro model was set up, calibrated, validated, and regionalized over the GLB and then derived using the bias-corrected/downscaled GCMs, and the hydrological responses of WRF-Hydro were evaluated in the historical period (1985-2014) and projected in the future (2071-2100). Additionally, the characteristics of LCDF were calculated based on WRF-Hydro’s outputs (runoff and soil moisture), precipitation, and a merged three-variate index. The study showed that in Canada, the east and west coasts and the GLB are hotspots for these LCDFs and low-frequency variability modes, especially at higher quantiles, affect the magnitude of LCDF. Additionally, the frequency of SWWWD and SWDWW are increasing by climate change. Future soil moisture, Snow Water Equivalent, and runoff are projected to have almost no change, reduction, and increase in the GLB, respectively. The WRF-Hydro-based LCDFs suggest an increase in the intensity of LCDF based on the four indices in the GLB, along with a decrease in the transition time, indicating a more significant event in the future. The findings of this thesis support the future development of robust disaster risk measures and effective water resource planning and mitigation strategies.