Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Doctor of Philosophy

Program

Civil and Environmental Engineering

Supervisor

Najafi, Mohammad Reza

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.

Summary for Lay Audience

Lagged compound drought and flood (LCDF) events are defined as a succession or transition of droughts and floods in a region within a short time. An example of these lagged compounds occurred in California in 2017 where a 2012-2017 drought event swung to a heavy precipitation event and as a result, the Oroville dam’s spillway, the second largest reservoir in California, collapsed and about 200000 people were evacuated. As this example shows, the impact of this swing can be more severe than the impact of a drought or a flood event. In this study, we calculate the change in the characteristics of these swings including frequency, transitioning time, and magnitude. Climate change is affecting these swings and to calculate its effect on these lagged compounds we will need to increase the resolution and bias-correct the results of eight climate models. In this study, we employ both observations and simulations to characterize the change in the lagged compounds’ characteristics in both historical and future periods compared to the historical. To assess these compounds using the hydrological variables besides the precipitation, a Weather Research and Forecasting Hydrological modelling system (WRF-Hydro) is set up, calibrated and validated over the Great Lakes and St. Lawrence River basin (GLB). The outputs of WRF-Hydro including soil moisture, and runoff besides precipitation are first evaluated and then used for calculating the LCDF characteristics. The results show that in Canada the areas in the vicinity of water are most prone to these LCDF. WRF-hydro’s output, soil moisture, shows almost no change in most of the basin in the future. SWE shows a reduction in the future in the basin and runoff is projected to increase in most of the basin. The WRF-Hydro-based LCDFs suggest an increase in the intensity of these LCDFs based on the four indices in the majority of the GLB along with a decrease in the transitioning 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.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Download

Available for download on Tuesday, December 31, 2024

Share

COinS