It is my great pleasure to invite you to the public portion of my Ph.D. defense on Wednesday, May 31st at 2:00pm PT, titled "Characterizing Hydrologic and Economic Risk due to Flooding Driven by Atmospheric Rivers."

Abstract:
Atmospheric rivers (ARs), sometimes called “rivers in the sky,” are long, narrow bands in the atmosphere that carry high levels of moisture from the tropics to the mid-latitudes. They deliver up to half of California's annual water supply, but they also can cause extreme precipitation and floods. The overall goal of this dissertation is to identify which ARs are most likely to cause damaging flooding.
First, I connect AR hazard, which is based only on the intensity of the atmospheric event, to AR risk, which includes the exposure and vulnerability of infrastructure and communities. Using tools from earthquake engineering, probabilistic risk analysis, and interpretable machine learning, I characterize AR-driven flood risk from both a process-based (top-down) and a data-driven (bottom-up) perspective. These two complementary approaches are used to identify influential drivers of extreme consequences.

I then quantify the contribution of temporal compounding to the hydrologic and economic impacts of ARs. Temporal compounding is the risk amplification that occurs when two or more AR storms occur in close succession. The series of ARs that affected California in the early months of 2023 are an example of the significant consequences that temporal compounding can cause when the hydrologic
environment does not have time to recover between events. I create a new metric, AR sequences, to identify when temporal compounding is contributing to risk. I show that sequences are associated with higher levels of hydrologic impacts, such as extreme runoff and soil moisture, than ARs are on their own. They also increase both the probability and the magnitude of economic impacts from damaging
flooding. Finally, sequences are expected to increase in frequency, intensity, and duration in a future climate, with the largest frequency increases occurring at the longest durations. Altogether, this dissertation both identifies a growing threat to California's water resources and introduces a suite of AR flood risk assessment tools to manage that threat.