Efforts to comprehend and assess social vulnerability amidst environmental hazard events are crucial for fostering adaptive and resilient communities, thereby mitigating risks posed to humans by environmental hazards. However, the intricate interactions between humans and environmental hazards give rise to highly interactive and complex systems, commonly known as coupled human and natural systems (CHANS), necessitating a nuanced approach for accurately assessing environmental and social vulnerability. This dissertation bridges a research gap and provides novel insights into social vulnerability within CHANS, such as understanding the dynamics that the behaviors of one stakeholder group can influence another stakeholder group in the system by affecting the environment, using Lake Erie's harmful algal blooms (HABs) as a case study.This dissertation comprises three main chapters, each offering distinct perspectives. Chapter Two introduces a 5-theme hierarchical spatial framework for assessing social vulnerability to HABs at the county level. This framework not only generates a vulnerability index composed of socioeconomic, resource dependence, and spatial factors affecting vulnerability to HAB events but also provides a practical tool for policymakers and professionals to identify and prioritize communities for intervention. Chapter Three focuses on developing an integrated agent-based and multicriteria evaluation model aimed at simulating the dynamics in the system to pinpoint communities with high vulnerability. The agent-based section of the model simulates the CHANS from a bottom-up perspective to ensure the inclusion of interactions and dynamics, making the model more realistic and applicable. The model outputs are then used in the multicriteria evaluation section, which incorporates criteria representing the three pillars of social vulnerability factors suggested by the Intergovernmental Panel on Climate Change. In Chapter Four, sensitivity and scenario analyses are conducted to scrutinize the model's behavior, introduced in Chapter Three, shedding light on contributing factors to community vulnerability and providing insights for future research and policy development. This dissertation has identified high-vulnerability areas affected by Lake Erie HABs, offering significant insights into environmental and social vulnerability and thereby informing crucial policymaking recommendations. The studies yield three major findings: 1) The social vulnerability indices to harmful algal blooms, generated from both models in Chapters Two and Three, present clear spatial patterns; 2) The spatial distribution of the resulting indices, along with the social status of spatial units, provides valuable information to prioritize policy implementation, e.g., census tracts around the center of Lucas County, and inform targeted policies, e.g., focusing on alternative drinking water resource accessibility to enhance community resilience for most tracts in Wood County; and 3) Selected best management practices, such as cover crops, play a significant role in mitigating HAB severity in Lake Erie in the long run. The intellectual merit of this dissertation is twofold. Methodologically, through the adaptive agent-based and multicriteria analysis framework, we advocate for increased focus on addressing the inherent multifaceted complexities of the vulnerability within CHANS. This includes understanding how the behaviors of one component in a system indirectly affect another component by influencing the severity of environmental hazard events, thereby enriching the research field of environmental social vulnerability. From the perspective of applied science, these studies yield insights crucial for guiding targeted community adaptation policies to lessen the negative societal impacts of HABs in Lake Erie and enhance community resilience in the study area by informing agricultural regulations to mitigate HAB severity in the lake and other aquatic systems prone to HABs.
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