Browsing by Author "Fenn, Abby M., author"
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Item Embargo Assessing the triple bottom line co-benefits and life cycle cost tradeoffs of cloudburst infrastructure in New York City(Colorado State University. Libraries, 2024) Fenn, Abby M., author; Arabi, Mazdak, advisor; Grigg, Neil, committee member; Sharvelle, Sybil, committee member; Conrad, Steve, committee memberUrbanization and climate change have increased the risk of urban flooding. Specifically, more frequent cloudburst events are on the rise in cities across the globe. Cloudbursts are characterized by high intensity rainfall over a short duration, causing unpredictable, localized flooding. Effective stormwater management is essential to manage extreme precipitation and runoff induced by cloudbursts. Stormwater control measures have evolved over time shifting from gray infrastructure to nature-based and green solutions. Recently, cloudburst specific infrastructure has emerged as a stormwater intervention strategy designed to handle larger volumes of water by capturing, storing, or conveying excess water in highly impervious areas. Cloudburst infrastructure systems are inextricably linked with land use in cities and thus, their implementation should incorporate life cycle costs, and social and ecological co-benefits. This study assesses the Triple Bottom Line co-benefits and environmental effects of cloudburst systems for flood control in New York City. Specifically, we explore the tradeoffs between the costs and co-benefits of alternative surface vegetation including grass, diverse vegetation, and trees. The study identifies the Pareto optimal set of solutions and quantifies effects of incorporating vegetation into the urban landscape via cloudburst systems. The results indicate that surface vegetation plays a key role in altering the co-benefits and life cycle costs of cloudburst infrastructure. Trees were the most frequent non-dominated solution and were linearly related to Triple Bottom Line score and exponentially related to Life Cycle Cost. The framework and results of this study provide valuable insight to support informed decision-making.