Pluvial flooding is a costly, injurious, and even deadly phenomenon with which cities will always contend. However, cities may reduce their risk of flood exposure by changing historically dominant patterns of development that have removed natural landscape features and reduce the damages that flooding causes by identifying and supporting vulnerable populations. Accomplishing either goal requires the development and application of appropriate frameworks for modeling or recording flood exposure. In this dissertation, I used modeling and surveying methods for assessing pluvial flood exposure in two cities, first in Valdivia, Chile, and then in Hermosillo, México. I open with a summary on pluvial flood risk in the present day and the threat it may pose under changing climates. In the second chapter, I explored how a form of urban ecological infrastructure (UEI), the wetland, is being wielded in Valdivia toward pluvial flood mitigation, and found that wetland daily, seasonal, and interannual changes in wetland surface and soil water storage alter pluvial flood risk in the city. In the third chapter, I used a mixed methodology, including projections of future land cover generated by cellular automata models with inputs from visioning workshops conducted by the Urban Resilience to Extremes Sustainability Research Network (UREx SRN), and found that wetland loss in future land configurations may lead to increased pluvial flood risk. In the fourth chapter, I combined these land cover models from the third chapter with downscaled climate data on precipitation, also generated by the UREx SRN, and found that wetland conservation can help to mitigate the pluvial flood risk posed by changing patterns of rainfall. In the fifth chapter, I applied the Arc-Malstrøm method for pluvial flood assessment in Hermosillo, México, and compared it with the more traditional rational method for flood assessment, and through accompanying surveys found that perception of flood risk is significantly affected by flood dimensions and impacts. This dissertation concludes with a synthesis of pluvial flood risk assessment, suggestions for improvements to modeling, as well as suggestions for future research on pluvial flood risk assessment in cities. This dissertation advances the understanding of the utility of inland wetland UEI in cities under present and future land cover and climate conditions. It also qualifies the utility of common and new pluvial flood risk assessments and offers research directions for future pluvial flood assessments.

Primary producers, from algae to trees, play a pivotal role in community structure and ecosystem function. Primary producers vary broadly in their functional traits (i.e., morphological, physiological, biochemical, and behavioral characteristics), which determine how they respond to stimuli and affect ecosystem properties. Functional traits provide a mechanistic link between environmental conditions, community structure, and ecosystem function. With climate change altering environmental conditions, understanding this mechanistic link is essential for predicting future community structure and ecosystem function. Competitive interactions and trait values in primary producers are often context dependent, whereby changes in environmental conditions and resources alter relationships between species and ecosystem processes. Well-established paradigms concerning how species in a community respond to each other and to environmental conditions may need to be re-evaluated in light of these environmental changes, particularly in highly variable systems. In this dissertation, I examine the role of primary producer functional traits on community structure and ecosystem function. Specifically, I test a conceptual framework that incorporates response traits, effect traits, and their interaction, in affecting primary producer communities and ecosystem function across different aquatic systems. First, I identified species-specific responses to intensifying hydrologic stressors important in controlling wetland plant community composition over time in an aridland stream. Second, I found that effect traits of submerged and emergent vegetation explained differences in ecosystem metabolism and carbon dynamics among permafrost mire thaw ponds. Next, I examined response-effect trait interactions by comparing two dominant wetland plant species over a water-stress gradient, finding that responses to changes in hydrology (i.e., altered tissue chemistry) in turn affect ecosystem processes (i.e., subsurface CO2 concentration). Finally, I demonstrate how indirect effects of diatom functional traits on water chemistry and ecosystem metabolism help explain disconnects between resource availability and productivity in the Colorado River. By expanding my understanding of how metabolic processes and carbon cycling in aquatic ecosystems vary across gradients in hydrology, vegetation, and organic matter, I contributed to my understanding of how communities influence ecosystem processes. A response-effect trait approach to understanding communities and ecosystems undergoing change may aid in predicting and mitigating the repercussions of future climate change.

Traditional infrastructure design approaches were born with industrialization. During this time the relatively stable environments allowed infrastructure systems to reliably provide service with networks designed to precise parameters and organizations fixated on maximizing efficiency. Now, infrastructure systems face the challenge of operating in the Anthropocene, an era of complexity. The environments in which infrastructure systems operate are changing more rapidly than the technologies and governance systems of infrastructure. Infrastructure systems will need to be resilient to navigate stability and instability and avoid obsolescence. This dissertation addresses how infrastructure systems could be designed for the Anthropocene, assessing technologies able to operate with uncertainty, rethinking the principles of technology design, and restructuring infrastructure governance. Resilience, in engineering, has often been defined as resistance to known disturbances with a focus on infrastructure assets. Resilience, more broadly reviewed, includes resistance, adaptation, and transformation across physical and governance domains. This dissertation constructs a foundation for resilient infrastructure through an assessment of resilience paradigms in engineering, complexity and deep uncertainty (Chapter 2), ecology (Chapter 3), and organizational change and leadership (Chapter 4). The second chapter reconciles frameworks of complexity and deep uncertainty to help infrastructure managers navigate the instability infrastructure systems face, with a focus on climate change. The third chapter identifies competencies of resilience in infrastructure theory and practice and compares those competencies with ‘Life’s Principles’ in ecology, presenting opportunities for growth and innovation in infrastructure resilience and highlighting the need for satisficed (to satisfy and suffice) solutions. The fourth chapter navigates pressures of exploitation and exploration that infrastructure institutions face during periods of stability and instability, proposing leadership capabilities to enhance institutional resilience. Finally, the dissertation is concluded with a chapter synthesizing the previous chapters, providing guidance for alternative design approaches for advancing resilient infrastructure. Combined, the work challenges the basic mental models used by engineers when approaching infrastructure design and recommends new ways of doing and thinking for the accelerating and increasingly uncertain conditions of the future.