Resilience of Stormwater Treatment Systems under Changing Climates
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Resilience of Stormwater Treatment Systems under Changing Climates


Access to water is critical for societal development. Urban areas, where more than half of the world’s population currently lives, are projected to increase to 70% by 2050. This growth indicates that the water scarcity issue in urban areas will get worse unless alternative water resources are utilized. Stormwater may serve as an alternative water source, but stormwater often contains many contaminants including pathogens, heavy metals, motor oils, nutrients, pesticides, herbicides, polyaromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), per- and polyfluorinated substances (PFAS), microplastics, and other emerging organic contaminants. To manage and treat stormwater in urban areas, stormwater control measures (SCM) or green infrastructures have been used. However, traditional stormwater control measures are highly unreliable. The performance variability of SCM is due to varying stormwater, weather conditions, and design factors. To reduce the performance variability and make SCM more reliable, the development of climate resilient is required, which will result in increased water security in urban areas. In stormwater treatment systems, the resilience concept involves four central elements: stressors, indicators of resilience, metrics and the intervention. In this dissertation, I researched about each of the four central elements of resilience for stormwater treatment systems in order to develop climate resilient SCM. I researched about the stressor elements in Chapter 2 and 3. In Chapter 2, I showed that both design and local climate can explain nitrate removal variability by critically analyzing data reported on the international BMP database for nitrate removal by four common types of SCM: bioretention cells, grass swales, media filters, and retention ponds. In Chapter 3, I analyzed 7,421 data collected from 19 retention ponds across North America showed that FIB removal in retention ponds is sensitive to weather conditions or seasons, but temperature and precipitation data failed to describe the variable FIB removal. In Chapter 4 and 5, I quantified the performance variability of SCM through metrics. In Chapter 4, I examined how post-wildfire runoff containing burned residues affect the transport and survival of indicator bacteria, resulting in changes in the microbial quality of surface water and subsurface soil. In Chapter 5, I demonstrated how the deposition of wildfire residues could increase methane emissions in wetland sediments by up to 56%, but the emission depended on the amount of wildfire residues deposited. Finally, in Chapter 6 I researched about the last resilience concept: intervention or mitigation strategies. I showed in Chapter 6 that biochar’s capacity to remove pathogens from stormwater can vary by orders of magnitude, but the usage of machine learning techniques can predict biochar’s performance based in their commonly reported properties: surface area, carbon content, ash content, and volatile organic carbon content. This dissertation advances the science applied to climate resilient stormwater treatment systems.

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