This study assessed the effect of an application of mycorrhizal fungi to stormwater filter media on urban bioswale soil and stormwater in an infiltration-based bioswale aged 20 years with established vegetation. The study tested the use of commercially available general purpose biotic soil blend PermaMatrix® BSP Foundation as a treatment to enhance Earthlite™ stormwater filter media amelioration of zinc, copper, and phosphorus in an ecologically engineered structure designed to collect and infiltrate urban stormwater runoff before it entered the nearby Willamette River. These results show that the application of PermaMatrix® BSP Foundation biotic soil amendment to Earthlite™ stormwater filter media contributed to the reduction of extractable zinc in bioswale soil (-24% and -26%), as compared to the control, which received a treatment of Earthlite™ stormwater filter media only, and experienced an increase in extractable zinc levels (23% and 39%). The results presented also show evidence that after establishment mycorrhizal treatment demonstrated lowered levels of phosphorus in bioswale soil (-41%) and stormwater (-100%), in contrast to the control, which had increased phosphorus levels. The treatment contributed to reductions between 67% and 100% in every metric detected in stormwater after an establishment period of 17 weeks, while the bioswale with no mycorrhizal treatment had increases between 50% and 117%. Treatment also appeared to enhance the reduction of ammonium and nitrates, while contributing to a greater increase in soil pH.

The aim of this dissertation was to develop a multi-criteria decision support system (MCDSS) to allow a specified manager to select with confidence one or many of these BMPs for a particular site. The principal design approach was a review of South African and international literature pertaining to stormwater management techniques, in particular BMPs. This information was formulated into a primary matrix using a rank-and-weighting method. The scores were then checked against the literature to ensure that they were reasonable, culminating in the initial MCDSS. The MCDSS was then provided with seven scenarios, described in the literature, and the output reviewed. Although, the MCDSS would select appropriately when given few criteria for selection when these were increased, inappropriate outcomes resulted. Consequently, weighting factors were assigned to each criterion. The MCDSS was further tested using all the selection criteria and the output deemed satisfactory. The MCDSS was then tested in a case study of the Town Bush stream catchment at eleven sites along the river network and the results were adequate. Taking into consideration the economic aspects of BMP implementation a need also arose for the sites to be allocated to certain authorities depending upon ownership or responsibility. The sites were prioritised depending on potential threat to property and lastly by the hydrological nature of the stream at each site. A stormwater plan for the study area was also proposed. Although the MCDSS was functioning adequately it was not without its limitations. Limitations included the use of drainage areas as a surrogate measure for peak discharge thus, not allowing the user to design a series of BMPs or treatment chain. A second limitation was that initially the BMPs were designed as offline systems where stormwater is managed before entering the channel but in this study they were used as inline systems. Hence the ultimate selection was biased towards those BMPs able to deal with large drainage areas. Recommendations for further improvement include the development of a surrogate measure for drainage area thus allowing the user to design a treatment chain of BMPs; testing the MCDSS in more diverse circumstances; developing a more comprehensive set of selection criteria; and developing a clearer priority-setting model as the one used was rather simplistic. In conclusion the MCDSS provides the user with a useful tool where the selection and implementation of BMPs no longer has to take place in an ad hoc manner. / Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 2001

Urbanization has posed great challenges for environmental sustainability, human health, and wellbeing. One of these challenges is stormwater management stemming from widespread imperviousness in urban areas. For many cities, including New York City, stormwater management issues are being exacerbated by the impacts of climate change, which is increasing the frequency and intensity of wet weather flows in multiple regions of the world. In New York City, stormwater runoff is collected with wastewater sewage in a combined sewer system (CSS) that dates back to over a century ago. At the time the system was put in place, it was designed to transport a combination of storm and wastewater to local treatment plants with a capacity of about twice the dry-weather flow. With the expansion of urbanization and population growth, this outdated system is now easily overwhelmed during wet weather flow. In some areas of the City, rainfall of less than a few millimeters can cause untreated combined storm and waste water in excess of the system’s capacity (Schlanger, 2014), to be discharged directly into a nearby surface water. The combination of storm and wastewater is referred to as combined sewerage, and overflow events are referred to as combined sewer overflows (CSOs). CSOs are a leading source of local water body pollution in NYC, as well as countless other older cities in the US and abroad that operate with combined sewer systems. To solve the CSO problem, many cities, including NYC, have adopted green infrastructure (GI) plans that aim to capture stormwater locally before it can make its way into a CSS. In New York City, right-of-way bioswales (ROWBs) are composed of about 60% of the GI that has been implemented to date (The New York City Department of Environmental Protection, 2020) for stormwater management and CSO reduction. However, despite the popularity of ROWBs as a GI intervention, few research studies have focused on quantifying their hydrological performance. This can be attributed, in part, to the greater complexity of ROWB behavior in comparison to other GI interventions, such as green roofs, which have attracted wider research interest. In addition, because ROWBs are located in the public right-of-way, monitoring and measurement of the behavior of these systems also poses additional challenges. The first study in this dissertation presents three new field methods for quantifying the stormwater retention capacity of individual ROWBs. By applying the field methods at a ROWB site located in the Bronx, NYC, the influence of rainfall characteristics and the monitored soil moisture content of the ROWB on the ROWB’s hydrological performance was explored. A definition of a so-called ‘rain peaky event’ (RPE) was introduced to divide an individual storm into several sub-events. A RPE event-based empirical model for predicting the stormwater retention behavior of the ROWB was then developed based on the monitored soil moisture content of the ROWB and the rain depth recorded every 15 minutes during a storm event. This study found that the predicted stormwater retention volume per rain depth per unit drainage area of the studied ROWB, is not significantly different from that of several NYC based extensive green roofs. However, compared to the drainage area of the green roofs, which is the same as the roof’s surface area, the drainage area of the studied ROWB was about 84 times its surface area. Thus, per unit area, the ROWB was found to have significantly higher (almost two orders of magnitude) total stormwater capacity than the extensive green roofs. The second study in this dissertation assessed the applicability of the physics-based one-dimensional finite element model HYDRUS-1D, for simulating the infiltration process of a ROWB during storm events using long-term monitored soil moisture content as an input. The simulation results from the HYDRUS-1D was validated by field measurement results taken at the ROWB site located in the Bronx, NYC, and compared with the RPE event-based empirical model presented in the first study. The HYDRUS-1D model was found capable of predicting the ROWB’s cumulative stormwater retention at intervals of one minute, as well as the total retention volume of stormwater inflows into the ROWB per rain peaky event, except for events with an average stormwater inflow intensity high than 20 cm/hr. The study revealed that HYDRUS-1D has a tendency to under-predict the retention capacity of the studied ROWB for a storm with an inflow intensity high than 20 cm/hr, thus providing a lower bound on ROWB stormwater retention. The current published version of the HYDRUS-1D was also found to be erroneous when simulating the ROWB stormwater infiltration process in cases where the ROWB’s soil moisture content was close to saturation. The third study investigated the effectiveness of increased perviousness on CSO reduction and water quality improvement in NYC, toward an aim of understanding how GI implementation can improve city-wide stormwater management issues. By using the enterococci (ENT) concentration as an indicator of water quality and the runoff coefficient to represent land perviousness over an area, a random forest classification model was developed for predicting whether a water body is swimmable or not at 50 shore sites along the main waterways of NYC. The model revealed the significant contribution of land perviousness, and hence GI interventions and green space, to CSO pollution reduction for CSO-shed areas located adjacent to slower-moving waterways. For CSO-shed areas located adjacent to faster moving waterways, the influence of land perviousness was found to be negligible. The random forest classification model developed in this third study can be used as a tool for city planners and agencies as part of plans for GI implementation that focus on the optimization of local water quality, among other objectives. Overall, the research presented in this dissertation aimed to provide a deeper insight into the factors governing the hydrological performance of the most prevalent GI in NYC – namely right-of-way bioswales. In addition, the research aimed to provide insight into linkages between land perviousness and CSO pollution levels in NYC local waterways, which can be used to inform the implementation and overall performance of the entire NYC GI system.

Cities are home to more than half of the world’s population, and this figure is set to continue to rise amidst ongoing global urbanization trends. Against this backdrop, urban development is increasingly confronted with multifaceted challenges. These range from public health emergencies, exemplified by the COVID-19 global pandemic, to the environmental hazards driven by climate change, including extreme heat waves and more frequent severe storms. Confronted with these substantial risks, the urgency of devising and implementing strategies for sustainable and resilient urban development has become paramount. Given this context, the work presented in this thesis aims to advance understanding of some critical urban sustainability challenges, and to develop models, tools, and sensing systems that can support progress towards a more sustainable and resilient urban future. The first part of the thesis focuses on the role and usage of urban parks during a global public health emergency. Urban parks became critical for maintaining the well-being of urban residents during the COVID-19 global pandemic. To examine the impact of COVID-19 on urban park usage, New York City (NYC) was selected as a case study, and SafeGraph mobility data, which was collected from a large sample of mobile phone users, was used to assess the change in park visits and travel distance to a park based on park type, the income level of the visitor’s census block group (visitor CBG) and that of the park census block group (park CBG). All analyses were adjusted for the impact of temperature on park visitation, and the research work was focused primarily on park visits made by NYC residents. Overall, for the eight most popular park types in NYC, namely – Community Park, Flagship Park, Jointly Operated Playground, Nature Area, Neighborhood Park, Playground, Recreation Field/Courts and Triangle/Plaza – visits dropped by 49.2% from 2019 to 2020. The peak reduction in visits occurred in April 2020. Visits to all park types, excluding Nature Areas, decreased from March to December 2020 as compared to 2019. Parks located in higher-income CBGs tended to have lower reductions in visits, with this pattern being primarily driven by visits to large parks, including Flagship Parks, Community Parks and Nature Areas. All types of parks saw significant decreases in distance traveled to visit the park, with the exception of the Jointly Operated Playground, Playground, and Nature Area park types. Visitors originating from lower-income CBGs traveled shorter distances to parks and had less reduction in travel distances compared to those from higher-income CBGs. Furthermore, both before and during the pandemic, people tended to travel a greater distance to parks located in high-income CBGs compared to those in low-income CBGs. Finally, multiple types of parks proved crucial destinations for NYC residents during the pandemic. These included Nature Areas to which the visits remained stable, along with Recreation Field/Courts which had relatively small decreases in visits especially for lower-income communities. Results from this particular research study can support future park planning by shedding light on the different users of certain park types before and during a global crisis, where access to green spaces can help alleviate the human well-being consequences associated with mitigating the crisis, including the type of “lockdown” or limited mobility policies implemented in 2020 during the COVID-19 global pandemic. The second part of the thesis investigates the role of urban greening and other land surface features in influencing the urban heat island effect in NYC. The urban heat island (UHI) effect describes the phenomenon whereby cities are generally warmer than surrounding rural areas. UHI effects can exacerbate extreme heat events, leading to an increase in heat-related illness and mortality. Here, the runoff coefficient was used as a numerical surrogate for urban greening, with lower runoff coefficients being associated with higher fractions of urban greening. Using a high-resolution landcover GIS dataset developed for New York City (NYC), which classified the city into more than 13 million land patches, the runoff coefficient of land use across the entire city was mapped down to a resolution of 30m×30m, along with five other variables including surface albedo, distance to water bodies, land surface elevation, building density and building height. Daytime land surface temperature (LST) in summer was used as a surrogate for the UHI effect in NYC, and the work investigated the relationship between the runoff coefficient and LST. The work also examined the relationship between LST and the variables of surface albedo, distance to a water body, land surface elevation, building density and building height. Results indicate that runoff coefficient can explain a large portion of variability related to urban LST, with lower runoff coefficients (more greenery) being associated with lower LST. Use of the five other variables improves the predictability of LST, although the influence each variable has on LST varies with urban setting and context. The research work presented in this part of the thesis also shows the disproportionately higher exposure to urban heat in lower-income communities in NYC. The findings can be used to develop strategies to mitigate UHI effects in NYC and other cities around the world. In the third part of the thesis, a wireless environmental sensing system is developed for monitoring urban green spaces, with demonstrated application for stormwater management. The monitoring of urban green spaces, including monitoring of soil conditions and soil health, is crucial for sustainable urban development and ecological resilience. Leveraging advances in wireless environmental sensing, a LoRaWAN-based system capable of measuring air temperature/humidity, soil temperature and moisture, and soil moisture dynamics is designed and deployed across seven diverse urban green spaces for a full year at Columbia University’s Morningside Campus in New York City. The data collected by this sensing network reveals notable variations in soil moisture across the seven monitored sites, which are influenced by a combination of vegetation type, soil conditions, and physical settings. Monitored lawns consistently showed higher soil moisture levels due to their slower draining soil type, underlying concrete structures, and lower canopy rainfall interception and transpiration loss, whereas one monitored tree pit site with a more rapidly draining soil type showed significantly lower soil moisture throughout the study period, despite having comparable physical settings with another monitored site. Seasonal trends indicated lower summer moisture in some monitored areas due to increased evaporation and transpiration under high temperatures, while others areas maintained higher soil moisture as a result of frequent irrigations. Models were developed to quantify soil moisture response to rainfall events. It was found that the increase in soil moisture at each monitored site was highly dependent on the rainfall depth and the initial soil moisture. Overall, the results show that a range of diverse green spaces can help retain and drain storms up to certain sizes of 30-50mm. However, proactively designed soil drainage systems are needed to handle extreme storm events above 50mm. The study highlights the effectiveness of LoRaWAN technology in urban environmental monitoring and provides valuable insights into how different urban green spaces can contribute to stormwater management. The findings presented in this portion of the thesis demonstrate the instrumental role that monitoring, data analysis and modeling can play in helping city planners and environmental managers optimize urban green spaces for ecological benefits and enhance urban resilience, including in the face of stressors such as climate change. Overall, with its data-driven, evidence-based insights, this work contributes to the understanding of the multifaceted urban sustainability challenges in a changing environment, including public health emergencies such as the COVID-19 global pandemic, and climate change induced environmental hazards such as extreme heat events and more frequent severe storms. Alongside deepening understanding, the developed quantitative models and sensing technologies presented in this thesis offer practical solutions to support urban development towards a more sustainable and resilient future.

Lau Wai Kee Albert. / "Architecture Department, Chinese University of Hong Kong, Master of Architecture Programme 2000-01, design report." / On double leaves. / Includes bibliographical references. / Chapter Chapter 1 --- Prologue --- p.1 / Definition of the unseen space --- p.2 / Unseen space in the city --- p.3 / Chapter Chapter 2 --- Justification of selected unseen space --- p.4 / Definition of nullah --- p.6 / Surface transformation of the nullah --- p.8 / People perception of the nullah --- p.10 / People perception of wastewater --- p.12 / Chapter Chapter 3 --- Justification of site selection --- p.15 / Site analysis --- p.18 / Transportation character --- p.22 / Chapter Chapter 4 --- Physical identity of nullah --- p.25 / Intrinsic meaning of nullah --- p.26 / Chapter Chapter 5 --- Philosophy of nullah --- p.30 / Concept --- p.34 / Project mission --- p.38 / Conceptual strategy --- p.39 / Chapter Chapter 7 --- Philosophical meaning of water --- p.46 / People perception to water --- p.50 / Basic concept in water space design --- p.52 / Chapter Chapter 8 --- Precedent study --- p.56 / Urban rivers --- p.57 / Local rivers --- p.66 / Chapter Chapter 9 --- Design ideas --- p.68 / Appendix / Water quality of Kai Tak nullah --- p.75 / Annual rainfall --- p.76 / "Interview with Dr. Chung, Dept. of Biology, CUHK" --- p.78 / Biblography --- p.80