Advancing Understanding of Green Infrastructure Performance Through Field Measurements and Modeling
By: Siyan Wang
Publisher: [publisher not identified]
Published: 2020
Place of publication: [New York, N.Y.?]
Language: eng
Description: 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 With the expansion of urbanization and population growth, this outdated system is now easily overwhelmed during wet weather flow.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.
Notes: Department: Civil Engineering and Engineering Mechanics.

Thesis advisor: Patricia J. Culligan.

Thesis (Ph.D.)--Columbia University, 2020.