Urban Flooding, Infrastructure, and its Link to Social Vulnerability and Mobility: A Place-Based Study in Washington, D.C.
This study explores infrastructure, flooding, and its connection to social vulnerability and mobility in Washington, D.C. We use secondary flood and infrastructure data to model flood risks and exposures and subsequent infrastructure failures to understand the extent to which flooding reduces the quality and serviceability of infrastructure, including public transit, schools, energy, and community facilities that provide essential services. We also use primary interview data to further contextualize flood impacts and whether repeated flooding creates a negative cycle that prohibits social mobility, particularly among socially vulnerable populations.
Using the Internet of Things (IoT) and Sensor Technology to Improve Stormwater Management
The goal of this project is to use an Internet of Things (IoT) framework along with smart sensors to monitor and improve stormwater management on the University of Maryland Campus. This project would provide real-time and continuous data that can inform both short-term responses and longer-term restoration retrofits to treat stormwater surface runoff. More and better data are needed to protect our natural waterbodies, address stormwater runoff issues, establish best management practices, and inform sustainable development. Internet of things (IoT), sensor technology, big data analytics, and real-time event monitoring are among the myriad ways that communities are getting “smarter” to improve stormwater management.
Citizen Science for Infrastructure Monitoring at the Neighborhood Level
In the pursuit of safe and reliable infrastructure systems, monitoring data are collected to assess the condition, usage, and in-service performance of these systems. This research pursues to design and test protocols and techniques for collecting infrastructure monitoring data at the neighborhood level by volunteer citizen scientists. This project will contribute to understanding the factors that influence the reliability and validity of citizen-generated infrastructure monitoring data, with a focus on stormwater infrastructure. Successful implementation of protocols and techniques for collecting infrastructure monitoring data by residents would accelerate the production of high-quality data at the neighborhood level.
A Partnership for Advancing Participatory Methods and Technologies in Stormwater System Management in Disadvantaged Communities
The aims of this work is to design and field test new methods and digital technologies to enable citizens to provide data for and participate in the decision-making processes pertaining to managing stormwater systems, including both housing and neighborhood infrastructure. The ultimate purpose of these methods and technologies is to improve the resilience of disadvantaged communities to flood and stormwater-related hazards in ways that also empower them to advocate for equitable and prudent use of public resources. These participatory methods and tools could help build trust and facilitate engagement between the residents and their local government, a challenge commonly found in minority and disadvantaged communities.
Landscape Performance as an Evaluation Tool for Green Infrastructure Masterplans Produced Through Service Learning
Community visioning and neighborhood-scaled design is the first step in the development process, but can be a hurdle for communities who lack the capacity to conduct and evaluate such work in an inclusive manner. Service-learning projects implemented through university-community partnerships can assist communities in increasing resilience through the development of master plans that include green infrastructure adaptations. However, too often, the products generated through service-learning projects conclude at the conceptual level, with no evaluation of the feasibility of their implementation. This study examines how landscape performance models can be used as an analytic tool to evaluate proposed master plan design parameters.
A Multi-Method Approach to Assess Sanitary Risks and Pathways to Waterborne Microbial Exposures Associated with Vulnerable Infrastructure in Baltimore, Maryland
This study uses a multi-method approach to assess sanitary sewer overflow (SSO), among other sanitary risks and exposure to bacteria from contaminated surfaces within the built environment across Baltimore neighborhoods. The study will use SSO incident data, waste and trash data, land use data, and American Community Survey Data to map and statistically model incident risks, along with environmental sampling data, stakeholder interview data, and household surveys to understand exposure and impacts.
A Qualitative Study of U.S. Black Settlements, Community and Infrastructure Development, Chronic Flooding, and Environmental Justice
During U.S. reconstruction, settlements and townships were established by free and recently freed African Americans throughout the United States. Many of these lands were physically characterized by dirt roads, swampy areas, and “bottomlands” or floodplains. Using a combined social vulnerability to disasters, environmental justice, and critical race theory approach, this work seeks to explore the historical and political context through which African American communities in the U.S. were formed and analyze the resulting challenges that these places have faced in dealing with flooding over the years.