Tag Archives: inequity

PI Philip Orton, Co-I Kaijian Liu, Stevens Institute of Technology

Co-I Malgosia Madajewicz, Columbia University

Co-I Greg Smithsimon, Brooklyn College

PhD student: Shima Kasaei, Stevens Institute 

Project manager/ collaborator: John Warner, US Geological Survey

Funding agency/program:  US Geological Survey

Project Period:  September 2022 to August 2025

Recent flood disasters arising from coastal storms (e.g., Harvey and Ida) have demonstrated the critical importance of incorporating rainfall into assessments of coastal flood risk. However, studies of present and future coastal flood risk and adaptation nearly always neglect rainfall and thus have biases that may lead to suboptimal government planning decisions. Climate change is leading to both increasing rainfall intensity and rising coastal floods, worsening these biases and the dangers they represent.

Vulnerability to flooding, which includes exposure, defined as living in an area that may flood, susceptibility to suffer damage if flooding occurs, and capacity to recover, differs across communities with different socio-economic characteristics. Prior research characterizes how vulnerability to flooding driven by coastal storms differs in the population in the urban neighborhoods of New York City (NYC). Vulnerability to nuisance, tidal, and pluvial flooding is much less well documented and understood. Impacts of and therefore vulnerability to nuisance and pluvial flooding can differ from coastal storm flooding. For example, anecdotal evidence suggests that the danger posed to residents of basement apartments can be particularly acute in the case of flash flooding driven by extreme rainfall. Residents of basement apartments are often disadvantaged in many ways, being low-income, from minority racial groups, or recent immigrants. 

In this study, we will combine novel modeling and assessment of compound coastal-pluvial flood hazard with analyses of flood vulnerability in populations with different characteristics around Jamaica Bay, NYC. Innovative hydrodynamic and machine learning (ML) models will be developed and applied for integrated flood modeling for Jamaica Bay, both validated using existing citizen science observations and ultrasonic sensor measurements of street flooding. We will collect and analyze social data through interviews and household surveys to document impacts of and recovery from flooding in neighborhoods that have recently been impacted by pluvial and high-tide flooding and that represent a broad range of natural and built environmental and socio-economic conditions. We will combine investigation of social vulnerability to pluvial and high-tide flooding with existing understanding of social vulnerability to coastal storm flooding in urban neighborhoods, to assess inequities in the burden of flood risk and inform policies that can advance equitable adaptation to flood risk.