A Digital Model for Flood Risk Assessment in NYC
- Riccardo Negri, PhD student, Civil engineering, data analysis, disaster risk analysis, NYU Disaster Risk Analysis Lab (DRAL)
- Prof. Luis Ceferino
New York City has long been exposed to disastrous floods causing billions of dollars in damage. Better policies could mitigate the consequences of catastrophic events, but agreement on which actions to implement and which areas to prioritize is not always easy to achieve. Policymakers need information on potential flood-related losses to allocate the proper resources for mitigation measures. This project aims to create a digital model of New York City that can estimate potential disruption for given flood scenarios. It will incorporate diverse data on buildings, transportation and social vulnerability, to provide a broad perspective on risk to city government agencies and residents.
Category: Urban Infrastructure
Project Description & Overview
This project aims to create a model that takes flood maps of New York City and estimates the associated socio-economic losses. The work will be divided into two phases: in the first phase, students will combine the maps and data relating to the built environment, critical services such as hospitals and fire stations, public and private transport, and the social vulnerability of local communities to assess the exposure to floods. In the second phase, students will evaluate socio-economic losses, such as damage to buildings, disruption of transport networks, etc. Students will use flood maps provided by the NYC Mayor’s Office of Climate and Environmental Justice, apply geospatial techniques to estimate the extent of infrastructure affected by each flood scenario, and quantify losses using fragility functions, such as those provided by the Federal Emergency Management Agency. The final deliverable will be an automated tool to predict losses for any future climate scenario, and guide decision makers, activists, and residents in taking mitigation actions.
For this project, the following datasets will be used. Other datasets may be identified along the way.
NYC Stormwater Flood Map – Moderate Flood with Current Sea Levels
NYC Stormwater Flood Map – Moderate Flood with 2050 Sea Level Rise
NYC Stormwater Flood Map – Extreme Flood with 2080 Sea Level Rise
NYC Primary Land Use Tax Lot Output – Map (MapPLUTO)
CDC/ATSDR Social Vulnerability Index
MTA’s public turnstile data
NYS Traffic Data Viewer
The following competencies would be preferred to fully accomplish the scope of the project.
Statistical modeling of natural events
Python libraries: Pandas and Geopandas
Learning Outcomes & Deliverables
Students will learn about different types of floods, how they are modeled, and various methods for quantifying socio-economic losses due to natural hazards. They will consolidate their knowledge of geospatial analysis software, such as QGIS and Geopandas, and the methods for combining them into a single analysis stream. They will also be exposed to the initiatives that the NYC government is pursuing to mitigate the impacts of climate change on its communities.