Project Abstract

Extreme events stress New York City’s (NYC’s) interdependent water and energy infrastructures; impact human livelihood; and can disrupt local ecosystems. The dependence of water and wastewater operations on power implies that a blackout, coupled with backup system components’ failures, can force the discharge of untreated wastewater into NYC’s waterways, and result in a public health emergency. Data-driven and optimization techniques can leverage publicly available data to reveal vulnerabilities in electricity, water, and wastewater infrastructures. Our analysis can aid policy design against natural hazards and cyberattacks, and thus inform the modernization of interdependent urban water and electricity infrastructures.

Project Description & Overview

This project aims to identify supply chain vulnerabilities of New York City’s physical water and wastewater infrastructure; understand water-energy interdependencies; and inform resilience policies against natural disasters. The project will:

• Provide a water and wastewater management framework which integrates publicly available databases.
• Assess vulnerabilities and inform water and energy infrastructure policy design in New York City against extreme events and potential cyberattacks.

Students will collect and process data either on water supply chains (i.e., from reservoirs to NYC water consumption), or on wastewater supply chains (i.e., from water consumption and drainage to wastewater treatment). Between February and May, students will integrate databases that include water consumption and technical features of reservoirs, tunnels, the drainage system, and wastewater treatment facilities. Between May and August, the students will use optimization, statistical methods, machine learning, or a combination of techniques to identify critical assets, interconnections, or spatial and temporal interdependencies with the electricity sector within the water and wastewater supply chains that are vulnerable to disruptions. This project will provide comprehensive databases of the different components of New York City’s water and wastewater infrastructures.

Datasets

• NYC Open Data:
  • New York City (NYC) aggregate water consumption
  • NYC Aggregate Population
  • NYC water consumption per capita
• US Census Bureau:
  • NYC population by zip code
• NYC Open Data:
  • Energy and Water Data on privately owned buildings over 25,000 ft2 and in City-owned buildings over 10,000 ft2
• Open Sewer Atlas NYC:
  • Wastewater treatment facilities & sewersheds
• NYC Environmental Protection Agency:
  • Map of reservoir capacities
• United States Geological Survey (USGS):
  • US county-level water use
  • US county-level water and energy use data
  • Reservoirs capacity
• EIS document (New York City Department of Environmental Protection):
  • Capacity of Tunnels 1, 2, & 3 (billion gallons per day)

Competencies

• Knowledge of Python, R, Julia, Matlab, other data-processing languages, or Excel.
• Familiarity with statistical, optimization, or machine-learning inference methodologies.
• Familiarity with data-visualization tools in R, Matlab, Python, Julia, or other language.

Learning Outcomes & Deliverables

Through this project, the candidate(s) will:

• Integrate and analyze large datasets to provide a comprehensive dataset which include interconnected operations within water supply or wastewater infrastructures.
• Broaden their understanding of the economic, environmental, and health impacts of failures in modern urban water and wastewater infrastructures.
• Identify spatial and temporal vulnerabilities of urban water infrastructures against potential natural hazards and cyber threats and provide policy recommendations.

Students

Seung Hwa Lee, Wonchan Lee, Vaishnavi Muthukrishnan