Award Abstract # 1937099
Convergence Accelerator Phase I (RAISE): The Urban Flooding Open Knowledge Network

NSF Org: ITE
Innovation and Technology Ecosystems
Recipient: CINCINNATI UNIV OF
Initial Amendment Date: September 10, 2019
Latest Amendment Date: January 30, 2020
Award Number: 1937099
Award Instrument: Standard Grant
Program Manager: Lara Campbell
ITE
 Innovation and Technology Ecosystems
TIP
 Directorate for Technology, Innovation, and Partnerships
Start Date: September 1, 2019
End Date: May 31, 2021 (Estimated)
Total Intended Award Amount: $1,000,000.00
Total Awarded Amount to Date: $1,027,958.00
Funds Obligated to Date: FY 2019 = $1,000,000.00
FY 2020 = $27,958.00
History of Investigator:
  • Lilit Yeghiazarian (Principal Investigator)
    yeghialt@ucmail.uc.edu
  • Sankarasubraman Arumugam (Co-Principal Investigator)
  • Ximing Cai (Co-Principal Investigator)
  • Venkatesh Merwade (Co-Principal Investigator)
  • Torsten Hahmann (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Cincinnati Main Campus
2600 CLIFTON AVE
CINCINNATI
OH  US  45220-2872
(513)556-4358
Sponsor Congressional District: 01
Primary Place of Performance: University of Cincinnati Main Campus
OH  US  45221-0012
Primary Place of Performance
Congressional District:
01
Unique Entity Identifier (UEI): DZ4YCZ3QSPR5
Parent UEI: DZ4YCZ3QSPR5
NSF Program(s): CA-HDR: Convergence Accelerato,
EnvS-Environmtl Sustainability
Primary Program Source: 01001920DB NSF RESEARCH & RELATED ACTIVIT
01002021DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 049Z, 7556
Program Element Code(s): 095Y00, 764300
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.084

ABSTRACT

The NSF Convergence Accelerator supports team-based, multidisciplinary efforts that address challenges of national importance and show potential for deliverables in the near future.

The broader impact and potential societal benefit of this Convergence Accelerator Phase I project is to minimize economic and human losses from future urban flooding in the United States. Floods impact a series of interconnected urban systems (referred to in this project as the Urban Multiplex) that include the power grid and transportation networks, surface water and groundwater, sewerage and drinking water systems, inland navigation and dams, and other system, all of which are intertwined with the socioeconomic and public health sectors. This project uses a convergent approach to integrate these multiple interconnected systems and merges state-of-the-art practices in hydrologic and hydraulic engineering; systems analysis, optimization and control; machine learning, data and computer science; epidemiology; socioeconomics; and transportation and electrical engineering to develop an Urban Flood Open Knowledge Network (UF-OKN). The UF-OKN will be built by bringing together academic and non-academic researchers from engineering, computer science, social science, and economics. The UF-OKN is envisioned to empower decision makers and the general public by providing information not just on how much flooding may occur from a future event, but also to show the cascading impact of a flood event on natural and engineered infrastructure of an urban area, so that more effective planning and decision-making can occur.

The real impacts of flooding across the Urban Multiplex is currently unquantifiable because many of the systems, although interconnected, are independently designed and managed. Therefore, an open knowledge network that facilitates detailed understanding of the interconnectedness of these systems and how they impact each other is critically needed. An important gap that this Phase I effort will fill is the development of a common set of ontologies for describing and traversing the data relationships among Urban Multiplex subsystems. This Phase I effort will lay the groundwork for a production-scale UF-OKN in Phase II but will also make publicly available the prototype UF-OKN and its applications. The outcome of a potential Phase II project would be a fully functional UF-OKN that would respond to plain English Internet queries with actionable information on what infrastructure across the Urban Multiplex would be impacted during storms and flooding, facilitating both short-term and long-term planning with information on sustainability metrics associated with different decisions. This deliverable would be potentially transformative to researchers, decision-makers and the general public in terms of how they engage with and act upon information about urban flooding.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Hahmann, Torsten and Powell, Robert "Automatically Extracting OWL Versions of FOL Ontologies" International Semantic Web Conference (ISWC 2021) , 2021 Citation Details
Johnson, J. Michael and Narock, Tom and SinghMohudpur, Justin and Fils, Doug and Clarke, Keith C. and Saksena, Siddharth and Shepherd, Adam and Arumugam, Sankar and Yeghiazarian, Lilit "Knowledge graphs to support realtime flood impact evaluation" AI Magazine , v.43 , 2022 https://doi.org/10.1002/aaai.12035 Citation Details
Stephen, S. and Hahmann, T. "Model-Finding for Externally Verifying FOL Ontologies: A Study of Spatial Ontologies" Proc. of the International Conference on Formal Ontology in Information System (FOIS-2020) , 2020 https://doi.org/10.3233/FAIA200675 Citation Details

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

The NSF Convergence Accelerator supports team-based, multidisciplinary efforts that address challenges of national importance and show potential for deliverables in the near future. The broader impact and potential societal benefit of this Convergence Accelerator project is to minimize economic and human losses from future urban flooding in the United States. Floods impact a series of interconnected urban systems (referred to in this project as the Urban Multiplex) that include the power grid and transportation networks, surface water and groundwater, sewerage and drinking water systems, inland navigation and dams, and other systems, all of which are intertwined with the socioeconomic and public health sectors. This project uses a convergent approach to integrate these multiple interconnected systems and merges state-of-the-art practices in hydrologic and hydraulic engineering; systems analysis, optimization and control; machine learning, data and computer science; socioeconomics; transportation and electrical engineering to develop an Urban Flooding Open Knowledge Network (UFOKN). The UFOKN is an information system that will empower decision makers and the general public by providing information not just on how much flooding may occur from a future event, but also to show the cascading impact of a flood event on natural and engineered infrastructure of an urban area, so that more effective planning and decision-making can occur.

Some of the major goals in Phase I of this project were to i) bring together a team of experts that can successfully tackle these multi-disciplinary issues related to urban flooding, ii) create a feasible sustainability plan beyond Phase II, and iii)  build partnerships that provide the team with real-life practical expertise in flood mitigation and planning as well as field data and product testing. To achieve these goals, the UFOKN team pursued an iterative human-centered approach, consisting of product prototyping, workshops, interviews and one-on-one meetings.

In November 2019, the team convened its first user workshop in Raleigh, NC and presented the UFOKN concept to prospective partners. The objective of this workshop was to identify the User Personas whose needs the UFOKN should solve. We mapped their daily journeys, conducted interviews and hands-on breakouts to draw out their interactions with the future UFOKN. A thematic analysis of user journeys identified 9 user personas representing urban planners, emergency responders, utility managers, private citizens, governmental agencies, academic researchers and private industry that informed Phase I prototyping , as well as the work plan for Phase II.

Following this workshop, the team started developing UFOKN1.0 – the system prototype. It coupled a select number of easily accessible sub-systems of the Urban Multiplex (surface and groundwater, stormwater and sewage systems, and some civil infrastructure such as transportation network, buildings and bridges) for the city of Houston. Houston was chosen because we had rich historical data from Hurricane Harvey, and a set of validated hyper- resolution hydrologic/hydraulic models in place. A second workshop was held in January 2020 in Houston, TX to demonstrate this prototype, solicit feedback, and discuss future avenues of partnerships in Phase II.

As a result of these efforts, the UFOKN team created more than 30 partnerships including partners from academic institutions; industry; cities, states and federal agencies; and national labs. Furthermore, the UFOKN team was expanded to bring needed expertise in areas of entrepreneurship, socio-hydrology, economics and artificial intelligence. The team demonstrated its ability to address critical societal needs and was awarded a Phase II grant, wherein UFOKN will deliver riverine flood forecasts at Continental U.S. scale, integrated urban flood forecasts for select cities, as well as capabilities to identify and map cascading infrastructure impacts.


Last Modified: 10/08/2021
Modified by: Lilit Yeghiazarian

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