loading page

Closing the Gap from Uncertainty Quantification to Decision Making: Integrated Prediction-Optimization Modeling of the Critical Infrastructure Flood Resilience
  • +7
  • Erhan Kutanoglu,
  • Wen-Ying Wu,
  • Sabiha Tabassum,
  • Ashutosh Shukla,
  • Zong-Liang Yang,
  • Carey King,
  • Surya Santoso,
  • Brent Austgen,
  • John Hasenbein,
  • Joshua Yip
Erhan Kutanoglu
The University of Texas at Austin

Corresponding Author:[email protected]

Author Profile
Wen-Ying Wu
University of Texas at Austin
Author Profile
Sabiha Tabassum
University of Texas at Austin
Author Profile
Ashutosh Shukla
University of Texas at Austin
Author Profile
Zong-Liang Yang
Univ Texas Austin
Author Profile
Carey King
University of Texas at Austin
Author Profile
Surya Santoso
University of Texas at Austin
Author Profile
Brent Austgen
The University of Texas at Austin
Author Profile
John Hasenbein
University of Texas at Austin
Author Profile
Joshua Yip
The University of Texas at Austin
Author Profile

Abstract

Our research team is involved in several projects that seek to integrate the science-based prediction models of flood-causing events such as hurricanes with the decision-making models for critical infrastructure resilience. To this end, we use the state-of-the-art hydrological models such as WRF-Hydro and ADCIRC to simulate potential realizations of inland and coastal flooding events caused by tropical storms. We use these simulations to generate statistically sound scenarios to populate the inputs of several resilience-based decision making models, all developed using the state-of-the-art scenario-based stochastic and robust optimization methodologies. We identify three time lines where these models can be used to improve the quality of decision making processes: (1) Short-term preemptive resource allocation (preparedness) just before impending tropical storms, (2) Mid-term hardening and resilience investment strategies (mitigation) within a multi-season horizon considering multitudes of potential storms, and (3) Long-term resilience investment and infrastructure design strategy development considering potentially increasing flooding risks due to climate change and sea level rise. We present the overall framework that our team developed relying on the team’s in-progress work, particularly for the short- and mid-term prediction-optimization models. We use two specific infrastructures as examples to instantiate our models: (1) Evacuation of patients from healthcare facilities (hospitals and nursing homes), and (2) Substation hardening and preparation for power grids. To create realistic, high-resolution case studies, we consider historical and synthetic storms that impact actual healthcare facilities and power grid for Texas.