When forces collide: Developing a scalable framework for compound flood risk assessment
Principal Investigator:
Thomas Wahl Project Period: 09/2020 – 09/2022
Total Project Funding: $336,824 |
Collaborators:
Katherine Serafin (University of Florida) Robert Jane (University of Central Florida) Md Mamunur Rashid (University of Central Florida) |
Project Description.
Traditional approaches for identifying flood risk, like those used by the Federal Emergency Management Agency (FEMA) during Flood Insurance Risk Map (FIRM) development, rely on low probability scenarios such as the 1-percent-annual-chance (or 100-year) flood event, which is defined in terms of univariate forcing. In areas potentially exposed to both fluvial and ocean-driven hazards, the current modeling approach involves running two simulations using an extreme discharge and non-extreme still water level and vice versa, under current climate conditions. The along-river water level corresponding to the 1-percent-annual-chance condition is given by the maximum water level extracted from the two simulations. This approach contains three inherent assumptions: (1) the forcing conditions are independent and coincide only by chance, (2) there is no transition zone along the river where both fluvial and ocean-driven processes may be important for driving flood levels, and (3) the present-day 1-percent-annual-chance condition is an appropriate measure to assess flooding risk. Heavy rainfall and river discharge exhibit significant correlations with storm surges at localities in all regions of the U.S., indicating that the first assumption, forcing conditions are independent, does not hold everywhere. Regarding the second assumption focused on transition zones, various recent case studies have demonstrated that transition zones exist where extreme water levels along tidal rivers are influenced by both streamflow and coastal water levels. The third assumption includes the subjective choice (especially when moving to multivariate return periods) of a given hazard scenario and does not account for graduated risk or climate change effects. Our overarching goal is to develop a scalable hybrid (statistical/numerical) modelling framework to incorporate compound flooding from oceanographic and fluvial drivers into graduated coastal hazard risk assessments at the structure level. By considering a range of boundary conditions, our proposed approach allows for the quantification of the uncertainty of flood levels and highlights the spatially explicit differences in forcing conditions. As the statistical models are non-stationary, the effects of changing physical conditions (e.g., sea level rise, changes in storminess) can be easily included in future assessments. |
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All Rights Reserved.
Website developed and maintained by Javed Ali.