Flood Memory and Uncertainty

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Award Year: 
2019
Principal Investigator: 
James Knighton, SESYNC Postdoctoral Fellow
Rebecca Elliott, Collaborating Mentor

Flooding risk has been recognized as a societal hazard and documented for centuries, yet nations continue to progress without leveraging the full depth of our global scientific knowledge. Developing countries often exist within deserts of hydrologic and atmospheric data, leading to the growth of nations in the face of high risk uncertainty. Nations, with ample resources, continue to develop infrastructure with a focus on short-term economic gains and often fail to consider the reality of flooding. Land Surface Models (LSMs) are an emerging research tool used by nations for predicting flood hazard across broad regions. LSM grids are most commonly developed for simulation of the atmospheric general circulation, and not necessarily optimized to represent land surface hydrology. Issues of scale result in poor representations of the atmospheric processes which generate extreme precipitation, as well as over-generalization of the physical (e.g. variable source areas) and ecological (plant transpiration) land surface controls on extreme runoff. National strategies for future floods risk mitigation are frequently designed from an imperfect memory of past flooding events rather than robust projections of future hazards. How societal memory and anticipation of future risks influence policy decisions and individual perspectives remains a critical open question in establishing meaningful risk mitigation practices. In this research we aim to determine whether national policies are driven by: a knowledge deficit related to imperfect LSMs, institutional memory of naturally infrequent flood processes and inertia towards short-term economic goals, or anticipation of the future climate projections.

Associated SESYNC Researcher(s): 
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