Science-integrated Artificial-intelligence for Flooding and precipitation Extremes (SAFE)
- Northeastern Univ., Boston, MA (United States)
- National Center for Atmospheric Research (NCAR), Boulder, CO (United States)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Univ. of Minnesota, Minneapolis, MN (United States)
- Columbia University; (United States)
- Univ. of Colorado, Boulder, CO (United States)
- Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)
- Tufts Univ., Medford, MA (United States)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
A grand challenge in hydrologic science is to understand why signals of climate change and variability, which are often visible in precipitation extremes at aggregate scales, are not consistently observed in the case of extreme flooding. However, a solution to this challenge may prove elusive unless the water cycle is viewed in an integrative manner. Thus, for riverine flooding, while Hortonian (infiltration excess) runoff may have stronger correlation with precipitation extremes and hence perhaps to warming trends or climate oscillators, Dunne (saturation excess) runoff may have a more complex relationships with time series of precipitation and with evaporation and transpiration, but rain-on-snow and snowmelt events may depend on land-surface and atmospheric temperatures. Atmospheric rivers and tropical cyclones lead to precipitation or flooding and are impacted by climate. Flooding assessments need to consider long-term baselines, evolving risk factors, coupled natural-human systems, and novel adaptation such as nature-inspired design.
- Research Organization:
- Northeastern Univ., Boston, MA (United States); National Center for Atmospheric Research (NCAR), Boulder, CO (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Minnesota, Minneapolis, MN (United States); Columbia Univ., New York, NY (United States); (United States); Univ. of Colorado, Boulder, CO (United States); Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Tufts Univ., Medford, MA (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI ID:
- 1769776
- Report Number(s):
- AI4ESP1047
- Country of Publication:
- United States
- Language:
- English
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