Rapid Probabilistic Assessment of Wave and Surge Hurricane Risk

Abstract

A probabilistic framework is presented for evaluation of hurricane wave and surge risk with particular emphasis on real-time, automated estimation for hurricanes approaching landfall. The basis of this framework is the characterization of hurricane scenarios through five model parameters: the landfall location and heading, the central pressure, the forward speed, and the radius of maximum winds. Description of the uncertainty in these parameters, through appropriate probability models, leads then to quantification of hurricane risk through a probabilistic integral. Its assessment relies on the development a surrogate model for the rapid evaluation of hurricane waves, water levels, and runup. This surrogate model is established using a response surface methodology fed by information from hundreds of pre-computed, highresolution model runs. The surrogate model is able to evaluate the maximum wave height, water level, and runup for any storm at a cost that is more than seven orders of magnitude less than the high fidelity models and thus meet time constraints imposed by emergency managers. An illustrative example is presented that considers applications of these tools for hurricane risk estimation for Oahu. The development of standalone executables to facilitate this risk estimation is also discussed.