Projecting Climate Dependent Coastal Flood Risk With a Hybrid Statistical Dynamical Model.

ABSTRACT: Numerical models for tides, storm surge, and wave runup have demonstrated ability to accurately define spatially varying flood surfaces. However these models are typically too computationally expensive to dynamically simulate the full parameter space of future oceanographic, atmospheric, and hydrologic conditions that will constructively compound in the nearshore to cause both extreme event and nuisance flooding during the 21st century. A surrogate modeling framework of waves, winds, and tides is developed in this study to efficiently predict spatially varying nearshore and estuarine water levels contingent on any combination of offshore forcing conditions. The surrogate models are coupled with a time-dependent stochastic climate emulator that provides efficient downscaling for hypothetica

SUBMITTER: Anderson DL 

PROVIDER: S-EPMC9286665 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature