Probabilistic Flood Hazard Assessment Framework Development: Extreme Rainfall Analysis
Engineer Research and Development Center Vicksburg
Pagination or Media Count:
This report introduces a framework for probabilistic flood hazard assessment PFHA whose basis leverages recent advances in the science of spatial extremes. The framework basis includes a latent variable model LVM or a max-stable process application wherein for either case model inference is likelihood based. The framework is flexible in that it can leverage robust approaches to quantify model uncertainty while also supporting the capacity to readily combine additional relevant data types for example, historical andor paleoflood data for flood frequency analyses. This report profiles applications of Bayesian inference for flood hazard curve development for at-site and spatial LVM analyses. Pointwise spatial model development using an LVM or a max-stable process requires the parameters of the model characterizing the pointwise extremes to vary spatially as a function of gridded covariate data relevant to the hydrometeorological extreme under consideration. Recent advances in mathematical regularization facilitate spatial pointwise model reduction. The PFHA framework accommodates the multiple model parameterizations encapsulated within a given LVM or max-stable process deployment by generalizing model choice using information criteria.
- Hydrology, Limnology and Potamology