Bayesian estimation of extreme flood quantiles using a rainfall-runoff model and a stochastic daily rainfall generator

摘要

Highlights?We indirectly estimate extreme flood quantiles within a Bayesian framework.?We model extreme rainfall with an upper-bounded distribution function.?Regional PMP information is used for eliciting an informative prior distribution.?We use an alternative statistical model for calibration residuals.?The Bayesian approach allows estimating the predictive uncertainty of maximum floods.AbstractExtreme flood estimation has been a key research topic in hydrological sciences. Reliable estimates of such events are necessary as structures for flood conveyance are continuously evolving in size and complexity and, as a result, their failure-associated hazards become more and more pronounced. Due to this fact, several estimation techniques intended to improve flood frequency analysis and reducing uncertainty in extreme