Abstract. The purpose of this study is to propose the Bayesian Network (BN) model to estimate flood peak from Atmospheric Ensemble Forecasts (AEFs). The Weather Research and Forecasting model was used to simulate historic storms using five cumulus parameterization schemes. The BN model was trained to forecast flood peak from AEFs. Mean Absolute Relative Error was calculated as 0.076 for validation data while it was calculated as 0.39 in artificial neural network (ANN) as a widely used model. It seems that BN is less sensitive to small data set, thus it is more suited for forecasting flood peak than ANN.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.