Author(s): Saba Mirza Alipour; Kolbjorn Engeland; Joao Leal

Linked Author(s): Saba Mirza Alipour

Keywords: Bootstrap; Monte Carlo; Uncertainty analysis; Flood modeling

Abstract: Uncertainty is unavoidable in flood modeling practices and should be properly communicated. There are a variety of methods and techniques for uncertainty analysis, but normally they require a large number of hydrological/hydrodynamic model realizations. Among several uncertainty analysis methods, bootstrap is a popular technique which is carried out to make statistical inferences by using limited (or small) number of realizations without imposing much structural assumptions. This study has critically assessed the applicability of bootstrap method for assessing the uncertainty in flood mapping and compared the results with those that are obtained from Monte Carlo method. The results challenge the applicability of bootstrap method as an alternative to the more computationally intensive methods such as Monte Carlo. Furthermore, the results suggest that the mean parameter’s variation, which is typically undertaken as a convergence criterion in uncertainty analysis, can lead to early stopping of the process and consequently wrong statistical inferences.

DOI: https://doi.org/10.3850/IAHR-39WC252171192022651

Year: 2022