ABSTRACT
Flood modeling and flood forecasting uncertainties are essential to estimate the accuracy of modeling. Uncertainty permits us to evaluate the performance of a model and allows us to account for discharge, flood extent, and flood depth in probabilistic terms. The classical approach used to consist of calibration/validation to reduce the uncertainty of the model with different methods. However, multi-model flood modeling has emerged as a method to estimate uncertainty in flood modeling. It gained awareness from the Bayesian modeling approach using Markov chain/stochastic to estimate the likelihood of parameters derived from classical sensitivity analysis. Furthermore, the development of ensemble methods in the weather forecast/climate field has led to a practical way to estimate the uncertainty of models and is currently used in flood forecast modeling deriving from the strong uncertainty associated with atmospheric initial conditions. This study reviewed the uncertainties associated with flood modeling and forecasting and the various techniques for reducing the uncertainty of flood models.
