Sensitivity analysis of SCHADEX extreme flood estimations to observed hydrometeorological variability

Stochastic flood simulation methods are typically based on a rainfall probabilistic model (used for simulating continuous rainfall series or for estimating probabilities of random rainfall events) and on a rainfall-runoff model. Usually, both of these models are calibrated over observed hydrometeorological series, which may be subject to significant variability and/or nonstationarity over time. The general aim of this study is thus to propose and test a methodology for performing a sensitivity analysis of extreme flood estimations to observed hydrometeorological variability. The methodology consists of performing a set of block-bootstrap experiments: for each experiment, the data used for calibration of a particular model (e.g., the rainfall probabilistic model) is bootstrapped while the model structure and the calibration process are held constant. The SCHADEX extreme flood estimation method has been applied over six catchments located in different regions of the world. The results show first that the variability of observed rainfall hazard has the most significant impact on the extreme flood estimates. Then, consideration of different rainfall-runoff calibration periods generates a significant spread of extreme flood estimated values. Finally, the variability of the catchment saturation hazard has a nonsignificant impact on the extreme flood estimates. An important point raised by this study is the dominating role played by outliers within the observed records for extreme flood estimation.