Sensitivity analysis of SCHADEX extreme flood estimations to observed hydrometeorological variability

Abstract

[1] 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 blockbootstrap 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.

Evaluation of a compound distribution based on weather pattern subsampling for extreme rainfall in Norway

“…It has also been applied successfully in France (Garavaglia et al, 2011;Neppel et al, 2014), Austria and West Canada (Brigode et al, 2014). MEWP is a general model imposing no specific hypotheses on the data, so its application in other regions of the world is absolutely worth considering.…”

“…MEWP is a general model imposing no specific hypotheses on the data, so its application in other regions of the world is absolutely worth considering. The only limitation is that a classification into weather patterns suitable for evaluating extreme precipitation is needed as a precursor to such an analysis, but this is already available in several regions around the world (see Brigode et al, 2014) …”

“…SCHADEX has been developed and applied in France by Electricité de France (EDF) for dam spillway design since 2006. It has also recently been applied in different regions of the world (in France, Austria, Canada and Norway) (e.g., Brigode et al, 2014) and has been more extensively evaluated for three catchments in Norway in Lawrence et al (2014). Of particular interest in Norway is the need for a method which takes the combined probability of extreme rainfall and snowmelt into account, for which SCHADEX is well suited in comparison with event-based approaches.…”

A stochastic event-based approach for flood estimation in catchments with mixed rainfall/snowmelt flood regimes

“…Other studies have also shown that the soil saturation level is not as important in comparison with the parameters of the hydrological model. For example, Brigode et al (2014) tested the sensitivity of the SCHADEX model using a set of block bootstrap method. In each of these experiments, different sub-periods selected from the observation record were used in turn to calibrate the rainfall model, 20 the hydrological model and to determine the sensitivity to the soil saturation level.…”

An objective cross-validation framework for mapping rainfall hazard based on rain gauge data

“…Although the mixture of distributions over weather patterns has revealed efficient in other countries (e.g. in Norway and Canada, Brigode et al, 2014;Blanchet et al, 2015), it might be less relevant in, e.g., monsoon climate regions where the consideration of seasons seems Figure 10. Map of the probability of daily rainfall to exceed 1mm and of the mean of nonzero rainfall in the three WPs of the season-at-risk.…”