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Overall, the method proposed represents a straightforward and consistent way to estimate flooding hazards to inform both the planning of future roadways and the maintenance of existing roadways.
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However, several methods, using different approaches, can be used to estimate flood damages.
To estimate flood quantiles in different return periods at ungauged reaches, we used regional flood frequency analysis.
To accurately estimate floods with hydrological models, the model parameters and the initial state variables must be known.
The extreme rainfall estimates were then entered into a two-dimensional (2D) non-uniform flow model to estimate flood inundation information.
Regional Flood Frequency Analysis (RFFA) is a statistical method widely used to estimate flood quantiles of catchments with limited streamflow data.
One must estimate flood figures with high return periods (R ⩾ 1000 10,000 years) but statistical methods involve large uncertainties because of the short length of the available records.
In order to evaluate the applicability of the proposed hierarchical Bayesian model for regional flood frequency analysis, we estimate flood quantiles for three randomly chosen out-of-sample sites and compare with classical estimates using the index flood method.
However, it is increasingly clear that relying on the historical record to estimate flood risk is likely to lead us to underestimate the dangers to which we are exposed".
Regional flood frequency techniques are widely used to estimate flood quantiles when flow data is unavailable for the basin under study or the record length is insufficient for reliable analyses.
A flood volume area relationship derived from the flood inundation time series, which is generated by analysing daily MODIS imagery, is used to estimate flooded area for the overbank flow.
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