A reliable and long dataset describing urban flood locations, volumes and depths would be an ideal prerequisite for assessing flood frequency distributions. However, data are often piecemeal and long-term hydraulic modelling is often adopted to estimate floods from historical rainfall series. Long-term modelling approaches are time- and resource-consuming, and synthetically designed rainfalls are often used to estimate flood frequencies. The present paper aimsto assess the uncertainty of such an approach and for suggesting improvements in thedefinition of synthetic rainfall data for flooding frequency analysis. According to this aim, a multivariate statistical analysis based on a copulamethod was applied to rainfall features (total depth, duration and maximum intensity) to generate synthetic rainfalls that are more consistent with historical events. The procedure was applied to a real case study, and the results were compared with those obtained by simulating other typical synthetic rainfall events linked to intensity-duration-frequency (IDF) curves. The copula-based multi-variate analysis ismore robust and adapts well to experimental flood locations even if it is more complex and time-consuming. This study demonstrates that statistical correlations amongst rainfall frequency, duration, volume and peak intensity can partially explain the weak reliability of flood-frequency analyses based on synthetic rainfall events. © IWA Publishing 2011.
|Numero di pagine||10|
|Rivista||Water Science and Technology|
|Stato di pubblicazione||Published - 2011|
All Science Journal Classification (ASJC) codes
- Environmental Engineering
- Water Science and Technology