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Abstract Every year, extreme rainfall events cause human deaths and economic losses around the world. Risk reduction strategies may involve the implementation of structural measures that are widely extended and financial relevant. Despite the high reliance on these mitigation measures, there might occur instances of overload, i.e. events with intensities exceeding the design value of these structures, that may have catastrophic consequences. In this framework, it is crucial to improve hydraulic works management, thus, we introduce a procedure at rain gauge scale for revising design variables throughout their operational lifespan. This enables us to enhance the assessment of the probability of failure of these works. Finally, we investigate instances where design variables experience overload during the recording period, thus assessing the occurrence of rare yet possible events. To this aim we find the most-suitable probability distribution to describe daily rainfall maxima in Italy. Specifically, we test the performance of four widely used bi-parametrical distributions with different tail behaviour, by analysing an impressive dataset consisting of 2282 rain gauges observations from 1860 to 2022. Our results show that: (1) 78% of the empirical samples exhibits heavy-tail behaviour; (2) when the update procedure is applied, 64% of the samples shows a higher-than-expected probability of failure; (3) at least one case of overload associated to a 100-years return period is recorded in almost all regions. Based on our results, existing hydraulic works designed to safeguard populations and their activities from catastrophic events may face a higher risk of failure than initially expected.
Moccia et al. (Thu,) studied this question.