Uncertainty Analysis in the Evaluation of the DDF Curves Parameters in Climate Change Scenarios

Abstract

On the global scale, there is a robust observational evidence that, over the last decades, the frequency and intensity of extreme events significantly changed, even if regional and local studies have highlighted complex and non-uniform spatial patterns. Climate change can cause increased rainfall intensities which leads to an additional impact on drainage systems, due to the alteration of magnitude and frequency of peak flows over their service life. For this reason, the design criteria of urban drainage infrastructures need to be revised and updated, in order to take into account the possible variations of extreme rainfall. In particular, the Depth-Duration-Frequency (DDF) curves, widely used in engineering to assess the return periods of rainfall events, require an adjustment for climate change. The main purpose of this study is to provide a methodology to assess the DDF curves parameters in climate change scenarios, once the evidence of a statistically significant trend in extreme rainfall was verified. Specifically, a Bayesian procedure has been applied for two cases of study located in the Sicily (Southern Italy), in order to incorporate the effects of extreme rainfall variations on the definition of DDF curve for a future climate condition and to evaluate the uncertainty related to such projection. The climate projection has been compared with a baseline scenario representative of current climate conditions. Finally, the implications of the uncertainty related to the DDF parameters estimation on the design of real detention tanks were analyzed, thus providing an evaluation of their hydraulic performance under the assumption of climate change. Results showed that the assessment of DDF parameters from historical extreme rainfall series could not be adequate to provide reliable estimations of future design storm. Therefore, the occurring climate change cannot be neglected in the design procedure based on extreme rainfall estimation.