SCALING AND MULTISCALING MODELS OF DEPTH-DURATION-FREQUENCY CURVES FOR STORM PRECIPITATION

The scaling properties of temporal rainfall are shown to dictate the f orm of the depth-duration-frequency (DDF) curves of station precipitat ion, which are widely used in hydrological practice to predict design storms. Scale invariance of extreme storm probabilities is investigate d, and the conservative (simple scaling) as well the dissipative (mult iple scaling) nature of storm rainfall are considered, thus introducin g a general distribution-free framework to derive DDF curves. A log-no rmal model is also introduced to represent either simple or multiple s caling DDF curves from extreme value storm data. This model allows for a parsimonious and efficient parametrisation of DDF curves, and its p erformance is shown to improve the accuracy and robustness of design s torm predictions as compared with those achievable by interpolating th e quantile predictions of extreme rainfall data for specified duration s.