Analysing random spatio-temporal variability of storm events for hydrological modelling

Events-based hydrology phenomena are affected by extreme spatio-temporal variability. Precipitation is the first source of variability. Storms can start at different times across a catchment and can evolve differently over time thus creating a complex frame for events-based hydrological modelling. Both are affected by a random character. On many occasions a scarce number of weather stations are available within the catchments so researchers and hydrologists are forced to use interpolation methods for estimating precipitation. Classical interpolation methods base on deterministic algorithms not properly accounting for the random character of storm. In this work we analyse the spatial variability of the recorded storms in a set of urban weather stations in Madrid delivering some criteria for dealing with spatio-temporal variability of storms for modelling events-based hydrological processes.