The present work aims to propose a methodology for identifying the specific time periods in which rainfall influences the effluent of an urban catchment, in terms of pollutants loads. By the use of online measurements, a dry and wet weather probabilistic characterisation regarding the time series of TSS pollutants loads was undertaken (Kernel Density Estimators). In addition, by the use of signal processing techniques (ACF, Median Filter and Step Detection), the identification of complete time windows in which the recorded TSS signal ranged outside of its typical dry weather behaviour can be assessed. The proposed methods were implemented for a study case (Gibraltar sub-basin Bogotá, Colombia), obtaining a total of seven fully-identified rainfall events. The identification seems to be appropriate, as it was consistent with the recorded rainfall pulses.