Abstract. Flood and flash floods are complex events, depending on weather dynamics, basin physiographical characteristics, land use cover and water management. For this reason, prediction of such events usually deals with very accurate model tuning and validation, which is usually site-specific and based on climatological data, such as discharge time series or flood databases. In this work, we developed and tested two hydrological stress indices for flood detection in the Central Italy Apennine District: a heterogeneous geographical area, characterized by complex topography and medium-to-small catchment extension. Proposed indices are threshold-based and developed taking into account operational requirements of civil protection end-users. They are calibrated and tested through the application of signal theory, in order to overcome data scarcity over ungauged areas, as well as incomplete discharge time series. The validation has been carried out on a case study basis, through the use of flood reports from various source of information, as well as hydrometric level time series, which represent the actual hydrological quantity monitored by civil protection operators. Obtained results shows as the overall accuracy of flood prediction is greater than 0.8, with false alarm rates below 0.5 and probability of detection ranging from 0.51 to 0.80. A slight anticipation of peak occurrence was found, however, the time shift of indices signal peak it is strongly dependent on the presence of dams that regulates the flood propagation. Moreover, the different nature of the proposed indices suggests their application in a complementary way, as the index based on drained precipitation appears to be more sensible to rapid flood propagation in small tributaries, while the discharge-based index is particularly responsive to main channel dynamics.