Sediment connectivity underlies the relationships between sediment source areas and stream network and the use of topography‐based indices, such as the index of connectivity (IC), has become a common approach to investigate these relationships. However, few studies have tested the potential of the IC as an independent variable for predicting observable processes. In this study, the aim is the validation of the IC as a semi‐quantitative tool for depicting structural connectivity and predicting sediment dynamics linking sediment sources to the channel network after a large infrequent disturbance in the Rio Cordon catchment (Italy). First, the assessment of lateral connectivity was carried out using a combination of remote sensing data and field observations. In this way, it was possible to classify the sediment sources into disconnected, connected or functionally connected. Second, logistic regression analyses were performed using different IC variants, with different weighting factors and spatial resolutions as independent variables and connectivity status as dependent variable. Hence, the predictive capacity of the IC was tested and a threshold was derived to distinguish between low and high sediment connectivity. The results showed that only 15% of sediment sources are connected to the stream network. Moreover, the IC proved to be a reliable tool for depicting structural connectivity when using surface roughness as weighting factor and high‐resolution digital terrain models. On the contrary, it failed at predicting sediment dynamics as it did not classify correctly the functionally connected areas, so it cannot infer functional sediment connectivity in this case study. As a consequence, it was possible to obtain an IC threshold of −2.32, capable of differentiating between low and high structural sediment connectivity and useful for future management decisions. The threshold, in fact, represents an objective boundary between disconnected and connected sources in the Rio Cordon catchment.

Mountain streams are frequently characterized by step–pool morphology that provides stability and energy dissipation to the channel network. Large flooding events can overturn the equilibrium of the step–pool condition by altering the entire configuration. This work focuses on the impact of the “Vaia” storm (27–30 October 2018) on a step–pool mountain stream (Rio Cordon, Northeast Italy) and on its evolution after two years of ordinary flow conditions. To achieve the aims, this work uses both remote sensing data (LiDAR and UAV) and direct field measurements (i.e., longitudinal profiles and grain sizes distributions) performed pre-event, post-event, and 2 years later (current conditions). The results show a significant widening (width +81%, area +68%) and the creation of a new avulsion after the storm and a substantial change between the number of units (51 in the pre-event, 22 post-event, and 51 in the current conditions) and characteristics of step–pool sequences between pre- and post-conditions. Furthermore, it proves the ongoing processes of morphological stabilization since the current step–pool sequences parameters are heading back to the pre-event values. Such results suggest clear susceptibility of step–pool to exceptional events and fast recovery of such setting during barely two years of ordinary flow conditions.