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<p>Sediment production and delivery are hillslope processes characterized by significant variability and uncertainty, especially in mountain drainage catchments. Although sediments can be originated from several phenomena, such as slope instabilities, soil erosion and streambank failures, rainfall-induced landsliding, eventually turned into debris flows, is the dominant mechanism producing and conveying huge volumes of solid material to downstream areas through the channel network and therefore causing an increase of flood frequency.</p> <p>Such landslide-derived mechanisms cause damage, directly and indirectly, to public and/or private properties and infrastructure on alluvial fans that are basically due to the increase of clogging probability of bridges, instream sediment accumulation, and significant geomorphological change. Identifying the sediment upstream source areas and quantifying a probability distribution of the mobilized- and delivered-sediment volume, then, is crucial for the protection of downstream areas. However, such purpose still remain extremely challenging because of scarcity, or even lack, of time-consuming direct measurements that are generally carried out at small scale and cover short time periods.</p> <p>On this background, this work proposes a simplified procedure to estimate a probability distribution of the sediment yields combining: (i) rainfall intensity-duration-frequency (IDF) relationships for estimating synthetic precipitation with specific return time; (ii) a three-dimensional slope stability model to assess the rainfall-induced shallow landslides susceptibility; (iii) a connectivity index for mapping the probability of sediment delivery; and (iv) a simple hydrological model based on SCS-CN method to estimate the flood peak, and furthermore the probability distribution of sediment flux. The procedure requests low-resolution maps, usually available at the regional scale, such as digital elevation model, land cover, geology, lithology, and IDF curves, and represents a planning tool for climate and land cover change mitigation that can be extremely useful for forest managers, hydraulic engineering and watershed planners.</p> <p>The procedure was tested on several small mountainous headwater catchments in Valle Camonica, located into the Central Italian Prealps, mostly covered by forests, with settlements on alluvial fans, and prone to shallow landslide, debris flood, and debris flow. It was qualitatively validated on the landslide inventory and the mapped flood areas, showing comparable results.</p>

<p>River channels and floodplains have been highly modified over the last 70 years to mitigate flood risk and to gain lands for agricultural activities, settlements and soft infrastructures (e.g., cycle paths). River engineering measures simplified the geomorphologic complexity of river system, usually from braided or wandering channels to highly-confined single-thread channel. Meanwhile, rivers naturally adjust and self-organise the geomorphologic function as response of all the disturbances (e.g., flood events, river-bed degradation, narrowing, control works) altering sediment and water transfer, exacerbating bank erosion processes and streambank failures, and exposing bare sediment that can be subsequently colonized by pioneer species. In this context, river management has to address river dynamics planning sustainable practices with the aim to combine hydraulic safety, river functionality, and ecological/environmental quality. These actions require the detection of river processes by monitoring the geomorphological changes over time, both over the active riverbank and the close floodplains. Thus, remote sensing technology combined with machine learning algorithms offers a viable decision-making instrument (Piégay et al., 2020).</p><p>This study proposes a procedure that consists in applying image segmentation and classification algorithms (i.e., Random Forest and dendrogram-based method) over time-series high resolution RGB-NIR satellite-images, to identify the fluvial forms (bars and islands), the vegetation patches and the active riverbed. The study focuses on three different reaches of Oglio River (Valcamonica, North Italy), representative of the most common geomorphic changes in Alpine rivers.</p><p>The results clearly show the temporal evolution/dynamics of vegetated and non-vegetated bars and islands, as consequence of human and natural disturbances (flood events, riparian vegetation clear-cutting, and bank-protection works). Moreover, the procedure allows to distinguish two stages of riparian vegetation (i.e., pioneer and mature vegetated areas) and to quantify the timing of colonization and growth. Finally, the study proposes a practical application of the described methodology for river managers indicating which river management activity (including timing, intensity and economic costs) is more appropriate and sustainable for each studied reach.</p><p> </p><p>References: Piégay, H., Arnaud, F., Belletti, B., Bertrand, M., Bizzi, S., Carbonneau, P., Dufour, S., Liébault, F., Ruiz‐Villanueva, V. and Slater, L.: Remotely sensed rivers in the Anthropocene: state of the art and prospects, Earth Surf. Process. Landf., 45(1), 157–188, https://doi.org/10.1002/esp.4787, 2020.</p>