The current climate change could lead to an intensification of extreme weather events, such as sudden floods and fast flowing debris flows. Accordingly, the availability of an early-warning device system, based on hydrological data and on both accurate and very fast running mathematical-numerical models, would be not only desirable, but also necessary in areas of particular hazard. To this purpose, the 2D Riemann–Godunov shallow-water approach, solved in parallel on a Graphical-Processing-Unit (GPU) (able to drastically reduce calculation time) and implemented with the RiverFlow2D code (version 2017), was selected as a possible tool to be applied within the Alpine contexts. Moreover, it was also necessary to identify a prototype of an actual rainfall monitoring network and an actual debris-flow event, beside the acquisition of an accurate numerical description of the topography. The Marderello’s basin (Alps, Turin, Italy), described by a 5 × 5 m Digital Terrain Model (DTM), equipped with five rain-gauges and one hydrometer and the muddy debris flow event that was monitored on 22 July 2016, were identified as a typical test case, well representative of mountain contexts and the phenomena under study. Several parametric analyses, also including selected infiltration modelling, were carried out in order to individuate the best numerical values fitting the measured data. Different rheological options, such as Coulomb-Turbulent-Yield and others, were tested. Moreover, some useful general suggestions, regarding the improvement of the adopted mathematical modelling, were acquired. The rapidity of the computational time due to the application of the GPU and the comparison between experimental data and numerical results, regarding both the arrival time and the height of the debris wave, clearly show that the selected approaches and methodology can be considered suitable and accurate tools to be included in an early-warning system, based at least on simple acoustic and/or light alarms that can allow rapid evacuation, for fast flowing debris flows.

San Nicola Island, pertaining to the Tremiti Archipelago (Southern Adriatic Sea, Italy), is widely affected by cliff retreat and gravitational phenomena which severely threaten its monumental historical and natural value. In this study, geomorphological features of the area were derived following a stepwise approach, combining multitemporal stereoscopic aerial photo interpretations with morphometric analyses and detailed field surveys. A rockfall susceptibility map was created following a heuristic approach based on morphometric and geothematic parameters, accounting for slope, slope aspect, outcropping lithologies, structural discontinuities density, distance from landslide scarps, and presence of anthropic caves. Cliff sectors set on dolomitic limestones feature the highest susceptibility values, especially along the southeastern sector; medium values, instead, are found along the island flanks and along scarps located within the inner sectors; and the lowest values are detected on summit tabular surfaces. The achieved results were compared with historical maps and seismic data derived from local and national archives and catalogues, respectively. These analyses allowed us to define the role played by litho-structural and tectonic features on landslide occurrence and distribution, and their interplay in driving landscape evolution over centuries. Finally, this work represents a valuable scientific tool to support geomorphological studies for landslide hazard assessment and proper territorial planning in any other small insular areas, showing similar geological–geomorphological features and landscape values.

The paper presents a map of sediment surface distribution and bedforms in the Harle tidal inlet, German Wadden Sea. Data collection, processing, and map editing were realized within the sublittoral mapping program of Lower Saxony national waters carried out by the NLWKN – Coastal Research Station. The map is the result of the combined use of multibeam echosounder, sub-bottom profiler, and ground-truth data. The sediment characterization is achieved by an unsupervised approach using an Object-Based Image Analysis (OBIA) on a normalized backscatter mosaic, verified by nineteen sediment samples. Morphometrical parameters and sub-bottom data provided important information to identify hard substrates and bedforms.

This paper presents the results of the 2021 and 2022 field activities carried out at San Nicola Island (Tremiti Islands, Southern Adriatic Sea) by two groups of students as part of the Environmental Geomorphology Field Mapping course held within the Master's Degree in Geological Sciences and Technologies of Earth and Planets at University ‘G. d'Annunzio’ of Chieti-Pescara. Field activities were carried out following an integrated approach that involved morphometric, geological, and geomorphological analyses, supported by the combination of traditional methods with modern survey instruments and techniques. The Main Map (1:2,500 scale) comprehensively depicts the landscape of San Nicola Island, which is affected by both long- and short-term evolutionary processes, as witnessed by widespread slope landforms. The cartographic products presented in this work can represent a useful tool in territorial planning and management, as well as a valuable base for further scientific studies.