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A high-magnitude flash flood, which took place on 25 October 2011 in the Magra River catchment (1717 km 2 ), central-northern Italy, is used to illustrate some aspects of the geomorphic response to the flood. An overall methodological framework is described for using interlinked observations and analyses of the geomorphic impacts of an extreme event.The following methods and analyses were carried out: (i) hydrological and hydraulic analysis of the event; (ii) sediment delivery by event landslide mapping; (iii) identification and estimation of wood recruitment, deposition, and budgeting; (iv) interpretation of morphological processes by analysing fluvial deposits; (v) remote sensing and geographic information system (GIS) analysis of channel width changes.In response to the high-magnitude hydrological event, a large number of landslides occurred, consisting of earth flows, soil slips, and translational slides, and a large quantity of wood was recruited, in most part deriving from floodplain erosion caused by bank retreat and channel widening. The most important impact of the flood event within the valley floor was an impressive widening of the overall channel bed and the reactivation of wide portions of the pre-event floodplain. Along the investigated (unconfined or partly confined) streams (total investigated length of 93.5 km), the channel width after the flood was up to about 20 times the channel width before the event.The study has shown that a synergic use of different methods and types of evidence provides fundamental information for characterizing and understanding the geomorphic effects of intense flood events. The prediction of geomorphic response to a flood event is still challenging and many limitations exist; however a robust geomorphological analysis can contribute to the identification of the most critical reaches.

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Deltaic systems are broadly recognized as vulnerable hot spots at the interface between land and sea and are highly exposed to harmful natural and manmade threats. The vulnerability to these threats and the interactions of the biological, physical, and anthropogenic processes in low-lying coastal plains, such as river deltas, requires a better understanding in terms of vulnerable systems and to support sustainable management and spatial planning actions in the context of climate change. This study analyses the potential of Bayesian belief network (BBN) models to represent conditional dependencies in vulnerability assessment for future sea level rise (SLR) scenarios considering ecological, morphological and social factors using Earth observation (EO) time series dataset. The BBN model, applied in the Po Delta region in the northern Adriatic coast of Italy, defines relationships between twelve selected variables classified as driver factors (DF), land cover factors (LCF), and land use factors (LUF) chosen as critical for the definition of vulnerability hot spots, future coastal adaptation, and spatial planning actions to be taken. The key results identify the spatial distribution of the vulnerability along the costal delta and highlight where the probability of vulnerable areas is expected to increase in terms of SLR pressure, which occurs especially in the central and southern delta portion.

Abstract. The vulnerability of flood-prone areas is determined by the susceptibility of the exposed assets to the hazard. It is a crucial component in risk assessment studies, both for climate change adaptation and disaster risk reduction. In this study, we analyse patterns of vulnerability for the residential sector in a frequently hit urban area of Milan, Italy. The conceptual foundation for a quantitative assessment of the structural dimensions of vulnerability is based on the modified source–pathway–receptor–consequence model. This conceptual model is used to improve the parameterization of the flood risk analysis, describing (i) hazard scenario definitions performed by hydraulic modelling based on past event data (source estimation) and morphological features and land-use evaluation (pathway estimation) and (ii) the exposure and vulnerability assessment which consists of recognizing elements potentially at risk (receptor estimation) and event losses (consequence estimation). We characterized flood hazard intensity on the basis of variability in water depth during a recent event and spatial exposure also as a function of a building's surroundings and buildings' intrinsic characteristics as a determinant vulnerability indicator of the elements at risk. In this sense the use of a geographic scale sufficient to depict spatial differences in vulnerability allowed us to identify structural vulnerability patterns to inform depth–damage curves and calculate potential losses from mesoscale (land-use level) to microscale (building level). Results produces accurate estimates of the flood characteristics, with mean error in flood depth estimation in the range 0.2–0.3 m and provide a basis to obtain site-specific damage curves and damage mapping. Findings show that the nature of flood pathways varies spatially, is influenced by landscape characteristics and alters vulnerability spatial distribution and hazard propagation. At the mesoscale, the “continuous urban fabric” Urban Atlas 2018 land-use class with the occurrence of at least 80 % of soil sealing shows higher absolute damage values. At microscale, evidence demonstrated that even events with moderate magnitude in terms of flood depth in a complex urbanized area may cause more damage than one would expect.

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