Contact CEH NORA team at noraceh@ceh.ac.ukThe NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner. 1The following paper is the final version prior to publication on 22 September 2015. are proposed, the way in which indicators could contribute to classification is discussed. All of the methods described in Table 1 consider a hierarchy of spatial units, but the degree to which they develop the other aspects of the conceptual approach proposed by Frissell et al.(1986) varies widely.2. Many of the frameworks focus entirely on hydromorphological processes and forms that are either directly measured or inferred. This is because interactions between processes and forms control the dynamic morphology or behaviour of rivers and their mosaics of habitats.Hydromorphological processes drive longitudinal and lateral connectivity within river networks and corridors, the assemblage and turnover of physical habitats, and the sedimentary and vegetation structures associated with those habitats.3. Some frameworks are conceptual, providing a way of thinking about or structuring analyses of river systems, and interpreting their processes, morphology and function (e.g. Frissell et al., 1986;Habersack, 2000;Fausch et al., 2002;Thorp et al., 2006;Beechie et al., 2010;McCluney et al., 2014). Some frameworks are more quantitative, generating one or more indices or classifications of spatial units that support assessment of river systems (e.g. Rosgen, 1994;González del Tánago and García de Jalón, 2004;Merovich et al., 2013;Rinaldi et al., 2013Rinaldi et al., , 2015a MacDonald, 2002;Brierley and Fryirs, 2005;Beechie et al., 2010; Rinaldi et al., 2013a Rinaldi et al., , 2015.In some cases, theoretical or historical analyses or consideration of specific future scenarios are used to develop space-time understanding that can support management decisionmaking (e.g. Buffington, 1997, 1998;Montgomery and MacDonald, 2002;Benda et al., 2004;Brierley and Fryirs, 2005;McCluney et al., 2014 , 1997, 1998Montgomery and MacDonald, 2002;Benda et al., 2004;Brierley and Fryirs, 2005;Merovich et al., 2013;Rinaldi et al., 2013Rinaldi et al., , 2015a. Furthermore, some of the frameworks include indicators of human pressures and their impacts (e.g. Merovich et al., 2013;McCluney et al., 2014;Rinaldi et al., 2013Rinaldi et al., , 2015a.6. Finally, although most frameworks could be described as incorporating processes to some degree, some methods are particularly process-based, even when processes are inferred from forms and associations rather than being quantified by direct measurements.Frameworks that consider temporal dynamics and trajectories of historical change (see point 4, above) are particularly effective in developing understanding of processes and the impacts of changed processes cascading through time and across spatial scales.Although the list of frameworks presented in Table 1 is far from comprehensive, ...

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Abstract. In this paper we use a multi-hazard approach to analyse the 9 September 2010 flash flood in the Dragone basin, a 9 km 2 catchment located along the Amalfi rocky coastal range, southern Italy. In this area, alluvial fan flooding has been the most frequent and destructive geologic hazard since Roman times. Sudden torrents of water (flash floods) are caused by high-intensity and very localized cloudbursts of short duration, inducing slope erosion and sediment delivery from slope to stream. The elevated bed load transport produces fast-moving hyperconcentrated flows with significant catastrophic implications for communities living at the stream mouth.The 9 September 2010 rainstorm event lasted 1 h with an intensity rainfall peak of nearly 120 mm h −1 . High topographic relief of the Amalfi coastal range and positive anomalies of the coastal waters conditioned the character of the convective system. Based on geological data and post-event field evidence and surveys, as well as homemade videos and eyewitness accounts, it is reported that the flash flood mobilized some 25 000 m 3 of materials with a total (water and sediment) peak flow of 80 m 3 s −1 . The estimated peak discharge of only clear water was about 65 m 3 s −1 . This leads to a sediment bulking factor of 1.2 that corresponds to a flow with velocities similar to those of water during a flood.

The ISPRA (Italian National Institute for Environmental Protection and Research) has developed a GIS based procedure (BIGBANG 1.0—“Nationwide GIS-based hydrological water budget on a regular grid”) for evaluating all the factors of the monthly groundwater balance at National scale, using Python programming language. The procedure is based on spatial environmental information at very high resolution, often available on the WEB, in formats easily usable by the main geographic information systems. The hydrological factors of total precipitation, actual evapotranspiration, surface runoff and aquifer recharge are evaluated for a grid of 1 km resolution. The tool has been applied to the Campania Region (southern Italy) for the period 1996–2015, also defining for all factors the LTAA (Long Term Annual Average). These results and the monthly evaluations have been compared with groundwater balances carried out at local scale, in a carbonate groundwater body. The comparison shows that the lithological and hydrogeological features, much more detailed at local scale, can influence some factors of the balance, but the final amount of the recharge is comparable. Finally, this comparison, apart the above cited observations, represents a valid test for the BIGBANG 1.0 procedure and for its future implementation in the next versions