The RISC-KIT storm impact database: A new tool in support of DRR

This paper presents a new storm impact database for European coastlines that facilitates the upload, browsing and download of a broad range of physical and impact information related to historical and recent marine storm events. The database is transparent in terms of open access to raw data and metadata, makes use of version control systems through the OpenEarth repository and promotes the use of international standards. A total of 298 storm events are currently stored in the database from the ten RISC-KIT case study sites, including historical events dating back to the sixteenth century. To demonstrate the application of the tool, examples of typical event data contained within the database as well as the ability of the database to identify impacts of events across regions are presented. It is envisaged that this database will expand beyond the ten case study sites, with the aim of promoting and greatly improving the collection and reporting of extreme hydro-meteorological events across Europe into the future

Sedimentation Processes on Intertidal Areas of the Lagoon of Venice: Identification of Exceptional Flood Events (Acqua Alta) Using Radionuclides

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Can an early-warning system help minimize the impacts of coastal storms? A case study of the 2012 Halloween storm, northern Italy

Abstract. The Emilia-Romagna early-warning system (ER-EWS) is a state-of-the-art coastal forecasting system that comprises a series of numerical models (COSMO, ROMS, SWAN and XBeach) to obtain a daily 3-day forecast of coastal storm hazard at eight key sites along the Emilia-Romagna coastline (northern Italy). On the night of 31 October 2012, a major storm event occurred that resulted in elevated water levels (equivalent to a 1-in-20- to 1-in-50-year event) and widespread erosion and flooding. Since this storm happened just 1 month prior to the roll-out of the ER-EWS, the forecast performance related to this event is unknown. The aim of this study was to therefore reanalyse the ER-EWS as if it had been operating a day before the event and determine to what extent the forecasts may have helped reduce storm impacts. Three different reanalysis modes were undertaken: (1) a default forecast (DF) mode based on 3-day wave and water-level forecasts and default XBeach parameters; (2) a measured offshore (MO) forecast mode using wave and water-level measurements and default XBeach parameters; and (3) a calibrated XBeach (CX) mode using measured boundary conditions and an optimized parameter set obtained through an extensive calibration process. The results indicate that, while a "code-red" alert would have been issued for the DF mode, an underprediction of the extreme water levels of this event limited high-hazard forecasts to only two of the eight ER-EWS sites. Forecasts based on measured offshore conditions (the MO mode) more-accurately indicate high-hazard conditions for all eight sites. Further considerable improvements are observed using an optimized XBeach parameter set (the CX mode) compared to default parameters. A series of what-if scenarios at one of the sites show that artificial dunes, which are a common management strategy along this coastline, could have hypothetically been constructed as an emergency procedure to potentially reduce storm impacts

RISC-KIT: resilience-increasing strategies for coasts

High-impact storm events have demonstrated the vulnerability of coastal zones in Europe and beyond. These impacts are likely to increase due to predicted climate change and ongoing coastal development. In order to reduce impacts, disaster risk reduction (DRR) measures need to be taken, which prevent or mitigate the effects of storm events. To drive the DRR agenda, the UNISDR formulated the Sendai Framework for Action, and the EU has issued the Floods Directive. However, neither is specific about the methods to be used to develop actionable DRR measures in the coastal zone. Therefore, there is a need to develop methods, tools and approaches which make it possible to: identify and prioritize the coastal zones which are most at risk through a Coastal Risk Assessment Framework, and to evaluate the effectiveness of DRR options for these coastal areas, using an Early Warning/Decision Support System, which can be used both in the planning and event-phase. This paper gives an overview of the products and results obtained in the FP7-funded project RISC-KIT, which aims to develop and apply a set of tools with which highly-vulnerable coastal areas (so-called “hotspots”) can be identified

Introduction to RISC-KIT: Resilience-increasing strategies for coasts

Recent and historic low-frequency, high-impact events have demonstrated the flood risks faced by exposed coastal areas in Europe and beyond. These coastal zone risks are likely to increase in the future which requires a re-evaluation of coastal disaster risk reduction (DRR) strategies and a new mix of PMP (prevention, e.g., dike protection; mitigation, e.g., limiting construction in flood-prone areas and eco-system based solutions; and preparedness, e.g., Early Warning Systems, EWS) measures. In response to these challenges, the RISC-KIT project has delivered a set of open-source and openaccess methods, tools and management approaches to reduce risk and increase resilience to lowfrequency, high-impact hydro-meteorological events in the coastal zone (the “RISC-toolKIT”). These products enhance forecasting, prediction and early warning capabilities, improve the assessment of long-term coastal risk and optimise the mix of PMP-measures. In this paper an introduction is provided to the objectives, products, applications and lessonslearned of the RISC-KIT project, which are the subjects of this Special Issue. Subsequent papers provide details on the tools and their application on 10 case study sites in Europe

Observations on the Green Vine Snake

This is where the abstract of this record would appear. This is only demonstration data

Installation of ECR2 at LNS and Preliminary tests

The source ECR2 has been built in 1998 by Pantechnik, according to the design suggested by LNS Ion Source Group. This design entails some improvements with respect to a standard CAPRICE-type source: a) the magnetic field (up to 1.6 T axial, 1.1 T radial) allows to operate the source at 14 GHz in High B mode and at 18 GHz; b) two frequency heating can be used; c) an aluminum made plasma chamber is used in place of the stainless steel one. The main features of ECR2 along with a review of the preliminary tests will be outlined. Typical currents for fully stripped nitrogen are about 25 emA; for the heaviest ions, 1 emA of Kr28+ and 10 emA of Ta27+ have been measured. The installation at LNS has been completed recently and the details will be given

Assessment of satellite-derived shorelines automatically extracted from Sentinel-2 imagery using SAET

The definition of the shoreline position from satellite imagery is of great interest among coastal monitoring techniques. Understanding the reality mapped by the resulting shorelines and defining their accuracy is of paramount importance. The assessment described in this paper constitutes a validation of the shorelines obtained by using the novel tool SAET (Shoreline Analysis and Extraction Tool) for automatic shoreline extraction. The resulting shorelines applying the different parameters available in SAET are assessed in 9 test sites with diverse morphology and oceanographic conditions along the Atlantic European and Western Mediterranean coasts. The reference data is obtained along large coastal segments (covering up to about 240 km) from nearly coincident very high-resolution satellite images. Different image processing levels and extraction methods have been tested, showing their key role in the accuracy of shoreline position. When defining the approximate shoreline position the Automated Water Extraction Index for images without shadows (AWEInsh) with a 0 threshold generally constitutes the best segmentation method. In turn, the employment of the mathematical morphological operations of dilation or erosion considerably improves the results in certain coastal typologies. On the contrary, the employment of atmospherically-corrected images has a smaller influence on the accuracy of the SDSs. Results support the idea that the magnitude of the errors is strongly related to the specific coastal conditions- In general, the lowest errors appear in low-energetic microtidal sites, contrary to the energetic and mesotidal coasts with gentle slopes. The shoreline errors range between 3.7 m and 13.5 m RMSE (root-mean-square error) among the different coastal types when selecting the most appropriate extraction parameters. The shoreline position identified with SAET shows a similar or better accuracy to that obtained by other tools