Nature based solutions (NBSs) address key societal challenges through the protection, sustainable management and restoration of both natural and modified ecosystems. In this work we present a modeling application of this innovative approach, inspired by nature, with the goal of mitigating coastal erosion. Within the framework of the OPEn-air laboRAtories for Nature baseD solUtions to Manage environmental risks (OPERANDUM) project, the natural reserve of Bellocchio in Lido di Spina (Italy) faces frequent marine floods and intense erosive phenomena, hence being chosen as Open-Air Laboratory for the NBS implementation. The project aims to mitigate coastal erosion through the realization of an artificial sand dune made of natural materials, such as sand, wood, geotextiles and geomembranes and covered by native herbaceous and shrubby vegetation. We present the modeling activities carried out in the context of the project, aiming on the performance and efficiency evaluation  of the designed NBS, with a specific focus on the coastal morphological modelling. Thus, a numerical modeling chain has been set-up to simulate a long-term current scenario with and without the NBS. The chain is composed of the wave model WAVEWATCH III, the oceanographic model SHYFEM and the morphodynamic model XBeach for the coastal area.XBeach was validated with available and specific (for the project) topo-bathymetric surveys of the area of interest as means to define the more accurate set-up of the model parameters. The 10 years period 2010-2019 was defined as the time range for modelling simulations. Sea level outputs from SHYFEM and wave outputs from WAVEWATCH III for the 10 years simulations are used to force the coastal model XBeach. Given the huge computational costs related to long-term simulations, an input-schematization was applied (so called “input reduction”). The approach followed for the long-term morphodynamic modelling of the NBS-XBeach setting will be shown. Moreover, the chosen coastal model domain, the model set-up and the input reduction applied will be presented.

The low lying and sandy coastal areas of the Emilia-Romagna region are heavily threatened by sea storms, often leading to flooding and coastal erosion events with severe impacts on citizens’ quality of life, damages to the cultural heritage and effects on economic activities (e.g. aquaculture, fisheries, tourism, beach facilities). Climate change projections reinforce the need of strategies and tools to prevent damages and promptly react to extreme events. In this context and in the framework of non-structural mitigation measures, the Hydro-Meteo-Climate Service of Arpae Emilia-Romagna (Arpae-SIMC) developed and operationally manages a Coastal Early Warning System (EWS) for the Emilia-Romagna Region (Northeast Italy).The EWS was developed during the EU Project FP7-MICORE and it is a state-of-the-art coastal forecasting system that follows a chain of operational numerical models: the meteorological model COSMO, the wave model SWAN-MEDITARE, the ocean model AdriaROMS, and the morphodynamic model XBeach. The latter is currently implemented on a series of cross-shore beach profiles covering eight locations distributed along the Emilia-Romagna shore. Deterministic daily forecasts (72-hours) are generated and Storm Impact Indicators (SIIs) used to assess sea-storm induced coastal risk along the region’s littoral (geo.regione.emilia-romagna.it/schede/ews). It is widely known that among the limitations of deterministic approaches, the lack of uncertainty estimation is often problematic as decision-makers might be misled if the only forecast available underestimates (or overestimates) incoming conditions. Hence, following the success of probabilistic forecasting in meteorological applications, storm surge EWSs following ensemble frameworks have been recently developed, allowing for more information available to sustain the decision-making process. Towards the new paradigm change, one of the foreseen outputs of the European Interreg Italy-Croatia CBC Programme project Strategic development of flood management (STREAM) involves the development of a “probabilistic EWS for coastal risk implemented and tested on at least one location along the Emilia-Romagna Coast”. The initial implementation of the (semi-)probabilistic framework benefits from the EU ADRION I-STORMS (Integrated Sea Storm Management Strategies) project outcomes, in which wave and sea level multi-model ensembles were developed for the Adriatic Sea giving origin to the Transnational Multi-Model Ensemble (TMES). The TMES was made available as one of the six Integrated Web System (IWS) components, combining five wave and six sea level forecasting systems as means to provide 48-hour forecasts in terms of sea level and wave characteristics (Hs, Tm and Dm). Ensemble mean and standard deviation (SD) are calculated based on different forecasting systems’ results. In the initial approach, four TMES combinations have been tested as XBeach forcing: the TMES mean; the mean minus one SD; the mean plus one SD; the mean plus two SDs. Two months were analyzed together with the already implemented deterministic system for two profiles along the region’s coast.The methodology followed for the test period will be shown as well as the results. Furthermore, the methodology under development will be also shown as means to enhance the discussion involving storm surge ensemble applications.

Long-term sea level variations can affect specific ocean basins, potentially leading to significant conse-quences for coastal areas, especially where changes in mean sea level are combined with subsidence or negative vertical land motion (VLM). This phenomenon is particularly noticeable along the northern Italian Adriatic coast, which are becoming increasingly vulnerable to flooding. To monitor sea level rise and develop detailed, site-specific adaptation strategies, regional and national institutions manage integrated tide gauge networks. The integration and enhancement of monitoring systems along the Adriatic Sea have been supported by several EU programs, including the Interreg Italy-Croatia AdriaClim project. This has led to the installation of GNSS instruments co-localised with tide gauges, allowing continuous monitoring of the vertical motion of sea level references. Furthermore a levelling activity was carried out in the Emilia-Romagna coastal areas to address the lack in updated vertical reference systems. The vertical reference is crucial for ensuring comparability of data from different stations and for correctly applying forecasting outputs to local conditions. Sea level data from three referenced tide gauge stations were validated and analysed to assess climate change indicators. The mean sea level trend in the northern Adriatic was evaluated using the Seasonal Trend decomposition based on Locally weighted regression smoothing using Loess (STL) method, applied to long-term historical time series from Venezia and Trieste. The Porto Garibaldi time series, however, only became available in 2009, so that a linear regression had to be used to analyse its trend. For comparison, the Venezia and Trieste time series for the same period were also analysed using the linear regression. The main results show site-specific behaviour and emphasise the importance of stable and correctly referenced stations. In fact, it is thanks to the information on VLM computed using the so-called GPS Imaging that we have been able to distinguish between the Relative Sea Level (RSL) component and the Absolute Sea Level (ASL) rise.