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Coastal flooding caused by extreme sea levels (ESLs) is one of the major impacts related to the climate change. It is expected to increase in the future due to sea level rise and storm surge intensification. Estimates of return levels obtained under the framework provided by extreme events theory might be biased under climatic non-stationarity. Additional uncertainty is related to the choice of the model. In this work, we fit several extreme values models to a long-term (96 years) sea level record from the city of Venice (NW Adriatic Sea, Italy): a Generalized Extreme Value distribution (GEV), a Generalized Pareto Distribution (GPD), a Point Process (PP), and the Joint Probability Method (JPM) under different detrending strategies. We model non-stationarity with a linear dependence of the model’s parameters from the mean sea level. Our results show that non-stationary GEV and PP models fit the data better than stationary models even with detrended data. The non-stationary PP model is able to reproduce the rate of extremes occurrence fairly well. Actualized estimates of the return levels for non-stationary models are generally higher than estimates from stationary models. Thus, projections of return levels in the future might be significantly different from those calculated using stationary models. Overall, we show that non-stationary extremes analyses can provide more robust estimates of return levels to be used in coastal protection planning.

This paper analyses the variability of the sea level barotropic components in the Mediterranean Sea and their reproduction using a hydrodynamic model with and without data assimilation. The impact of data assimilation is considered both in reanalysis and short-forecast simulations. We used a two-dimensional finite element model paired with an ensemble Kalman filter, which assimilated hourly sea level data from 50 stations in the Mediterranean basin. The results brought about a significant improvement given by data assimilation in the reanalysis of the astronomical tide, the surge, and the barotropic total sea level, even in coastal areas and far from the assimilated stations (e.g. the southeastern Mediterranean Sea). As with the reanalysis simulations, the forecast simulations, which start from analysis states, improve, especially on the first day (37 % average error reduction) and when seiche oscillations are triggered. Since seiches are free barotropic oscillations that depend only on the initial state, their reproduction improves very effectively with data assimilation. Finally, we estimate the periods and the energy of these oscillations by means of spectral analysis, both in the Adriatic Sea, where they have been extensively studied, and in the Mediterranean Sea, where the present documentation is scarce. While the periods are well reproduced by the model even without data assimilation, their energy shows a good improvement when using it.

This paper analyses the variability of the sea level barotropic components in the Mediterranean Sea and their reproduction using a hydrodynamic model with and without data assimilation. The impact of data assimilation is considered both in reanalysis and short-forecast simulations. We used a two-dimensional finite element model paired with an ensemble Kalman filter, which assimilated hourly sea level data from 50 stations in the Mediterranean basin. The results brought about a significant improvement given by data assimilation in the reanalysis of the astronomical tide, the surge, and the barotropic total sea level, even in coastal areas and far from the assimilated stations (e.g. the southeastern Mediterranean Sea). As with the reanalysis simulations, the forecast simulations, which start from analysis states, improve, especially on the first day (37 % average error reduction) and when seiche oscillations are triggered. Since seiches are free barotropic oscillations that depend only on the initial state, their reproduction improves very effectively with data assimilation. Finally, we estimate the periods and the energy of these oscillations by means of spectral analysis, both in the Adriatic Sea, where they have been extensively studied, and in the Mediterranean Sea, where the present documentation is scarce. While the periods are well reproduced by the model even without data assimilation, their energy shows a good improvement when using it.

Extreme sea levels (ESLs) affect coastal ecosystems worldwide. Protection and adaptation strategies rely on the characterization of the extreme's occurrence probability in the future. However, knowledge on the occurrence rate and duration of ESLs is also needed to properly characterize the associated future risk. In this paper, we focus on the Venice lagoon, where a system of storm surge barriers can disconnect the lagoon from the sea to mitigate ESLs. Using long-term (96 years) sea level records, we model occurrence rate and duration of ESLs while accounting explicitly for seasonality and mean sea level rise. While historically ESLs occurred in the winter season, we project a significant increase (up to 10-fold with a mean sea level increase of +100 cm) of the occurrence rate also in the summer season, when disconnections from the sea can have profound impacts on the lagoon's ecosystem. We also predict an increase in ESLs durations up to 200 h, leading to longer disconnections of the lagoon from the sea in the future. Therefore, several adaptation strategies will be needed to limit the adverse effects of storm surge barriers on the lagoon ecosystem.

Large lagoons usually show a salinity gradient due to fresh water tributaries with inner areas characterized by lower mean values and higher fluctuation of salinity than seawater-dominated areas. In the Venice Lagoon, this ecotonal environment, characterized in the past by oligo-mesohaline waters and large intertidal areas vegetated by reedbeds, was greatly reduced by historical human environmental modifications, including the diversion of main rivers outside the Venice Lagoon. The reduction of the fresh water inputs caused a marinization of the lagoon, with an increase in salinity and the loss of the related habitats, biodiversity, and ecosystem services. To counteract this issue, conservation actions, such as the construction of hydraulic infrastructures for the introduction and the regulation of a fresh water flow, can be implemented. The effectiveness of these actions can be preliminarily investigated and then verified through the combined implementation of environmental monitoring and numerical modeling. Through the results of the monitoring activity carried out in Venice Lagoon in the framework of the Life Lagoon Refresh (LIFE16NAT/IT/000663) project, the study of salinity is shown to be a successful and robust combination of different types of monitoring techniques. In particular, the characterization of salinity is obtained by the acquisition of continuous data, field campaigns, and numerical modeling.

Responses of the macrozoobenthic community to an ecological restoration activity in the northern Venice lagoon were studied, within the scope of the project LIFE SEagrass RESTOration aimed at recreating aquatic phanerogam meadows largely reduced in recent decades. Transplants were successful in almost all project areas. Macrozoobenthos was sampled in eight stations before (2014) and after (2015, 2016, 2017) transplanting activities. An increase in abundance and fluctuations in richness and univariate ecological indices (Shannon’s, Margalef’s, Pielou’s indices) resulted during the years. Comparing non-vegetated and vegetated samples in 2017, every index except Pielou’s increased in the latter. Multivariate analysis (hierarchical cluster analysis, MDS, PERMDISP, SIMPER) grouped samples by localization rather than years, with differences between stations due to the abundance of common species. In 2017, results were also grouped by the presence or absence of aquatic plants, with differences in the abundance of grazer and filter-feeding species. Results of ecological index M-AMBI depicted conditions from moderate to good ecological status (sensu Dir.2000/60/EC) with similar fluctuations, as presented by univariate indices from 2014 to 2017. Responses of the macrozoobenthic community were more evident when comparing vegetated and non-vegetated samples, with the vegetated areas sustaining communities with greater abundance and diversity than non-vegetated samples, thus demonstrating the supporting function of aquatic plants to benthic communities.

This paper reviews the state of the art in storm surge forecasting and its particular application in the northern Adriatic Sea. The city of Venice already depends on operational storm surge forecasting systems to warn the population and economy of imminent flood threats, as well as help to protect the extensive cultural heritage. This will be more important in the future, with the new mobile barriers called MOSE (MOdulo Sperimentale Elettromeccanico, Experimental Electromechanical Module) that will be completed by 2021. The barriers will depend on accurate storm surge forecasting to control their operation. In this paper, the physics behind the flooding of Venice is discussed, and the state of the art of storm surge forecasting in Europe is reviewed. The challenges for the surge forecasting systems are analyzed, especially in view of uncertainty. This includes consideration of selected historic extreme events that were particularly difficult to forecast. Four potential improvements are identified: (1) improve meteorological forecasts, (2) develop ensemble forecasting, (3) assimilation of water level measurements and (4) develop a multimodel approach.

Eutrophication represents one of the most impacting threats for the ecological status and related ecosystem services of transitional waters; hence, its assessment plays a key role in the management of these ecosystems. A new multi-index method for eutrophication assessment, based on the ecological index MaQI (Macrophyte Quality Index), the trophic index TWQI (Transitional Water Quality Index), and physicochemical quality elements (sensu Dir. 2000/60/EC), was developed including both driver and impact indicators. The study presents a large-scale implementation of the method, which included more than 100 Italian lagoon sites, covering a wide variability of lagoon typologies and conditions. Overall, 35% of sites resulted in eutrophic status, 45% in mesotrophic, and 25% in oligotrophic status.

We have monitored and analyzed, through remote sensing and ancillary field surveys, the rapid (O(1) year) development of a tidal network within a newly established artificial salt marsh in the Venice Lagoon. After the construction of the salt marsh, a network of volunteer creeks established themselves away from an artificially constructed main channel (with mean and maximum annual headward-growth rates of 11 m/yr and 18 m/yr, respectively). The rapid formation of this system of tidal creeks provides a unique opportunity to test the reliability of a model of tidal network initiation and development, previously proposed by the authors. The restored marsh presents the characteristics of a controlled environment analogous to a large-scale field laboratory, as it allows comparison of the morphologic features of real and simulated network structures under the reasonable assumption of neglecting accretion and deposition processes over the timescales of observation. Our results compare favorably with observational evidence, showing that the model proves reasonably capable of reproducing the main features of the actual channel-network patterns. The model reproduces statistical network characteristics of eco-morphodynamic and hydrodynamic relevance and captures the dominant modes of the network-incision process. © 2007 Elsevier B.V. All rights reserved.