NH5.4

Sea defences such as vertical breakwaters are critical marine infrastructures that safeguard communities and properties behind the structure from coastal flooding arising from wave-induced overtopping. In the context of future climate change, the frequency and magnitude of extreme wave events that threaten the functional performance of these defense lines and cause flooding is expected to increase. The capacity to reliably predict mean overtopping rates and individual overtopping volumes at these structures is therefore critical in deriving the tolerable limits of overtopping hazards. Common approaches for predicting overtopping rates at sea defences (such as vertical seawalls) have typically relied on physical, empirical and numerical methods. Notwithstanding the accuracy of these approaches, they are often complex and determining reliable predictions requires considerable expertise and time. Of late, the use of soft computing techniques such as Machine Learning (ML) algorithms have been employed to predict overtopping rates with comparable accuracy to the more common approaches. A significant advantage of ML methods are associated with their straightforward construction that can efficiently use existing databases, such as EurOtop 2018, in their training and testing to produce satisfactory results.

Research to date has, for the most part, focused on the application of  ML algorithms (such as decision tree and artificial neural network) to predict overtopping rates at sea defenses.  However,  the trade-offs of these methods (e.g., altered performance from missing values in the database) have not yet been investigated. Here, we investigate the application of two advanced ML methods, a Gradient-Boosting based Decision Tree (GBDT), and a feed forward based Artificial Neural Network (ANN) framework. Both algorithms were trained and tested using the CLASH database to predict mean overtopping rates at seawalls.  The CLASH database for this study comprises more than 1500 overtopping entries and a train-test split of 70% and 30%, respectively, was applied. Hyperparameter tuning was performed on the GBDT algorithm to refine the outputs. A provision was included in the ANN algorithm for it to detect, check and impute missing values as ANN does not implement when there is missing values and also imputing for a large number of missing values may negatively impact the performance of GBDT models.  

Results of this study revealed that the GBDT algorithm, overall, performed marginally better the ANN algorithm. The root-mean-squared errors (RMSE) for the GBDT and ANN models were 0.50 and 0.52, respectively. The Pearson R values for the GBDT and ANN algorithms were 0.92 and 0.90, respectively, confirming a strong correlation between the predicted and measured overtopping discharges for methods. Additionally, by permutation importance analysis, the GBDT algorithm was shown to be capable of identifying influential overtopping parameters, with significant wave height and crest-freeboard being shown to be significant in this study.  

Keywords: Machine Learning, Wave Overtopping, Climate Resilience. Climate Change

How to cite: Habib, M. A., O'Sullivan, J., and Salauddin, M.: Comparison of machine learning algorithms in predicting wave overtopping discharges at vertical breakwaters, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-329, https://doi.org/10.5194/egusphere-egu22-329, 2022.

Coastal flood risk is a major global challenge facing current and future generations. Indeed, this risk is expected to increase over the next several decades due to the changing climate, increased urbanization within flood-prone areas, loss of natural coastal defenses, and underground resource extraction, among other global factors. A number of risk reduction strategies have been posited as methods of mitigating the deleterious impacts of coastal flooding and investigated thoroughly through several existing small-scale applications around the world.

On the global scale, however, efforts to model the effects of such risk reduction strategies in the future are rather limited. Most global modeling efforts that have been undertaken typically examine the potential risk reductions of structural measures (e.g., dykes and levees). And while some initial progress has been made in recent years on assessing alternative risk reduction strategies, the majority of this work still looks to quantify the effects of individual strategies alone. In reality, the hybridization of risk reduction strategies may be the most cost effective or environmentally feasible pathway forward for different segments of society.

We look to quantify the risk reductions expected from employing multiple strategies at once. Within the same global flood risk modeling framework, we model the dry-proofing of urban assets, restriction of future development within flood-prone zones, and conservation of foreshore vegetation. In addition to modeling these strategies individually, we determine what risk reductions are possible when they are hybridized, both with each other and also structural measures. By using a disaster risk framework – risk defined as a product of hazard, exposure, and vulnerability – and a benefit-cost analysis that measures financial and human impacts of each strategy, we determine expected levels of risk reduction for different regions of the world. These results are available for various points in the future under various representative concentration pathway and shared socioeconomic pathway combinations. Further, we demonstrate which (combinations of) strategies may be able to achieve similar levels of overall risk reduction that would be anticipated with solely structural measures. This work not only demonstrates how the envelope of potential options can be expanded for decision makers addressing coastal flood risk, but also can be used as the foundation of future risk flood reduction assessments that incorporate more options than those examined here.

How to cite: Mortensen, E., Tiggeloven, T., Haer, T., Eilander, D., Muis, S., Sperna Weiland, F., le Bars, D., Aerts, J., de Ruiter, M., and Ward, P.: Quantifying the effects of employing multiple disaster risk reduction strategies in a coastal flood risk context on the global scale, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-602, https://doi.org/10.5194/egusphere-egu22-602, 2022.

The Mediterranean basin occasionally hosts small intense vortices that evolve in tropical-like cyclones, also called “medicanes”. Although they are more intense over the sea, their landfall may be associated with destructive extreme events, such as heavy precipitation, windstorms, flooding, and marine storminess. On 18 September 2020, medicane Ianos hit the western coast of Greece resulting in flooding and severe damages at specific coastal locations. In this work, we aim at evaluating the impact of medicane Ianos on the sea state and water level through the use of numerical simulations. We applied a coupled wave-current model to an unstructured mesh representing the whole Mediterranean Sea, with a grid resolution varying from 15 km in the open sea to 2 km along the predetermined cyclone path, and up to 500 m along the landfall area (the western Greek coast). In order to investigate the uncertainty of the ocean model derived by the atmospheric modelling of such an intense event, we performed an ensemble of simulations using several coarse (10 km) and high-resolution (2 km) meteorological forcings from different mesoscale models. Also, results obtained using ERA5 reanalysis or IFS analysis are considered as a benchmark. The multi-model approach allows us to assess how the uncertainty propagates from meteorological fields to the ocean quantities and the subsequent coastal impact. The model performance was evaluated against observations retrieved from fixed monitoring stations and satellites. The numerical results show a large spread of the simulated sea conditions. Due to the rugged and complex coastline,  extreme sea levels are localized at specific coastal sites. The ensemble results were combined for proving a set of indicators of the potential impact of such an intense event, in order to assess the effectiveness of this multi-model ensemble approach. This work is part of the COST action CA19109 MEDCYCLONES (European Network for Mediterranean Cyclones in weather and climate) and of the Interreg Italy-Croatia STREAM project (Strategic development of flood management, project ID 10249186).

How to cite: Bajo, M., Ferrarin, C., Pantillon, F., Davolio, S., Miglietta, M., Flaounas, E., and Carrió, D.: Assessing the coastal impact of medicane Ianos through a wave-current model forced by a multi-model atmospheric ensemble, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-844, https://doi.org/10.5194/egusphere-egu22-844, 2022.

Atoll islands are among the places most vulnerable to climate change due to their low elevation above mean sea level. Even today, some of these islands suffer from severe flooding generated by wind-waves, that will be exacerbated with mean sea-level rise. Wave-induced flooding is a complex physical process that requires computationally-expensive numerical models to be reliably estimated, thus limiting its application to single island case studies. Here we present a new model-based parameterisation for wave setup and a set of numerical simulations for the wave-induced flooding in coral reef islands as a function of their morphology, the Manning friction coefficient, wave characteristics and projected mean sea level that can be used for rapid, broad scale flood risk assessments. We apply this new approach to the Maldives to compute the increase in wave hazard due to mean sea-level rise, as well as the change in island elevation or coastal protection required to keep wave-induced flooding constant. While future flooding in the Maldives is projected to increase drastically due to sea-level rise, we show that similar impacts in nearby islands can occur decades apart depending on the exposure to waves and the topobathymetry of each island. Such assessment can be useful to determine on which islands adaptation is most urgently needed.

How to cite: Amores, A., Marcos, M., Le Cozannet, G., and Hinkel, J.: Coastal flooding and mean sea-level rise allowances in atoll island, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1595, https://doi.org/10.5194/egusphere-egu22-1595, 2022.

The Thai-coast project aims to improve scientific understanding of the vulnerability of Thailand's shoreline and coastal communities to hydro-meteorological hazards, including storms, floods and coastal erosion, under future climate change scenarios. Coastal erosion and flooding affect more than 11 million people living in Thailand’s coastal zone communities (17% of the country's population). Each year erosion causes Thailand to lose 30 km² of coastal land (Department of Marine and Coastal Resources (DMCR), Ministry of Natural Resources and Environment). Sea level is predicted to rise by 1 metre in the next 40 -100 years, impacting at least 3,200 km² of coastal land, through erosion and flooding, at a potential financial cost to Thailand of 3 billion baht [~ £70 million; Office of Natural Resources and Environmental Policy and Planning]. We address an urgent need to enhance the resilience and adaptation potential of coastal communities, applying scientific research to inform more robust and cost-effective governance and institutional arrangements.

The Thai-coast project has established causal links between climate change, erosion and flooding and is using this information to assess natural and social processes’ interactions to enhance coastal community resilience and future sustainability. We focus on two study areas, Nakhon Si Thammarat Province and Krabi Province, selected on the basis of DMCR coastal erosion data and with contrasting natural and socio-economic characteristics. Using a multidisciplinary approach, we integrate climate science, geomorphology, socio-economics, health and wellbeing science and geo-information technology to improve understanding of hydro-meteorological hazard occurrence, their physical and socioeconomic, health and wellbeing impacts on Thailand's coastal zone and the ways in which governance and institutional arrangements mitigate their impact. Examining future scenarios of climate change hydrometeorology, coastal landform and land use change scenarios we have assessed and modelled impacts (erosion, flooding, coastal community vulnerability), and population and community adaptation. Our collaborative team of natural and social scientists, from UK, US and Thai research institutions work closely with Thai Government and UK and Thai industry partners to ensure that results are policy and practice-relevant.

Key findings indicate that erosion and accretion rates are more dramatic on mangrove coastlines (-34.5 and 21.7 m/year) compared with sandy coastlines (-4.1 and 4 m/year). Modelled future climate changes indicate more extended and severe floods in Southern Thailand with the risk of flash floods increasing significantly. Socio-economic resilience is generally higher in more urbanized areas but there are greater variations amongst subdistricts. Different communities within the coastal regions have different levels of resilience and adopt different coping strategies when faced with emergency situations. When physical and socio-economic indices are compared, Krabi Province has a higher level of physical vulnerability than Nakhon Si Thammarat (NST), whilst NST is has a higher level of socio-economic vulnerability than Krabi.  When physical and socio-economic factors are combined to generate the Coastal Vulnerability Index (CVI), the results show that the two provinces have relatively comparable CVI despite the underlying variability in physical and socio-economic resilience.

How to cite: Moses, C., Nakhapakorn, K., Ward, R., Wang, Y., Langkulsen, U., Cheewinsiriwat, P., Chamchan, C., Boonmanunt, S., Alamirew, N., Barlow, J., Curoy, J., Dudia, J., and Martin, D.: Coastal Vulnerability, Resilience and Adaptation in Thailand., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2026, https://doi.org/10.5194/egusphere-egu22-2026, 2022.

Combination estuarine flooding is driven by extreme sea-levels and river discharge occurring at the same time, or in close succession. We hypothesise the drivers of flooding rarely occur independently and operate and co-operate at sub-daily timescales. There is a need to accurately capture fluvial and sea-level interactions at a sub-daily timescale to understand the relative timing and duration of compound flooding hazards in estuaries to support forecasts and warnings, emergency response and long-term management plans. This research analyses the co-cooccurrence of extreme sea-level and river discharge events using historic river flow data from 126 gauges and tide gauge data from 27 locations across Britain, which were analysed to identify estuaries that are susceptible to compound flooding events. Daily mean and maximum river discharge, and river discharge at 15-minute frequency were analysed to identify extreme peaks in the records, and corresponding skew surge values identified within a time window based on average hydrograph duration. Results show that daily mean river discharge underestimates peaks in the record and does not accurately capture hydrograph behaviour. This research is the first time that 15-minute frequency river discharge data has been used to characterise hydrograph behaviour and identify i) peaks over threshold; ii) top 500 peaks and corresponding skew surges to determine dependence based on Kendall’s rank correlation and the number of occurrences between extreme drivers each storm season (May-June). Different methods of data selection and identification of peak river discharge events generates different results. The duration of river discharge peaks, total water level, lag time, and overlap between peaks is calculated to identify locations where co-occurrences are likely to happen. The results identify a clear east-west split in dependence, with gauges on the west coast of Britain showing stronger correlations. There are more co-occurrences of extreme sea and fluvial levels each storm season in Northwest England and West Scotland. Estuaries that are most susceptible to compound events based on the Kendall’s rank correlation τ, seasonal occurrences, and potential for river discharge and sea-level peaks to overlap based on duration and lag time are identified. The results identify 46 gauges that are highly susceptible to compound flooding, notably the Rivers Lune and Eden, with strongest correlation coefficients and highest number of seasonal occurrences. The results highlight spatial variability to the sensitivity of estuaries to combination flood hazard, and the impact of future changes in flood risk that are unresolved currently in management plans.

How to cite: Lyddon, C., Robins, P., Lewis, M., Barkwith, A., Haigh, I., Vasilopoulos, G., and Coulthard, T.: Historic spatial patterns of compound flood events in UK estuaries, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2999, https://doi.org/10.5194/egusphere-egu22-2999, 2022.

Low-standing deltas are a home for half a billion of people that are extremely vulnerable to sea level variations. Justly only in the Ganges-Brahmaputra-Meghna (GBM) delta, over 100 million people suffer every year from floods due to storm surges and monsoons exacerbated by the ongoing sea level rise. The aim of our study is to re-assess the variations of extreme sea levels (ESL), as well as the interactions between the relative sea level rise and the ESL in the GBM delta. A set of hourly tide gauge records from the Bay of Bengal, especially from the low-lying Bangladesh's coastal area, has been used to evaluate ESL changes over the past decades. We focus on the variations of extreme high waters and their components (surge and tide), and on the interaction between them by applying advanced methods of statistical extreme values analysis. An assessment of temporal changes in storm surge duration and their intensity was obtained in the framework of a rigorous re-analysis of the past storm surge events.

How to cite: Mussa, A., Becker, M., and Karpytchev, M.: Changing extreme sea levels in the Ganges-Brahmaputra-Meghna delta, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3052, https://doi.org/10.5194/egusphere-egu22-3052, 2022.

Sea level time series of up to 19 years length, recorded with one-minute sampling interval at 18 tide gauges, evenly distributed along the eastern and western coast of the Adriatic Sea, were analysed in an attempt to quantify hazard related to the Adriatic Sea level extremes.  Prior to analysis, quality control and pre-processing were done: all unphysical spikes and outliers were removed; shorter gaps were interpolated, and time series were de-tided.

For each tide gauge, two types of sea level extremes were defined and extracted from residual time series: (1) extremes related to storm surges, i.e. extremes that dominate the total residual signal; (2) extremes related to meteotsunamis, i.e. extremes that dominate the high-frequency signal (T < 2 h). The two types of extremes were analysed in detail and following conclusions were reached: (1) on average, extremes related to storm surges are stronger than those related to meteotsunamis; (2) nonetheless, there are stations at which two types of extremes are of almost comparable strength (e.g. Vela Luka, Stari Grad); (3) high-frequency oscillations can contribute significantly (up to 30% of residual signal) to the storm surge related extremes  at most areas; (4) extremes related to storm surges mostly happen from October to January while the second type of extremes happen more throughout the year, with peak appearances of the strongest ones from May to September. 

Conclusively, for both types of episodes, it has been shown that the high-frequency signal contributes significantly to total extremes and that analysis of sea level time series sampled at a one-minute time interval is a prerequisite for proper analysis of hazards related to sea level extremes.

How to cite: Ruić, K., Šepić, J., Mlinar, M., and Međugorac, I.: Storm surges and meteotsunamis of the Adriatic Sea: interplay and quantification of hazard level, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4452, https://doi.org/10.5194/egusphere-egu22-4452, 2022.

Tsunami disasters can cause infiltration of seawater into coastal unconfined aquifers over large scales, which would induce long-term salinization of groundwater resources. According to the report by Cabinet Office of Japan (2011), an earthquake of 9.0 M_w will very possibly occur along the Nankai Trough during the years 2011-2030. Under the worst tsunami scenario, the coastal area of Niijima Island, Japan, will be inundated by seawater up to about 15 m a.m.s.l. (above mean sea-level) (Tokyo Disaster Management Council, 2013). As a result, groundwater, the only freshwater source for the island, will face severe salinization. In order to assess the risk of groundwater salinization under such scenario, a 3-D numerical model of Niijima Island was developed using the HydroGeoSphere code which can solve coupled surface-subsurface flow processes.  The results showed that the simulated early stage seawater ponding at the land surface was controlled by the type (DEM or DSM) and spatial resolution of topographic data  used in the model. This suggested that high-resolution topographic data considering the existence of artificial structures should be preferred for modeling seawater ponding and infiltration after tsunamis in urbanized areas. Furthermore, compared with the baseline case, the reduction in hydraulic conductivity and the Manning’s roughness coefficient in places of buildings and roads reduced the amount of seawater infiltration. The results highlighted the land surface conditions as an important indicator for the vulnerability of groundwater resources to tsunami-induced seawater infiltration.

How to cite: Liu, J., Brunner, P., and Tokunaga, T.: Modeling seawater flooding, ponding, and infiltration processes under future tsunami scenarios: A case study at Niijima Island, Japan, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4643, https://doi.org/10.5194/egusphere-egu22-4643, 2022.

Lowland coasts, accounting for ca. 30% of the global coastline, are significantly threatened by the climate change, related sea-level rise and enhanced storminess. However, the role of key factors controlling the frequency and extent of extreme storm surges of inundation regime are not yet fully understood. In the present research we seek for the answer what are factors governing the susceptibility of the coast to storm surge flooding: is it coastal landforms development, storminess or rising sea-level?

            The southern Baltic Sea coast presents an ideal target for the research on the frequency and intensity of catastrophic storm surge flooding as it is nontidal/microtidal sea, where major water level fluctuations are related to well-documented past sea-level changes and storm surge floodings. Moreover, it is located in the area highly sensitive to latitudinal shifts in North Atlantic Oscillation and changes of the westerly storm tracks. Furthermore, the southern Baltic coast has recently been identified as the region where the storm surge flooding overtopping coastal barriers is one of the highest in the world and is expected to increase in the near future together with the climate change.

             We documented the longest to date, high-resolution sedimentary succession from the Polish coastal wetland located at Mechelinki, Puck Bay within the Gulf of Gdańsk at the southern Baltic sea coast. There, high-resolution records of extreme storm surge flooding of inundation regime within two periods: 3.6-2.9 ka BP and from ca. 0.7 ka BP until present, are preserved. The studied wetland succession, including sedimentary archive of storm surges, has been analyzed by sedimentological (grain size, loss-on-ignition, micromorphology), geochronological (¹⁴C, ²¹⁰Pb, ¹³⁷Cs), geochemical (XRF), mineralogical (heavy minerals) and micropaleontological (diatoms) methods. The results indicated that both periods were characterized by high-frequency storm surge flooding in order of 1.3 – 4.2 events per century. They are correlated to widely recognized enhanced storminess periods in NW Europe and took place during both rising and fluctuating sea levels. Our results show that the storm surge driven coastal inundation frequency and extent largely depend on the development of coastal barriers (e.g., beach ridges). Thus, in the context of the future coastal storm surge hazard, the protection of existing coastal barriers should be the prime concern.

The research project CatFlood is funded by National Science Centre, Poland, OPUS grant nr: 2018/29/B/ST10/00042

How to cite: Leszczynska, L., Karl, S., Damian, M., Robert, J., Mikołaj, K., Przemysław, N., and Witold, S.: Major controls on storm surge flooding: sea-level rise, climate or coastal landforms?  Insights from the coastal sedimentary record of southern Baltic Sea, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6805, https://doi.org/10.5194/egusphere-egu22-6805, 2022.

Without adaptation, coastal erosion and flooding are projected to significantly increase during the 21^st century due to sea-level rise (SLR). Yet, many important coastal practitioners have limited knowledge of their exposure to future sea-level rise, which prevents them from taking informed adaptation decisions.  Here, we quantify the exposure of the coastal land heritage owned by the French Conservatoire du Littoral (CdL), the French coastal conservation agency, over the metropolitan France, which protects 1,450km (13%) of the coastline in France. This updates a previous assessment performed in 2006, since when both sea-level projections and land area of the CdL have changed (Clus-Auby et al., 2006). Ultimately, this assessment informs the land acquisition strategy of the CdL, in order to review and adapt its long term strategy by aiming to acquire in the next decades the “shores of tomorrow” and ensure its primary mission: the conservation of coastal natural shorelines and emblematic landscapes for the benefit of future generations.

We focus on three types of land areas:

• The protected area, which is the land and the real estate already owned by the CdL;
• The authorized perimeter, which is the area that the CdL is currently already authorized to acquire;
• The 2015-2050 Strategy, which identifies areas that are considered for future acquisitions, in order to meet the strategic objective of protecting 33% of the coastline up to 2050.

Change in exposure of these lands are quantified by a cross-analysis between these CdL land assets on the one hand, and flooding and erosion prone areas under various SLR scenarios and horizons on the other hand. More specifically, the flood prone areas are calculated as the land area below the highest astronomical tide level plus a SLR elevation scenario (ranging from 0 to 4 m) and rely on high resolution (1 m) LIDAR data (bathtub approach). Erosion projections make use of empirical erosion models constrained by historical records of shoreline position and consider SLR using the Bruun rule.       

At the scale of metropolitan France, we find that the degree and evolution of the land exposure strongly varies with regions. For instance, in French Brittany, for present conditions (i.e. SLR at 0 m), flood prone area cover less than 20% of the protected area and increase linearly of ~5% per m of SLR. Hence under the highest SLR estimate of the AR6 in 2100 (SSP5-8.5), exposure of protected area only increase by a few % for this region. Conversely, for the same time horizon, the Western French Mediterranean coast shows a much larger increase of ~20% (SSP1-2.6) to ~50% (SSP5-8.5) of the protected area exposure. Overall, our results reveal that land area exposure change is more sensitive to SLR increases in the range 0-1 m than SLR increases beyond 2 m.

Clus-Auby, C., Paskoff, R. and Verger, F., 2006. Le patrimoine foncier du Conservatoire du littoral et le changement climatique: scénarios d'évolution par érosion et submersion. In Annales de géographie (No. 2, pp. 115-132). Armand Colin.

How to cite: Thiéblemont, R., Le Cozannet, G., Rohmer, J., Quique, R., Guidez, R., Negulescu, C., Philippenko, X., and Privat, A.: Exposure of coastal land owned by the French Coastal Conservation Agency to sea-level rise until 2150., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7687, https://doi.org/10.5194/egusphere-egu22-7687, 2022.

Sea level rise (SLR) increases the likelihood of storm surges by shifting their frequency distribution to higher base levels. Shallow lagoons are located along many coasts, providing natural protection against storm surges by significantly reducing the surge heights inside the lagoons compared to the open coast.

In this study, we investigate the effect of SLR on storm surge heights by using a numerical model of the Western Baltic Sea with a resolution of 200 m. We find that SLR linearly increases storm surge heights at most areas of the open Western Baltic Sea coast, e.g., a storm surge of one meter height in the present time would increase to 1.2 m height at an SLR of 20 cm. For shallow lagoons, on the other hand, the results suggest surge height increases of up to 30% additional to SLR, e.g., at an SLR of 20 cm, the surge height inside the lagoon would increase to 26 cm. We investigate this behavior in further detail with a box model to study the parameter space using the following lagoon parameters: lagoon surface area, depth and width of the connection to the open water, friction, and varying surge shapes and heights.

We find that the increase is largest for lagoons where the ratio of the width of the connection to the area of the lagoon is close to ~10⁻⁵ m⁻¹. The additional surge height decreases with increasing depth of the connection. We further find that surge height increases with surge height itself, e.g., higher surges will increase more in the future than lower surges. We find increases up to 30% for lagoons in the Baltic Sea and for lagoons in the Gulf of Mexico up to 10%.

In summary, our results highlight that additional (non-linear) surge height increase needs to be considered when evaluating and planning future coastal protection measures in shallow coastal lagoons.

How to cite: Lorenz, M., Arns, A., and Gräwe, U.: Sea Level Rise Weakens the Natural Protection against Storm Surges in Shallow Lagoons, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7902, https://doi.org/10.5194/egusphere-egu22-7902, 2022.

Climate change and its consequences on coastal erosion, flooding and water quality are becoming a major concern for a significant percentage of littorals in the world. This issue is particularly challenging for gentle-sloping sandy coasts which are vulnerable to slow and continuous changes related to rising sea-levels and to extreme storm surge and wave events.

Here we present a multidisciplinary research combining satellite image with machine learning and GIS spatial analysis tools to analyze coastal erosion risk in the Venice shoreline over the period 2015-2019. Firstly, an advanced image preprocessing was performed on satellite images (e.g. co-registration, colors normalization) to prepare the input dataset. Secondly, different supervised and unsupervised machine learning classification methods were tested to accurately define shoreline position by recognizing land-sea areas in each image and the Digital Shoreline Analysis System (DSAS) tool in ArcGis was applied to evaluate the net shoreline movement overtime. Finally, a GIS-based Bayesian Network (BN) approach was developed, to evaluate the probability and uncertainty of coastal erosion risks, and the cascading effects on water quality variation, against multiple ‘what-if’ scenarios related to extreme sea levels and wave conditions under climate change for the period 2040-2050.

According to the spatial resolution of the available data for the case study of Venice (Veneto Region-Italy), the proposed BN-model was trained and validated by considering atmospheric, oceanographic and water quality parameters over the 2015-2019 timeframe, allowing to capture local-scale coastal progression and related driving forces.

Results showed general shoreline stability in the considered reference timeframe. However, the high presence of anthropogenic structures (e.g. jetties, breakwaters) induces the formation of well-delimited hotspots of erosion/accretion. Future trends from the BN-based scenario analysis, according to RCP8.5 scenario within the 2040-2050 period, showed that, even if in minor extent, water quality parameters (i.e. suspended matter, diffuse attenuation) will increase. On the other hand, shoreline evolution trend will face a decreasing probability of the stable class, which in turn will increase instability.

Despite constraints posed by the spatial resolution of the available data for the investigated case, the outcomes of the performed assessment represent valuable information to support adaptive policy pathways in the context of Integrated Coastal Zone Management and Disaster Risk Reduction in the Venice coastal area.

How to cite: Dal Barco, M. K., Pham, H. V., Fogarin, S., Zanetti, M., Cadau, M., Harris, R., Rubinetti, S., Rubino, A., Zanchettin, D., Barbariol, F., Benetazzo, A., Furlan, E., Torresan, S., and Critto, A.: Evaluating climate change and coastal erosion risks on the Venice coastline: a Machine Learning approach supporting multi-risk scenario analysis, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8105, https://doi.org/10.5194/egusphere-egu22-8105, 2022.

The methods used to generate global to local sea-level projections have evolved significantly since the publication of the first set of UK national sea-level projections in 2009 (UKCP09; Lowe et al, 2009), including improved process understanding, ice-sheet modelling advances, the use of emulators and development of high-end scenarios. The UK Climate Projections in 2018 (UKCP18) presented local mean sea-level projections for the UK coastline for the 21st century based on CMIP5 models, with an emulator-based methodology to provide traceable extended projections to 2300 (Palmer et al, 2018). First, we present the evolution of UK sea-level projections since UKCP09 and discuss how these projections have been used by UK stakeholders. Second, we compare UKCP18 global and local sea-level projections with those recently presented in the IPCC Sixth Assessment Report (AR6). We find that although the likely range projections (i.e the characterisation of the central two-thirds of the distribution) are broadly similar, larger AR6 contributions from oceanographic processes and the Antarctic ice sheet give rise to discrepancies at selected tide gauge locations of up to 30%. In AR6, high-end scenarios for sea-level rise were presented as low-likelihood high-impact storylines. These offer some comparison with the high-end H++ range presented at 2095 for UKCP09, showing reasonable agreement for London. Future UK sea-level projections would benefit from updated scenarios for high-end sea-level change which extend beyond 2100 as well as an improved understanding of observed sea-level change drivers. This will enhance the usability of these local sea-level projections by UK stakeholder groups and coastal decision-makers.

How to cite: Weeks, J. H., Harrison, B. J., and Palmer, M. D.: The evolution of UK sea-level projections, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9605, https://doi.org/10.5194/egusphere-egu22-9605, 2022.

Forecasting the coastal response to climate change is a complex problem due to the nonlinear interplays at multiple scales between the different hazards, i.e. flooding and erosion. To handle this challenge, the use of simple and computationally efficient, yet accurate tools is required. The combination of reduced-complexity shoreline modelling and efficient physics-based flood spread models is an appropriate way to project coastal risks under climate scenarios, being a balanced solution regarding computational time and accuracy. We present a methodology comprised by an efficient wave downscaling methodology, the recently developed shoreline evolution model IH-LANS (Alvarez-Cuesta et al., 2021a), flood-spread modeling and an ensemble treatment of climate-related uncertainty as in (Alvarez-Cuesta et al., 2021b) to forecast the evolution of coastal risk. The methodology is applied at a vulnerable low-lying coastal area in Murcia, Spain and it allowed to highlight the coastal hotspots and the definition and evaluation of adaptation measures. This application strengthen the suitability of reduced-complexity modeling to guide decision making in complex coastal settings.

Alvarez-Cuesta, M., Toimil, A., & Losada, I. J. (2021a). Modelling long-term shoreline evolution in highly anthropized coastal areas . Part 1 : Model description and validation. Coastal Engineering, 169(July), 103960. https://doi.org/10.1016/j.coastaleng.2021.103960

Alvarez-Cuesta, M., Toimil, A., & Losada, I. J. (2021b). Modelling long-term shoreline evolution in highly anthropized coastal areas . Part 2 : Assessing the response to climate change. Coastal Engineering, 168(July), 103961. https://doi.org/10.1016/j.coastaleng.2021.103961

How to cite: Álvarez-Cuesta, M., Toimil, A., and Losada, I.: Reduced-complexity modeling as a valuable tool for studying the coastal impacts of climate change, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11246, https://doi.org/10.5194/egusphere-egu22-11246, 2022.

Climate change is posing growing risks to coastal areas exacerbating the problems these systems already face. One of these problems is coastal erosion, which happens at two different time scales. On one hand, mean sea-level rise leads to the chronic loss of beach surface; on the other, the combined effect of waves, storm surges and tides causes episodic erosion, which due to this increase in mean sea level will become more frequent. In light of this, while some systems will be able to undergo a landward retreat, others will suffer from coastal squeeze, which occurs when an eroding coast approaches seawalls or resistant natural cliffs, leading to adverse impacts to both environment and society. Coastal erosion risks need to be addressed with adaptation, and this is particularly challenged by the high uncertainty in climate change-related erosion forcing conditions. Expanding scientific knowledge of uncertainty treatment in climate-change coastal erosion projections is thus key to effective decision making (Toimil et al., 2021a). Here, we show progress on decomposition, factorisation, attribution, and visualisation of the uncertainty sources involved in shoreline change projections, which arise from climate-change scenarios, climate models, and erosion models, and cascade through the complete impact modelling process. This uncertainty accumulates in coastal erosion estimates, is further inherited by erosion risks and can highly influence adaptation planning (Toimil et al., 2021b).

Toimil A, Camus P, Losada IJ, Álvarez-Cuesta M (2021a) Visualising the uncertainty cascade in multi-ensemble probabilistic coastal erosion projections. Front. Mar. Sci. 8:683535.

Toimil A, Losada IJ, Hinkel J, Nicholls RJ (2021b) Using quantitative dynamic adaptive policy pathways to manage climate change-induced coastal erosion. Clim. Risk Manag. 33, 100342.

How to cite: Toimil, A., Losada, I. J., and Álvarez-Cuesta, M.: On the need of considering the uncertainty cascade for decision making on climate-change adaptation to coastal erosion, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11419, https://doi.org/10.5194/egusphere-egu22-11419, 2022.

Climate change effects on wave regime are affecting Sardinian beaches and coasts. Sardinia island is in the centre of western Mediterranean basin, and its coasts are mainly under two main opposite winds, the mistral and the sirocco, which affect north-west and south-east coasts of the island respectively. We analysed historical wind intensities and wave heights in Sardinian coasts, for detecting historical trends which can explain the alarming increase of coastal erosion of the island. In this sense, we investigated two case studies located in the two opposite quadrants of Sardinia, the Gulf of Alghero and in the Gulf of Cagliari that are in the North-West and South-East quadrants, respectively. For the wind analysis we used the values of speed and direction of the anemometer stations of Alghero and Elmas (Cagliari), for which long series of data are available. The wind most frequently detected by the station of Elmas is the sirocco, with a linear growth for the period of analysis (1943-2021) with higher values of 3, 4 and 5 m/s for 2 consecutive days of sirocco. On the other hand, in Alghero, for 2 consecutive days of mistral, there is a linear decrease for the analysis period (1957-2021) with values greater than 3, 4 and 5 m/s. For the analysis of wave data in the quadrants of Sardinian coasts we compared the ECMWF, the Copernicus and the SIMAR database. The direction and wave height values from the models were validated with observed data of the buoy wavemeters in the Gulf of Alghero and in the Gulf of Cagliari, which data are available for shorter periods.to. Annual maximum significant wave heights are increasing in both the Gulf of Cagliari and the Gulf of Alghero. In particular, the increase in wave heights is more evident in the last two decades (from 1998 to 2019). The increase of the average sea level and the intensification of extreme events in the South-East quadrant of Sardinia is accelerating the erosion of the wonderful beaches of Nora, Capoterra, Sarroch and Poetto in the Gulf of Cagliari, which reduction was dramatic (up to 70 m). Climate change effects on wind frequency and intensity and wave can affect island tourism, an important source of income for Sardinia, and in the extreme cases is leading to damage to housing, alarming resident population.

How to cite: Piras, R., Montaldo, N., and Corona, R.: The Increase of Sardinian Coastal Erosion and the Historical Climate Change Effects on Wind and Wave Height, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11530, https://doi.org/10.5194/egusphere-egu22-11530, 2022.

Ho Chi Minh City (HCMC) is characterized by rapid urbanization, socio-economic transitions and significant climate/environment influences at a low lying flood prone area, which in combination results in more frequent and intense floods. Accordingly, flood coping measures and adaptation actions have been carried out by various stakeholders for years, especially the diverse responses at household level. However, there is a lack of substantial understanding on the profiles of different households regarding their flood response measures, the driving factors, particularly with regards to dynamically changing socio-economic groups and the question of individual vs. collective action for flood risk reduction. Based on a large scale household survey conducted in HCMC in September and October 2020, the study classifies different flood coping/adaptation measures. A cluster analysis of multiple factors is carried out to clarify the major factors and to identify the features of households and their networks in each cluster. Specific data analysis indicates: 1) Majority of local people don’t receive external supports, due to the fact of moderate flood events and that they subjectively don’t concern much to the impacts (have got used to floods). 2) The most vulnerable groups did receive various supports, which indicates the existence of a basic flood-safe system in HCMC. 3) Long-term adaptation measures are not often applied, because vulnerable groups are not able to while rich people don’t need to. Findings of the study help to better understand the local status of flood responses against the backdrop of underlying socio-economic transformations.

How to cite: Yang, L. E. and Garschagen, M.: Understanding household-level flood responses in Ho Chi Minh City: who acts what and why?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12142, https://doi.org/10.5194/egusphere-egu22-12142, 2022.

Common structure to protect the coastline against wave impact and erosion are seawalls. Whereas seawalls are effective at preventing coastal erosion during storm events, the wave energy is not dissipated. Waves are propagation on a sloping beach towards the seawall, where they interact with the vertical structure. Resulting from the incident and reflected waves, downward directed vertical velocity components cause a region of increased bed shear stress at the toe of the seawall, ultimately leading to local scour. Future climate change induced sea level rise and increased wave heights create a need for estimating possibly larger scour holes around seawalls which can threaten their structural stability. In this contribution, a solution strategy for the prediction of seawall scour scenarios for different water levels and wave conditions is presented. The high-resolution NavierStokes solver of the open-source hydrodynamics framework REEF3D is used to calculate the waves impacting the seawall. The interface capturing level set method for the free surface makes it possible to resolve the complex wave pattern in front of the seawall including the breaking of individual waves. Based on the near-bed flow conditions, the bed shear stress is calculated. Then bed load and suspended sediment transport formulations are numerically solved. Erosion and deposition of the sediment is calculated with Exner’s equation for the conservation of sediment mass. The morpho-hydrodynamic solver requires relatively large computational resources and is suitable for the near-field solutions. In order to predict realistic wave conditions at a given coastline location, more efficient large-scale wave models are required. A coupling strategy for a fully nonlinear potential flow model to the Navier-Stokes solver is presented. The numerical modeling results are validated against measured wave and sediment data from laboratory experiments.

How to cite: Bihs, H., Wang, W., Ehlers, R., and Kamath, A.: A Numerical Modeling Approach to Capture Erosion around Coastal Protection Structures under Wave Impact, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12987, https://doi.org/10.5194/egusphere-egu22-12987, 2022.

Adaptation to sea-level rise (SLR) will be necessary to protect people at risk from flooding due to a combination of tide, surge and SLR in the future. This adaptation commitment requires adequate time and resources to prepare for the impacts of SLR that are expected within this century and beyond (here until 2150). In this study, we address the question of “when” in addition to “how much” adaptation to SLR is needed. We use a scenario-neutral approach to assess the amount of people at risk from flooding under different SLR magnitudes. We combine this scenario neutral approach with SLR projections for the SSPs in AR6 and population growth scenarios in the coastal zone to identify the timing, in which the number of additional people affected by SLR alone or in combination with a 100-year storm event will exceed a set of thresholds. The comparison of the timing for different SSPs demonstrates that it is rather a question of “when” than “if” these thresholds will be exceeded. Some countries will need to adapt to SLR within the next few decades to prevent an additional 1–5 million people from becoming affected by flooding. Other countries have more time for adaption but will face a rapid increase in the number of people at risk from flooding beyond 2100. Combining SLR impacts with projected population change further increases the number of people at risk in the middle of this century for most SSPs. Considering low-confidence high-end SLR scenarios that include the possibility for a more rapid melting of the ice sheets may shift expected impacts approximately 50 years forward. This means that adaptation needs to be implemented faster and sooner than previously anticipated, which may have consequences for the available adaptation options. Ignoring the potential and long-term (including beyond 2100) commitment for adaptation may lead to an adaptation gap and subsequently expensive retrofitting of infrastructure, creation of stranded assets, and less time to adapt at greater cost. In contrast, acknowledging and acting upon the long-term adaptation commitment can encourage timely adaptation and its alignment with other societal ambitions.

How to cite: Winter, G., Haasnoot, M., Brown, S., Dawson, R., Ward, P., and Eilander, D.: A first order assessment of long-term sea-level rise impacts beyond 2100 and the global and regional urgency for adaptation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12485, https://doi.org/10.5194/egusphere-egu22-12485, 2022.