The need to stabilise and protect beaches and coastlines is important due to the increasing recreational activities in the coastal zone. In Taiwan, the coastal area is hit by about four typhoons a year, and the large waves caused by the typhoons often lead to coastal disasters and beach erosion. The beach could also be the buffer zones against the large wave attack and coastal flooding and erosion. Although the gravel beaches have a great advantage over the sandy beaches in terms of energy absorption capacity, this advantage disappears under the strong wave attack during the typhoon season in Taiwan. The gravel is carried offshore, and it is difficult to return to the beach under the swell wave. During the extreme wave induced in typhoon conditions associated with storm surge, it causes gravel beach closer to the steep nearshore zone, which may then be irreversibly evacuated downslope. The extreme waves bring breaking waves high up on the beach, creating the step-reflecting berms. Energy reflection can thus contribute to further downslope transport of gravel to depths from which it can no longer be recovered by fair-weather waves. The gravel beach can be very steep, accompanied by a typically narrow surf zone and an energetic shore break.

The FuAng coast in the south of Taiwan has suffered severe beach erosion since the construction of breakwaters in 2015. The strong reflection creates partial standing waves that scour the sediment at the toe of the beach. In addition, the mixed sand and gravel beach is washed offshore during storms and cannot be brought back to the beach by the weak swell wave. The aim of this paper is to analyse the erosion problem using the shoreline evolution from the satellite images, the variation of the beach profile in several sections and the volumetric variation of the bathymetry. An integrated coastal protection countermeasure using submerged detached breakwaters with artificial beach nourishment is proposed to mitigate the beach erosion problem. Physical experiment and numerical simulation are used to verify the proposed countermeasure. The results show that the proposed method can effectively protect the coast, prevent the beach erosion and form a salient to be a good buffer zone to prevent the wave impact.

How to cite: Hsu, H.-C.: Morphological variation of the beach under the construction of submerged breakwaters-a case study in Pintung coastal area of Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-191, https://doi.org/10.5194/egusphere-egu24-191, 2024.

The seabed depth on the western coast of Taiwan is approximately between 20 to 50 meters, making it suitable for the installation of offshore wind turbines with a tripod foundation. Under the influence of water flow, the surrounding sand of the foundation can be eroded, forming scour holes and subsequently reducing the foundation's bearing capacity. The scour holes, influenced by the inherent angle of repose of the sand, undergo continuous erosion and collapse due to water flow, eventually reaching dynamic equilibrium. This study employs the Discrete Element Method (DEM) to conduct numerical simulations of scouring around the tripod foundation of offshore wind turbines. Different diameter particles are used to construct models of the offshore wind turbine tripod foundation and the sand. The dimensions of the seabed sand are 150 cm * 100 cm * 30 cm, with a particle diameter of 20 mm. This study observes the scouring of sand particles under different normal and shear stiffness conditions, resulting in various forms of scouring. The variations in scouring depth, length, and width under different normal and shear stiffness conditions will be discussed.

How to cite: Yang, Y., Lo, C.-M., and Lai, Y.-S.: Study on the influence of scour around tripod foundation for offshore wind turbine using Discrete Element Method, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1641, https://doi.org/10.5194/egusphere-egu24-1641, 2024.

The Bay of Bengal is a well-known hotspot for cyclone formation. Multiple recent cyclones, such as the Odisha Super Cyclone in 1999 and Cyclone Fani in 2019, along with a series of historical cyclones, have severely impacted the east coast of India, particularly the coastal regions of Odisha and West Bengal States. However, the existing cyclone record from the area is insufficient for multi-decadal recurrence analysis, rarely extending beyond last few decades. Hence, understanding and integrating historical, prehistorical, and geological cyclone records from the area can provide information on the social, economic, and environmental impacts of cyclones. This information will aid in planning response strategies and implementing policies to mitigate cyclone effects. This study investigates the geological record of cyclones buried in the prograded beach systems near Konark in Odisha over the past few hundred years. Shore-normal ground penetrating radar (GPR) reflection profiles were collected using the 250 and 500 MHz antennas of the pulseEKKO PRO GPR system. Sediment cores and excavated faces were analysed along the same GPR lines, and optically stimulated luminescence ages provide a chronological framework over the last 300 years. Processed GPR profiles exhibit a number of high-angle erosional surfaces. These surfaces were likely caused by erosion during severe cyclones in the region, spanning at least the last three centuries. Eight such erosional surfaces were identified from the GPR profile near Konark. Trench and core data from the swales also highlight several distinctive layers rich in heavy minerals, possibly the result of repetitive cyclones in the area. One prominent sand layer gives an interim age of 150 years, likely linked to a late 19^th century washover event. The data presented in this study indicate that geological records can be used to build a long-term cyclone record for the area. Given the increasing population density in the region, a comprehensive cyclone record can provide valuable insights into the changes in frequency and intensity over the long term, which can be used to inform decision-making processes for coastal management and development.

How to cite: Kumar, R., Switzer, A., Nugraha, A., Singh, R., Banerjee, S., Rath, S., Horton, B., Prizomwala, S., and Bristow, C.: Geological Records of Past Cyclones Preserved in the Beach Ridge Systems on the East Coast of India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4365, https://doi.org/10.5194/egusphere-egu24-4365, 2024.

Offshore tsunami deposits have received considerably less attention than their onshore counterparts, despite the fact that they have a higher likelihood of being preserved in the sedimentary record, especially in sufficiently deep marine environments, below the storm wave base. Here we provide the first results from our study of Holocene tsunami deposits offshore the Shetland Islands. The region is characterized by an irregular coastline with fjords and numerous embayments, and relatively deep waters (up to 100 meters in depth),  providing a sheltered environment, and by an extensively studied and well-documented onshore record of tsunami deposits, which should facilitate correlations between onshore and offshore event deposits. 
Within the NORSEAT Project (North Sea Tsunami Deposits Offshore Shetland Island), we aim to identify and trace tsunami deposits offshore, thoroughly study their characteristics and extent, and determine whether the offshore record holds evidence of events additional to those already known from the onshore record (i.e. the Storrega tsunami and two events at ca. 5500 yr and ca. 1500 yr BP), which would offer new insights into recurrence intervals. Two surveys with RV Belgica have already been conducted, during which high-resolution geophysical data (multibeam bathymetry and backscatter, geoacoustic and seismic data) were collected, along with several vibrocores, in three embayment areas around the Shetland Islands.
Bathymetric data and sub-bottom profiles reveal a complex geomorphology, including a.o. elevated features, like bedrock exposures, and isolated depressions that function as sub-basins. The sedimentary sequences infilling these sub-basins are characterized by a complex stratigraphy and comprise several different sedimentary units. Along the west and east fjords of Sullom Voe, three distinct sub-environments (inner, middle, and outer voe) exhibit a diverse and well-preserved stratigraphy, potentially including a significant event deposit. A set of prominent strong reflectors at a depth of 1-2 m below the seafloor is interpreted as dynamic shallow marine deposits, which is supported by the results of the vibrocores retrieved at these sites. Out of the total 31 sediment cores taken, many contain coarser-grained layers sandwiched between finer-grained deposits. These coarser layers, often with sharp basal contacts and normal grading patterns, suggest temporary interruptions of the steady-state sedimentary regime and are interpreted as possible event deposits based on their contrasting textural and lithological characteristics.
In the next phase of our analysis, we aim to obtain the exact timing and detailed information about the depositional setting based on radiocarbon dating, grain size analysis, geochemical analysis, mineral distribution patterns, and the distribution of microfossils within the sediment cores, which should help us to build a robust tsunami event stratigraphy for the region, combined with planned sea-level reconstructions, assess their run-up heights based on the onshore-offshore connection and the fundamental research on sedimentary signatures and facies patterns of offshore tsunami deposits.

How to cite: Nahar, R., Costa, P., Van Daele, M., Dawson, S., Engel, M., Scheder, J., Goovaerts, T., Heyvaert, V., and De Batist, M.: Constructing an offshore tsunami event stratigraphy for the Shetland Islands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9556, https://doi.org/10.5194/egusphere-egu24-9556, 2024.

This study examines ground penetrating radar (GPR) records of beach ridge stratigraphy as a proxy for reconstructing regional sea-level and tsunami histories in the tropics. We present topographically corrected GPR profiles on a prograded coast in Phra Thong Island, Thailand where we 1) identify downlap points marking the boundary between foreshore / beachface and upper shoreface facies and use this as past sea-level marker and 2) identify ‘cut and fill’ packages in the upper fill that we infer to be records of past erosion and recovery following repeated tsunami events. Optically Stimulated Luminescence (OSL) dates collected at locations slightly offset from the same profile line were incorporated to create the temporal record. The shore-normal GPR record shows ~0.82 m fall in the sea-level between 2659±139 years BP to 367±27 years BP that is consistent with other proxy based sea-level curves obtained in the region. The early part of the record (before ~2600 years) presents a period of rapid progradation and relatively stable sea level conditions. From ~2600 years BP to ~2200 years BP the record shows a steeper fall in sea level followed by a relatively stable to slightly falling phase between ~2200 years BP and ~550 years BP. Finally, for the seaward side, between ~550 years BP and ~350 years BP, the record indicates falling relative sea-level. The cut and fill packages suggest that Phra Thong has experienced 5 tsunami events in the last 2600 years including two events in close succession around 500 years ago that are recorded in the most landward part of the sequence.  This study confirms that the study of tropical beach ridge systems using GPR and OSL techniques can be highly effective for reconstructing regional sea-level trends and tsunami histories through the Common Era and beyond.

How to cite: Switzer, A., Kumar, R., Gouramanis, C., Bristow, C., Shaw, T., Kruawun, J., and Brill, D.: Ground Penetrating Radar of a beach ridge system on Phra Thong Island, Thailand reveals repeat Late-Holocene tsunami events on a background of falling sea level, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4910, https://doi.org/10.5194/egusphere-egu24-4910, 2024.

High-resolution reconstructions of the relative sea-level (RSL) evolution are important for managing coastal-protection challenges and for hazard assessment. For the determination of palaeo-tsunami run-up heights in the Shetland Islands, United Kingdom, within the NORSEAT Project (Storegga and beyond – North Sea tsunami deposits offshore Shetland Islands), RSL reconstructions far beyond existing data are needed. Existing RSL data is limited to two time frames (ca. 7900–5990 cal BP and around 3500 cal BP) and include a large vertical error (approximately ±8 m around the time of the Storegga tsunami). More detailed Holocene RSL reconstructions shall be enabled by a combined modern training set of foraminifers and ostracods from three different voes of Shetlands largest island, Mainland. The training set serves as a basis for a RSL transfer function, which relates the elevation of surface samples to the modern microfaunal associations. This transfer function will be a valuable tool for high-resolution RSL reconstructions from the Holocene stratigraphic record around the Shetland Islands as shown by previous studies in Northern Germany.

Investigations of 44 surface samples, which were collected from three salt marshes and adjacent tidal flats (south Dales Voe, Dury Voe and north Dales Voe), are in progress. First results show highly diverse foraminifer and ostracod associations in the salt marsh and very low occurrence of microfauna in the very coarse parts of the tidal flat. Small areas of very muddy tidal flats suggest higher abundances than the latter. Aside from the investigation of the microfaunal distribution, analyses of environmental parameters like the grain-size distribution and the carbonate and organic matter content are still in progress. Multivariate statistics will determine the main influencing factor of the microfauna distribution between these environmental proxies and the elevation relative to mean sea level.

If the training set is feasible for a RSL transfer function, in a next step, it will be applied to Holocene deposits from offshore cores around Shetland that were conducted within the NORSEAT Project. The resulting new RSL reconstructions will enable more accurate determination of run ups of the currently identified palaeo-tsunamis (Storegga and two younger events). 

How to cite: Scheder, J., Dawson, S., Goovaerts, T., Engel, M., Costa, P., Van Daele, M., Nahar, R., De Batist, M., and Heyvaert, V. A. M.: A combined modern training set from three salt marshes and tidal flats of Mainland, Shetland Islands, as a tool for local relative sea-level reconstruction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17053, https://doi.org/10.5194/egusphere-egu24-17053, 2024.

Global climate change is expected to increase the proportion of intense tropical cyclones in the Northwest Pacific. This study focuses on how factors, especially extreme events, may affect disaster losses. To address this issue, an event-based multivariate tropical cyclone risk assessment model, which employs Copula, generalized additive model, and undersampling extreme gradient boosting decision tree techniques, is developed to enhance the accuracy of disaster loss prediction. The results suggest that on Hainan Island, the rate of the affected population is positively correlated with maximum wind speed and maximum daily rainfall but negatively correlated with gross domestic product and elevation. The study also shows that the tropical cyclone risk in the cities in Hainan increases as the return periods expand, and each return period scenario shows a unique geospatial distribution of the tropical cyclone risk on Hainan Island, with higher risks in coastal and eastern regions. These results emphasize the importance of implementing effective disaster management strategies to mitigate the impact of severe tropical cyclones in the region.

How to cite: Meng, C. and Xu, W.: Quantitative Assessment of Affected Population Risk by Tropical Cyclones Using the Hybrid Modeling Combining GAM and XGBoost: A Case Study of Hainan Province, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6922, https://doi.org/10.5194/egusphere-egu24-6922, 2024.

Coastal flooding, often triggered by the convergence of high tides and intense storm surges and waves, poses a grave threat to global coastal communities, leading to widespread property damage and loss of life. Tropical cyclones (TCs) in particular have been responsible for the majority of the most devastating coastal flood events in the recent years, causing billions of dollars in damages over the last decade within the US alone. Further, the compounded impact of rising sea levels, fuelled by a warming climate, along with projected population growth and continued development in the flood zone, is widely expected to increase these risks to coastal communities in the future. 
It is essential to many end users, from environmental mangers to (re)insurers, to accurately characterize the risk of coastal flooding over large, often national scales, both under current and highly uncertain, future climate conditions. This poses a number of challenges. For instance, in many of the most heavily impacted regions of the world, the majority of the coastal flooding stems from severe TC induced storm surge events. The rarity of these events means that the historical record alone is insufficient to truly capture the current risk, let alone represent the vast range of potential future climate conditions and their subsequent impacts upon TC-induced flood risk. To provide the information required catastrophe model frameworks that can efficiently represent the full range of potential flooding events, from hazard generation through to financial impacts, and how their frequencies might change through time, are essential. 
This research introduces a comprehensive TC-induced storm surge catastrophe modelling framework. An extensive catalogue of synthetic TC wind and pressure fields, under current and future climate forcing, is utilised. The SCHISM model suite is used to numerically model surge and waves to generate boundary conditions to the reduced physical solver, SFINCS, which is used to model the nearshore and overland inundation processes. Using an example US implementation, novel approaches developed to enable the efficient representation of approximately 2.5 million unique TC events are discussed, and preliminary results presented. The proposed catastrophe model framework offers a valuable tool for those interested in coastal flooding, enabling a robust evaluation of TC-induced risk under any climate scenario, over extensive geographical domains.   

How to cite: Quinn, N., Collings, T., Pranantyo, I., Bruneau, N., Wilkinson, H., Haigh, I., and Haylock, M.: Tropical cyclone induced coastal flooding under current and future climates: A novel model framework for continental scale applications. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9395, https://doi.org/10.5194/egusphere-egu24-9395, 2024.

Sea cliffs comprise approximately 80% of the world’s coasts. Rapidly retreating cliffs are a widespread problem that threatens property, transport infrastructure and public safety. Cliff retreat rates depend on highly localised characteristics of the cliff itself, as well as on the land behind the cliff and the intertidal and marine environments in front of it. In addition to these physical properties, retreat rates are also influenced by the methodology applied. Traditionally, estimates of coastal cliff top retreat have been based on historic map and arial photograph (century scale) analyses that provide long-term rates but fail to provide information in short-term processes driving coastal evolution. Newer datasets from satellite imagery and uncrewed aerial vehicles (UAV’s) are being coupled with new techniques like Structure-from-Motion (SfM) to dismantle cliff top and cliff face dynamics at shorter timescales (weeks to months). It is now accepted that estimates of cliff retreat rates can differ substantially when calculated from cliff top versus cliff face analyses, usually finding that cliff-top retreat rates are higher than cliff-face retreat rates.

This study combines historical data (maps and aerial photographs 1842 – 2000) with contemporary UAV imagery (2019 – 2023) to analyse cliff top and cliff face dynamics of a 250 m wide coastal drumlin at Silverstrand in Galway Bay on the west coast of Ireland. The cliff top changes were analysed using the Digital Shoreline Analysis System (DSAS) in the ESRI ArcGIS Desktop platform. Cliff face change detection was done using a Multiscale Model to Model Cloud Comparison (M3C2) in CloudCompare. By using these different types of data and methods, we were able to calculate retreat rates of the cliff top and the cliff face independently. The average cliff top retreat rate between 1842 and 2023 (181 years) was estimated to be 0.14 +/- 0.02 m/year. The average cliff face retreat between 2019 and 2023 (4.45 years) was estimated to be 0.08 +/- 0.02 m/year. For both, cliff top and cliff face retreat rate, we found that the long-term retreat rates are lower than the short-term retreat rates and that the western part of the cliff experiences higher erosion than its eastern counterpart. This variability might reflect multiple erosional processes and differences in magnitude-frequencies of erosional events at the cliff top and cliff face, or even the application of various methods and datasets.

Our results are consistent with other soft rock cliffs in Ireland and globally in similar settings. Nonetheless, more detailed observations using shorter timescales and monitoring intervals are warranted to identify and quantify the rates, patterns, timing and magnitude- frequency of cliff retreat phenomena.

How to cite: Rink, G., Bromley, G., and Farrell, E.: Measuring cliff top and cliff face retreat rates of a coastal drumlin using Structure-from-Motion in Galway Bay, Ireland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10979, https://doi.org/10.5194/egusphere-egu24-10979, 2024.

We examined sedimentary records in a coastal lagoon on Saint Martin Island in the Lesser Antilles to identify and characterize extreme-wave events (EWEs), such as hurricanes and tsunamis. Employing a comprehensive approach involving sedimentological, geochemical, and radiocarbon dating analyses, complemented by X-ray computed microtomography (micro-CT) for examining sediment fabrics, we applied this multiproxy method to three oriented short sediment cores along a transect. This allowed us to identify sediment layers linked to both tsunami- and hurricane-induced EWEs. Five out of the seven EWEs were identified as paleo-tsunamis through their geochemical, sedimentary, and structural signatures. These five paleotsunamis were successfully dated over the last 3500 years, including the well-documented Pre-Columbian tsunami at approximately 1400 yrs CE and the transatlantic Lisbon tsunami at 1755 CE. This suggests a tentative local tsunami chronology of five well-documented events over the last 3500 years with a recurrence interval of 400 to 500 years.

However, the most recent EWE corresponded to the powerful Category 5 Hurricane Irma in 2017. Over the last 150 years, another 14 less intense hurricanes impacted the island, leaving no sediment imprints in the lagoon. This finding is in line with most recent publications showing that tropical storm intensification rates have already changed as anthropogenic greenhouse gas emissions have warmed the globe (Garner, 2023).

Furthermore, micro-CT-based sediment analysis provided a deeper understanding of the relationship between sediment fabric and tsunami wave dynamics. Therefore, we used the deposits of the Pre-Columbian tsunami and compared paleo-flow directions from micro-CT-derived fabric patterns to those from numerical tsunami models. The results that best explain the Pre-Columbian tsunami deposit emplacement are in line with a Mw 8.5–8.7 megathrust earthquake source located on the subduction interface at the Puerto Rico Trench, north of Anegada Island (Cordrie et al., 2022). Ultimately, integrating deposits of EWEs with numerical models is pivotal for devising effective hazard mitigation strategies tailored to vulnerable coastal communities.

Cordrie, L., Feuillet, N., Gailler, A., Biguenet, M., Chaumillon, E., Sabatier, P., 2022. A Megathrust earthquake as source of a Pre-Colombian tsunami in Lesser Antilles: Insight from sediment deposits and tsunami modeling. Earth Sci Rev 228, 104018. https://doi.org/10.1016/j.earscirev.2022.104018

Garner, A.J. Observed increases in North Atlantic tropical cyclone peak intensification rates. Sci Rep 13, 16299 (2023). https://doi.org/10.1038/s41598-023-42669-y

How to cite: Fabbri, S. C., Sabatier, P., Paris, R., Falvard, S., Feuillet, N., Lothoz, A., St-Onge, G., Gailler, A., Cordrie, L., Arnaud, F., Biguenet, M., Coulombier, T., Mitra, S., and Chaumillon, E.: Linking sedimentary imprints of storms and tsunamis with numerical wave modeling: A case from a coastal lagoon in the Lesser Antilles (Saint Martin), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15411, https://doi.org/10.5194/egusphere-egu24-15411, 2024.

Suspended and bedload sediment transport in shallow water environments is a critical factor influencing coastal morphology, ecosystem health, and infrastructure stability.  We present a new model for suspended and bedload sediment transport in shallow flows that takes into account vertically varying velocity profiles. We achieve this by using the recently developed shallow water moment model (SWME). The SWME employs a unified modeling framework that incorporates a polynomial expansion of the velocity profile in vertical direction, which represents a paradigm shift compared to the standard assumption of constant velocity profiles. The expansion coefficient equations constitute a hierarchical PDE system that improves accuracy when more equations are considered. The SWME model is then augmented by equations governing suspended sediment concentration and bedload transport. In this talk, we discuss the assumptions and general derivation of the 1D model, along with the theoretical analysis and the extension of this model to complex fluid phenomena.

How to cite: Parvin, A., Koellermeier, J., and Samaey, G.: Shallow water moment model for sediment transportation in coastal area, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19322, https://doi.org/10.5194/egusphere-egu24-19322, 2024.

Advances in machine learning and deep learning approaches have drawn substantial interest across diverse research domains, including environmental studies. These innovative techniques have transformed the approaches to measuring marine parameters by facilitating automated and remote data collection. This study focuses on the implementation of a deep learning model to automatically assess tide and surge, aiming for precise outcomes through the analysis of surveillance camera imagery.

Utilizing the Inception v3 structure, the deep learning model was applied to predict tide and storm surge from surveillance cameras strategically positioned in two distinct coastal regions, namely Santa Lucia in southeastern Sicily and Lignano Sabbiadoro in Friuli Venezia Giulia, Italy. The deep learning model is based on classification methods to assign a value of water level to a given frame. This approach is particularly advantageous in scenarios where traditional tide sensors face inaccessibility or are distant from measurement points, especially during extreme events demanding accurate surge measurements. The dataset used for the training and validation of the deep learning model covers the entire tide values that could be observed in the study areas. Predictions of the deep learning model were compared with tide gauge values in order to assess the system accuracy.

The conducted experiments demonstrate the efficiency of the model in remotely and effectively measuring tide and surge, achieving an accuracy exceeding 90% while maintaining a loss value below 1 for the deep learning model. These findings underscore its potential to fill the data collection gap in challenging coastal environments, offering valuable insights for coastal management and hazard assessment. This study makes an important contribution to the rapidly growing field of remote sensing and machine learning applications in environmental monitoring, facilitating greater comprehension and decision-making in coastal areas.

How to cite: Sabato, G., Scardino, G., Kushabaha, A., Casagrande, G., Chirivì, M., Fontolan, G., Fracaros, S., Luparelli, A., Spadotto, S., and Scicchitano, G.: A deep learning method to automatically measure tide and surge in coastal areas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8103, https://doi.org/10.5194/egusphere-egu24-8103, 2024.

Several cyclogenesis processes affect the Mediterranean Sea, causing significant impacts along its coastline. This study focuses on mapping the effects of cyclones in the Mediterranean Sea, particularly Mediterranean hurricanes, which cause severe damage to coastal areas. Advanced remote sensing and Geographic Information System (GIS) techniques are used to analyse climatic data and observe geomorphological evidence, such as flooding, coastal erosion, landslides, alluvial flooding and debris flow. By integrating climate features and geomorphological evidence, this research establishes a connection with the occurrence of Mediterranean cyclones. The study specifically examines the south-eastern coasts of Sicily, where Mediterranean Hurricanes have caused extensive damages, including flooding, erosion, and storm surges. Pre and post-storm morpho-topographical surveys were conducted to assess coastal flooding and erosion through aerial photogrammetry and Terrestrial Laser Scanner surveys. The collected data were stored in a geodatabase, allowing for the display of climate features and geomorphological evidence. Additionally, the development of an open-source Web-GIS platform integrated with the geodatabase can facilitate the dissemination of geographic information to stakeholders and researchers, promoting collaboration and informed decision-making. This study contributes to a better understanding of Mediterranean cyclones, enabling the development of effective coastal management strategies to mitigate the challenges posed by Mediterranean Hurricanes.

How to cite: Kushabaha, A., Scardino, G., Sabato, G., Scicchitano, G., and Borzi, A. M.: Integration of relational geodatabase in a web-GIS platform for Mapping the effects of Mediterranean Cyclone., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8125, https://doi.org/10.5194/egusphere-egu24-8125, 2024.

Coastal areas are primarily exposed to a range of coastal hazards, including both climate- and marine-related processes, due to their close proximity to the sea. In this context, the Maltese Islands, located in the centre of the Mediterranean Sea, are prone to be affected by various coastal risks in the form of erosion, flooding, landslides, storm surges and, on a longer-term, permanent inundation as a consequence of the ongoing sea level rise. These Islands have evolved over time from a complex interplay of marine, morphodynamic and tectonic processes resulting in highly diversified coastal landforms and scenic landscapes.

Considering primary and secondary data sources, this study investigates the coastal vulnerability of the north-west coast Malta with respect to a series of hazardous processes by applying an index-based approach supported by extensive field surveys. This stretch of coastal area attracts a large number of visitors each year, raising serious concerns about coastal vulnerability, thus, challenging sustainable management of coastal touristic assets.  In the first phase of this research, a set of indicators pertaining to the local land use, anthropogenic, and natural assets were used in order to estimate the level of coastal exposure. The following phase entailed the zonation of the areas exposed to rock falls, and storm surges, erosion and sea level rise, which enabled us to estimate the overall coastal vulnerability. The results show that the bay areas of the north-west coast of Malta dominated by tourist activities can be considered as the most vulnerable zones and targets of different climate- and marine-related impacts. These are the areas where it would be challenging to prevent future impacts if no adaptation and sustainable management strategies are taken into account.

How to cite: Sarkar, N., Rizzo, A., Vandelli, V., and Soldati, M.: Coastal vulnerability assessment in the central Mediterranean area: A case study of the Maltese coast, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1128, https://doi.org/10.5194/egusphere-egu24-1128, 2024.

The island of Gotland located in the middle of the Baltic Sea is Sweden's largest island, and also a county and municipality with the population of about 60,000, employed mainly in agriculture and tourist sectors. Gotland is a very popular domestic tourist destination for mainland Swedes, reaching nearly 2 million ferry and plane passengers per year. Gotland experiences limited capacity in groundwater reservoirs combined with increased demand during the warm season when tourists visits peak leading to recurring water stress. Desalination of drinking water from the Baltic Sea is a promising alternative to complement municipal water supply. The operation of the two major desalination treatment plants becomes however disturbed by compound hazards due to extreme sea weather events (marine heatwaves, strong upwelling events) and related hydro-sedimentary and biological processes (macro- and microalgae blooms) that are predicted to intensify under the climate change. Developing an apt forecasting system for this "multi-hazard" to inform sustainable management of Gotland's water resources becomes thus a priority and is of broader relevance to other regions in Sweden.

The ALGOTL project, funded by the Swedish research council for sustainable development (FORMAS), is a collaboration between Stockholm University, the Swedish Meteorological and Hydrological Institute (SMHI) and Region Gotland to develop a novel forecast framework for natural hazard impacts on management of water resources, both short term (early warning) and long term (climate scenarios). The project aims at development of Lagrangian- and risk modelling tools based on the operational ocean state forecast at SMHI. Our stakeholders on Gotland will provide input on adverse impacts, information required for management, and feedback on the forecast framework during the project.

This contribution will summarize results from observational and modelling analysis of the oceanographic, hydrological and biological conditions due to the Hans storm event in August 2023 that led to the disturbance in operation of the desalination plants on Gotland, located at the Herrvik (eastern side) and Kvarnåkershamn (western side of the island). The storm triggered an upwelling event leading to sea temperature changes of 10 K (prompting the change from summer to winter operational mode) and high vertical and horizontal velocities and associated excessive transport of sediment and biological (algae) material disrupting the filtering process. We will also show results from Lagrangian backtracking of the source waters reaching the desalination plants and present prospects for developing of a forecast system for related events in the future.

More information about the ALGOTL project: https://www.su.se/english/research/research-projects/algotl-forecast-framework-for-algae-blooms-to-secure-water-supply-on-gotland

How to cite: Koszalka, I. M., Masini, M., Antivachis, D., Döös, K., Karlsson, A., Karlsson, B., Axell, L., and Arneborg, L.: Analysis and modelling of compound hazards to the desalination plants on Gotland: The Hans Storm 2023 event, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11851, https://doi.org/10.5194/egusphere-egu24-11851, 2024.