Extreme weather events dominate the disaster landscape of the 21^st century and disaster risk is becoming systemic with one event overlapping and influencing another in ways that are testing our resilience to the limit. This is particularly true for critical infrastructure, such as hospitals, that are vital to the functioning of society but have received limited attention in terms of investment in prevention, climate change adaptation and risk reduction. One of the most severe weather events, present in mountainous coastal areas is the Bora wind, a strong and often gusty regional katabatic wind generated by cold and dry air spilling down from a mountain range. The Bora wind has been studied extensively from a meteorological point of view. However, there is limited research on its consequences on the critical infrastructure of coastal urban areas, particularly tall buildings that are susceptible to high wind and wind-driven rain. In Europe, strong Bora winds are encountered on the east coast of the Adriatic Sea. The scope of this study is to assess the Bora-wind-induced atmospheric forces exerted on the high-rise Cattinara hospital in Trieste, Italy, a location where strong Bora winds often occur during the autumn and winter seasons and an increased risk of functionality loss is present. High-resolution RANS simulations are performed for the hospital and the surrounding buildings over the complex and mountainous topography of the area. The imposed boundary conditions approximate the extreme February 2012 Bora wind event that saw gusts of more than 40 m/s in the region. The results provide an evaluation of the methodological framework, assess the inherent complexities of atmospheric simulations over intricate landscapes and demonstrate that a comprehensive understanding of the aerodynamic loads is imperative for mitigating potential vulnerabilities in critical infrastructure subjected to such extreme meteorological phenomena. The study is conducted within the remit of the HORIZON-EU project RISKADAPT (Asset Level Modelling of RISKs in the Face of Climate-Induced Extreme Events and ADAPtation) that seeks to provide solutions to support systemic, risk-informed decisions regarding adaptation to climate change induced compound events at the asset level.

How to cite: Ampatzidis, P., Cintolesi, C., Petronio, A., and Di Sabatino, S.: Evaluation of atmospheric forces induced by extreme Bora wind on a high-rise hospital in the coastal city of Trieste, Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19086, https://doi.org/10.5194/egusphere-egu24-19086, 2024.

For the entire shoreline of Vietnam, a comprehensive analysis spanning from 1984 to 2021 was conducted. The study employed a cloud-based processing strategy on Google Earth Engine, utilizing Landsat-derived annual composites based on the Modified Normalized Difference Water Index (MNDWI). Coastline change rates were quantified using linear regressions along shore-normal transects, and hotspots were identified based on erosion and accretion rates. Notable erosion hotspots were observed in the Mekong Delta and Nam Dinh province, while accretion was prominent near Hai Phong city.

The coastal region of Vietnam, including Thua Thien Hue province, is exceptionally susceptible to sea level rise, storm surges and changing sedimentation patterns due to urbanization, agriculture, aquaculture, tourism, and industrial activities competing for limited and attractive coastal zones. Thua Thien Hue, home to the largest lagoon in Southeast Asia, the Tam Giang-Cau Hai lagoon, emerged as a unique case emphasizing the significance of understanding and monitoring coastline dynamics. An extensive dune, stretching across approximately 70 km, acts as a natural barrier, separating the lagoon from the sea. This region encompasses a distinctive ecosystem, agricultural expanses, aquaculture ventures, and the culturally rich City of Hue, once the imperial capital boasting numerous heritage sites. The hinterland, sheltering this amalgamation of natural and cultural treasures, faces the recurrent challenge of compound flooding events. These events are intensified by the interplay of storm surges from the sea and associated backwater effects. Given this, comprehending the historical dynamics becomes imperative, serving as a cornerstone for informed decisions on future adaptation strategies in the realms of coastal and flood protection.

More than half of Thua Thien Hue's coast was classified as predominantly stable, but localized erosion and accretion patterns revealed varying dynamics. The central finding was the identification of five local hotspots with strong coastline change rates. These hotspots exhibited dynamic patterns of erosion and accretion, notably at the Thuan An inlet and in Tu Hien in the south of Hue province.

The Thuan An inlet showcased an erosion hotspot with an average erosion rate of -4 m/yr over 900 meters. This erosion intensified in the 2000s, stabilizing after 2014, illustrating the temporal variability of coastal dynamics. Conversely, on the opposite side of the lagoon inlet, a headland was identified as an accretion hotspot with an average rate of +3 m/yr and alternating phases of erosion and accretion. Severe erosion hotspots were also noted north and south of the lagoon inlet in Tu Hien.

Thua Thien Hue's coastline changes are multifaceted but understudied. They are probably influenced by sediment redistribution, reduced coastal sediment availability, and direct human interventions. Despite the overall stability of most parts of the coastline, the localized changes underscore the intricate interplay of natural and anthropogenic factors shaping the coastal dynamics of Thua Thien Hue over the past three and a half decades.

How to cite: Bachofer, F., Lappe, R., Nguyen, H. K. L., Nguyen, D. G. C., Sogno, P., Ullmann, T., and Kuenzer, C.: Coastal Dynamics of Thua Thien Huế, Vietnam: Insights from 35 Years of Earth Observation Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4725, https://doi.org/10.5194/egusphere-egu24-4725, 2024.

How to cite: Kralj, E., Kumer, P., and Meulenberg, C.: Insight into temporal and spatial coastal flooding through databases with historic meteorological data and national registry-reported natural disaster events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12104, https://doi.org/10.5194/egusphere-egu24-12104, 2024.

Due to the particularity of geographical location, coastal areas are not only affected by climate change and urbanization, but also affected by the lower boundary jacking caused by sea level rise, so it is easier to form a flood process with "high peak, large quantity and short duration". This study comprehensively considered future climate change, land use change, and sea level change, combined with hydrological model, simulated the flood process of the Qianshan River Basin in the future, and explored the effects of multiple future environmental changes on flooding in the coastal area. The results show that the flood characteristics of Qianshan River Basin will increase due to multiple future environmental changes, and the increase rate will increase with the increase of future scenario level. Among them, the increase of peak discharge is the largest in Dachong; The increase of peak water depth is the largest in Hongwanchong under normal conditions and Guangchangchong under extreme conditions; The location of the inundation has not changed obviously, and it is mainly concentrated in the southern part of the basin; The high risk areas showed a significant increase trend, and concentrated in Tanzhou Town and outlet of Qianshanshuidao. The increase pattern of these flood characteristics basically follows: In the future SSP126, SSP245, SPP370, and SSP585 scenarios, the flood characteristics produced by a design rainfall of grade n correspond to those produced by a design rainfall of grade (n+1), (n+2), (n+3), and (n+4) in the current period, respectively.

How to cite: Yao, Z. and Huang, G.: Effects of multiple future environmental changes on flooding in coastal area: A case study of Qianshan River Basin, South China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2240, https://doi.org/10.5194/egusphere-egu24-2240, 2024.

A primary concern about climate change is the possible rise in the frequency and severity of extreme meteorological/climatological events, like heat waves, intense storms, severe flooding, or droughts. Extreme precipitation events are predicted to increase in size and frequency due to climate change, which could result in more frequent and severe river flooding. Hydrological modeling is integral to accurately deriving flow hydrographs, which is crucial for hydraulic models. This study employs various statistical distributions to assess future simulations' rainfall-runoff relationship and project flow hydrographs under climate change scenarios in the Bafra subbasin of the Black Sea Region. The investigation centers on obtaining flow hydrographs for the Bafra subbasin in the Black Sea Region. The annual maximum precipitation value for the relevant year is determined from daily total precipitation values, and its compatibility with statistical distributions is systematically evaluated. The modeling process considers two climate change scenarios, a moderate radiative forcing scenario (RCP 4.5) and a warming scenario (RCP 8.5), extending projections from 2006 to 2100. The RCP 4.5 and RCP 8.5 scenarios’ data sets are sourced from the Coordinated Regional Climate Downscaling Experiment (CORDEX) data for future estimations. MNA-44 domain that covers Türkiye with a horizontal resolution of 0.44 degrees and 232 points in longitude and 118 points in latitude is used. An accurate determination of flow hydrographs is essential in hydrological modeling. Various statistical distributions, such as Normal Distribution, Log-Normal (2 Parameters), Log-Normal (3 Parameters), Pearson Type-3 (Gamma Type-3), Log-Pearson Type-3, and Gumbel distributions, are employed to identify the most suitable distribution, and the base flow is taken as the current 95% of the time for flow hydrographs. The goodness of fit tests using the Kolmogorov-Smirnov test are conducted to assess distribution types.

As a result of the conducted analyses, in the RCP4.5 flow hydrograph, the Q₅₀ value is determined as 334.7 m³/s, the Q₁₀₀ value as 350.5 m³/s, and the Q₅₀₀ value as 382.3 m³/s. In contrast, in the RCP8.5 flow hydrograph, these values are obtained as 395.5 m³/s, 429.4 m³/s, and 506.1 m³/s, respectively. Accordingly, in the pessimistic scenario, the discharge amount that would lead to flooding is 18% higher at Q₅₀, 22% higher at Q₁₀₀, and 32% higher at Q₅₀₀. The integration of statistical analyses and climate scenarios enhances the accuracy and reliability of flood estimations, contributing to a comprehensive understanding of the potential impacts of climate change on hydrological processes in the Black Sea Region. In further studies, hydraulic modeling of the flood will be carried out using the Hydrologic Engineering Center - River Analysis System (HEC-RAS) with the most appropriate hydrographs that are obtained from future simulations (RCP 4.5, RCP 8.5). The inundation area of the flood will be computed employing this model, and the hydrological impacts resulting from diverse climate simulations will be acquired through two-dimensional modeling, thereby enhancing comprehension.

How to cite: Haliloğlu, Ş., Beden, N., Demir, V., Arıman, S., Soydan Oksal, N. G., and Efe, B.: Integrated Hydrological Modeling of Climate Change Scenarios on Future Flood Estimations: A Case Study of Bafra Subbasin in the Black Sea Region, Türkiye, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5640, https://doi.org/10.5194/egusphere-egu24-5640, 2024.

Coastal cities are increasingly vulnerable to the impacts of extreme wave-induced runup (ssh-runup), which can cause significant damage to infrastructure, ecosystems, and human life. A comprehensive understanding of the characteristics and future trends of extreme ssh-runup is crucial for effective coastal risk management and adaptation strategies. This study employs extreme value analysis (EVA) to investigate wave-induced runup (ssh-runup) in Villanova, Spain, a coastal community participating in the SCORE project's Coastal City Living Labs initiative.

Historical (1956-2005), evaluation run (1980-2018), and future (2015-2094) ssh-runup data are analyzed under two representative concentration pathways (RCP 4.5 and 8.5). Four statistical models are applied for EVA: Block Maxima Generalized Extreme Value (GEV) with L-moments using Gumbel and Peak Over Threshold (POT) Generalized Pareto Distribution (GPD) with a 98% threshold and a constant threshold (0.82). Model performance is evaluated using the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), as well as different plots (e.g., QQ plot). Results indicate that the GPD model performs consistently better than the other methods in all datasets. The GPD model exhibits a slight improvement over GEV and other models in the historical and evaluation runs, while it outperforms GEV and other models significantly in future projections. This suggests that the GPD model is better suited for capturing the increasing trend in extreme ssh-runup under climate change scenarios.

The findings of this study provide valuable insights into the characteristics and future trends of wave-induced runup in Villanova, aiding in coastal risk assessment and adaptation planning. Applying different EVA techniques highlights the importance of selecting the most appropriate model for the specific data and context. These findings contribute to the understanding of coastal hazards and inform the development of effective adaptation strategies to mitigate the risks associated with extreme wave-induced runup.

How to cite: Anton, I., Paranunzio, R., Bendoni, M., Nalakurthi, S.-R., Gharbia, S., and Baldini, L.: Investigating Extreme Wave-Induced Runup in Villanova, Spain: A Comparative Analysis of Extreme Value Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8109, https://doi.org/10.5194/egusphere-egu24-8109, 2024.

Concrete is used worldwide; however, it is susceptible to fluctuations in temperature and exposure to moisture. Coastal concrete structures, in particular, are exposed to extreme conditions brought about by hydrometeorological processes. The Philippines, as a maritime country, is highly dependent on its coastal structures for its economic development, mobility, and national defense. The country is exposed to the impacts of extreme conditions and natural hazards by virtue of its geologic setting.

In this study, concrete assessment is applied to three major ports using concrete petrography complemented by standard physical tests. Petrography offers information on concrete composition, distribution of air voids, water-cement ratio used, depth of carbonation, and the presence and degree of cracking and concrete deterioration phases. The use of petrography in concert with physical testing greatly expands the understanding of the impacts of extreme coastal conditions to these port structures. Structures assessed exhibited carbonation of the cement paste and the presence of cracking, alkali-silica reaction, and delayed ettringite formation. The researchers investigated further, the possible causes of the concrete degradation including the material sources, the existing coastal and climatological conditions on site, and past extreme weather events such as tropical storms and high waves. These technical findings will contribute to the formulation of standards and recommendations on appropriate concrete cover thickness and mix designs for the assurance of resilient coastal concrete structures in the face of extreme weather conditions.

How to cite: Ybañez, A. A., Aguda, N., Cuyno, K., Jimenez, J. J., Tanpoco, C. M., Antonio, R., and Arcilla, C.: Assessment of Coastal Concrete Structures Exposed to Extreme Weather Conditions using Concrete Petrography (ASTM C856), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18909, https://doi.org/10.5194/egusphere-egu24-18909, 2024.

Climate change and sea level rise is expected to increase the flood risk in coastal regions. These areas will not only suffer from more frequent and severe storm surges, it will also become increasingly challenging to naturally discharge the excess water from rivers and precipitation. Large pumping stations along the coast can contribute in discharging excess water if high sea levels prevent the natural outflow. A large pumping station is already employed in the Netherlands at IJmuiden, which is responsible for the drainage of a large area in the western Netherlands, including cities as Amsterdam and Utrecht. Pumping stations will often not function at full capacity due to failures, maintenance, or high sea water levels that may reduce the operational pump capacity or even exceed the operational threshold.  Pump reliability can have a significant effect on the flood risk in a water system and thereby strongly influence the optimal investment strategy. Nevertheless, the influence of pump reliability is not considered when designing pumping-sluice stations.  Two separate approaches (graphical and computational modelling) were developed in this study to include pump reliability in when determining the required buffer and pump capacity in a water system. The graphical approach is most suitable for comprehensive visualizations and sensitivity analysis of the water system, while the computational modelling approach allows for a more detailed analysis. Including pump reliability in the design can lead to an increase in required buffer capacity or pumping capacity. However, it can also optimize the mitigation strategy and prevent unnecessary investments as the sensitivity of water systems depends on the system’s characteristics such as water storage capacity.

How to cite: Van Gijzen, L. and Bakker, A.: The effect of the reliability of pumping stations on coastal flood risk under a changing climate , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16618, https://doi.org/10.5194/egusphere-egu24-16618, 2024.

Physical barriers such as subsurface dams (SSD) and cutoff walls (COW) and hydraulic barriers such as freshwater recharge and saltwater pumping are some of the widely studied control measures to mitigate saltwater intrusion (SWI) in coastal aquifers. Past studies have focused on optimizing the design of these control measures, including installation location, depth, pumping, and injection rates under the specified hydraulic and boundary conditions of the aquifer. On the other hand, sea-level rise (SLR) and freshwater flux reduction (FFR) (caused by groundwater pumping and/or reduced aquifer recharge) alter the hydraulic conditions and can potentially change the optimum design of these control measures as well as their performances. Unlike hydraulic barriers with some potential to adapt to these altered hydraulic conditions (by modifying pumping and injection rates), physical barriers are fixed and not easily modifiable. Hence, the performances of physical barriers are highly subjected to changing climate conditions (SLR and FFR), and systematic vulnerability assessment of physical barriers is lacking. Here, we use a widely studied field-scale problem to assess the vulnerability of SSD and COW under SLR and FFR scenarios using constant flux inland boundary conditions. Our results indicate that SSD and COW are resilient to SLR, with SSD being more effective compared to COW. Furthermore, SSD and COW are highly vulnerable to FFR. While SSD is more effective than COW under small declines in FFR, COW outperforms SSD under large FFR. Using sensitivity simulations, we show that our results are valid across a range of aquifer and barrier parameters. These results add insights to the design of physical barriers, taking into account future climatic conditions. Also, our analysis aids in selecting appropriate mitigation measures to address the changing climatic conditions.

How to cite: Sadhasivam, R., Srinivasan, V., and Nambi, I.: Are the physical barriers sustainable to saltwater intrusion under changing climatic conditions?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18125, https://doi.org/10.5194/egusphere-egu24-18125, 2024.

Small Island Developing States (SIDS) comprise a group of 58 nations identified by the United Nations as facing unique sustainability challenges. These challenges include high exposure to climate change and a lack of data and limited resources. The effects of climate change are already observed in SIDS, notably an increase in the magnitude and frequency of natural disasters, biodiversity loss, ocean acidification, coral bleaching, sea-level rise, and coastal erosion. The coastal zone is considered to be the main economic, environmental, and cultural resource of SIDS, making them particularly vulnerable to the adverse effects of climate change. This project focuses on quantifying and disentangling coastal changes, including erosion, accretion and coastline stability. Existing literature lacks a comprehensive understanding of the patterns of coastal changes, as well as the main anthropogenic and environmental drivers involved. We address this research gap by quantifying the challenges that SIDS encounter, with a particular emphasis on coastal changes.

The approach is data-driven, relying on observational time series extracted from remote sensing (e.g., Sentinel-2, Planet Scope, Landsat missions), in situ measurements (e.g., tide gauge data), and open-access databases. We have developed a robust method based on image segmentation to extract the island's shape over time, enabling us to illustrate the island's dynamics and obtain reliable time series of the coastline position.

 The main drivers of coastal changes are then identified and quantified using time series analysis methods, including causal inference and discovery methods, for SIDS worldwide. We place a specific focus on the Maldives (Indian Ocean) due to its low elevation and high human activity. Additionally, the methodology expands to investigate a spectrum of issues, including the impacts of human activities (e.g., land reclamation, sand mining, shoreline armouring) on the natural responses of coastlines, as well as the effects of confounding factors or common drivers (e.g., Indian monsoon, tropical cyclones, and El Niño/Southern Oscillation). The ultimate goal is to develop a spatiotemporal variable coastline vulnerability index by integrating socioeconomic and environmental time series data, facilitating the assessment of environmental policies in SIDS.

How to cite: Prasow-Émond, M., Plancherel, Y., Mason, P. J., Piggott, M. D., and Wahl, J.: Impacts of Climate Change on Small Island Nations: A Data Science Framework using Remote Sensing and Observational Time Series, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18919, https://doi.org/10.5194/egusphere-egu24-18919, 2024.

In the intricate tapestry of coastal urban areas, the realities of climate change unfold with discernible impacts across regions like Nigeria, Chad, Cameroon, Rwanda, Somalia, and Kenya. Experiencing a spectrum of climate-related challenges, from extreme weather patterns to rising sea levels, these areas underscore the pressing need for proactive measures. The Lake Chad Basin, encompassing Nigeria, Chad, and Cameroon, grapples with heightened climate upheavals, exacerbating existing insecurities. Simultaneously, nations in East Africa, such as Rwanda, Somalia, and Kenya, navigate the repercussions of unpredictable weather patterns affecting agriculture, water resources, and community livelihoods. The humanitarian community, entrenched in its response, often finds itself constrained by the reactive nature of interventions. Here, the transformative potential of predictive analysis and artificial intelligence (AI) shines a light on proactive measures. Consider the INFORM Climate Change Index¹, a forward-looking projection providing quantified estimates of climate change impacts on the future risk of humanitarian crises and disasters. Developed through collaboration between the Euro-Mediterranean Center on Climate Change and the Joint Research Centre of the European Commission, this innovative index modifies indicators in the hazard and exposure dimensions based on projected climate and socio-economic trends. The link between anticipatory humanitarian action and predictive analysis becomes more apparent when we delve into the numbers. Incorporating digital solutions, especially AI, significantly boosts the effectiveness of anticipatory measures. Recent initiatives show that when predictive analysis, AI-driven solutions, and innovative indices are integrated, a substantial percentage of climate-related events can be avoided. These digital tools empower coastal urban communities to construct preemptive barriers, devise effective mitigation strategies, and navigate challenges with resilience. The transformative impact is not just theoretical; it's quantifiable, with numbers indicating that a significant portion of potential crises can be averted through proactive measures informed by predictive analytics. This groundbreaking approach, where digital solutions are seamlessly integrated into anticipatory humanitarian action, transforms coastal urban communities from mere responders to architects of their climate destinies. The narrative, rooted in real-world examples and bolstered by numerical evidence, showcases the tangible benefits of technology. The path forward involves AI, predictive analysis, and innovative indices as indispensable tools in scripting resilience stories. As we explore the depths of climate-induced insecurities across diverse regions, the abstract underscores the pivotal role of AI, coupled with innovative indices like INFORM Climate Change, in guiding coastal urban communities towards a future where climate challenges are met with informed, proactive, and resilient responses.

¹https://drmkc.jrc.ec.europa.eu/inform-index/INFORM-Climate-Change

How to cite: Ndatabaye, S., Dabiri, Z., Lang, S., and Wendt, L.: Anticipatory Climate Resilience in Coastal Urban Areas: Transformative Impact of Predictive Analysis, AI Solutions, and Innovative Indices, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20281, https://doi.org/10.5194/egusphere-egu24-20281, 2024.

Inland and coastal floods are becoming more frequent and severe, affecting natural and socioeconomic systems. Coastal urban areas, where population and economic activity are highly concentrated, appear as particularly vulnerable to these events. Local adaptation to climate change benefits from the integration of opinions from different stakeholders in the design and decision process, helping practitioners, planners, and policy makers to address climate change. This process can be operated under the umbrella of Living Labs, where innovative solutions to specific problems can be defined, designed and created through a social-iterative approach. Multicriteria analysis (MCA) is a suitable decision-making tool to develop within the context of Living Labs and climate change adaptation as it allows to capture perceptions from different actors about adaptation measures characterised though various criteria. This study presents the results of an MCA applied to the evaluation of Ecosystem-based Adaptation (EbA) to flooding in three Coastal City Living Labs of the Iberian Peninsula: An ex-ante analysis in Vilanova i la Geltrú (Spain) focused on potential measures to be implemented in an intermittent river-stream; Benidorm (Spain) followed an interim evaluation of planned EbA to address flooding in different city areas; and an ex-post analysis was performed in Oeiras (Metropolitan area of Lisbon; Portugal) to assess the perception of different stakeholders about the performance of already implemented measures along a river stream.

How to cite: Riera Spiegelhalder, M. and Campos Rodrigues, L.: The contribution of participatory decision making in the planning of ecosystem-based adaptation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1285, https://doi.org/10.5194/egusphere-egu24-1285, 2024.

Now, more than ever, the ‘eye-in-the-sky’ needs to work with the ‘grunt-on-the-ground’. This is
not just a matter of ground-truth checks on accuracy of remote mapping. For biodiversity
forecasts, of abundance, threats and restoration for species and systems, one needs to map not
only ground cover, but soil and water quality and content, not to mention individuals of small
species. Beneficial activities at local community and citizen level are needed too, as well as
guidance and motivation from above. This will require engagement and love of nature as well as
the support of governments that enable services from nature and do not ignore climate change.
Encouraging benefits at local level, and linkage with guidance or imagery from above, requires
simple communication and for conservation chores to become fun. It requires conservation
communication networks for the 80% in the world who do not speak English. Ideas for
transacting local knowledge as an enjoyable engagement were developed in a Framework 7
project to design a Transactional Environmental Support System but considered too challenging
socially. This verdict stimulated multilingual networking in the civic sector, leading to 10-
language www.sakernet.org (2014) and 23-language www.perdixnet.org (2017) for UNEP and
NGOs, before 43-language www.naturalliance.org was launched for IUCN in 2019. A new
Horizon project is now addressing issues of social motivation for engagement with such systems
in a project for A PROactive approach for COmmunities to enAble Societal Transformation which
is running from November 2023 for 3 years. PRO-COAST (project 101082327) brings together 20
partners from 14 countries to develop, apply and validate an innovative socio-ecological
framework for the study of coastal ecosystem dynamics for the benefit of the people most
exposed to risk deriving from biodiversity loss. Starting in 9 case studies across Europe, it will
develop scaled-up multilingual networking for much wider areas along coasts and inland, using
the global-with-local information networking developed by European Sustainable Use Group.

How to cite: Mühle, J., Ewald, J. A., and Kenward, R. E.: Does everyone speak English?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21671, https://doi.org/10.5194/egusphere-egu24-21671, 2024.