Climate change threatens coastal heritage worldwide

Climate change threatens coastal heritage worldwide | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Physical Sciences - Article Climate change threatens coastal heritage worldwide Michalis Vousdoukas, Joanne Clarke, Roshanka Ranasinghe, David Bescoby, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7654288/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Sea levels are increasing at an accelerated rate 1,2 and this is expected to increase flooding along coastlines worldwide 3 . While cultural and natural heritage sites are among the assets most exposed to this threat 4,5 , a unified global assessment is currently lacking. Here we assess coastal flood exposure of all nearshore UNESCO World Heritage sites worldwide, under different global warming scenarios. We estimate that for a scenario with current climate mitigation policies and action, by the end of this century around one third of World Heritage Sites could be exposed to floods, corresponding to more than 1.1 million hectares of protected and preserved land. Limiting warming to the 1.5°C Paris agreement target would save 89 heritage sites from being exposed. Large countries are projected to face widespread exposure while smaller nations risk losing entire heritage systems. Combining our findings with the ND-GAIN index 6 shows that 32 countries with low adaptive capacity are expected to experience high heritage exposure, especially Small Island Developing States. To safeguard these irreplaceable cultural and natural treasures, it is imperative to scale up heritage adaptation efforts and increase support for vulnerable regions. Earth and environmental sciences/Climate sciences/Climate change/Climate-change impacts Scientific community and society/Social sciences/Interdisciplinary studies Earth and environmental sciences/Natural hazards Scientific community and society/Scientific community/Culture/Architecture Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Main Coastal flooding is already affecting nearshore development and ecosystems and this is expected to more frequent and more severe due to climate change and sea-level rise (SLR) 1,7 . At the present, global mean sea level is rising at a rate exceeding 4 mm per year 2 and median SLR by the end of the century is projected to vary between 44 and 70 cm under 1.5 o C and 4 o C global warming, respectively 8 . Consequently, several studies have assessed the extent and the impacts of the anticipated increase in coastal floods, projecting extensive loss and damage to coastal populations and unprecedented challenges to coastal adaptation 3,9,10 . In addition to nearshore assets and critical infrastructure, rising seas are expected to also affect natural and cultural heritage worldwide 4,11,12 . World Heritage Sites (WHS) can vary from ancient castles and cities to biodiversity-rich ecosystems. They are increasingly threatened by rising temperatures, extreme weather events, and environmental change across all regions of the world 5,13–15 . These impacts include physical degradation of historic buildings, loss of archaeological sites and threats to intangible heritage such as traditional knowledge and cultural practices, especially among Indigenous communities 16–18 . Cultural heritage fosters identity, continuity, and community cohesion 19 and natural heritage, apart from habitats, can provide valuable carbon sinks and green infrastructure for ecosystem-based adaptation 20,21 . UNESCO therefore highlights that heritage must be safeguarded not only for its intrinsic value but also for its potential to foster resilience, identity, and sustainable development across generations 22 . The UNESCO World Heritage List currently includes over 1,200 WHS across 168 countries, comprising cultural, natural, and mixed sites that vary widely in heritage type and size, from compact monuments to vast natural reserves 23 . A site is considered as World Heritage when it possesses Outstanding Universal Value; i.e. a cultural or natural significance so exceptional that it transcends national boundaries and is of common importance for present and future generations 23 . Local and regional assessments of the exposure and vulnerability of coastal heritage to climate change have been growing in the past decade 4,12,24–27 . Yet a global assessment of coastal flood risk is missing, even though such information is particularly needed to help coordinate global adaptation efforts, such as those under the Global Goal on Adaptation (GGA) 28,29 . The latter recognizes the need to protect cultural heritage from the impacts of climate change, including the preservation of cultural practices and heritage sites. In this study, we deliver the first comprehensive global flood risk assessment for UNESCO WHS found along the world’s coastlines. As a foundation, we develop a global geospatial dataset capturing the constituent components of coastal WHS located below 20 m above sea level 30 . This dataset comprises 1,211 digitized site polygons derived from 385 coastal WHS spanning cultural, natural, and mixed designations, and covering over 235 million hectares worldwide. We then combine the WHS dataset with the latest SLR projections and other ocean/geospatial data, conducting simulations with a state-of-the-art hydrodynamic model. We assess global warming scenarios of 1.5 o C, 2 o C, 3 o C and 4 o C above pre-industrial level and the 100-year flood event. Results are reported at site, country, regional and global scales, covering both median estimates, and the very likely range (5 th -95 th percentile). Global Heritage is already exposed to coastal floods At present, approximately 117 [115-122] WHS are globally exposed to a 1-in-100-year coastal flood event (values in brackets correspond to the 5 th - 95 th percentile), accounting for circa 10% of the total inventoried coastal sites. This represents an affected area between 78,940 and 167,130 hectares at a 90% confidence interval and approximately 0.11% of the total coastal heritage area. Europe accounts for the largest share of currently affected WHS (36%), followed by Asia (23%), Africa (13%), North America (11%), and Small Island Developing States (SIDS) (10%; Figure 1c). However, when considering the proportion of sites affected within each region, North America and SIDS stand out, with nearly 30% of their WHS exposed (Figure 1b). Regarding the flooded heritage area, North America is disproportionately affected, accounting for more than 44% of the global, or 55,635 ha. Europe has 31,713 ha exposed, followed Africa (20,152 ha) and Australia/New Zealand (13,152 ha). These values correspond to circa 95% of the affected heritage area with SIDS and Asia contributing a minor share (2.10 and 0.94%, respectively), and Central and South America almost zero. It is important to highlight that more than 44% of the total heritage area presently flooded by the 100-year storm is found in USA, i.e. more than 55,421 ha (Figure 1d). Other countries already facing severe challenges to heritage include United States, Italy (24,774 ha), Mauritania (16,125 ha) and Australia (13,152 ha). When considering the number of affected WHS, the United Kingdom has the highest number (24), while Japan follows with 19 (Figure 1c) and countries such as Belize, the United States, and Australia have at least 5. In some cases, entire national heritage inventories are already at risk, such as those of Kiribati, Bangladesh, Fiji, and Palau (Figure 1a). Some of the above are SIDS, a fact that underscores the sensitive situation in such small islands, where even modest SLR can trigger frequent inundation of large portions of land and heritage assets, including globally significant breeding habitats for birds, corals, turtles and fish 32 and atoll-island cultural landscapes 33 . Increasing flood exposure of global heritage with global warming Flood exposure of coastal WHS continues to rise throughout the century for all warming scenarios. This is due to the fact that sea levels are projected to rise even after global temperatures stabilize 31 . By 2050, the median flooded heritage area is projected to more than double under 1.5 °C and almost triple under 4.0 °C warming compared to present-day conditions (Figure 2a). This corresponds to flooded areas ranging from approximately 258,736 to over 353,373 hectares, depending on the scenario. The number of affected sites rises at a slower rate than the flooded area, indicating that existing sites are projected to face worsening conditions rather than new sites becoming exposed (Figure 2a-b). By 2100, flood hazard is projected to further rise and almost a million hectares could be affected by a 100-year event under the 4.0 °C warming trajectory, a more than six-fold increase compared to the baseline (Figure 2a). Under the same scenario, the number of affected WHS could increase from 117 today to as many as 402 (Figure 2b). Limiting warming to 1.5 °C, in line with the Paris Agreement goals, would prevent 101 WHS from being affected worldwide, in comparison to the 4.0 °C warming scenario. Under 1.5 °C warming, North America is projected to have the largest share of flooded heritage area by the end of the century (46.96% of the global total), followed by Europe (21.08%) and Africa (20.33%; Figure 2d). Asia and Australia/New Zealand remain around 5% and SIDS along with Central and South America contribute only marginally compared to the other regions. These relative contributions are consistent across warming scenarios, although the absolute magnitudes increase with higher warming. For example, under 4.0 °C warming, North America and SIDS will have more than half of their WHS affected (73% and 55%, respectively), while 37% of sites in Africa and Australia/New Zealand are projected to be at risk. In the remaining regions, approximately 30% of sites are projected to be affected. Central and South America is the region with largest projected increase by 2100 compared to the baseline, both in terms of the number of affected WHS (from 3 to 16 under 4.0 °C warming) and the heritage area affected (from 8 to 5,490 ha). Substantial increases are also projected for Europe, with the affected heritage area growing sixfold and the number of affected sites increasing from 42 to 199 by the end of the century (Figure 2c). In Asia the affected area increases almost 20-times, with the number of affected sites tripling. Assessing the percentage of each site’s area affected provides a more detailed perspective on flood exposure and helps focusing on smaller (mainly) cultural WHS where even partial inundation can compromise integrity and cultural value. By 2050, under 1.5 °C warming, the number of WHS with less than 25% of their area exposed (‘mild exposure’) increases from 112 (Figure 3a) in the baseline to 197 (Figure 3b). Nine sites fall into the ‘moderately affected’ (25%-50% of area affected), while one site enters the ‘high exposure’ category (50%-75%). These transitions represent a net increase of 95 affected WHS globally at 1.5 °C, with all still experiencing partial rather than total inundation. By 2100, and under the same warming scenario, 89 more WHS are exposed to the 100-year event, which means 67, 7 and 15 sites additional sites are exposed mildly, moderately and highly, respectively, compared to the year 2050 (Figure 3c). Not mitigating emissions and allowing the temperature to reach 4 o C, will result in 14 severely exposed WHS, the majority of which are found in Europe (Figure 3d). The highest exposure is concentrated among smaller cultural sites, such as the Tower of Belem, Portugal (‘moderate exposure’ by 2050 under 1.5 °C; ‘severe exposure’ by 2100 under 4.0 °C), Miike Coal Mine and Miike Port, part of the Sites of Japan’s Meiji Industrial Revolution, Japan (‘high exposure’ by 2100 under 1.5 °C; ‘severe exposure’ by 2100 under 4.0 °C). Two iconic WHS projected to escalate rapidly to ‘high exposure’ by 2100 under 4 °C are the Al Zubarah Archaeological Site, Qatar, and La Tour Dorée de Camaret-sur-Mer, part of the larger "Fortifications of Vauban", France. At the national level, Mexico stands out as the most exposed country, accounting for circa 25% of the global flooded heritage area by 2100, across all considered warming scenarios (Figure 4b). The United States is another country with extensive land area, long coastline and sizable heritage inventory projected to contribute between 20% and 22.6% of the total global affected heritage area, depending on the scenario. Mauritania and Romania each account for 8%–9% of the global flooded area, highlighting the exposure of low-lying heritage-rich regions in both Africa and Europe. In terms of the number of affected WHS, larger countries dominate. By 2100, under a 1.5 °C warming scenario, the United Kingdom is projected to contribute nearly 16% of all affected sites, followed by Japan (13%), the Russian Federation (9%), and Mexico (6%). These countries also show the largest increases in newly affected sites compared to present-day conditions, i.e. 24 in the UK, 20 in Japan, 26 in Russia, and 16 in Mexico (Figure 4a). Discussion Our findings reveal the multiple levels and dimensions of coastal heritage exposure to SLR. It is important to highlight that there is not a single indicator that could be representative worldwide. The area or the percentage of each WHS affected can be a valid criterion for sites that are homogenous, but the latter is often not the case. For example, the Island of Rapa Nui (Easter Island) covers over 16,600 ha of land 34 , from which only 0.001% is projected to be affected by flooding (up to 17.8 ha; 4.0 °C by 2100). Yet, more than 90% of standing moai that represent Rapa Nui’s most iconic attributes are positioned along the coast 35 , implying that the part of the site that is most exposed to floods has disproportionately higher heritage value (Figure 5a). Similar challenges arise for many sites where important heritage attributes are close to the sea. Some such examples include the north African archaeological sites of Leptis Magna 36 in Libya (6.8 ha; 4.0 °C by 2100; Figure 5b) and Tipasa 38 in Algeria (6.8 ha; 4.0 °C by 2100); Chief Roi Mata's Domain 39 in Vanuatu (12.8 ha; 4.0 °C by 2100); the Statue of Liberty 40 (1.4 ha; 4.0 °C by 2100); and the iconic 15th Century Khan-e-Jahan architecture at the Historic Mosque City of Bagerhat 37 (13 ha; 4.0 °C by 2100; Figure 5c). Several of the WHS that are projected to be severely exposed (Figure 3) have coastal fortifications in place, many of which are centuries old. These may prove resilient to limited erosion and episodic inundation but may not sustain contemporary or projected rates of sea-level rise. For example, the Tower of Belem, Portugal was built in 1514 to commemorate Vasco da Gama's expedition. Site-level vulnerability assessments will be necessary to determine the resilience of such sites against higher sea levels. Further, several WHS include ‘buffer zones’ that serve as special protection zones around each World Heritage property. These buffer zones are important to the integrity and authenticity of the WHS, positioning the site within a wider cultural and heritage landscape, particularly when viewed from the sea. Recent research highlights how even modest global warming scenarios could translate into a sharp increase in heat and moisture disturbance of World Heritage 13 . Our study shows that coastal WHS could substantially suffer additional strain from coastal flooding. Large countries contribute substantially to global totals due to the size and proximity of their heritage inventories (Figure 4). Smaller nations often face existential risks to their entire heritage systems. This underscores the need for differentiated adaptation strategies that address both the widespread exposure in large countries and the concentrated, high-stakes risks in smaller, low-lying nations. In addition, to be effective, heritage-focused adaptation planning must account for differentiation across the attributes of cultural, natural and mixed sites. At the same time, many WHS, especially in low- and middle-income countries, face limited adaptive capacity stemming from technological, financial, and governance challenges. These systemic constraints are captured by the Notre Dame Global Adaptation Index (ND-GAIN) 6 , which evaluates a country’s vulnerability to climate change and its readiness to implement adaptation measures. The index draws from over 45 indicators across six sectors (food, water, health, ecosystem services, human habitat, and infrastructure) and assesses readiness through economic, governance, and social dimensions. A score below 50 indicates limited capacity to absorb and operationalize adaptation investments. To highlight disparities in adaptive capacity and associated risks, we mapped heritage exposure against ND-GAIN scores (Figure 6; Supplementary Table 1). Focusing on values for the median 1.5 °C warming scenario by 2100, we identify 32 countries with ND-GAIN scores below 50 that host WHS projected to be exposed to coastal flooding. Among these, Mexico and South Africa stand out for having more than 10 affected WHS, while Mauritania, Namibia, Senegal, and Vietnam rank in the top 20% for total heritage area affected; each exceeding 5,500 hectares. Additionally, Cote d'Ivoire, Micronesia, and Venezuela are among the countries with the highest percentage of their heritage area affected, surpassing 3%. These findings underscore a growing inequality in climate impacts on cultural heritage. Countries with limited adaptive capacity are not only more vulnerable to sea-level rise but also less equipped to implement adaptive measures. This calls for targeted international support, capacity-building, and inclusive adaptation planning to safeguard heritage in regions where the risks are greatest and the resources most constrained. Many communities have already begun implementing adaptation strategies providing valuable lessons for safeguarding WHS. Urban and cultural landscapes require integrated flood risk mapping, drainage improvement and infrastructure retrofitting. For example, in Venice, Italy, the MOSE flood barrier system shields the city from high tides, complemented by more local upgrades in the drainage network and buildings 41,42 . The Statue of Liberty in the United States underwent infrastructure elevation and flood-proofing following Hurricane Sandy 43 . In Puerto Rico, Fort San Juan de la Cruz has been stabilized and retrofitted to withstand storm surges and salt spray 44 . Natural heritage sites have distinct characteristics and require different adaptation strategies, such as ecosystem restoration and community-based conservation. Belize’s Bacalar Chico National Park uses mangrove restoration and marine protected areas to buffer storm surges and support biodiversity 45 . Vietnam’s Ha Long Bay integrates mangrove reforestation and coral reef protection through its Integrated Coastal Zone Management (ICZM) plan 46 . The Everglades National Park in the United States is undergoing large-scale wetland restoration to combat saltwater intrusion 47 . Policy and planning frameworks are increasingly incorporating climate resilience. The Wadden Sea, shared by Germany, the Netherlands, and Denmark, employs a trilateral Climate Change Adaptation Strategy 48 . Qatar’s Al Zubarah site benefits from a national climate action plan and site-specific management measures 49 . Archaeological and coastal fortifications benefit from structural reinforcement and digital documentation. In the UK, Hadrian’s Wall is part of a UNESCO pilot project using GIS tools and stakeholder engagement to inform climate-resilient heritage management 50 , including coastal risks. Safeguarding heritage in the face of rising seas will require coordinated global action involving national governments, UNESCO and other key actors. This could include targeted support for countries with low adaptive capacity through loss and damage and other such instruments, integration of cultural heritage into national adaptation plans, and investment in long-term resilience. The upcoming rounds of nationally determined contributions (NDCs) and national adaptation plans (NAPs) under the Paris Agreement offer a critical opportunity to embed heritage protection into climate policy frameworks 51 . Ultimately, protecting coastal heritage is a shared global responsibility, not only about preserving the past, but also about securing cultural identity, ecological integrity, and social cohesion for future generations. Methods Global Coastal Heritage Data Set This study utilizes a newly developed global geospatial dataset of UNESCO World Heritage Sites (WHS) located within the Low-Elevation Coastal Zone (LECZ). The dataset comprises 1,211 digitized site polygons derived from 385 UNESCO WHS that include cultural, natural, and mixed designations 30 . These sites span over 235 million hectares globally including 990 cultural sites, 204 natural sites and 17 mixed sites. The selection of sites was based on UNESCO’s official WHS list as of 2023 and were included if any part of their designated area was located at or below 20 m AMSL 52 . It represents the first comprehensive spatial delineation of coastal WHS at global scale, enabling quantitative exposure assessments to climate-related coastal hazards. A standardized digitization protocol was developed to ensure consistency and accuracy across the dataset. The primary tools used were Google Earth Pro and georeferenced UNESCO site maps. Digitization was performed by a trained team of 10 individuals, coordinated by GIS and heritage experts. The digitization process involved site identification, site polygon creation, resolution reconciliation, integration of existing data sets, attribution data, and technical validation. A heritage specialist reviewed UNESCO site coordinates and maps to identify qualifying sites. Google Earth (GE) imagery and elevation data were then used to verify site location and elevation. Digitizers used GE to delineate site boundaries, either directly from satellite imagery or by overlaying georeferenced UNESCO maps. Tie-points were used for georeferencing maps lacking coordinate grids. Sites were digitized at a nominal scale of 1:1000, with finer scales (e.g., 1:250) used for small or complex sites. Only core site boundaries were digitized; buffer zones were excluded due to lack of standardization and some sites were split into sub-sites to reflect geographic separation necessary for analysis (e.g., islands or atolls). Each polygon was assigned standardized metadata, including site name, UNESCO code, country, area, and regional classifications (UNESCO and IPCC WGII sub-regions). Digitizers maintained logs documenting source quality, digitization challenges, and decisions made during the process. These logs supported subsequent quality control and validation. In addition to original digitization, data from four external sources were integrated: African coastal WHS from Vousdoukas et al. 12 , Mediterranean WHS from Reimann et al. 4 , protected area polygons from the World Database on Protected Areas (WDPA) 53 , and UK coastal WHS from Historic England 54 . All external data were reviewed for spatial accuracy and adjusted to conform to the GHMP digitization protocol. A stratified sampling approach was used to validate the spatial accuracy and attribute integrity of the dataset. Sixty WHS (5% of the total) were randomly selected across 30 strata defined by polygon area and geographic sub-region. Validation involved both qualitative and quantitative assessments of source map quality based on legibility, spatial referencing, and boundary clarity; Google Earth Imagery Visibility based on the clarity of site features in satellite imagery; and polygon accuracy assessed using a 5-meter buffer around each polygon. Deviations from visible boundaries in GE were measured and normalized by polygon perimeter. WHS scoring below a defined threshold were flagged for review. Of the 60 sampled WHS, 92% were deemed to have optimal digitization accuracy. Approximately 8% showed errors and 6.7% had attribute data inaccuracies that were corrected. Coastal flood modelling framework We assess the WHS’ flood hazard from Sea-Level Rise (SLR) and episodic flooding during the 21st century. The analysis is based on the modular framework LISCOAST (Large-scale Integrated Sea-level and Coastal Assessment Tool). We consider four global warming levels that span a range from ambitious mitigation to no emission policies: 1.5°C, 2°C, 3°C, and 4°C relative to pre-industrial times. For each of these scenarios we generate probabilistic projections of mean and extreme sea levels that give rise to episodic flooding and combine them with the WHS dataset to assess flood exposure. Present day extreme sea levels Coastal areas are exposed to rising mean sea level (MSL) and episodic high sea levels under extreme atmospheric conditions. Extreme sea levels (ESL) are driven by the combined effect of MSL, tides and water level fluctuations due to waves and storm surges. We derive the contribution of each of these drivers with state-of-the-art modelling tools and datasets and combine them to obtain ESLs every 1 km along the ice-free coastline. For the baseline period, spanning from 1980 until 2020, we run a reanalysis of waves and storm surges based on a two-way coupled ocean model using an unstructured grid with a resolution ranging from ~50 km offshore to ~2 km nearshore. The coupled model system includes the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM) 55 , configured in its two-dimensional barotropic mode and the 3rd-generation spectral wave model (WWM-V) 56 . The model accounts for the combined effects of wind, atmospheric pressure gradients, and tides. We use bathymetric data from the European Marine Observation and Data Network (EMODnet), available in angular coordinates at a resolution of 1/8 arc-minute (0.0021° of latitude and longitude; http://www.emodnet.eu/bathymetry) which we interpolate onto the computational grid. We apply the coupled model to produce a reanalysis of waves and storm surges, forced by sea-level pressure and wind speed data from ERA5 57 . The reanalysis is carried out without tidal forcing to ensure that our hindcast resolves the weather-driven component of ESLs; without the stochastic modulation of spring/neap tidal variations. Further details about the model setup and the validation can be found in Mentaschi et al. 58 . Since, it is known that non-linear interactions between tides, waves and storm surges can be important in some areas, we apply a correction for these effects following an approach similar to Arns 59 . To that end, we run a shorter 10-year reanalysis including tidal forces and from the overlapping time series we construct copulas to produce a correction function for non-linear tidal effects on the water level anomaly and the significant wave height. To improve the accuracy of the reanalysis data we implement some additional steps as detailed below. Using satellite altimetry data we apply a Quantile Mapping Bias Correction on both the water level anomaly and the significant wave height. This is done after compiling all coinciding model and satellite values along 1 o x 1 o cells. To further improve the cyclone related storm surge estimates which have not been sufficiently resolved by our reanalysis, we did additional simulations of tropical cyclone driven sea level anomalies using the Delft3D-FM model 60 forced by the IBTrACS best-track archive 61 . The reanalysis values are corrected by considering the tropical cyclone runs values when they are higher than those of our ERA5 runs. More information about the approach and data can be found in Vousdoukas et al 10,62 . Spectral wave parameters provide one characteristic estimate for wave height, direction and period from the whole spectrum and therefore lack the detail needed to describe wave processes along complex shorelines. To overcome this shortcoming, we use the spectral peaks from the WWM-V model output and we propagate each peak along a global transect dataset with 1 km alongshore resolution. The transect dataset includes information on the shoreline position, orientation, submerged and subaerial slope, among others. Details of the data and methods used to generate transects are provided in Athanasiou et al. 63 . We benefit from the complete spectral information from the wave model to propagate each peak at each time stamp along its corresponding transect using Snell’s law 64 . We then estimate the wave breaking height combining the peak wave parameters with the submerged profile slope. Subsequently, we obtain the wave run-up height R 2 based on the Stockdon empirical formula 65 , after combining the breaking wave height and period with the subaerial beach profile slope. The above steps result in wave runup height estimates for each spectral peak and we consider the highest value as the characteristic for the specific time stamp. We then combine the wave runup with the storm surge to obtain the meteorological tide and apply non-stationary extreme value analysis 66 to the time series to obtain estimates for different return periods. Baseline ESLs are produced by combining the final meteorological tide time series with tidal elevations obtained from the FES2022 model 67 . Following the approach of Vousdoukas et al. 62 , the high tide water level is considered taking into account the range due to the spring-neap tide cycle. Sea-level rise projections Relative SLR projections are obtained from latest IPCC AR6 assessment 8,68,69 and incorporate the effects of the various components of future SLR, including steric SLR, dynamic sea-level change, contributions from glaciers and ice-caps, land-water storage and Glacial Isostatic Adjustment, among others. Projections of ESLs up to 2100 All ESL components (RSLR, tide, surges and R 2 ) are expressed as probability density functions (PDFs) that account for the different sources of uncertainty and are combined through Monte Carlo simulations to generate probabilistic estimates of ESLs for all scenarios in each coastal segment (1 km alongshore resolution). Non-stationary extreme value analysis 66 is then applied to performed for a range of return periods (i.e. 1, 2, 5, 10, 20, 50, 100, 200, 500, 1000 and 5000 years) PDFs of the corresponding return values of ESL throughout this century. Coastal flooding Following Vousdoukas et al. 70 , we perform 2-D hydraulic simulations along the entire coastline to estimate inundation extent and depth. To that end, we use the Lisflood-ACC model 71 at 30 m spatial resolution, using the estimated ESLs as forcing and considering hydraulic roughness derived from land-use maps 72 . Up to high-tide water levels (i.e. combination of mean sea level and high-tide) we apply the bathtub approach, and land below this sea water level and the corresponding assets are considered permanently inundated due to sea-level rise. For episodic flooding, Liscflood-ACC is applied for each coastal segment with the model domain extending up to 200 km landwards to ensure the inclusion of all potentially hydrologically connected areas that may lie inland and away from the coast. The flood simulations are based on the recently released Delta DTM 73 . Finally, flood maps were superimposed on the WHS polygons to identify the portions of heritage sites exposed to flooding. Declarations Data availability The models and datasets presented are part of the integrated risk assessment tool LISCoAsT (Large scale Integrated Sea-level and Coastal Assessment Tool) developed by the Joint Research Centre of the European Commission. All data used are open access and links are provided, while all source data are provided in the Supplementary Dataset. Coastal heritage data set is available here: https://doi.org/10.25375/uct.28547267 . Code availability Most of the code that supported the findings of this study is already open access with references provided in the manuscript; specific tools which are not available in public repositories will be available on reasonable request from the corresponding authors. Acknowledgements This research received support through Schmidt Sciences (N.P.S. and C.H.T.), Irish Aid (NPS), NERC Discipline Hopping for Environmental Solutions (Grant Number NE/X018385/1) (J.C. and D.B.) and the British Academy ODA Challenge-Oriented Research Grants 2024 (Grant Number IOCRG\100137) (N.P.S.). We thank the sea-level projection authors for developing and making the sea-level rise projections available, multiple funding agencies for supporting the development of the projections, and the NASA Sea-Level Change Team for developing and hosting the IPCC AR6 Sea-Level Projection Tool. Author Contributions Statement M.I.V., L.M., N.P.S. and L.F., Conceptualization; M.I.V., L.M., N.P.S., R.N., J.C., and R.R., Preliminary and Exploratory Analysis; M.I.V., N.P.S., D.B. and L.F. Methodology; all authors, Validation; M.I.V., Formal analysis; M.I.V. and N.P.S., Investigation; M.I.V., N.P.S., J.C., C.H.T., and L.F., Resources; M.I.V., L.M., D.B., J.C., N.K. and N.P.S., Data Integration; M.I.V., N.P.S. and L.F. Writing - Original Draft; all authors, Writing - Review & Editing; M.I.V, Visualization. The information and views set out are those of the author(s) only and should not be considered as representative of the European Commission’s official position. Competing Interests Statement The authors declare no competing interests. Ethics & Inclusion statement The authors declare no ethics issues such as research on race, sex, ethnicity, clinical trials or humans or animals. The list of authors is broad while local and regional studies have been considered. Supplementary information Supplementary Table 01. Country level estimates of heritage risk vs Adaptive capacity. Countries with lower adaptation readiness, i.e. Notre Dame Global Adaptation Index (ND-GAIN < 50) and their number of total and affected heritage sites, as well as the corresponding heritage area affected from coastal floods, as absolute value or percentage of the total. All values are for the median 1.5 o C warming scenario and the end of the century. References Hermans, T. H. J. et al. The timing of decreasing coastal flood protection due to sea-level rise. Nat. Clim. Change 13 , 359–366 (2023). Hamlington, B. D. et al. 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Arns, A. et al. Non-linear interaction modulates global extreme sea levels, coastal flood exposure, and impacts. Nat. Commun. 11 , 1918 (2020). Muis, S., Verlaan, M., Winsemius, H. C., Aerts, J. C. J. H. & Ward, P. J. A global reanalysis of storm surges and extreme sea levels. Nat Commun 7 , (2016). Knapp, K. R., Kruk, M. C., Levinson, D. H., Diamond, H. J. & Neumann, C. J. The International Best Track Archive for Climate Stewardship (IBTrACS). Bull. Am. Meteorol. Soc. 91 , 363–376 (2010). Vousdoukas, M. I. et al. Global probabilistic projections of extreme sea levels show intensification of coastal flood hazard. Nat. Commun. 9 , 2360 (2018). Athanasiou, P. et al. Global Coastal Characteristics (GCC): A global dataset of geophysical, hydrodynamic, and socioeconomic coastal indicators. Earth Syst. Sci. Data Discuss. 1–32 (2023) doi:10.5194/essd-2023-313. US Army Corps of Engineers. Coastal Engineering Manual . (U.S. Army Corps of Engineers, Washington, DC, 2002). Stockdon, H. F., Holman, R. A., Howd, P. A. & Sallenger, J. A. H. Empirical parameterization of setup, swash, and runup. Coast. Eng. 53 , 573–588 (2006). Mentaschi, L. et al. The transformed-stationary approach: a generic and simplified methodology for non-stationary extreme value analysis. Hydrol. Earth Syst. Sci. 20 , 3527–3547 (2016). Lionel, T. M. et al. The New FES2022 Tidal Atlas. https://meetingorganizer.copernicus.org/EGU23/EGU23-9008.html (2023) doi:10.5194/egusphere-egu23-9008. Fox-Kemper, B. et al. Ocean, Cryosphere and Sea Level Change. in Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (eds Masson-Delmotte, V. et al.) 1211–1362 (Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2021). doi:10.1017/9781009157896.01. Kopp, R. E. et al. The Framework for Assessing Changes To Sea-level (FACTS) v1.0-rc: A platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change. EGUsphere 2023 , 1–34 (2023). Vousdoukas, M. I. et al. Developments in large-scale coastal flood hazard mapping. Nat. Hazards Earth Syst. Sci. 16 , 1841–1853 (2016). Bates, P. D., Horritt, M. S. & Fewtrell, T. J. A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling. J. Hydrol. 387 , 33–45 (6 AD). European Space Agency. Land Cover CCI Product User Guide Version 2. Tech. Rep. (2017). Pronk, M. et al. DeltaDTM: A global coastal digital terrain model. Sci. Data 11 , 273 (2024). Additional Declarations There is NO Competing Interest. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7654288","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Physical Sciences - Article","associatedPublications":[],"authors":[{"id":522812144,"identity":"70ad36ec-44e4-4a56-a2ef-46f51916fda4","order_by":0,"name":"Michalis 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04:20:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7654288/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7654288/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":93369132,"identity":"36eb54a8-66ff-4cd0-a5fd-fe8b5aad29f2","added_by":"auto","created_at":"2025-10-13 06:07:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":293049,"visible":true,"origin":"","legend":"\u003cp\u003ePresent day exposure of coastal heritage to floods. Global map showing the percentage of heritage sites affected per country (a), pie plots of the number of affected heritage sites per region (b) and country (c), as well as the country level flooded heritage area (d). All plots refer to the present day, median, 100-year event. CSA: Central and South America, AUS/NZ: Australia and New Zealand, SIDS: Small Island Developing States.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7654288/v1/23806e51ff5a2b7d1b832c8e.png"},{"id":93368901,"identity":"e6033435-aa92-42be-8285-7d3b4cd12cc7","added_by":"auto","created_at":"2025-10-13 05:59:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":178962,"visible":true,"origin":"","legend":"\u003cp\u003eCoastal heritage will face increasing coastal flood risk throughout the 21\u003csup\u003est\u003c/sup\u003e century. Flooded heritage area and corresponding number of affected heritage sites globally (a,b), as well as for each of the considered geographical regions (c,d), under the following warming scenarios: 1.5\u003csup\u003eo\u003c/sup\u003eC (blue), 2\u003csup\u003eo\u003c/sup\u003eC (green), 3\u003csup\u003eo\u003c/sup\u003eC (orange), and 4\u003csup\u003eo\u003c/sup\u003eC (red). The thicker lines (a,b) and bars (c,d) express the median projections for the 100-year event, while the shaded areas (a,b) the 5\u003csup\u003eth\u003c/sup\u003e-95\u003csup\u003eth\u003c/sup\u003e confidence interval. Plots a and b show the temporal evolution of the global total, while c and d the regional distribution of the 2100 values. CSA: Central and South America, AUS/NZ: Australia and New Zealand, SIDS: Small Island Developing States.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7654288/v1/ec4b75a4afb3f8a9330c0356.png"},{"id":93368895,"identity":"9a63bcd1-adc0-4a90-8931-c75b6f975c46","added_by":"auto","created_at":"2025-10-13 05:59:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":321837,"visible":true,"origin":"","legend":"\u003cp\u003eIncreasing levels of coastal flood risk among global heritage sites. Global maps showing the level of flood intensity among coastal heritage sites worldwide, for the present day (a) as well as the years 2050 and 2100 under 1.5°C warming (b, c, respectively) and under 4°C warming scenario in 2100 (d). The values express the median projections, while the colors correspond to no (grey), mild (less than 25% of the site’s area affected; blue), moderate (25%-50%; green), high (50%-75%; orange) and severe (\u0026gt;75%; red) exposure to coastal floods.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7654288/v1/eb7813729966bced7b7413bb.png"},{"id":93369133,"identity":"7702d257-faa6-4bec-bf62-8b5059aa3b80","added_by":"auto","created_at":"2025-10-13 06:07:27","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":138350,"visible":true,"origin":"","legend":"\u003cp\u003eCountry level exposure of coastal heritage to floods. Global maps showing the number (a) and percentage (c) of heritage sites affected per country, as well as the corresponding heritage area affected for median estimate of the 100-year event, in the year 2100 and under 1.5°C warming.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7654288/v1/0f09d54c09be35657cadb9d9.png"},{"id":93368898,"identity":"e2cc9b55-eefa-4527-9945-b0c9cba0b438","added_by":"auto","created_at":"2025-10-13 05:59:27","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":423406,"visible":true,"origin":"","legend":"\u003cp\u003eExamples of cultural heritage exposed to sea-level rise. \u003cstrong\u003ea,\u003c/strong\u003e Ahu on Rapa Nui (Easter Island), \u003cstrong\u003eb\u003c/strong\u003earchaeological site of Leptis Magna, Libya, and \u003cstrong\u003ec,\u003c/strong\u003e Historic Mosque City of Bagerhat, Bangladesh. All panels are drawn from Wikimedia Commons CC license (CC BY, CC BY-SA).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7654288/v1/193c6a7d4d518c8c9cbebe0e.png"},{"id":93369134,"identity":"4cafd6f3-9f11-45cd-9a05-9102c6d9541d","added_by":"auto","created_at":"2025-10-13 06:07:27","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":133468,"visible":true,"origin":"","legend":"\u003cp\u003eCountry level estimates of heritage risk vs Adaptive capacity. Scatter plot showing the relationship between number of affected heritage sites and the Notre Dame Global Adaptation Index (ND-GAIN) adaptation readiness score for all countries containing heritage in the 21st century. The size and the color of the dots express the heritage area affected from coastal floods and the percentage of the total, respectively, all values are for the median 1.5\u003csup\u003eo\u003c/sup\u003eC warming scenario and the end of the century.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7654288/v1/27d32ab86b390ed4e3915f28.png"},{"id":93369728,"identity":"46daa468-74a2-48c9-b443-5114ee35adf3","added_by":"auto","created_at":"2025-10-13 06:15:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2085656,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7654288/v1/1ec061c7-2c1d-45fd-8d29-7652f8af8d6a.pdf"},{"id":93368894,"identity":"d8086be5-8836-492e-b7d6-090b944b17ec","added_by":"auto","created_at":"2025-10-13 05:59:27","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19521,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-7654288/v1/b5cc21cad3ec8b42860792fb.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Climate change threatens coastal heritage worldwide","fulltext":[{"header":"Main","content":"\u003cp\u003eCoastal flooding is already affecting nearshore development and ecosystems and this is expected to more frequent and more severe due to climate change and sea-level rise (SLR)\u003csup\u003e1,7\u003c/sup\u003e. At the present, global mean sea level is rising at a rate exceeding 4 mm per year\u003csup\u003e2\u003c/sup\u003e and median SLR by the end of the century is projected to vary between 44 and 70 cm under 1.5\u003csup\u003eo\u003c/sup\u003eC and 4\u003csup\u003eo\u003c/sup\u003eC global warming, respectively\u003csup\u003e8\u003c/sup\u003e. Consequently, several studies have assessed the extent and the impacts of the anticipated increase in coastal floods, projecting extensive loss and damage to coastal populations and unprecedented challenges to coastal adaptation\u003csup\u003e3,9,10\u003c/sup\u003e. In addition to nearshore assets and critical infrastructure, rising seas are expected to also affect natural and cultural heritage worldwide\u003csup\u003e4,11,12\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWorld Heritage Sites (WHS) can vary from ancient castles and cities to biodiversity-rich ecosystems. They are increasingly threatened by rising temperatures, extreme weather events, and environmental change across all regions of the world\u003csup\u003e5,13–15\u003c/sup\u003e. These impacts include physical degradation of historic buildings, loss of archaeological sites and threats to intangible heritage such as traditional knowledge and cultural practices, especially among Indigenous communities\u003csup\u003e16–18\u003c/sup\u003e. Cultural heritage fosters identity, continuity, and community cohesion\u003csup\u003e19\u003c/sup\u003e and natural heritage, apart from habitats, can provide valuable carbon sinks and green infrastructure for ecosystem-based adaptation\u003csup\u003e20,21\u003c/sup\u003e. UNESCO therefore highlights that heritage must be safeguarded not only for its intrinsic value but also for its potential to foster resilience, identity, and sustainable development across generations\u003csup\u003e22\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe UNESCO World Heritage List currently includes over 1,200 WHS across 168 countries, comprising cultural, natural, and mixed sites that vary widely in heritage type and size, from compact monuments to vast natural reserves\u003csup\u003e23\u003c/sup\u003e. A site is considered as World Heritage when it possesses Outstanding Universal Value; i.e. a cultural or natural significance so exceptional that it transcends national boundaries and is of common importance for present and future generations\u003csup\u003e23\u003c/sup\u003e. Local and regional assessments of the exposure and vulnerability of coastal heritage to climate change have been growing in the past decade\u003csup\u003e4,12,24–27\u003c/sup\u003e. Yet a global assessment of coastal flood risk is missing, even though such information is particularly needed to help coordinate global adaptation efforts, such as those under the Global Goal on Adaptation (GGA)\u003csup\u003e28,29\u003c/sup\u003e. The latter recognizes the need to protect cultural heritage from the impacts of climate change, including the preservation of cultural practices and heritage sites.\u003c/p\u003e\n\u003cp\u003eIn this study, we deliver the first comprehensive global flood risk assessment for UNESCO WHS found along the world’s coastlines. As a foundation, we develop a global geospatial dataset capturing the constituent components of coastal WHS located below 20 m above sea level\u003csup\u003e30\u003c/sup\u003e. This dataset comprises 1,211 digitized site polygons derived from 385 coastal WHS spanning cultural, natural, and mixed designations, and covering over 235 million hectares worldwide. We then combine the WHS dataset with the latest SLR projections and other ocean/geospatial data, conducting simulations with a state-of-the-art hydrodynamic model. We assess global warming scenarios of 1.5\u003csup\u003e\u0026nbsp;o\u003c/sup\u003eC, 2\u003csup\u003e\u0026nbsp;o\u003c/sup\u003eC, 3\u003csup\u003eo\u003c/sup\u003eC and 4\u003csup\u003eo\u003c/sup\u003eC above pre-industrial level and the 100-year flood event. Results are reported at site, country, regional and global scales, covering both median estimates, and the very likely range (5\u003csup\u003eth\u003c/sup\u003e-95\u003csup\u003eth\u003c/sup\u003e percentile).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eGlobal Heritage is already exposed to coastal floods\u003c/h2\u003e\n\u003cp\u003eAt present, approximately 117 [115-122] WHS are globally exposed to a 1-in-100-year coastal flood event (values in brackets correspond to the 5\u003csup\u003eth\u003c/sup\u003e - 95\u003csup\u003eth\u003c/sup\u003e percentile), accounting for circa 10% of the total inventoried coastal sites. This represents an affected area between 78,940 and 167,130 hectares at a 90% confidence interval and approximately 0.11% of the total coastal heritage area. Europe accounts for the largest share of currently affected WHS (36%), followed by Asia (23%), Africa (13%), North America (11%), and Small Island Developing States (SIDS) (10%; Figure 1c). However, when considering the proportion of sites affected within each region, North America and SIDS stand out, with nearly 30% of their WHS exposed (Figure 1b).\u003c/p\u003e\n\u003cp\u003eRegarding the flooded heritage area, North America is disproportionately affected, accounting for more than 44% of the global, or 55,635 ha. Europe has 31,713 ha exposed, followed Africa (20,152 ha) and Australia/New Zealand (13,152 ha). These values correspond to circa 95% of the affected heritage area with SIDS and Asia contributing a minor share (2.10 and 0.94%, respectively), and Central and South America almost zero.\u003c/p\u003e\n\u003cp\u003eIt is important to highlight that more than 44% of the total heritage area presently flooded by the 100-year storm is found in USA, i.e. more than 55,421 ha (Figure 1d). Other countries already facing severe challenges to heritage include United States, Italy (24,774 ha), Mauritania (16,125 ha) and Australia (13,152 ha).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhen considering the number of affected WHS, the United Kingdom has the highest number (24), while Japan follows with 19 (Figure 1c) and countries such as Belize, the United States, and Australia have at least 5. In some cases, entire national heritage inventories are already at risk, such as those of Kiribati, Bangladesh, Fiji, and Palau (Figure 1a). Some of the above are SIDS, a fact that underscores the sensitive situation in such small islands, where even modest SLR can trigger frequent inundation of large portions of land and heritage assets, including globally significant breeding habitats for birds, corals, turtles and fish\u003csup\u003e32\u003c/sup\u003e and atoll-island cultural landscapes\u003csup\u003e33\u003c/sup\u003e.\u003c/p\u003e\n\u003ch2\u003eIncreasing flood exposure of global heritage with global warming\u003c/h2\u003e\n\u003cp\u003eFlood exposure of coastal WHS continues to rise throughout the century for all warming scenarios. This is due to the fact that sea levels are projected to rise even after global temperatures stabilize\u003csup\u003e31\u003c/sup\u003e. By 2050, the median flooded heritage area is projected to more than double under 1.5 °C and almost triple under 4.0 °C warming compared to present-day conditions (Figure 2a). This corresponds to flooded areas ranging from approximately 258,736 to over 353,373 hectares, depending on the scenario. The number of affected sites rises at a slower rate than the flooded area, indicating that existing sites are projected to face worsening conditions rather than new sites becoming exposed (Figure 2a-b). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBy 2100, flood hazard is projected to further rise and almost a million hectares could be affected by a 100-year event under the 4.0 °C warming trajectory, a more than six-fold increase compared to the baseline (Figure\u0026nbsp;2a). Under the same scenario, the number of affected WHS could increase from 117 today to as many as 402 (Figure\u0026nbsp;2b). Limiting warming to 1.5 °C, in line with the Paris Agreement goals, would prevent 101 WHS from being affected worldwide, in comparison to the 4.0 °C warming scenario.\u003c/p\u003e\n\u003cp\u003eUnder 1.5 °C warming, North America is projected to have the largest share of flooded heritage area by the end of the century (46.96% of the global total), followed by Europe (21.08%) and Africa (20.33%;\u0026nbsp;Figure\u0026nbsp;2d). Asia and Australia/New Zealand remain around 5% and SIDS along with Central and South America contribute only marginally compared to the other regions. These relative contributions are consistent across warming scenarios, although the absolute magnitudes increase with higher warming. For example, under 4.0 °C warming, North America and SIDS will have more than half of their WHS affected (73% and 55%, respectively), while 37% of sites in Africa and Australia/New Zealand are projected to be at risk. In the remaining regions, approximately 30% of sites are projected to be affected.\u003c/p\u003e\n\u003cp\u003eCentral and South America is the region with largest projected increase by 2100 compared to the baseline, both in terms of the number of affected WHS (from 3 to 16 under 4.0 °C warming) and the heritage area affected (from 8 to 5,490 ha). Substantial increases are also projected for Europe, with the affected heritage area growing sixfold and the number of affected sites increasing from 42 to 199 by the end of the century (Figure 2c). In Asia the affected area increases almost 20-times, with the number of affected sites tripling.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAssessing the percentage of each site’s area affected provides a more detailed perspective on flood exposure and helps focusing on smaller (mainly) cultural WHS where even partial inundation can compromise integrity and cultural value. By 2050, under 1.5 °C warming, the number of WHS with less than 25% of their area exposed (‘mild exposure’) increases from 112 (Figure 3a) in the baseline to 197 (Figure 3b). Nine sites fall into the ‘moderately affected’ (25%-50% of area affected), while one site enters the ‘high exposure’ category (50%-75%). These transitions represent a net increase of 95 affected WHS globally at 1.5 °C,\u0026nbsp;with all still experiencing partial rather than total inundation.\u003c/p\u003e\n\u003cp\u003eBy 2100, and under the same warming scenario, 89 more WHS are exposed to the 100-year event, which means 67, 7 and 15 sites additional sites are exposed mildly, moderately and highly, respectively, compared to the year 2050 (Figure 3c). Not mitigating emissions and allowing the temperature to reach 4\u003csup\u003eo\u003c/sup\u003eC, will result in 14 severely exposed WHS, the majority of which are found in Europe (Figure 3d). The highest exposure is concentrated among smaller cultural sites, such as \u0026nbsp;the Tower of Belem, Portugal (‘moderate exposure’ by 2050 under 1.5 °C; ‘severe exposure’ by 2100 under 4.0 °C), Miike Coal Mine and Miike Port, part of the Sites of Japan’s Meiji Industrial Revolution, Japan (‘high exposure’ by 2100 under 1.5 °C; ‘severe exposure’ by 2100 under 4.0 °C). Two iconic WHS projected to escalate rapidly to ‘high exposure’ by 2100 under 4 °C are the Al Zubarah Archaeological Site, Qatar, and La Tour Dorée de Camaret-sur-Mer, part of the larger \"Fortifications of Vauban\", France.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt the national level, Mexico stands out as the most exposed country, accounting for circa 25% of the global flooded heritage area by 2100, across all considered warming scenarios (Figure 4b). The United States is another country with extensive land area, long coastline and sizable heritage inventory projected to contribute between 20% and 22.6% of the total global affected heritage area, depending on the scenario. Mauritania and Romania each account for 8%–9% of the global flooded area, highlighting the exposure of low-lying heritage-rich regions in both Africa and Europe.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn terms of the number of affected WHS, larger countries dominate. By 2100, under a 1.5 °C warming scenario, the United Kingdom is projected to contribute nearly 16% of all affected sites, followed by Japan (13%), the Russian Federation (9%), and Mexico (6%). These countries also show the largest increases in newly affected sites compared to present-day conditions, i.e. 24 in the UK, 20 in Japan, 26 in Russia, and 16 in Mexico (Figure 4a).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings reveal the multiple levels and dimensions of coastal heritage exposure to SLR. It is important to highlight that there is not a single indicator that could be representative worldwide. The area or the percentage of each WHS affected can be a valid criterion for sites that are homogenous, but the latter is often not the case. For example, the Island of Rapa Nui (Easter Island) covers over 16,600 ha of land\u003csup\u003e34\u003c/sup\u003e, from which only 0.001% is projected to be affected by flooding (up to 17.8 ha; 4.0 °C by 2100). Yet, more than 90% of standing moai that represent Rapa Nui’s most iconic attributes are positioned along the coast\u003csup\u003e35\u003c/sup\u003e, implying that the part of the site that is most exposed to floods has disproportionately higher heritage value (Figure 5a). Similar challenges arise for many sites where important heritage attributes are close to the sea. Some such examples include the north African archaeological sites of Leptis Magna\u003csup\u003e36\u003c/sup\u003e in Libya (6.8 ha; 4.0 °C by 2100; Figure 5b) and Tipasa\u003csup\u003e38\u003c/sup\u003e in Algeria (6.8 ha; 4.0 °C by 2100); Chief Roi Mata's Domain\u003csup\u003e39\u003c/sup\u003e in Vanuatu (12.8 ha; 4.0 °C by 2100); the Statue of Liberty\u003csup\u003e40\u003c/sup\u003e (1.4 ha; 4.0 °C by 2100); and the iconic 15th Century Khan-e-Jahan architecture at the Historic Mosque City of Bagerhat\u003csup\u003e37\u003c/sup\u003e (13 ha; 4.0 °C by 2100; Figure 5c).\u003c/p\u003e\n\u003cp\u003eSeveral of the WHS that are projected to be severely exposed (Figure 3) have coastal fortifications in place, many of which are centuries old. These may prove resilient to limited erosion and episodic inundation but may not sustain contemporary or projected rates of sea-level rise. For example, the Tower of Belem, Portugal was built in 1514 to commemorate Vasco da Gama's expedition. Site-level vulnerability assessments will be necessary to determine the resilience of such sites against higher sea levels. Further, several WHS include ‘buffer zones’ that serve as special protection zones around each World Heritage property. These buffer zones are important to the integrity and authenticity of the WHS, positioning the site within a wider cultural and heritage landscape, particularly when viewed from the sea.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRecent research highlights how even modest global warming scenarios could translate into a sharp increase in heat and moisture disturbance of World Heritage\u003csup\u003e13\u003c/sup\u003e. Our study shows that coastal WHS could substantially suffer additional strain from coastal flooding. Large countries contribute substantially to global totals due to the size and proximity of their heritage inventories (Figure 4). Smaller nations often face existential risks to their entire heritage systems. This underscores the need for differentiated adaptation strategies that address both the widespread exposure in large countries and the concentrated, high-stakes risks in smaller, low-lying nations. In addition, to be effective, heritage-focused adaptation planning must account for differentiation across the attributes of cultural, natural and mixed sites.\u003c/p\u003e\n\u003cp\u003eAt the same time, many WHS, especially in low- and middle-income countries, face limited adaptive capacity stemming from technological, financial, and governance challenges. These systemic constraints are captured by the Notre Dame Global Adaptation Index (ND-GAIN)\u003csup\u003e6\u003c/sup\u003e, which evaluates a country’s vulnerability to climate change and its readiness to implement adaptation measures. The index draws from over 45 indicators across six sectors (food, water, health, ecosystem services, human habitat, and infrastructure) and assesses readiness through economic, governance, and social dimensions. A score below 50 indicates limited capacity to absorb and operationalize adaptation investments.\u003c/p\u003e\n\u003cp\u003eTo highlight disparities in adaptive capacity and associated risks, we mapped heritage exposure against ND-GAIN scores (Figure 6; Supplementary Table 1). Focusing on values for the median 1.5 °C warming scenario by 2100, we identify 32 countries with ND-GAIN scores below 50 that host WHS projected to be exposed to coastal flooding. Among these, Mexico and South Africa stand out for having more than 10 affected WHS, while Mauritania, Namibia, Senegal, and Vietnam rank in the top 20% for total heritage area affected; each exceeding 5,500 hectares. Additionally, Cote d'Ivoire, Micronesia, and Venezuela are among the countries with the highest percentage of their heritage area affected, surpassing 3%.\u003c/p\u003e\n\u003cp\u003eThese findings underscore a growing inequality in climate impacts on cultural heritage. Countries with limited adaptive capacity are not only more vulnerable to sea-level rise but also less equipped to implement adaptive measures. This calls for targeted international support, capacity-building, and inclusive adaptation planning to safeguard heritage in regions where the risks are greatest and the resources most constrained.\u003c/p\u003e\n\u003cp\u003eMany communities have already begun implementing adaptation strategies providing valuable lessons for safeguarding WHS. Urban and cultural landscapes require integrated flood risk mapping, drainage improvement and infrastructure retrofitting. For example, in Venice, Italy, the MOSE flood barrier system shields the city from high tides, complemented by more local upgrades in the drainage network and buildings\u003csup\u003e41,42\u003c/sup\u003e. The Statue of Liberty in the United States underwent infrastructure elevation and flood-proofing following Hurricane Sandy\u003csup\u003e43\u003c/sup\u003e. In Puerto Rico, Fort San Juan de la Cruz has been stabilized and retrofitted to withstand storm surges and salt spray\u003csup\u003e44\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eNatural heritage sites have distinct characteristics and require different adaptation strategies, such as ecosystem restoration and community-based conservation. Belize’s Bacalar Chico National Park uses mangrove restoration and marine protected areas to buffer storm surges and support biodiversity\u003csup\u003e45\u003c/sup\u003e. Vietnam’s Ha Long Bay integrates mangrove reforestation and coral reef protection through its Integrated Coastal Zone Management (ICZM) plan\u003csup\u003e46\u003c/sup\u003e. The Everglades National Park in the United States is undergoing large-scale wetland restoration to combat saltwater intrusion\u003csup\u003e47\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003ePolicy and planning frameworks are increasingly incorporating climate resilience. The Wadden Sea, shared by Germany, the Netherlands, and Denmark, employs a trilateral Climate Change Adaptation Strategy\u003csup\u003e48\u003c/sup\u003e. Qatar’s Al Zubarah site benefits from a national climate action plan and site-specific management measures\u003csup\u003e49\u003c/sup\u003e. Archaeological and coastal fortifications benefit from structural reinforcement and digital documentation. In the UK, Hadrian’s Wall is part of a UNESCO pilot project using GIS tools and stakeholder engagement to inform climate-resilient heritage management\u003csup\u003e50\u003c/sup\u003e, including coastal risks.\u003c/p\u003e\n\u003cp\u003eSafeguarding heritage in the face of rising seas will require coordinated global action involving national governments, UNESCO and other key actors. This could include targeted support for countries with low adaptive capacity through loss and damage and other such instruments, integration of cultural heritage into national adaptation plans, and investment in long-term resilience. The upcoming rounds of nationally determined contributions (NDCs) and national adaptation plans (NAPs) under the Paris Agreement offer a critical opportunity to embed heritage protection into climate policy frameworks\u003csup\u003e51\u003c/sup\u003e. Ultimately, protecting coastal heritage is a shared global responsibility, not only about preserving the past, but also about securing cultural identity, ecological integrity, and social cohesion for future generations.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eGlobal Coastal Heritage Data Set\u003c/h2\u003e\n\u003cp\u003eThis study utilizes a newly developed global geospatial dataset of UNESCO World Heritage Sites (WHS) located within the Low-Elevation Coastal Zone (LECZ). The dataset comprises 1,211 digitized site polygons derived from 385 UNESCO WHS that include cultural, natural, and mixed designations\u003csup\u003e30\u003c/sup\u003e. These sites span over 235 million hectares globally including 990 cultural sites, 204 natural sites and 17 mixed sites. The selection of sites was based on UNESCO\u0026rsquo;s official WHS list as of 2023 and were included if any part of their designated area was located at or below 20 m AMSL\u003csup\u003e52\u003c/sup\u003e. It represents the first comprehensive spatial delineation of coastal WHS at global scale, enabling quantitative exposure assessments to climate-related coastal hazards.\u003c/p\u003e\n\u003cp\u003eA standardized digitization protocol was developed to ensure consistency and accuracy across the dataset. The primary tools used were Google Earth Pro and georeferenced UNESCO site maps. Digitization was performed by a trained team of 10 individuals, coordinated by GIS and heritage experts. The digitization process involved site identification, site polygon creation, resolution reconciliation, integration of existing data sets, attribution data, and technical validation. A heritage specialist reviewed UNESCO site coordinates and maps to identify qualifying sites. Google Earth (GE) imagery and elevation data were then used to verify site location and elevation. Digitizers used GE to delineate site boundaries, either directly from satellite imagery or by overlaying georeferenced UNESCO maps. Tie-points were used for georeferencing maps lacking coordinate grids. Sites were digitized at a nominal scale of 1:1000, with finer scales (e.g., 1:250) used for small or complex sites. Only core site boundaries were digitized; buffer zones were excluded due to lack of standardization and some sites were split into sub-sites to reflect geographic separation necessary for analysis (e.g., islands or atolls). Each polygon was assigned standardized metadata, including site name, UNESCO code, country, area, and regional classifications (UNESCO and IPCC WGII sub-regions). Digitizers maintained logs documenting source quality, digitization challenges, and decisions made during the process. These logs supported subsequent quality control and validation. In addition to original digitization, data from four external sources were integrated: African coastal WHS from Vousdoukas et al.\u003csup\u003e12\u003c/sup\u003e, Mediterranean WHS from Reimann et al.\u003csup\u003e4\u003c/sup\u003e, protected area polygons from the World Database on Protected Areas (WDPA)\u003csup\u003e53\u003c/sup\u003e, and UK coastal WHS from Historic England\u003csup\u003e54\u003c/sup\u003e. All external data were reviewed for spatial accuracy and adjusted to conform to the GHMP digitization protocol.\u003c/p\u003e\n\u003cp\u003eA stratified sampling approach was used to validate the spatial accuracy and attribute integrity of the dataset. Sixty WHS (5% of the total) were randomly selected across 30 strata defined by polygon area and geographic sub-region. Validation involved both qualitative and quantitative assessments of source map quality based on legibility, spatial referencing, and boundary clarity; Google Earth Imagery Visibility based on the clarity of site features in satellite imagery; and polygon accuracy assessed using a 5-meter buffer around each polygon. Deviations from visible boundaries in GE were measured and normalized by polygon perimeter. WHS scoring below a defined threshold were flagged for review. Of the 60 sampled WHS, 92% were deemed to have optimal digitization accuracy. Approximately 8% showed errors and 6.7% had attribute data inaccuracies that were corrected.\u003c/p\u003e\n\u003ch2\u003eCoastal flood modelling framework\u003c/h2\u003e\n\u003cp\u003eWe assess the WHS\u0026rsquo; flood hazard from Sea-Level Rise (SLR) and episodic flooding during the 21st century. The analysis is based on the modular framework LISCOAST (Large-scale Integrated Sea-level and Coastal Assessment Tool). We consider four global warming levels that span a range from ambitious mitigation to no emission policies: 1.5\u0026deg;C, 2\u0026deg;C, 3\u0026deg;C, and 4\u0026deg;C relative to pre-industrial times. For each of these scenarios we generate probabilistic projections of mean and extreme sea levels that give rise to episodic flooding and combine them with the WHS dataset to assess flood exposure.\u0026nbsp;\u003c/p\u003e\n\u003ch3 id=\"_Toc50445558\"\u003ePresent day extreme sea levels\u003c/h3\u003e\n\u003cp\u003eCoastal areas are exposed to rising mean sea level (MSL) and episodic high sea levels under extreme atmospheric conditions. Extreme sea levels (ESL) are driven by the combined effect of MSL, tides and water level fluctuations due to waves and storm surges. We derive the contribution of each of these drivers with state-of-the-art modelling tools and datasets and combine them to obtain ESLs every 1 km along the ice-free coastline.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the baseline period, spanning from 1980 until 2020, we run a reanalysis of waves and storm surges based on a two-way coupled ocean model using an unstructured grid with a resolution ranging from ~50 km offshore to ~2 km nearshore. The coupled model system includes the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM)\u003csup\u003e55\u003c/sup\u003e, configured in its two-dimensional barotropic mode and the 3rd-generation spectral wave model (WWM-V)\u003csup\u003e56\u003c/sup\u003e. The model accounts for the combined effects of wind, atmospheric pressure gradients, and tides. We use bathymetric data from the European Marine Observation and Data Network (EMODnet), available in angular coordinates at a resolution of 1/8 arc-minute (0.0021\u0026deg; of latitude and longitude; http://www.emodnet.eu/bathymetry) which we interpolate onto the computational grid.\u003c/p\u003e\n\u003cp\u003eWe apply the coupled model to produce a reanalysis of waves and storm surges, forced by sea-level pressure and wind speed data from ERA5\u003csup\u003e57\u003c/sup\u003e. The reanalysis is carried out without tidal forcing to ensure that our hindcast resolves the weather-driven component of ESLs; without the stochastic modulation of spring/neap tidal variations. Further details about the model setup and the validation can be found in Mentaschi et al.\u003csup\u003e58\u003c/sup\u003e. Since, it is known that non-linear interactions between tides, waves and storm surges can be important in some areas, we apply a correction for these effects following an approach similar to Arns\u003csup\u003e59\u003c/sup\u003e. To that end, we run a shorter 10-year reanalysis including tidal forces and from the overlapping time series we construct copulas to produce a correction function for non-linear tidal effects on the water level anomaly and the significant wave height.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo improve the accuracy of the reanalysis data we implement some additional steps as detailed below. Using satellite altimetry data we apply a Quantile Mapping Bias Correction on both the water level anomaly and the significant wave height. This is done after compiling all coinciding model and satellite values along 1\u003csup\u003eo\u003c/sup\u003e x 1\u003csup\u003eo\u003c/sup\u003e cells. To further improve the cyclone related storm surge estimates which have not been sufficiently resolved by our reanalysis, we did additional simulations of tropical cyclone driven sea level anomalies using the Delft3D-FM model\u003csup\u003e60\u003c/sup\u003e forced by the IBTrACS best-track archive\u003csup\u003e61\u003c/sup\u003e. The reanalysis values are corrected by considering the tropical cyclone runs values when they are higher than those of our ERA5 runs. More information about the approach and data can be found in Vousdoukas et al\u003csup\u003e10,62\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eSpectral wave parameters provide one characteristic estimate for wave height, direction and period from the whole spectrum and therefore lack the detail needed to describe wave processes along complex shorelines. To overcome this shortcoming, we use the spectral peaks from the WWM-V model output and we propagate each peak along a global transect dataset with 1 km alongshore resolution. The transect dataset includes information on the shoreline position, orientation, submerged and subaerial slope, among others. Details of the data and methods used to generate transects are provided in Athanasiou et al.\u003csup\u003e63\u003c/sup\u003e. We benefit from the complete spectral information from the wave model to propagate each peak at each time stamp along its corresponding transect using Snell\u0026rsquo;s law\u003csup\u003e64\u003c/sup\u003e. We then estimate the wave breaking height combining the peak wave parameters with the submerged profile slope. Subsequently, we obtain the wave run-up height R\u003csub\u003e2\u003c/sub\u003e based on the Stockdon empirical formula\u003csup\u003e65\u003c/sup\u003e, after combining the breaking wave height and period with the subaerial beach profile slope. The above steps result in wave runup height estimates for each spectral peak and we consider the highest value as the characteristic for the specific time stamp. We then combine the wave runup with the storm surge to obtain the meteorological tide and apply non-stationary extreme value analysis\u003csup\u003e66\u003c/sup\u003e to the time series to obtain estimates for different return periods.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBaseline ESLs are produced by combining the final meteorological tide time series with tidal elevations obtained from the FES2022 model\u003csup\u003e67\u003c/sup\u003e. Following the approach of Vousdoukas et al.\u003csup\u003e62\u003c/sup\u003e, the high tide water level is considered taking into account the range due to the spring-neap tide cycle.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eSea-level rise projections\u003c/h3\u003e\n\u003cp\u003eRelative SLR projections are obtained from latest IPCC AR6 assessment\u003csup\u003e8,68,69\u003c/sup\u003e and incorporate the effects of the various components of future SLR, including steric SLR, dynamic sea-level change, contributions from glaciers and ice-caps, land-water storage and Glacial Isostatic Adjustment, among others.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eProjections of ESLs up to 2100\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eAll ESL components (RSLR, tide, surges and R\u003csub\u003e2\u003c/sub\u003e) are expressed as probability density functions (PDFs) that account for the different sources of uncertainty and are combined through Monte Carlo simulations to generate probabilistic estimates of ESLs for all scenarios in each coastal segment (1 km alongshore resolution). Non-stationary extreme value analysis\u003csup\u003e66\u003c/sup\u003e is then applied to performed for a range of return periods (i.e. 1, 2, 5, 10, 20, 50, 100, 200, 500, 1000 and 5000 years) PDFs of the corresponding return values of ESL throughout this century.\u003c/p\u003e\n\u003ch3\u003eCoastal flooding\u003c/h3\u003e\n\u003cp\u003eFollowing Vousdoukas et al.\u003csup\u003e70\u003c/sup\u003e, we perform 2-D hydraulic simulations along the entire coastline to estimate inundation extent and depth. To that end, we use the Lisflood-ACC model\u003csup\u003e71\u003c/sup\u003e at 30 m spatial resolution, using the estimated ESLs as forcing and considering hydraulic roughness derived from land-use maps\u003csup\u003e72\u003c/sup\u003e. Up to high-tide water levels (i.e. combination of mean sea level and high-tide) we apply the bathtub approach, and land below this sea water level and the corresponding assets are considered permanently inundated due to sea-level rise. For episodic flooding, Liscflood-ACC is applied for each coastal segment with the model domain extending up to 200 km landwards to ensure the inclusion of all potentially hydrologically connected areas that may lie inland and away from the coast. The flood simulations are based on the recently released Delta DTM\u003csup\u003e73\u003c/sup\u003e. Finally, flood maps were superimposed on the WHS polygons to identify the portions of heritage sites exposed to flooding.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eData availability\u003c/h2\u003e\u003cp\u003eThe models and datasets presented are part of the integrated risk assessment tool LISCoAsT (Large scale Integrated Sea-level and Coastal Assessment Tool) developed by the Joint Research Centre of the European Commission. All data used are open access and links are provided, while all source data are provided in the Supplementary Dataset. Coastal heritage data set is available here: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.25375/uct.28547267\u003c/span\u003e\u003cspan address=\"10.25375/uct.28547267\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eCode availability\u003c/p\u003e\u003cp\u003eMost of the code that supported the findings of this study is already open access with references provided in the manuscript; specific tools which are not available in public repositories will be available on reasonable request from the corresponding authors.\u003c/p\u003e\u003cp\u003eAcknowledgements\u003c/p\u003e\u003cp\u003eThis research received support through Schmidt Sciences (N.P.S. and C.H.T.), Irish Aid (NPS), NERC Discipline Hopping for Environmental Solutions (Grant Number NE/X018385/1) (J.C. and D.B.) and the British Academy ODA Challenge-Oriented Research Grants 2024 (Grant Number IOCRG\\100137) (N.P.S.). We thank the sea-level projection authors for developing and making the sea-level rise projections available, multiple funding agencies for supporting the development of the projections, and the NASA Sea-Level Change Team for developing and hosting the IPCC AR6 Sea-Level Projection Tool.\u003c/p\u003e\u003cp\u003eAuthor Contributions Statement\u003c/p\u003e\u003cp\u003eM.I.V., L.M., N.P.S. and L.F., Conceptualization; M.I.V., L.M., N.P.S., R.N., J.C., and R.R., Preliminary and Exploratory Analysis; M.I.V., N.P.S., D.B. and L.F. Methodology; all authors, Validation; M.I.V., Formal analysis; M.I.V. and N.P.S., Investigation; M.I.V., N.P.S., J.C., C.H.T., and L.F., Resources; M.I.V., L.M., D.B., J.C., N.K. and N.P.S., Data Integration; M.I.V., N.P.S. and L.F. Writing - Original Draft; all authors, Writing - Review \u0026amp; Editing; M.I.V, Visualization.\u003c/p\u003e\u003cp\u003eThe information and views set out are those of the author(s) only and should not be considered as representative of the European Commission\u0026rsquo;s official position.\u003c/p\u003e\u003cp\u003eCompeting Interests Statement\u003c/p\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003cp\u003eEthics \u0026amp; Inclusion statement\u003c/p\u003e\u003cp\u003eThe authors declare no ethics issues such as research on race, sex, ethnicity, clinical trials or humans or animals. The list of authors is broad while local and regional studies have been considered.\u003c/p\u003e\u003cp\u003eSupplementary information\u003c/p\u003e\u003cp\u003eSupplementary Table\u0026nbsp;01. Country level estimates of heritage risk vs Adaptive capacity. Countries with lower adaptation readiness, i.e. Notre Dame Global Adaptation Index (ND-GAIN\u0026thinsp;\u0026lt;\u0026thinsp;50) and their number of total and affected heritage sites, as well as the corresponding heritage area affected from coastal floods, as absolute value or percentage of the total. All values are for the median 1.5\u003csup\u003eo\u003c/sup\u003eC warming scenario and the end of the century.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHermans, T. H. J. \u003cem\u003eet al.\u003c/em\u003e The timing of decreasing coastal flood protection due to sea-level rise. \u003cem\u003eNat. Clim. Change\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 359\u0026ndash;366 (2023).\u003c/li\u003e\n\u003cli\u003eHamlington, B. D. \u003cem\u003eet al.\u003c/em\u003e The rate of global sea level rise doubled during the past three decades. \u003cem\u003eCommun. 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Data\u003c/em\u003e\u003cstrong\u003e11\u003c/strong\u003e, 273 (2024).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7654288/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7654288/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSea levels are increasing at an accelerated rate\u003csup\u003e1,2\u003c/sup\u003e and this is expected to increase flooding along coastlines worldwide\u003csup\u003e3\u003c/sup\u003e. While cultural and natural heritage sites are among the assets most exposed to this threat\u003csup\u003e4,5\u003c/sup\u003e, a unified global assessment is currently lacking. Here we assess coastal flood exposure of all nearshore UNESCO World Heritage sites worldwide, under different global warming scenarios. We estimate that for a scenario with current climate mitigation policies and action, by the end of this century around one third of World Heritage Sites could be exposed to floods, corresponding to more than 1.1 million hectares of protected and preserved land. Limiting warming to the 1.5°C Paris agreement target would save 89 heritage sites from being exposed. Large countries are projected to face widespread exposure while smaller nations risk losing entire heritage systems. Combining our findings with the ND-GAIN index\u003csup\u003e6\u003c/sup\u003e shows that 32 countries with low adaptive capacity are expected to experience high heritage exposure, especially Small Island Developing States. To safeguard these irreplaceable cultural and natural treasures, it is imperative to scale up heritage adaptation efforts and increase support for vulnerable regions.\u003c/p\u003e","manuscriptTitle":"Climate change threatens coastal heritage worldwide","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-13 05:59:22","doi":"10.21203/rs.3.rs-7654288/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"861e9824-b877-4f2b-84dc-3ef216438582","owner":[],"postedDate":"October 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":55571900,"name":"Earth and environmental sciences/Climate sciences/Climate change/Climate-change impacts"},{"id":55571901,"name":"Scientific community and society/Social sciences/Interdisciplinary studies"},{"id":55571902,"name":"Earth and environmental sciences/Natural hazards"},{"id":55571903,"name":"Scientific community and society/Scientific community/Culture/Architecture"}],"tags":[],"updatedAt":"2025-10-13T05:59:22+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-13 05:59:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7654288","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7654288","identity":"rs-7654288","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}