Unveiling the role of storm surges as a driver of flooding on the western Mediterranean: a case study of the Ebro Delta

Vol.:(0123456789) Natural Hazards https://doi.org/10.1007/s11069-024-06984-5 ORIGINAL PAPER Unveiling therole ofstorm surges asadriver offlooding onthewestern Mediterranean: acase study oftheEbro Delta RutRomero‑Martín1 · MarcSanuy1 · JoséA.Jiménez1 Received: 11 June 2024 / Accepted: 20 October 2024 © The Author(s) 2024 Abstract Storm surges in the Western Mediterranean are generally low in magnitude, making their contribution to coastal flooding less significant compared to wave overtopping. Nonetheless, low-lying, sheltered coasts such as deltas and wetlands, which are frequent along the Mediterranean basin are particularly vulnerable to storm surges. This study, focusing on the Ebro Delta as representative of this type of coastal environment, investigates the flooding caused by storm surge alone and in conjunction with other non-wave related factors like astronomical tides and sea level rise (SLR), using the LISFLOOD-FP model. The findings highlight the significant flooding potential of storm surges on passive, and unprotected coasts, while also indicate that astronomical tides have a minor effect on flood extent under prevalent microtidal conditions. SLR greatly increases the impact of storm surges, amplifying temporary inundation in the short term and becoming the dominant factor over time. The study underscores the importance of accurately representing surge duration and small topographic features in flood models to ensure robust coastal inundation assessments in low-lying areas. Keywords Storm surge· Coastal plain· Sheltered coasts· SLR· Inundation· Flood modelling 1 Introduction Storm surges are among the most important coastal hazards because of their significant role in flooding across the world’s coastlines (e.g. Nicholls 2006; Muis etal. 2016). They occur because of atmospheric pressure fluctuations (lowering) and landward-blowing winds during storms, which cause water levels at the shoreline to rise by several metres, particularly under the influence of hurricanes (Smith and Ward 1998). However, in the Mediterranean basin, except for the Adriatic Sea, their average magnitude is below 0.3m (e.g. Marcos etal. 2009; Androulidakis etal. 2015), a situation that is not expected to vary during this century due to climate change (Conte and Lionello 2013; Androulidakis * Rut Romero-Martín r[email protected] 1 Laboratori d’Enginyeria Marítima, Universitat Politècnica de Catalunya·BarcelonaTech, Barcelona, Spain Natural Hazards etal. 2015; Vousdoukas etal. 2016). In the Western Mediterranean, recorded storm surge magnitudes can reach up to approximately 0.50m, as evidenced by the impact of Storm Gloria in January 2020 along the Spanish Mediterranean coast (Pérez-Gómez etal. 2021). However, during extreme storms, the magnitude is notably lower than that of the waveinduced run-up (Mendoza and Jiménez 2009). Consequently, storm surges are not expected to contribute directly to coastal flooding; rather, it is their interaction with storm waves that becomes relevant (Sayol and Marcos 2018). As an example, Agulles etal. (2021) analysed beach flooding in the Balearic Islands under various storm conditions, including the effects of sea level rise (SLR), and determined that storm surges contributed approximately 10% to the estimated inundation of the shoreline. The relatively low magnitude of storm surges compared to the natural elevation of berms and dunes along sandy beaches suggests that their impact will primarily be felt in very low-lying areas (Krestenitis etal. 2011; Androulidakis etal. 2023). In this regard, the Mediterranean Basin encompasses numerous low-lying coastal features, such as deltas, wetlands, and lagoons. These areas exhibit very low topography and are often (partially or fully) bordered by passive coastlines comprising silt and muddy sediments. Unlike sandy coasts, these passive shores have a low dynamic because of their sheltered location results in reduced exposure to wave action. As a consequence, unless receiving significant sediment input contributing to their vertical accretion, their reduced dynamic results in a lack of morphological response to SLR. This lack of dynamic adjustment, combined with their low elevation, makes them particularly vulnerable to even small increases in water levels (e.g. Newton etal. 2014; Antonioli etal. 2020; López-Dóriga and Jiménez 2020). As SLR progresses, in addition to the rising risk of permanent inundation (e.g. Antonioli etal. 2020), the relative impact of storm surge-induced flooding will increase. Lower surges will reach the same total water levels as larger surges do today, significantly increasing the likelihood of flooding events (e.g. Passeri etal. 2015). In this context, analysing surge-induced inundation in isolation becomes crucial for better assessing the adaptation needs required to address this specific threat, both now and in future SLR scenarios. Despite their limited extent compared to sandy coastlines, these passive areas hold significant ecological value (Pérez-Ruzafa etal. 2011), and face substantial threats (e.g. Taylor etal. 2021; MartínezMegías and Rico 2022). Therefore, assessing these risks is essential for determining the need for targeted adaptation measures. Among these areas, the Ebro Delta stands out as one of the most important low-lying regions in the Western Mediterranean, characterised by its rich ecological value and extensive agricultural production. With a coastline 50km long, the delta exhibits a morphology highly vulnerable to coastal processes operating across various time scales (SánchezArcilla etal. 1998), as approximately 50% of its deltaic plain lies below 0.5 m above mean sea level, making it susceptible to storm impacts. Jiménez etal. (2012) reviewed the diverse impacts of storms along the delta coast, emphasising that the most significant impacts occur when eastern wave storms coincide with surged water levels (see also Grases etal. 2020). Valdemoro etal. (2007) highlighted the combined effects of surges and wave storms on the inundation of coastal lagoons along the outer deltaic coast. Alvarado-Aguilar etal. (2012) estimated the potential flooding of the delta under different SLR scenarios, and Sayol and Marcos (2018) assessed delta inundation considering the combined contribution of surges, waves, and SLR. Notably, no specific studies have investigated the isolated impact of storm surges on the Ebro delta flooding. However, part of the delta is bordered by a passive coastline, sheltered from wave action, including the bayside shores along two semi-enclosed lagoons. This area is characterised by a very low-lying, muddy/silty plain with channels and low banks, Natural Hazards making it a representative model of low-lying Mediterranean coastal zones. These features provide an ideal setting to investigate the potential influence of surges on episodic flooding. Within this context and to fill the above-described gap, the main aim of this study was to evaluate the role of storm surges, in the absence of waves, in driving flooding along the sheltered shoreline of the Ebro Delta. Secondly, the study also investigated the compounding effects of water level variations attributed to other factors operating over different timescales, such as astronomical tides and SLR on surge-induced flooding. This analysis enabled us to assess the impact on the study area as well as the potential significance of storm surges in driving flooding of low-lying coastal plains under typical Mediterranean conditions. From the practical standpoint, the resulting insights are crucial for developing adaptation strategies in the Ebro Delta to mitigate the impacts of SLR, aligning with ongoing efforts led by the Spanish Ministry of Environment (CEDEX 2021). The adopted approach involved simulating the inundation of the deltaic plain under representative storm surge conditions in the NW Mediterranean. These representative surge conditions were derived from an extreme water level climate and calculated using a long time-series of hindcasted surge data. Since surge inundation largely depends on water level exceedance above a certain threshold, we developed a method to estimate storm surge duration while conserving the water volume above specific heights. To evaluate the role of astronomical tide in this microtidal region, we analysed the impact of surge timing relative to tidal phases. Lastly, different SLRs were considered to assess potential future changes in surge-induced flooding. The structure of this paper is as follows: (i) Sect.2 describes the study area and the data used; (ii) Sect.3 presents the methodology, with emphasis on the developed approach for assigning surge duration to synthetic events for realistic inundation modelling; (iii) Sect.4 provides a detailed analysis of surge-induced flooding, including the compounding effects of waterlevel fluctuations at different time scales; (iv) Sect.5 discusses the results and the significance of surge-induced flooding in the studied environments; and (v) Sect.6 presents concluding remarks. 2 Study area anddata 2.1 Study area The Ebro Delta, situated approximately 200km south of Barcelona in the NW Mediterranean Sea (Fig.1), spans an emerging area of approximately 320 km2. Its topography renders it highly vulnerable to flooding, with approximately 50% of its surface lying below 0.5m above sea level and 70% below 1.0m (Alvarado-Aguilar etal. 2012; López-Dóriga and Jiménez 2020). Approximately 70% of the deltaic plain is dedicated to rice cultivation, resulting in an intricate network of irrigation and drainage channels crisscrossing the landscape that redistributes water throughout the plain (e.g. Alvarado-Aguilar etal. 2012). The deltaic plain is naturally protected from inundation by a sandy beach fringe along 50km of the outer coastline. Although the entire deltaic coast is highly susceptible to storm impacts (Jiménez etal. 2012), this study focused on the specific influence of storm surges. Consequently, the area selected as the study site was situated in the northern hemi-delta, particularly in the vicinity of a semi-enclosed lagoon known as Fangar Bay (Fig.1). The inner coastline of the deltaic plain is distinguished by a passive muddy coast sheltered from wave action by the Fangar spit, with the plain being partially safeguarded by small levees. Natural Hazards River management has resulted in a fully segmented river, with more than 97% of the basin being regulated by dams and reservoirs (Guillén and Palanques 1992, 1997). As a result, although the deltaic plain is not greatly affected by river floods, the vulnerability of the delta’s geomorphology has significantly increased in recent decades owing to the substantial decrease in fluvial sediment input from the Ebro River (Sánchez-Arcilla etal. 1998). Furthermore, like most deltaic areas, it is subject to subsidence, with mean values in the order of 3mm per annum (Ibáñez etal. 2010). 2.2 Data This study utilised various data sources to characterise mean water levels. Storm-surge data were extracted from the hindcast mean water levels at a coastal node within the study area (Fig.1), sourced from the Global Ocean Surge (GOS) database (Cid etal. 2014). The dataset consists of a 1-h interval mean water level time series spanning 1950–2014, with a horizontal resolution of 1/8° (approximately 14km). The dataset consists of simulated storm surges by modelling sea level variations driven by atmospheric pressure and wind. It was extensively validated using tide gauge measurements and satellite altimetry data. Astronomical tide data were obtained from a tidal gauge situated at the Tarragona port, part of the REDMAR network operated and maintained by Puertos del Estado (https:// portus. puert os. es/? locale= en#//). The total water level data for the study site during Storm Gloria in January 2020 were acquired from simulations conducted by Amores etal. (2020). The SLR Fig. 1 Location of the study area on the Mediterranean coast of Spain: Fangar Bay in the Ebro Delta (Tarragona), and the GOS (water level data) node Natural Hazards projection used for the area is based on the median estimate of the IPCC AR6 SP5-8.5 scenario, downscaled for Barcelona (Garner etal. 2021). This scenario assumes high greenhouse gas emissions with limited climate mitigation efforts and represents a worst-case, high-emission trajectory with no additional climate policies implemented. The topography of the site was characterised using two digital elevation models (DEM) with different resolutions (2m x 2m and 5m × 5m), both derived from lidar data provided by the Cartographic and Geological Institute of Catalonia (http:// www. icgc. cat). 3 Methods 3.1 General framework The methodological approach used in this study comprises two primary steps (Fig.2). First, the storm-surge climate was obtained from a long time series of meteorological tidal data, and then synthetic surge storms for selected return periods were fully defined by assigning them a given duration and storm shape (Sect.3.2). Subsequently, different scenarios were defined in terms of synthetic surges and compounding water levels, i.e., surge-tide and surge-SLR (Sect.3.3). Inundation under these storm scenarios was simulated using the LISFLOOD-FP numerical model (Sect.3.4), which was previously validated by simulating the inundation of the study area during the January 2020 Storm Gloria (Sect.3.5). 3.2 Storm surge climate Extreme surge events were identified by applying the peak-over-threshold (POT) method to the GOS dataset. Following Sanuy etal. (2020), a double-threshold strategy was implemented. The first threshold, set at the 0.98th quantile of the surge data (0.24m), identified storm candidates, imposing a minimum duration of 6h with a 24-h lag between consecutive events to ensure their independence. Subsequently, a second threshold equal to the 0.995th quantile (0.33m) was applied, retaining only the events that reached this level at their peak. Each surge event was characterised by its peak level and duration, defined as the time at which the water level exceeded the first threshold. Once events were identified, their probabilistic distribution was modelled by using the generalised Pareto distribution (GPD) (Davison and Smith 1990), which is given by (σ > 0 and y > 0): Fig. 2 Overview of the general methodological framework Natural Hazards where ξ and σ are the shape and scale parameters of the distribution. Following Egozcue etal. (2006), the peak surge values were first log-transformed, as the log scale represents an improved method for positive measurements with relative differences (Tarantola 2006). In addition to assessing the magnitude of storm surges associated with selected probabilities or return periods (T), defining synthetic storms for flood assessment requires consideration of surge duration and shape. To estimate the surge durations for synthetic storms, the relationship between surge intensity and duration was analysed for all identified events, fitting a power relationship between event durations and surge peak values. Subsequently, the assignment of shape (time evolution) to synthetic surges involved the assumption that events start and end at the 0.98th quantile level (0.24m), reaching their peak at the midpoint of their duration. The events dataset was then categorised into distinct groups based on the magnitude of the peak surge (0.33–0.35, 0.35–0.40, 0.40–0.45, 0.45–0.50, 0.50–0.55, 0.55–0.60, and > 0.60) to accommodate potential variations in shape linked to surge intensity. Within each group, the persistence of the storm above different surge levels at 0.025-m intervals from the threshold to the peak was retained for each event (Fig.3a). Normalising the surge steps and durations obtained by the event’s peak surge and total duration, respectively, enabled the construction of a synthetic shape for each group (Fig.3b and c). Mean values of relative surge were computed at discrete ranges of relative duration (0–10%, 10–20%, 20–30%, 30–40%, 40–50%, and 50–75%) (Fig.3b) to facilitate the assignment of a relative surge magnitude to each relative duration, thereby generating the final storm hydrograph shape for each group (Fig.3c). For a specified T, the process involved obtaining the corresponding peak surge from the fitted GPD. The surge peak value was used in a power-law equation to estimate the associated total duration using the power fit. Subsequently, to determine the storm shape, the peak surge was used to select the corresponding groups, and both the peak surge and total duration were used to translate the storm shape from relative to absolute values. It is important to note that because storm surges will be solely utilised for inundation purposes without morphodynamic feedback, the specific shape of the surge is not as crucial as ensuring that the selected shape maintains the duration of water levels above specified elevations throughout the entire event. The developed method consistently achieves preservation across a range of surge intensities. 3.3 Compounding scenarios To evaluate the importance of the compound effects resulting from various water-level variations in surge flooding, we considered the potential effects of both astronomical tides and SLR. To account for the compounding effect of the astronomical tide on surge flooding, we examined two specific scenarios: one in which the peak of the storm surge aligns with high tide and another in which it aligns with low tide. These scenarios captured the potential phase variations between both components and were constructed by integrating the spring astronomical tidal cycle obtained from the Tarragona port tide gauge with the surge events, considering the two specified combinations. To address SLR compounding with surges, we used SLR projections based on the IPCC AR6 medium confidence SSP5-8.5 scenario (Fox-Kemper et al. 2021; (1) F Y(y;𝜎,𝜉)=1− ( 1+𝜉 𝜎y )−1 𝜉 Natural Hazards Fig. 3 Synthetic storm shape construction for each group of peak surge magnitude. a Individual storm’s persistence over 0.025 surge steps (S1, …, S4) is retained. Surge levels relative to the peak and persistence relative to the event’s total duration are calculated (e.g., relative surge level S2/Peak has a relative persistence of (B* + C*)/Tot dur; where aisle S4/Peak has A*/Tot dur). b Values obtained from all storms in the group are divided into discrete ranges of relative duration, with mean values of relative surge obtained for each bin. c Mean surges are used to assemble the synthetic storm, with the peak location imposed at the centre of the event Natural Hazards Garner etal. 2021; Kopp etal. 2023). We selected three-time horizons–2050, 2075, and 2100–corresponding to SLR values for Barcelona (the closest location) of 0.2m, 0.58m, and 0.85m, respectively, relative to 2014. For each time horizon, the water level scenario was determined by considering that the mean sea level under which a given storm surge occurred had risen by the corresponding SLR. The analysis was conducted for storm surges associated with return periods of 1, 10, and 100years (T1, T10, and T100, respectively), which served as the baseline scenarios. Subsequently, this analysis was replicated for scenarios that incorporated the compound effects of astronomical tides and SLR. 3.4 Inundation modelling We utilised the LISFLOOD-FP inundation model to evaluate the extent of storm-surgedriven inundation (Bates etal. 2005). The model employs a storage-cell approach on a raster grid, allowing the approximation of 2D diffusive waves and momentum equations for floodplain flows. By simulating dynamic wave propagation over the floodplain, the model calculates the water depth in each grid cell at every time step by employing Manning’s law for the flow between cells (Bates etal. 2013). We used the numerical floodplain acceleration solver recommended for coastal modelling because of its comparable efficacy to solvers integrating full shallow-water equations while maintaining a reasonable computational time, as demonstrated in previous studies (Bates etal. 2010; Neal etal. 2012; Shaw etal. 2021; Le Gal etal. 2023). A uniform friction parameter (Manning’s coefficient) of 0.04 was applied across the domain, representing the average value for various land types, including paddy fields, wetlands, bare soil, and water (Chow etal. 1998; Vieux 2004). Considering the expectation of soil saturation during the simulated events, no infiltration into the soil was assumed. The model was applied to the northern hemi-delta, specifically focusing on the vicinity of Fangar Bay, with the domain to be simulated shown in Fig.1. The inflow boundary conditions were defined by an hourly water-level time series along the bayside shoreline. The remaining boundaries were designated free-flow conditions. For the compound SLR scenarios, the modelling approach followed two key steps. First, we performed an initial simulation to establish a baseline condition under the projected SLR. In this step, a constant elevated water level corresponding to the projected SLR was maintained, allowing the model to stabilize and reach a new equilibrium, representing the long-term effects of increased mean sea levels. This steady-state condition served as a reference, capturing the direct influence of SLR. In the second step, after the new equilibrium was established, we introduced storm surge events as additional forcing on top of the SLR-adjusted water level. This allowed us to simulate and analyse the combined impacts of storm surges and the elevated sea level, capturing the compound effects of SLR and extreme weather events on coastal inundation. Given the known influence of Digital Elevation Model (DEM) resolution on flood models (Bates etal. 2008; Seenath 2018) and the presence of an intricate network of channels and levees (Alvarado-Aguilar etal. 2012), two horizontal grid resolutions were tested (2m × 2m and 5m × 5m). The results indicated no significant differences, which led to the selection of a mesh composed of 5 × 5m cells to effectively reduce the computational time. Natural Hazards 3.5 Validation Prior to utilising the LISFLOOD-FP model to evaluate the areal extent of flood-prone areas under the selected scenarios, the model was qualitatively validated. This validation involved comparing its prediction with the observed inundation during the impact of Storm Gloria in January 2020 (Amores etal. 2020; Caballero etal. 2024). This event, characterised as the largest coastal storm recorded in the region, extensively affected the Spanish Mediterranean coast, resulting in significant damage attributed to flooding and erosion hazards (Canals and Miranda 2020). The Fangar Bay LISFLOOD model was applied using the total water level time series simulated by Amores etal. (2020) as the boundary conditions during the event. The recorded spatial variability in water levels was considered by preserving the temporal evolution of the storm at six locations along the coastal fringe of the study area and assigning these data to the nearest coastal segments (Fig.4). 4 Results 4.1 Storm‑surge climate POT analysis identified 136 independent surge events over the period 1950–2014 (~ 2.1 events per year). Figure5 illustrates the fitted GPD for extreme events, along with the power-fit model of the relationship between the event surge peaks and total durations. The mean surge peak for the 136 events was 0.42m, corresponding to a 1-year T, with an associated total duration of 28h. The magnitudes of the surges associated with Ts of 10 and 100years were 0.57m and 0.64m, respectively, with total durations of 82h and 127h. The surge climate and design values for the selected Ts captured the expected pattern for this Mediterranean region, which is characterised by relatively low surge magnitudes. Figure6 shows synthetic storm surge shapes, with baseline cases (Fig. 6a) showing slight variations in progression toward the peak owing to categorisation into different surge Fig. 4 a Digital elevation model of the LISFLOOD Fangar Bay model depicting node locations (BC1 to BC6) where boundary conditions from Amores etal. (2020) were extracted, and corresponding (coloured) coastal segments where they were applied. b Time series of the total water level during Storm Gloria in 2020 for nodes BC1 to BC6 as simulated by Amores etal. (2020) Natural Hazards 5 Discussion In this study, we examined the potential role of storm surges in driving flooding along the western Mediterranean coast of Spain. The geographical features of this region play a crucial role in shaping the extent of hazards. Thus, the prevailing conditions are given by low-magnitude surges, typically not exceeding 0.50m even under extreme conditions, and a micro-tidal environment characterised by astronomical tidal ranges of approximately 0.25m. Consequently, their impact on natural exposed sandy coastlines tends to be mitigated, as the elevation of berms and dunes typically prevents direct flooding in these areas. To validate this hypothesis, we analysed the role of storm surges acting in isolation as a primary driver of flooding in the Ebro Delta. Specifically, we focused on one of the delta’s sheltered passive coastlines, where the geomorphology creates potential susceptibility to surge-induced flooding. As previously mentioned, along the Mediterranean basin this type of low-lying coastal environment is found in the form of deltas, wetlands, and lagoons. Despite their limited extension, it is relevant to assess the potential impact of storm surges on these environments as these areas have significant ecological value to evaluate the associated risks and determine the necessity of implementing specific adaptation measures. As expected, our results revealed that events with lower probabilities of occurrence had a greater impact on the extent of flooding. Due to the shape of the probability distribution of surge intensity (Fig.5), the surge magnitude increased by approximately 50% across the range of analysed return periods (from 1 to 100years), equating to an absolute increase of approximately 0.20m. Despite this modest increment, there was a significant increase in flood extent from 64 to 474ha (an increase of approximately 750%). A substantial portion of this non-linear escalation can be attributed to the concurrent increase in the event duration for higher-intensity surges (Fig.5). The observed augmentation in both intensity and duration led to considerably larger water volumes penetrating the hinterland, up to 770% (from 1.08 hm3 to 9.39 hm3, for the 1-year to 100-year events, respectively). This underscores the critical importance of accurately determining event duration when evaluating flood extent (e.g. Höffken etal. 2020). In this sense, the construction of the synthetic storm surge to be simulated plays a crucial role in the assessment of coastal flooding. Unlike approaches employing basic geometrical shapes such as triangles (e.g. Purvis etal. 2008), the method presented in this study does not aim to closely replicate the shape of the recorded surges. Instead, it focuses on preserving the cumulative water level excess to minimise deviations that may impact the total water volume during the event. For storm waves, Callaghan etal. (2009) proposed a similar approach to reproduce the duration of events, while the uncertainty introduced by using triangular storm shapes has been analysed by Duo etal. (2020) among others. The discrepancy between the increase in the surge magnitude and flood extent was further influenced by the topography of the area. Despite being low-lying, the topography of the plain remains segmented and compartmentalised by a network of channels and levees that delineate the rice fields. This intricate network induces a pond-pool effect during the inundation, which is reflected in the variation pattern of flood depths for small changes in surge values. Alvarado-Aguilar etal. (2012) highlighted the significance of this network when analysing the inundation of the Ebro Delta plain due to SLR. Similar flood-control mechanisms facilitated by levees, channels, and other infrastructure in floodplains have been observed in various environments (Trigg et al. 2013). Under such circumstances, the resolution of the DEM used in flood modelling is crucial for accurately simulating the effects of connectivity and obstacles on water distribution across the plain. Common grid Natural Hazards cell resolutions, typically in the order of a few tens of metres, prove inadequate in representing these complexities and often lead to overestimation of the flood extent (e.g. Muthusamy etal. 2021). In our analysis, lidar-derived DEMs with resolutions of 2m and 5m yielded comparable results, and we chose the lower resolution to balance accuracy with computational efficiency (Xing etal. 2019; Muthusamy etal. 2021). The astronomical tide constitutes the deterministic component of the total water level during inundation in contrast to the stochastic nature of the surge. Consequently, we simulated the compounding effect by considering two scenarios: aligning the peak surge with high tide, and aligning it with low tide. This approach enabled us to assess the potential range of variations in flood characteristics. Although the compounding effects of astronomical tides and surges may have a significant impact during storm events in mesoand macro-tidal environments, leading to substantial increases in flood extent (Thomas etal. 2019), the western Mediterranean coast, characterised by very low tidal ranges and minimal surges, experiences a comparatively less pronounced effect. Results for the analysed case revealed an increase in the inundation extent from 30 to 100% for storm tides (surge peak during the high tide) when compared to scenarios without tidal influence, with the magnitude of increase correlating inversely with the intensity of the event, i.e., larger for events with lower T. Notably, this increase was observed regardless of whether the storm peak coincided with high or low tide, although the effect was notably smaller in the latter case. Although astronomical tides exert a smaller influence than mesoand macrotidal environments, their effect cannot be neglected when aiming to accurately predict the expected flood extent during storm surges. The compounding effect of SLR and storm surges in the area was examined by simulating inundation events under elevated mean sea levels over different time horizons using the AR6 SSP5-8.5 scenario. Although this method is commonly employed, it may not accurately represent the effects on open sandy coasts owing to its failure to consider dynamic coastal responses and morphological changes that typically occur in response to rising sea levels. Such simulations usually consider the same initial coastal configuration, simply submerged under a higher sea level, rather than allowing the shoreline morphology to adjust and evolve as sea levels rise over time (Grases etal. 2020). Consequently, such approaches tend to overestimate inundation levels (e.g. López-Dóriga etal. 2020). However, for passive coasts such as those analysed in this study, this approach remains plausible. This is because, in the absence of inorganic and organic contributions to vertical accretion in the plain, no morphological response to SLR is anticipated (Ibáñez etal. 2014). Consequently, the inclusion of SLR revealed a notable increase in inundation across the deltaic plain, consistent with previous analyses of SLR-driven inundation in the area (Alvarado-Aguilar etal. 2012; López-Dóriga etal. 2020). Thus, over the analysed time horizons, the flood extent corresponding to a 100-year return period will be experienced in events with reduced return periods, decreasing by a factor of 1/100 every 25years from 2050 to 2100 under the AR6 SSP5-8.5 scenario (Fig.12). For instance, inundation over a 100year return period under the present conditions will occur as frequently as an annual event by 2050. Subsequently, by 2075, the inundation corresponding to a 100-year return period in 2050 will be akin to a 1-year event. However, upon closer examination of surge contribution to future inundations, it became apparent that surge relevance diminishes over time. Specifically, for the analysed storm events and SLR projections, the significance of surge-induced flooding was highest at shorter time horizons, corresponding to lower SLR values (0.2m). Under these conditions, although the SLR component itself may not directly contribute significantly to plain inundation, the combined effect of surges acting on elevated water levels results in extensive Natural Hazards flooding compared to scenarios without SLR. This observation is particularly pertinent, as it leads to a notable increase in both the frequency and extent of flooding events. For longer time horizons, although the surge contribution to the flood extent increased compared to current conditions, relative surge significance decreased concerning SLR (Fig.12). By 2075, passive inundation driven solely by SLR is projected to surpass the flood-prone area for a 100-year surge under current conditions. Furthermore, by 2100, the SLR component is expected to exceed the total flood-prone area associated with a period of 100years by 2050. In essence, the characteristics of the study area’s topography and surge climate lead to the decreasing importance of surge inundation as SLR values increase. Notably, these effects may manifest earlier than projected due to the typical subsidence of these coastal plains (e.g. Vecchio etal. 2024); in the case of the Ebro Delta, subsidence has been estimated to occur at a maximum rate of approximately 2.7mm/year (RodríguezLloveras etal. 2020). The potential consequences of storm surges in the area are primarily related to their influence on rice agriculture, the dominant land use in the flood-prone region. It is crucial to consider the timing of surges concerning the agriculture cycle. Storm surges are most frequent between November and April (Fig.13), while the rice production cycle in the Ebro Delta extends from April to September (Fig.13, Soriano-González etal. 2022). Under these conditions, the direct impact of storm surges on rice crops, defined as the inundation of rice plants with seawater, is unlikely to be significant. However, such an impact could occur during rare, long return period surges in early spring (March–April), when the pre-flood fertilisation cycle is underway, potentially increasing soil salinity and, potentially, affecting rice production (e.g. Casanova 1998). It is also important to note that rice fields are typically inundated with freshwater to manage soil salinity and prepare for sowing. The future consequences of storm surges will largely depend on the time frame under consideration. In the near term, significant impacts from storm surges alone are unlikely under current conditions (Fig.9), except for rare events with long return periods, such as Fig. 13 Top: Number of surge events per month. Bottom: rice-farming calendar in the Ebro Delta (adapted from Soriano-González etal. 2022). The optimal water regime entails the post-harvest practice of either flooding fields (October to December) or allowing them to drain, following farmers’ practices Natural Hazards Storm Gloria. However, as the time horizon extends, SLR will increasingly contribute to inundation, substantially expanding flood-prone areas (Fig.11). While the timing of storm surge impacts is expected to remain consistent with present-day patterns, the extent of flooding will likely increase, exposing a broader floodplain and potentially impacting rice fields more frequently. This is due to the likelihood of shorter return periods for impactful events. By 2075 and 2100, SLR is expected to become the dominant concern, surpassing the effects of storm surges. This shift will expand flood-prone areas along passive coasts, intensifying the influence of saltwater on the hydrology of coastal plains. Although this poses challenges for agriculture, such as increased permanent inundation and higher soil salinity in low-lying areas (e.g. Genua-Olmedo etal. 2016), it also creates opportunities for the development of new natural areas, such as wetlands and marshes, within the inundated zones (Prado etal. 2019; López-Dóriga and Jiménez 2020). 6 Summary andconclusions Although storm surges themselves generally do not contribute substantially to coastal flooding along the western Mediterranean open coasts owing to their typically low magnitudes, this study highlights their potential relevance to passive coasts sheltered from wave action. The increase in flooded areas during low-probability events, as a combined result of the increased magnitude and duration of storm surges, underscores the importance of considering both factors in risk assessment and, therefore, the need to adopt methods that conserve water volume over different levels throughout the event. The compounding effects of mean water level variations over different timescales, such as astronomical tides and SLR, increase the contribution of storm surges to coastal flooding under Mediterranean conditions. As anticipated in a micro-tidal environment, although the compounding effect of astronomical tides was found to enhance storm-surge flooding, the projected increase was minor under the conditions tested. The compounding effect of SLR on storm-surge flooding was found to be highly significant, with its relative contribution varying over time. In the short term, although the impact of SLR on plain inundation was small, its compound effect substantially amplified the impact of storm surges. However, over longer time frames, the contribution of SLR predominates, overshadowing the influence of storm surges and becoming the primary factor controlling plain inundation. For the tested conditions, as the time horizon increased, an event with a 1/100 shorter return period is needed every 25years to generate an inundation extent equivalent to the flooding caused by less extreme, more probable events under present-day conditions. Although these conclusions may apply to other passive low-lying coasts of the Western Mediterranean, the specific characteristics of each local plain will modulate the magnitude of the effects on the flood extent. In the case under analysis, the presence of an established network of channels and levees, typical of an anthropized plain such as rice fields, plays a crucial role in regulating the water flow across the floodplain. Achieving an accurate representation of real-world conditions without overshadowing these effects requires the use of a high-precision DEM. In our study, this was accomplished using a 5m × 5m DEM derived from lidar data. The anticipated impact of inundation depends on local exposure values, although the predominant habitat types in these areas are typically natural and agricultural. Natural environments are generally adapted to temporary inundations, whereas the impact on agricultural land depends on the timing of storm surges relative to the farming cycle. In the Natural Hazards case under analysis, there appeared to be a lag between them, suggesting a limited direct influence. In conclusion, this study provides insights into the characterisation of the passive border of the Ebro Delta plain in semi-enclosed lagoons as an area sensitive to storm-surge flooding. Currently, the affected surface area is primarily significant during long-return-period events. However, without adaptation measures, it is projected that by 2050, the potential flood-prone area will increase substantially, even during annual events. Given these conditions, increasing soil salinity may diminish agricultural productivity, presenting an opportunity for area renaturalisation by converting rice fields into wetlands in low-lying affected regions. Appendix See Fig.14. Acknowledgements The authors want to thank IH Cantabria for water level (GOS) data used in this study, and to Prof. Marta Marcos (Universitat of Illes Balears) for supplying simulated water level time series in the study area during the Gloria storm. We thank the projection authors for developing and making the sealevel rise projections available, multiple funding agencies for supporting the development of the projections, Fig. 14 Flooded area in the corresponding SLR-alone simulations for 2050, 2075 and 2100, in Fangar Bay Natural Hazards and the NASA Sea Level Change Team for developing and hosting the IPCC AR6 Sea Level Projection Tool. Author contributions RR: methodology, formal analysis, investigation, data curation, visualization, writing (original draft). MS: methodology, formal analysis, investigation, data curation, visualization, writing (original draft). JAJ: conceptualization, methodology, investigation, writing (original draft), resources, supervision and project administration. All authors contributed to the interpretation and discussion of the obtained results and to the writing of the final manuscript. Funding Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This study was conducted within the framework of the C3RiskMed (PID2020-113638RB-C21, AEI/https:// doi. org/ 10. 13039/ 50110 00110 33) research project, funded by the Spanish Ministry of Science and Innovation. The first author was funded by a PhD Grant from the Ministry of Science and Innovation (PRE2018084174) and the second author by a Margarita Salas postdoc grant. Data availability All data used to inform this study are available from open-source databases identified in the text. GOS water level data were obtained from IH Cantabria (https:// ihdata. ihcan tabria. com/). Water level time series during the Gloria event were provided by Prof Marta Marcos (UiB). Tarragona tidal gauge data were obtained from Puertos del Estado (https:// www. puert os. es/ eses/ ocean ografi a/ Pagin as/ portus. aspx). Ebro delta DEM data were obtained from Institut Cartogràfic de Catalunya (https:// icgc. cat/ Desca rregu es/ Eleva cions/ Model-deleva cionsdelterre nyde5x5-m). SLR projections were obtained NASA/ IPCC Sea level projection tool (https:// seale vel. nasa. gov/ ipccar6sealevelproje ctiontool). Declarations Conflict of interests The contact author has declared that none of the authors has any conflict of interests. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. References Agulles M, Jordà G, Lionello P (2021) Flooding of sandy beaches in a changing climate. The case of the Balearic Islands (NW Mediterranean). Front Marine Sci. https:// doi. org/ 10. 3389/ fmars. 2021. 760725 Alvarado-Aguilar D, Jiménez JA, Nicholls RJ (2012) Flood hazard and damage assessment in the Ebro Delta (NW Mediterranean) to relative sea level rise. Nat Hazards 62(3):1301–1321. https:// doi. org/ 10. 1007/ s110690120149-x Amores A, Marcos M, Carrió DS, Gómez-Pujol L (2020) Coastal impacts of Storm Gloria (January 2020) over the north-western Mediterranean. Nat Hazards Earth Syst Sci 20(7):1955–1968. https:// doi. org/ 10. 5194/ nhess2019552020 Androulidakis YS, Kombiadou KD, Makris CV, Baltikas VN, Krestenitis YN (2015) Storm surges in the Mediterranean Sea: variability and trends under future climatic conditions. Dyn Atmos Ocean 71:56– 82. https:// doi. org/ 10. 1016/j. dynat moce. 2015. 06. 001 Androulidakis Y, Makris C, Mallios Z, Pytharoulis I, Baltikas V, Krestenitis Y (2023) Storm surges and coastal inundation during extreme events in the Mediterranean Sea: the IANOS Medicane. Nat Hazards 117(1):939–978. https:// doi. org/ 10. 1007/ s1106902305890-6 Antonioli F, De Falco G, Lo Presti V, Moretti L, Scardino G, Anzidei, etal (2020) Relative sea-level rise and potential submersion risk for 2100 on 16 coastal plains of the Mediterranean Sea. Water 12(8):2173. https:// doi. org/ 10. 3390/ w1208 2173 Bates PD, Dawson RJ, Hall JW, Horritt MS, Nicholls RJ, Wick J, Hassan MAAM (2005) Simplified twodimensional numerical modeling of coastal flooding and example applications. Coast Eng 52:793–810. https:// doi. org/ 10. 1016/j. coast aleng. 2005. 06. 001 Natural Hazards Bates PD, Horritt MS, Fewtrell TJA (2010) Simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling. J Hydrol 387:33–45. https:// doi. org/ 10. 1016/j. jhydr ol. 2010. 03. 027 Bates P, Trigg M, Neal J, Dabrowa A (2013) LISFLOOD-FP. School of Geographical Sciences, University of Bristol. Bristol, UK, User manual Bates P, Fewtrell T, Trigg M, Neal, J (2008) LISFLOOD-FP User manual and technical note, code release 4.3. 6. University of Bristol. Blay J, Àvila A (2020) Els efectes del temporal Glòria: una mostra de la necessitat d’actuació urgent al delta de l’Ebre. Treballs De La Societat Catalana De Geografia 89:163–189. https:// doi. org/ 10. 2436/ 20. 3002. 01. 195 Caballero I, Roca M, Dunbar MB, Navarro G (2024) water quality and flooding impact of the record-breaking storm Gloria in the Ebro delta (Western Mediterranean). Remote Sens 16:41. https:// doi. org/ 10. 3390/ rs160 10041 Cabezas-Rabadán C, Pardo-Pascual JE, Palomar-Vázquez J, Roch-Talens A, Guillén J (2024) Satellite observations of storm erosion and recovery of the Ebro Delta coastline. NE Spain Coast Eng 188:104451. https:// doi. org/ 10. 1016/j. coast aleng. 2023. 104451 Callaghan DP, Roshanka R, Andrew S (2009) Quantifying the storm erosion hazard for coastal planning. Coast Eng 56(1):90–93. https:// doi. org/ 10. 1016/j. coast aleng. 2008. 10. 003 Canals M, Miranda J (2020) Sobre el temporal Gloria (19–23.01.20), els seus efectes sobre el país i el que se’n deriva. Report de Resposta Ràpida (R3). Institut d’Estudis Catalans, Collecció Informes, Informe de la Secció de Ciències i Tecnologia, Barcelona. Casanova, D (1998). Quantifying the effects of land conditions on rice growth. A case study in the Ebro delta (Spain) using remote sensing. Ph D Thesis, Wageningen University, 132 pp. CEDEX (2021) Plan para la protección del Delta del Ebro. Technical report 2017–2020/95, MITECO, Madrid. Chow VT, Maidment DR, Mays LW (eds) (1998) Applied hydrology. McGraw-Hill, New York, pp 20–52 Cid A, Castanedo S, Abascal AJ, Menéndez M, Medina R (2014) A high resolution hindcast of the meteorological sea level component for Southern Europe: the GOS dataset. Clim Dynam 43:2167–2184. https:// doi. org/ 10. 1007/ s003820132041-0 Conte D, Lionello P (2013) Characteristics of large positive and negative surges in the Mediterranean Sea and their attenuation in future climate scenarios. Global Planet Change 111:159–173. https:// doi. org/ 10. 1016/j. glopl acha. 2013. 09. 006 Davison AC, Smith RL (1990) Models for exceedances over high thresholds. J R Stat Soc Ser B 52(3):393– 425. https:// doi. org/ 10. 1111/j. 25176161. 1990. tb017 96.x Duo E, Sanuy M, Jiménez JA, Ciavola P (2020) How good are symmetric triangular synthetic storms to represent real events for coastal hazard modelling. Coast Eng 159:103728. https:// doi. org/ 10. 1016/j. coast aleng. 2020. 103728 Egozcue JJ, Pawlowsky-Glahn V, Ortego MI, Tolosana-Delgado R (2006) The effect of scale in daily precipitation hazard assessment. Nat Hazards Earth Syst Sci 6(3):459–470. https:// doi. org/ 10. 5194/ nhess-64592006 Fox-Kemper B, Hewitt HT, Xiao C, Aðalgeirsdóttir G, Drijfhout SS etal (2021) 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, ed. V MassonDelmotte,P Zhai, APirani, SL Connors, C Péan, etal., pp. 1211–362. Cambridge, UK: Cambridge Univ. Press. Garner GG, Kopp RE, Slangen ABA, Edwards T, Levermann A (2021) IPCC AR6 Sea Level Projections. Version 20210809. Dataset accessed [2023-11-04] at https:// doi. org/ 10. 5281/ zenodo. 59147 09 Genua-Olmedo A, Alcaraz C, Caiola N, Ibáñez C (2016) Sea level rise impacts on rice production: the Ebro Delta as an example. Sci Total Environ 571:1200–1210. https:// doi. org/ 10. 1016/j. scito tenv. 2016. 07. 136 Grases A, Gracia V, García-León M, Lin-Ye J, Sierra JP (2020) Coastal flooding and erosion under a changing climate: implications at a low-lying coast (Ebro Delta). Water 12(2):346. https:// doi. org/ 10. 3390/ w1202 0346 Guillén J, Palanques A (1992) Sediment dynamics and hydrodynamics in the lower course of a river highly regulated by dams: the Ebro River. Sedimentol 39(4):567–579. https:// doi. org/ 10. 1111/j. 13653091. 1992. tb021 37.x Guillén J, Palanques A (1997) A historical perspective of the morphological evolution in the lower Ebro river. Environ Geol 30(3):174–180. https:// doi. org/ 10. 1007/ s0025 40050 144 Höffken J, Vafeidis AT, MacPherson LR, Dangendorf S (2020) Effects of the temporal variability of storm surges on coastal flooding. Front Mar Sci 7:98. https:// doi. org/ 10. 3389/ fmars. 2020. 00098 Natural Hazards Ibáñez C, Sharpe PJ, Day JW, Day JN, Prat N (2010) Vertical accretion and relative sea level rise in the Ebro Delta wetlands (Catalonia, Spain). Wetlands 30(5):979–988. https:// doi. org/ 10. 1007/ s131570100092-0 Ibáñez C, Day JW, Reyes E (2014) The response of deltas to sea-level rise: natural mechanisms and management options to adapt to high-end scenarios. Ecol Eng 65:122–130. https:// doi. org/ 10. 1016/j. ecole ng. 2013. 08. 002 Jiménez JA, Sancho A, Bosom E, Valdemoro HI, Guillén J (2012) Storm-induced damages along the Catalan coast (NW Mediterranean) during the period 1958–2008. Geomorphol 143–144:24–33. https:// doi. org/ 10. 1016/j. geomo rph. 2011. 07. 034 Kopp RE, Garner GG, Hermans THJ, Jha S etal (2023) The Framework for assessing changes to sealevel (FACTS) v1.0: a platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change. Geosci Model Dev 16:7461–7489. https:// doi. org/ 10. 5194/ gmd1674612023 Krestenitis YN, Androulidakis YS, Kontos YN, Georgakopoulos G (2011) Coastal inundation in the north-eastern Mediterranean coastal zone due to storm surge events. J Coast Conserv 15:353–368 Le Gal M, Fernández-Montblanc T, Duo E, Montes Perez J, Cabrita P, Souto Ceccon P, Gastal V, Ciavola P, Armaroli C (2023) A new European coastal flood database for low–medium intensity events. Nat Hazards Earth Sys Sci 23:3585–3602. https:// doi. org/ 10. 5194/ nhess2335852023 López-Dóriga U, Jiménez JA (2020) Impact of relative sea-level rise on low-lying coastal areas of catalonia, nw Mediterranean. Spain Water 12(11):3252. https:// doi. org/ 10. 3390/ w1211 3252 Marcos M, Tsimplis MN, Shaw AG (2009) Sea level extremes in southern Europe. J Geophys Res: Ocean. https:// doi. org/ 10. 1029/ 2008J C0049 12 Martínez-Megías C, Rico A (2022) Biodiversity impacts by multiple anthropogenic stressors in Mediterranean coastal wetlands. Sci Total Environ 818:151712. https:// doi. org/ 10. 1016/j. scito tenv. 2021. 151712 Mendoza E, Jiménez JA (2009) Regional geomorphic vulnerability analysis of Catalan beaches to storms. P I Civil Eng Mar En 162(3):127–135. https:// doi. org/ 10. 1680/ maen. 2009. 162.3. 127 Muis S, Verlaan M, Winsemius HC, Aerts JC, Ward PJ (2016) A global reanalysis of storm surges and extreme sea levels. Nat Commun 7(1):11969. https:// doi. org/ 10. 1038/ ncomm s11969 Muthusamy M, Casado MR, Butler D, Leinster P (2021) Understanding the effects of digital elevation model resolution in urban fluvial flood modelling. J Hydrol 596:126088. https:// doi. org/ 10. 1016/j. jhydr ol. 2021. 126088 Neal J, Villanueva I, Wright N, Willis T, Fewtrell T, Bates P (2012) How much physical complexity is needed to model flood inundation? Hydrol Process 26:2264–2282. https:// doi. org/ 10. 1002/ hyp. 8339 Newton A, Icely J, Cristina S, Brito A, Cardoso AC, Colijn F etal (2014) An overview of ecological status, vulnerability and future perspectives of European large shallow, semi-enclosed coastal systems, lagoons and transitional waters. Estuar Coast Shelf Sci 140:95–122. https:// doi. org/ 10. 1016/j. ecss. 2013. 05. 023 Storm surges in coastal areas. Natural Disaster Hotspots, Case Studies, The World Bank Hazard Management Unit, Disaster Risk Management Series 6:79-108. https:// doi. org/ 10. 1007/ s110690183553-z Passeri DL, Hagen SC, Medeiros SC, Bilskie MV, Alizad K, Wang D (2015) The dynamic effects of sea level rise on low-gradient coastal landscapes: a review. Earth’s Future 3(6):159–181. https:// doi. org/ 10. 1002/ 2015E F0002 98 Pérez-Gómez B, García-León M, García-Valdecasas J, Clementi E, Aranda CM et al (2021) Understanding sea level processes during western Mediterranean storm Gloria. Front Mar Sci 8:647437. https:// doi. org/ 10. 3389/ fmars. 2021. 647437 Pérez-Ruzafa A, Marcos C, Pérez-Ruzafa I (2011) Mediterranean coastal lagoons in an ecosystem and aquatic resources management context. Phys Chem Earth 36(5–6):160–166. https:// doi. org/ 10. 1016/j. pce. 2010. 04. 013 Prado P, Alcaraz C, Benito X, Caiola N, Ibáñez C (2019) Pristine vs. human-altered Ebro Delta habitats display contrasting resilience to RSLR. Sci Total Environ 655:1376–1386. https:// doi. org/ 10. 1016/j. scito tenv. 2018. 11. 318 Purvis MJ, Bates PD, Hayes CM (2008) A probabilistic methodology to estimate future coastal flood risk due to sea level rise. Coast Eng 55(12):1062–1073. https:// doi. org/ 10. 1016/j. coast aleng. 2008. 04. 008 Rodríguez-Lloveras X, Vilà M, Mora O, Pérez F, Pi R, Marturia J (2020) Detection of subsidence in the Ebro Delta plain using DInSAR: analysis of the measurements and the factors that control the phenomenon. P I Assoc Hydrol Sci 382:803–808. https:// doi. org/ 10. 5194/ piahs3828032020 Sánchez-Arcilla A, Jiménez JA, Valdemoro HI (1998) The Ebro delta: morphodynamics and vulnerability. J Coast Res 14(3):754–772 Natural Hazards Sanuy M, Jiménez JA, Ortego MI, Toimil A (2020) Differences in assigning probabilities to coastal inundation hazard estimators: event versus response approaches. J Flood Risk Manag 13:e12557. https:// doi. org/ 10. 1111/ jfr3. 12557 Sanuy M, Rigó T, Jiménez JA, Llasat MC (2021) Classifying compound coastal storm and heavy rainfall events in the north-western Spanish Mediterranean. Hydrol Earth Sys Sci 25:3759–3781. https:// doi. org/ 10. 5194/ hess2537592021 Sayol JM, Marcos M (2018) Assessing flood risk under sea level rise and extreme sea levels scenarios: application to the Ebro delta (Spain). J Geophys Res Ocean 123(2):794–811. https:// doi. org/ 10. 1002/ 2017J C0133 55 Seenath A (2018) Effects of DEM resolution on modeling coastal flood vulnerability. Mar Geodesy 41(6):581–604. https:// doi. org/ 10. 1080/ 01490 419. 2018. 15048 38 Shaw J, Kesserwani G, Neal J, Bates P, Sharifian MK (2021) LISFLOOD-FP 8.0: the new discontinuous Galerkin shallow-water solver for multi-core CPUs and GPUs. Geosci Model Dev 14:3577–3602. https:// doi. org/ 10. 5194/ gmd1435772021 Smith K, Ward R (1998) Floods: physical processes and human impacts. Wiley, Chichester, p 382 Soriano-González J, Angelats E, Martínez-Eixarch M, Alcaraz C (2022) Monitoring rice crop and yield estimation with sentinel-2 data. Field Crops Res 281:108507. https:// doi. org/ 10. 1016/j. fcr. 2022. 108507 Tarantola A (2006) Elements for physics: Quantities, qualities, and intrinsic theories. In Elements for Physics: Quantities, Qualities, and Intrinsic Theories. https:// doi. org/ 10. 1007/ 978-354031107-2 Taylor NG, Grillas P, Al Hreisha H, Balkız Ö etal (2021) The future for Mediterranean wetlands: 50 key issues and 50 important conservation research questions. Reg Environ Change 21:1–17. https:// doi. org/ 10. 1007/ s1011302001743-1 Thomas A, Dietrich JC, Asher TG, Bell M, Blanton BO etal (2019) Influence of storm timing and forward speed on tides and storm surge during Hurricane Matthew. Ocean Model 137:1–19. https:// doi. org/ 10. 1016/j. ocemod. 2019. 03. 004 Trigg MA, Michaelides K, Neal JC, Bates PD (2013) Surface water connectivity dynamics of a large scale extreme flood. J Hydrol 505:138–149. https:// doi. org/ 10. 1016/j. jhydr ol. 2013. 09. 035 Valdemoro HI, Sánchez-Arcilla A, Jiménez JA (2007) Coastal dynamics and wetlands stability. Ebro Delta Case Hydrobiol 577(1):17–29. https:// doi. org/ 10. 1007/ s107500060414-7 Vecchio A, Anzidei M, Serpelloni E (2024) Sea level rise projections up to 2150 in the northern Mediterranean coasts. Environ Res Lett 19(1):014050. https:// doi. org/ 10. 1088/ 17489326/ ad127e Vieux BE (2004) Distributed hydrologic modeling using GIS, 2nd edn. Kluwer Academic Publishers, The Netherlands, pp 91–128. https:// doi. org/ 10. 1007/ 978940159710-4 Vousdoukas MI, Voukouvalas E, Annunziato A, Giardino A, Feyen L (2016) Projections of extreme storm surge levels along Europe. Clim Dyn 47:3171–3190. https:// doi. org/ 10. 1007/ s003820163019-5 Xing Y, Liang Q, Wang G, Ming X, Xia X (2019) City-scale hydrodynamic modelling of urban flash floods: the issues of scale and resolution. Nat Hazards 96:473–496. https:// doi. org/ 10. 1007/ s110690183553-z Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.