Storm Surge Research Articles

Interactions between vegetation, sedimentation and flood inundation levels in wetlands

Wetlands produce key ecosystem services to mitigate the impacts of peak flows caused by pluvial or fluvial floods or storm surges. Sediment floods were characterized by a peak flow flowing over a simulated wetland, populated with two natural species. Floods have been drawn as flows of height H, into waters of height h, where H > h. Peak flow along the flume passed through: peak flow adjustment; peak flow; drag-dominated peak flow; and gravity current regimes. For high inundation wetland levels, settling rates of coarse and fine sediment were similar during the peak flow regime. At larger distances, sedimentation decreased monotonically, with higher sedimentation of fine particles. For low inundation levels, the sedimentation rate during the drag-dominated peak flow regime was higher for coarse particles. Vegetation decreased the inundation level needed for enhancing sedimentation. Our study then adds practical knowledge at considering that the synergies between the vegetation and the inundation level may enhance wetland services such as the mitigation of pluvial, fluvial or coastal floodings.

Effects of tropical cyclone intensity on spatial footprints of storm surges: an idealized numerical experiment

Abstract Storm surges caused by tropical cyclones (TCs) have long ranked first among all types of marine disasters in casualties and economic losses, and can lead to further regional exacerbation of consequences stemming from these losses along different coastlines. Understanding the spatial footprints of storm surges is thus highly important for developing effective risk management and protection plans. To this end, we designed an ideal storm surge model based on FVCOM to explore the relationship between TC intensity and the spatial footprint of storm surges, and its intrinsic mechanism. The spatial footprints of both positive and negative storm surges were positively correlated with TC intensity; however, the latter was more sensitive to the intensity when the TC intensity is weaker than CAT3 TC’s. The average positive storm surge footprint of CAT1 was 574 km, with CAT3 and CAT5 increasing by 6% and 25%, respectively, compared to CAT1. The average spatial footprint of the negative storm surge of CAT1 was 1,407 km, with CAT3 and CAT5 increasing by 18% and 29%, respectively, compared to CAT1. The decomposition and mechanism analysis of the storm surge show that the main contributing component of the total surge at the south end of the storm’s landfall and during the time of the forerunner was the Ekman surge, whereas the contribution of the normal surge component to the north and during the time of the main surge and resurgence was dominant. In addition, not all the spatial footprints of the storm surge components increased with the TC intensity, as the total surge did, similar to the Ekman surge. These quantitative analyses and intrinsic mechanisms provide a theoretical basis for predicting and evaluating storm surge risks.

Tropical Cyclone Storm Surge‐Based Flood Risk Assessment Under Combined Scenarios of High Tides and Sea‐Level Rise: A Case Study of Hainan Island, China

AbstractIn the context of climate change, coastal flood risk is intensifying globally, particularly in China, where intricate coastlines and frequent tropical cyclones make storm surges a major concern. Despite local government's efforts to initiate coastal monitoring networks and qualitative risk guidelines, there remains a gap in detailed and efficient quantitative assessments for combinations of multiple sea‐level components. To address this, we develop the Tropical Cyclone Storm Surge‐based Flood Risk Assessment under Combined Scenarios (TCSoS‐FRACS). This framework integrates impacts of storm surges, high tides, and sea‐level rise using a hybrid of statistical and dynamic models to balance reliability and efficiency. By combining hazard, exposure, and vulnerability, it incorporates economic and demographic factors for a deeper understanding of risk composition. Applying TCSoS‐FRACS to Hainan Island reveals that the combined effects of storm surges, high tides, and sea‐level rise significantly amplify local coastal flood risk, increasing economic losses to 4.27–5.90 times and affected populations to 4.96–6.23 times. Additionally, transitioning from Fossil‐fueled Development (SSP5‐8.5) to Sustainability (SSP1‐1.9) can reduce the risk increase by approximately half. The equivalence in flood hazard between current high tides and future sea level under a sustainable scenario boosts confidence in climate change adaptation efforts. However, coastal cities with low hazard but high exposure need heightened vigilance in flood defense, as future risk could escalate sharply. Our study provides new insights into coastal flood risk on Hainan Island and other regions with similar profiles, offering a transferable and efficient tool for disaster risk management and aiding in regional sustainable development.

Genus Level Classification of the Mangroves in Indian Sundarbans using Sentinel-2 Multispectral Imagery

Abstract Mangroves are the most productive ecosystems that provide stabilization to the coastlines, help in carbon sequestration, reduce storm surges, defend the coastal inhabitants and play a role in sustaining the local economy. Mangroves are halophytic in nature that typically thrive along tropical and subtropical coastlines in the saline intertidal zone. This paper explores the potentiality of Sentinel-2 MSI Imagery in separating different mangrove genus that has been evaluated using different classification algorithms like Maximum Likelihood Classifier (MLC), Mahalanobis Distance (MD), Minimum Distance (MD), Spectral Angle Mapper (SAM), knowledge-based classifier such as Random Forest (RF) and Support Vector Machine (SVM). The estimated accuracy is higher for Random Forest (88.50%) followed by Support Vector Machine (85.30%) and Maximum Likelihood Classifier (85.10%) as compared to Mahalanobis Distance (81.10%), Spectral Angle Mapper (71.20%), and Minimum Distance (75.30%). The result showed that Sentinel-2 Multispectral Imagery can efficiently discriminate 15 different mangrove genera distributed in the entire Indian Sundarbans and can simultaneously replace the barriers in terms of cost and availability of the spaceborne and airborne hyperspectral sensors.

Digitizing the Williamstown, Australia Tide‐Gauge Record Back to 1872: Insights Into Changing Extremes

AbstractFor Williamstown tide gauge, at the northern‐most point of Port Phillip Bay (PPB), Melbourne, Victoria, tide registers from 1872 to 1966 and marigrams from 1950 to 1966, were digitized to extend sea‐level records back almost 100 years. Despite some vertical datum issues in the early part of the record, the data set is suitable for extreme sea‐level trend analysis after removal of the annual mean sea level. The newly digitized data was combined with the digital record to produce a combined record from 1872 to 2020. Analysis of this record revealed known problems of siltation of the tide gauge stilling well and associated reduction in tidal range at times during 1880–1895 and 1910–1940. A positive trend in tidal amplitude of 0.41 ± 0.01 mm yr−1 was found over 1966–2020, likely due to reduced hydraulic friction at the narrow entrance to PPB. Extreme sea‐level trends were examined over 1872–2020 for storm tides (the combination of storm surge and tide) after removal of the annual mean, and residuals after subtraction of the predicted tides. A non‐stationary Gumbel distribution with a time‐varying location parameter revealed statistically significant declining trends in the residuals of −0.73 ± 0.02 mm yr−1, consistent with the observed poleward movement of storm surge‐producing mid‐latitude weather systems. For storm tides a smaller declining trend of −0.40 ± 0.01 mm yr−1 was found. These trends are approximately an order of magnitude smaller than the current positive rates of mean sea level rise, meaning that storm tide hazard will continue to increase in the future. This information is relevant for future adaptation planning.

Overcoming Barriers and Fostering Adoption: Evaluating the Institutional Mainstreaming of Nature-Based Solutions in the Emilia-Romagna Region’s Socio-Ecological System

International organizations like the EU and IUCN are advocating for nature-based solutions (NBSs) as green alternatives for climate change adaptation and mitigation, especially in disaster risk reduction and urban planning. The H2020 OPERANDUM project was designed to address the major hydro-meteorological risks (floods, droughts, landslides, storm surge, and coastal erosions) through the deployment and assessment of NBSs in different contexts and areas affected by specific hazards. Despite growing research and funding, NBSs are still in the early stages of mainstream adoption and face challenges in acceptance and dissemination. Although designed to benefit both social and ecological systems, they remain a niche area with low perceived effectiveness among technicians and decision-makers. Their uptake requires a paradigm shift that includes a change in cultural-cognitive institutions, a different and wider set of knowledge than traditional engineering (ecological, social), and an adaptive management approach, missing within the current governance system. Using a qualitative case study research method, this paper aims to identify barriers in mainstreaming NBSs for DRR (disaster risk reduction) in the Emilia-Romagna region—influenced not only by individual beliefs but also by variables tied to technical culture and local procedural norms—and emphasizing the importance of combining social and ecological indicators in socio-ecological system analysis.

Enhanced Carbon Accumulation in China's New Coastal Wetlands Over the 21st Century

AbstractWetlands formed by natural sediment deposition account for a large proportion of new coastal lands, and these new wetlands usually have active ecosystems and obvious ecological effects. However, previous studies largely overlooked this sediment‐caused wetland expansion, and the spatiotemporal variation in these wetlands and future response to sea‐level rise (SLR) have not been determined. Here, we employed satellite observations to quantify the seaward expansion of coastal lands in China over the past two decades. A total land expansion of 6,651 km2 was found, and wetlands and artificial surfaces dominated, accounting for 32% and 25%, respectively. Subsequently, we utilized an integrated model to estimate the response of these new wetlands to SLR in the 21st century, that is, we estimated the wetland gain from sediment deposition and loss due to SLR. The results indicate that under the current condition of sediment availability, the area of China's new coastal wetlands is projected to increase by 200%–261% compared to that in 2020 based on four SLR scenarios, despite the unavoidable impact of SLR. These increases are accompanied by the continuous enhancement of carbon accumulation. Wetland changes are influenced by factors such as sediment deposition, SLR and storm surges, as well as the continued effect of local natural and anthropogenic factors. These results show the importance of understanding the ecological effects of new wetlands and constructing specific protection measures for sustainable development.

Extreme Storm Surge Events and Associated Dynamics in the North Atlantic

AbstractStorm surges events are investigated using the ECHAR method, which identifies and quantifies the different dynamical structures of a typical storm surge event. In the North Atlantic, analysis of 65 tide gauges revealed that storm surge events display two major and two minor structures, each of them corresponding to specific ocean dynamics. The two major structures refer to a slow‐time Gaussian structure, lasting around 24 days, associated with the impact of the atmospheric pressure and a fast‐time Laplace structure, lasting around 1.4 days, mainly wind‐driven. The absence of the Gaussian structure along the North America coasts is explained by storms of smaller spatial extension, compared to Europe. Concerning the minor structures, a negative surge of around 6 cm just after the peak surge is observed over North America only. Such a sudden drop of the sea level is explained by the turning winds during the storm event, favored by the smaller spatial extension of storms. Finally, high frequency oscillations, with amplitude typically of 3 cm and up to 25 cm, are observed at some tide gauges. These oscillations refer to tide‐surge interactions and they are often maximum at a specific phase of the tide and/or enhanced because of resonant basins.

A study of ten tide gauge records from the Clyde in Western Scotland

ABSTRACT Sea level information, and its understanding, are essential for research in oceanography and coastal engineering. This paper describes sea level variability in the Clyde using data from 10 tide gauges. High coherence of sea level variability is found between the Firth of Clyde and estuary of the River Clyde, and between the Firth and estuary and the upstream part of the river. Consequently, if gaps exist in any of the records, missing information can be inferred from others. This applies to timescales of typically hours and longer, appropriate for storm surge or mean sea level change studies. No evidence exists for ‘see-saw’ oscillations of the river on subtidal timescales, as reported for the River Thames, but higher-frequency variability (typical period 45 minutes) is found with equal, or opposite, phase at different river locations. Such a standing wave behaviour would be one of the few reported examples of ‘river seiches’. Data from several agencies are used: two gauges of the UK National Network of the Environment Agency, five from the Scottish Environment Protection Agency, and three from Peel Ports. Only the former tend to be used in academic studies, but the present paper has demonstrated how useful complementary sources can be.

Contrasting organic carbon respiration pathways in coastal wetlands undergoing accelerated sea level changes

Carbon cycling in coastal wetland soil is controlled by a complex interplay between microbial processes and porewater chemistry that are often influenced by various external forcings like wind, river discharge, and sea-level changes, where most of the organic carbon is mineralized to its inorganic form by various aerobic and anaerobic respiration pathways. The export of this inorganic carbon (DIC) from coastal wetlands has long been recognized as a significant component of the global carbon cycle. The major objective of this work is to determine the relative contribution of various respiration pathways to seasonal DIC production in two contrasting marshes (brackish and salt). The DIC fluxes estimates for the brackish and salt marshes were found to range between 36.52 ± 5.81 and 33.98 ± 2.21 mmol m−2 d−1 in winter and 133.10 ± 102.60 and 82.37 ± 30.87 mmol m−2 d−1 during summer of 2020. For the brackish marsh, aerobic respiration and iron reduction were found to be the primary contributors to DIC production representing 17.91–35.21 % and 61.13–81.97 % of total measured organic matter (OM) respiration respectively. On the other hand, aerobic respiration and sulfate reduction were the primary contributors to DIC production in the salt marsh, accounting for 37.91–83.93 % and 15.87–62.04 % of the total measured OM respiration respectively. The Mississippi River Deltaic Plain experiences high relative sea level rise and expected to undergo rapid change in salinity regime in near future from additional changes in river discharge, proposed sediment diversion plans, and storm surge intensities. The current study represents the first attempt to concurrently estimate various respiration pathways in this region and more studies are needed to understand the trajectories of soil OM respiration pathways and its impact on coastal carbon cycling.

Hazard assessment of dynamic marine processes during two extreme weather systems near the Shandong Peninsula

Typhoons and extratropical cyclones both occurred frequently on the Shandong Peninsula and have induced severe dynamic marine disasters. In this study, the typhoons and extratropical cyclones that occurred from 1979 to 2018 were counted and classified according to their tracks. We simulated the storm surge and disastrous waves using a coupled ocean-wave model and assessed the hazard distribution under different types of typhoons and extratropical cyclones. Through comparison, it was found that the southern Yellow Sea steering type typhoons and Yangtze-Huai cyclones occurred most frequently and were most likely to cause disasters. Regarding the hazard posed by the storm surge, there was a clear demarcation between the northern and southern coasts of the peninsula, as well as between the eastern and western coasts. The western coast of the peninsula was more exposed to storm surges induced by typhoons, while the northern coast of the peninsula was more exposed to storm surges induced by extratropical cyclones. The hazard posed by waves exhibited a localized characteristic. The wave hazard was the greatest near the peninsula cape and the lowest surrounding the Laizhou Bay, which was contrary to the distribution of the storm surge hazard. The identification of key management areas for disasters provides basic data and a technical reference for coastal development planning and can play a positive role in disaster prevention.

Development of a novel storm surge inundation model framework for efficient prediction

Abstract. Storm surge is a natural process that causes flood disasters in coastal zones and results in massive casualties and property losses. Therefore, storm surge inundation is of major concern in formulating appropriate strategies for disaster prevention and mitigation. However, traditional storm surge hydrodynamic models have large limits with respect to computational efficiency and stability in practical applications. In this study, a novel storm surge inundation model was developed based on a wetting and drying algorithm established from a simplified shallow-water momentum equation. The wetting and drying algorithm was applied to a rectangular grid that iterates through a cellular automata algorithm to improve computational efficiency. The model, referred to as the Hydrodynamical Cellular Automata Flood Model (HCA-FM), was evaluated by comparing the simulations to regional field observations and to a widely used hydrodynamic numerical model. The comparisons demonstrated that HCA-FM can reproduce the observed inundation distributions and predict results that are consistent with the numerical simulation in terms of the inundation extent and submerged depth with much improved computational efficiency (predicting inundation within a few minutes) and high stability. The results reflect significant advancement of HCA-FM toward efficient predictions of storm surge inundation and applications at large spatial scales.

Aggravation Of the Climate Change Crisis in The Gulf Coast of The United States: A Review of Anthropogenic Factors

The Gulf Coast of the United States is increasingly at risk from the impacts of climate change, exacerbated by various human-induced factors. This review paper examined how human activities have worsened the effects of climate change in this region from 2005 to 2024, which is already vulnerable to hurricanes, sea-level rise, and coastal erosion. Influential factors include intensive industrial operations, such as oil and gas production, which release significant amounts of greenhouse gases and disrupt the natural landscape, leading to land subsidence and weakening coastal defenses. Urbanization and population growth have resulted in the loss of valuable wetlands and other natural buffers that mitigate flooding and storm surges. Alterations to river systems for flood control and navigation have reduced sediment deposition, affecting the preservation of coastal landforms. Agricultural practices in the region also play a role; fertilizer and pesticide runoff contaminate waterways and create hypoxic zones, impacting fisheries and marine habitats. The paper then emphasizes the need for impactful policy interventions and sustainable behaviors to address these human-induced pressures. In addition, the paper advocates for a comprehensive mitigation strategy that includes stricter emission controls, financial support for renewable energy sources, habitat restoration, and improved urban planning to enhance climate change resilience. After conducting a thorough review, we have discovered that the Gulf Coast region has experienced over fifteen deadly hurricanes over the past twenty years, poised to confront increasingly complex environmental and socioeconomic challenges if viable solutions are not implemented. These issues can potentially jeopardize the livelihoods of the region's inhabitants and the health of its diverse ecosystems.

Prediction of Pier Scour Depth under Extreme Typhoon Storm Tide

The Western Pacific region is highly vulnerable to typhoon storm surge disasters, with localized erosion posing a particularly prominent issue for coastal marine structures. The prevalence of extreme typhoon storm surges poses a significant threat to the safety of engineering projects in these areas. In this study, a parameterized wind field model with precise calculation of wind speed was employed to establish a numerical model for typhoon storm tides. Based on the Western Pacific typhoon data from 1949 to 2023, hydraulic simulations were conducted for Hangzhou Bay, Xiangshan Port, and Yueqing Bay, revealing maximum flow velocities of 4.5 m/s, 1.95 m/s, and 2.09 m/s, respectively. These velocities exceeded the maximum possible tidal flow by 0.47–1.17 m/s. Additionally, using Sun’s velocity formula, the initiation flow velocities were calculated to be 1.85 m/s, 1.81 m/s, and 2.06 m/s for the aforementioned locations. Through localized erosion tests conducted around typical bridge piers and the subsequent application of similarity criteria, the maximum depth of localized erosion in the study area was determined to range from 2.16 m to 16.1 m, which corresponds to 1.1–2.3 times the scour caused by the maximum tidal flow scenario. A comparison of the erosion test results with calculations based on several formulas demonstrated that the scour prediction formula proposed by Sun exhibited the highest accuracy. This study supplements the understanding of the impact of typhoon storm surges on bridge pier erosion and provides a scientific basis for the design of bridge foundations.

Influence of Grid Resolution and Assimilation Window Size on Simulating Storm Surge Levels

Grid resolution and assimilation window size play significant roles in storm surge models. In the Bohai Sea, Yellow Sea, and East China Sea, the influence of grid resolution and assimilation window size on simulating storm surge levels was investigated during Typhoon 7203. In order to employ a more realistic wind stress drag coefficient that varies with time and space, we corrected the storm surge model using the spatial distribution of the wind stress drag coefficient, which was inverted using the data assimilation method based on the linear expression Cd = (a + b × U10) × 10−3. Initially, two grid resolutions of 5′ × 5′ and 10′ × 10′ were applied to the numerical storm surge model and adjoint assimilation model. It was found that the influence of different grid resolutions on the numerical model is almost negligible. But in the adjoint assimilation model, the root mean square (RMS) errors between the simulated and observed storm surge levels under 5′ × 5′ and 10′ × 10′ grid resolutions were 11.6 cm and 15.6 cm, and the average PCC and WSS values for 10 tidal stations changed from 89% and 92% in E3 to 93% and 96% in E4, respectively. The results indicate that the finer grid resolution can yield a closer consistency between the simulation and observations. Subsequently, the effects of assimilation window sizes of 6 h, 3 h, 2 h, and 1 h on simulated storm surge levels were evaluated in an adjoint assimilation model with a 5′ × 5′ grid resolution. The results show that the average RMS errors were 11.6 cm, 10.6 cm, 9.6 cm, and 9.3 cm under four assimilation window sizes. In particular, the RMS errors for the assimilation window sizes of 1 h and 6 h at RuShan station were 3.9 cm and 10.2 cm, a reduction of 61.76%. The PCC and WSS values from RuShan station in E4 and E7 separately showed significant increases, from 85% to 98% and from 92% to 99%. These results demonstrate that when the assimilation window size is smaller, the simulated storm surge level is closer to the observation. Further, the results show that the simulated storm surge levels are closer to the observation when using the wind stress drag coefficient with a finer grid resolution and smaller temporal resolution.

The Influence of Modern Alluvial Areas on Sea Level Changes in The Neva Bay During Storm Surges in The Conditions of Operation of The Saint Petersburg Flood Prevention Faculty Complex

Using numerical experiments with a three-dimensional baroclinic hydrodynamic model of the Baltic Sea, which covers the refined grid area around the Neva Delta and Neva Bay, and takes into account the operations of the Saint Petersburg Flood Prevention Facility Complex (FPFC), we investigate the influence of modern alluvial areas on sea level changes in the Neva Bay and Neva Delta during storm surges, under different volumes of Neva River discharge. The hydrological conditions that developed in early December 2015, when Storm Desmond approached St. Petersburg, which caused three dangerous level rises in the east of the Gulf of Finland, one after the other. The alluvial deposits of territories do not have noticeable changes in the sea level of the Neva Bay with the gates of the FPFC closed during storm surges. It is shown that, depending on the runoff of the Neva, with the gates of the FPFC closed, additional sea level rises in the Neva Bay due to alluviation do not exceed 1–5 cm, while in the Neva Delta they reach 20.5 cm. The rise of the sea level to 161 cm at the Mining University, at which floods are recorded in St. Petersburg, occurs due to alluviation 1–2 hours earlier. At the maximum volume of Neva runoff for the autumn-winter period, 27 hours after the closure of the gates of the FPFC, a dangerous flood is recorded in the Neva Bay near the Mining University point, and 48 hours later — a particularly dangerous one.

Forecasting storm tides during strong typhoons using artificial intelligence and a physical model

Forecasting storm tides during strong typhoons using artificial intelligence and a physical model

Using Nighttime Light Data to Explore the Extent of Power Outages in the Florida Panhandle after 2018 Hurricane Michael

The destructive forces of tropical cyclones can have significant impacts on the land, contributing to degradation through various mechanisms such as erosion, debris, loss of vegetation, and widespread damage to infrastructure. Storm surge and flooding can wash away buildings and other structures, deposit debris and sediments, and contaminate freshwater resources, making them unsuitable for both human use and agriculture. High winds and flooding often damage electrical disubstations and transformers, leading to disruptions in electricity supply. Restoration can take days or even weeks, depending on the extent of the damage and the resources available. In the meantime, communities affected by power outages may experience difficulties accessing essential services and maintaining communication. In this study, we used a weighted maximum likelihood classification algorithm to reclassify NOAA’s National Geodetic Survey Emergency Response Imagery scenes into debris, sand, water, trees, and roofs to assess the extent of the damage around Mexico Beach, Florida, following the 2018 Hurricane Michael. NASA’s Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) was processed to estimate power outage duration and rate of restoration in the Florida Panhandle based on the 7-day moving averages. Percent loss of electrical service at a neighborhood level was estimated using the 2013–2017 American Community Survey block group data. Spatial lag models were employed to examine the association between restoration rates and socioeconomic factors. The analysis revealed notable differences in power-restoration rates between urbanized and rural areas and between disadvantaged and more affluent communities. The findings indicated that block groups with higher proportions of minorities, multi-family housing units, rural locations, and households receiving public assistance experienced slower restoration of power compared to urban and more affluent neighborhoods. These results underscore the importance of integrating socioeconomic factors into disaster preparedness and recovery-planning efforts, emphasizing the need for targeted interventions to mitigate disparities in recovery times following natural disasters.

Comprehensive economic losses assessment of storm surge disasters using open data: a case study of Zhoushan, China

ABSTRACT As climate change continues to worsen, coastal areas are increasingly vulnerable to more frequent and severe storm surges. This poses a significant risk to economic entities, particularly in areas that have undergone rapid development. However, quantitative assessment of economic losses from storm surge disasters in China has been challenging due to limited exposure and vulnerability data. This study proposes a framework for comprehensive economic losses assessment of storm surge disasters using open data, focusing on Zhoushan City as an example. The study quantifies economic loss ratios caused by storm surges by identifying essential urban land use/cover (EULUC) and considering the water depth of different EULUC types for quantitative vulnerability assessment. The study then calculates direct economic losses using the loss ratio maps and gridded gross domestic product data and quantifies indirect economic losses (IEL) using an input–output model to account for inter-industry correlation. Results show that under the scenario of a super typhoon intensity (915 hPa), the total economic loss can reach 131 million CNY, with IEL accounting for 60% of the total. The construction and industrial sectors experience higher IEL due to excessive dependence on upstream and downstream industries, with IEL accounting for approximately 70%.

Evaluating flood hazards in data-sparse coastal lowlands: highlighting the Ayeyarwady Delta (Myanmar)

Coastal lowlands and river deltas worldwide are increasingly exposed to coastal, pluvial and fluvial flooding as well as relative sea-level rise (RSLR). However, information about both single and multiple flood-type hazards, their potential impact and the characteristics of areas, population and assets at risk is often still limited as high-quality data either does not exist or is not accessible. This often constitutes a main barrier for generating sound assessments, especially for scientific and public communities in the so-called Global South. We provide a standardised, integrative approach for the first-order assessment of these single and multiple flood-type hazards and show how this can be conducted for data-sparse, hardly accessible and inaccessible coastal lowlands such as the Ayeyarwady Delta in Myanmar by using only open accessible and freely available datasets of satellite imagery, global precipitation estimates, satellite-based river discharge measurements, elevation, land use, and population data. More than 70% of the delta, mainly used for agriculture, and about 40% of its present population are prone to flooding due to either monsoon precipitation and runoff, storm surge, and RSLR, or their combination, jeopardising food security and economic development in the region. The approach allows for the integration and combination of various datasets, combined in a highly flexible workflow that performs at low computational capacities, supporting the evaluation of flood-prone areas on regional and local scale for data-sparse coastal lowlands worldwide. It thereby allows to attribute different types of flood hazards, complements concepts of vulnerability and risk, and supports risk-informed decision making and development of effective multi-flooding adaptation strategies.