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Recent studies along the southern Baltic Sea coast have revealed sedimentary records of catastrophic storm surges that significantly exceed the magnitude of storms documented by instrumental measurements. The present study aimed to apply heavy mineral analysis for storm surge deposits along coasts of Gulf of Gdansk (southern Baltic), as well as for contemporary marine, beach, dune and coastal plain sediments, to test the applicability of the method and to provide new insights into the depositional processes and sediment sources of the storm deposits. The transparent, 0.125–0.25 mm heavy mineral fraction (>2.85 g/cm3) in 118 sediment samples was investigated, and the results were subjected to multivariate statistical analyses (cluster, PCA, LDA). Storm deposits showed higher concentrations of heavy minerals comprising enrichment in garnet, zircon, and rutile. General heavy mineral assemblage depended on regional provenance and primary sediment sources. However, flooding regime (overwash or inundation) played a key role in selective hydrodynamic sorting of grains and mineralogical composition of storm deposits. Interpretation of deposits formed in inundation regime was more certain than deposits formed in overwash regime. In the latter case, deposits showed more similarities to adjacent mineral provinces. Statistical analyses proofed that heavy minerals together with other sedimentological descriptors may be a promising proxy for recognition of deposits related to defined sedimentary environment or identification of particular sedimentological process, e.g. event layers resulted from storm surges.

International audience; The current study tries a new approach to simulating interactions between waves and seagrass through Smoothed Particle Hydrodynamics (SPH). In this model, the plants are defined as a solid that respects Hooke's law, and are assumed to have direct interaction with the fluid. Given the characteristics of the SPH method, especially in terms of computational time, the dimensions of the simulations were limited. The first goal of the current study was to optimize the approach to avoid reaching certain limits such as the rupture of the simulated plant. Plant movements under waves and/or currents have been studied by several authors in various in-situ, physical, and numerical experiments concerning various vegetation species, thus proving that plant movements can be successfully reproduced by SPH 2D/3D. Manning's roughness coefficient, n, was calculated to confirm that the results were in accordance with what had been measured in flume studies. Even though there is still room for improvement, it is shown that this method can be used to estimate Manning's coefficient for coastal vegetation (seagrass and saltmarsh vegetation) and to greatly improve the modeling and forecasting of coastal erosion and storm surge risks by including the effects of vegetation in integrated models.

The intensification of extreme events, storm surges and coastal flooding in a climate change scenario increasingly influences human processes, especially in coastal areas where sea-based activities are concentrated. Predicting sea level near the coasts, with a high accuracy and in a reasonable amount of time, becomes a strategic task. Despite the developments of complex numerical codes for high-resolution ocean modeling, the task of making forecasts in areas at the intersection between land and sea remains challenging. In this respect, the use of machine learning techniques can represent an interesting alternative to be investigated and evaluated by numerical modelers. This article presents the application of the Long-Short Term Memory (LSTM) neural network to the problem of short-term sea level forecasting in the Southern Adriatic Northern Ionian (SANI) domain in the Mediterranean sea. The proposed multi-model architecture based on LSTM networks has been trained to predict mean sea levels three days ahead, for different coastal locations. Predictions were compared with the observation data collected through the tide-gauge devices as well as with the forecasts produced by the Southern Adriatic Northern Ionian Forecasting System (SANIFS) developed at the Euro-Mediterranean Center on Climate Change (CMCC), which provides short-term daily updated forecasts in the Mediterranean basin. Experimental results demonstrate that the multi-model architecture is able to bridge information far in time and to produce predictions with a much higher accuracy than SANIFS forecasts.

The shoreline of Gujarat in western coast of India has remained exposed to tsunamis and storm surges in past from distant to regional sources and processes. The catalogue of past tsunami and storm events whose geological signatures have been archived in the coastal records, often hints at frequency, magnitude and recurrence. In present work, we compile all possible signatures of palaeo-extreme wave events and attempt to assess the vulnerability to this rapidly developing shoreline. We report a total of six major extreme wave events, out of which atleast two have been identified to be associated with palaeotsunami deposits, whereas three are storm surge deposits and one is designated as a washover deposit. Archeological findings like the presence of thick walls around Dholavira (an ancient Harappan coastal trading centre) is also supportive of Harappan learning from the wrath of marine waves they would have faced. This study reports the wider time gap between the events, attributed to lack of preservation, difficulty in recognition, higher reworking or lack of detailed investigation ~ making the task of estimating recurrence a mammoth effort. The study shows that the shoreline of Gujarat has remained vulnerable to extreme wave events atleast during the last 6000 years, and have affected ancient settlers as well as modern anthropological activities.

The official website of the Philippine Atmospheric Geophysical and Astronomical Services Administration (PAGASA) said more tropical cyclones (TCs) enter the Philippine Area of Responsibility (PAR) than anywhere else in the world. With the average of 20 TCs per year, about eight (8) or nine (9) of them are crossing the Philippines. The peak of the typhoon season is July through October, when nearly 70% of all typhoons develop (http://bagong.pagasa.dost.gov.ph/climate/tropical-cyclone-information). Based on the report of the Asian Disaster Reduction Center (ADRC), five of the typhoons that visit the country are destructive and being situated in the “Pacific Ring of Fire” makes the country vulnerable to frequent earthquakes and volcanic eruptions. Its geographical location and physical environment also contribute to its high susceptibility to tsunami, sea-level rise, storm surges, landslides, flash/flood/flooding, and drought (https://www.adrc.asia/nationinformation.php?NationCode = 608&Lang = en). For the past years, some typhoons that visited the country brought serious damages and kill many Filipinos by floods and landslides. The researcher comes up with the idea of assessing the aftermath of 2020 typhoons that visited the country. The data used by the researcher were collected from different sources, namely NDRRMC (National Disaster Risk Reduction and Management Council), PAGASA, social media and other websites. The result of the study reveals that the most destructive typhoon in 2020 that caused huge damage on the infrastructure and agriculture is Ulysses followed by Rolly, Quinta, Ambo, Vicky, Pepito, Ofel, and Marce. Most of the affected areas are those nearer to water bodies, surrounded by mountains with few trees to absorb a huge amount of water and situated in the low-lying areas.

By the 2050s, more than 120 million people are predicted to settle in the Pearl River Delta (PRD), which covers large coastal cities such as Guangzhou, Shenzhen and Hong Kong. Cities in the PRD are vitally important to China in relation to their socio-economic contributions. From recent evidence, this strongly urbanized area is vulnerable to, and currently facing bigger incidences of, coastal and urban flooding. Flood risk is growing in low-lying coastal areas due to rapid urbanization and increasing flood hazards exacerbated by climate change. Frequent intensive rainstorms, sea-level rise, typhoons and surges threaten large populations and their economic assets, causing severe socio-economic and ecological impacts in the PRD cities. Current flood risk management (FRM) in the delta is still predominately focused on using traditional techno-fixes and infrastructure paradigms, lacking sufficient strategic planning and flood protection to develop adequate flood resilience. Recent urban floods, enhanced by storm surges and intensive rainstorms, have affected multiple PRD cities and drawn attention to flood risk as a major challenge in the PRD’s coastal cities. This review encourages development of long-term FRM practices with provincial and municipal authorities working together more closely to develop better-integrated regional FRM strategies for the PRD.

Alexandria Eastern Harbor (AEH) is constantly enduring the destructive problem of storm surges. Therefore, the investigation of the behavior of surges in the Harbor is crucial, and determining to which extent this is affected by the meteorological conditions is essential. We used hourly data of sea-level, from 10.06.2018 to 15.06.2020, to calculate AEH surge heights. Simultaneous records of winds and sea-level pressure (SLP) were used to examine their impact on the calculated surges. Also, an empirical equation was derived to estimate the surge height in AEH by knowing the SLP and winds. Results revealed a 99% contribution of surges to the recorded sea-level. Surge heights exhibited a seasonal pattern with lower values in spring and higher ones in summer. While the positive surges dominated the Harbor all the year-round, the negative surges appeared only in 8 months: January-June, in addition to October and November. The total and the positive surges were directly proportional to all wind components but the negative parallel ones. Contrariwise, the negative surge associated the decrease of all wind components except the negative parallel and the negative normal components. There was an inverse relationship between the total, positive and negative surge heights and the SLP.

This study presents a novel approach to determine the distribution of compound flood events composed of storm surge and static water levels along the Great Lakes shoreline. A mixture distribution of the bulk (Student-t) and tail (GPD-negative binomial) components of storm surge is estimated in a hierarchical Bayesian modeling framework. Parameters are modeled across the entire shoreline using Gaussian processes and hourly gauged data, with priors for spatial autocorrelation informed by numerical output from a lake hydrodynamic model. The distribution of total water levels is obtained through Monte Carlo sampling that combines the estimated distribution of surge with stochastic traces of static lake levels that account for water level management, seasonality, and plausible variability in water supplies. The approach can therefore support coastal flood risk assessments in cases when the distribution of static water levels changes are due to altered water level management or climate change. The model is applied in a case study on Lake Ontario. Results suggest that spatial variability in parameter estimates varies significantly by month and mixture distribution component. Evaluations of performance indicate the model is able to capture adequately storm surge behavior at gauges across the lakeshore, even under cross-validation. A frequency analysis of total water levels at two ungauged sites is presented, with specific attention given to the implications of model assumptions on uncertainty in design events. The paper concludes with a discussion of model limitations and avenues for future work.

This paper investigates the contemporaneous and long-term effects of tropical cyclones and the related policies on economic growth and associated structural changes. We consider three distinguishing features of tropical cyclones, including wind speed, precipitation, and storm surge height, as well as one policy-related feature of tropical cyclones in Hong Kong—the issuing of the No. 8 signal. Using data from Hong Kong for the period 1980–2018, we show that although tropical cyclone landfalls on the coast of Hong Kong have much higher average wind speeds, wind speed does not have a significant influence on either overall GDP or sectoral GDP. Economic losses from tropical cyclones are driven mainly by the issuing of the No. 8 signal, a climate policy in Hong Kong that suspends daily activities in dangerous tropical cyclone weather. With an average shutdown of 1.87 days due to No. 8 signals, the economic loss is about 0.9 billion U.S. dollars. However, in the long run, the No. 8 signal policy has delayed positive impacts on total GDP and some sectoral growth. Our analysis suggests that at least five years of recovery is necessary for damage attributed to severe tropical cyclones.

Hurricanes induce multiple hazards including high wind speeds, large waves, and storm surge. The characteristics of these hazards have an important effect on the design of offshore structures and determine the suitability of simplifying assumptions for modeling, such as whether the maxima can be reasonably modeled as occurring simultaneously during the hurricane and whether the N-year values of the hazards can be modeled separately and combined. Such assumptions are common in practice. Assessing the implications of these assumptions to better inform hazard modeling along the U.S. Atlantic coast is the central objective of this paper. To this end, the characteristics of wind speeds, waves, and storm surge during hurricanes are evaluated for ten areas where development of offshore wind is proposed. The assumptions are evaluated for a model of an offshore wind turbine using time histories of hazards during intense hurricanes and using so-called environmental contours constructed through a novel implementation of the Inverse First Order Reliability Method. The results of this study show that these assumptions are reasonably accurate, especially for wind and wave in shallow waters and for wind and surge in deep waters. Hazard ratios are proposed as a suitable representation of the characteristics of hazard maxima.

Globally, communities, ecosystems, and assets situated within the coastal zone will likely experience increased risk in the future owing to chronic and acute pressures associated with climate change and associated sea level rise. Gravel barrier islands represent an intermediate pathway between seaward hazards and vulnerable landward receptors and possess inherent morpho-sedimentary characteristics which confer allow coastal risk reduction functions. If gravel barriers are to be usefully and reliably integrated into broader coastal risk management strategies, there is a need to understand the extent to which these landforms are likely to remain resilient under future environmental conditions. Using the Blakeney Point Barrier System, southern North Sea, this study investigates the resilience of gravel barrier landforms to storm surge conditions under future sea level rise scenarios. Resilience is assessed through reference to barrier resistance, susceptibility to state change, persistence, and continued functional performance. Numerical modelling reveals that variable pre-surge barrier morphologies result in a spectrum of episodic resilience trajectories along the barrier frontage. This study also considers the role of humans in altering landscape resilience, demonstrating that previously managed barrier sections (through reprofiling to steepen and heighten the barrier) are more vulnerable to severe morphological change, and associated landward overtopping volume, compared to unmanaged barrier sections. This said, under moderate to high sea level rise, even unmanaged barrier sections failed to demonstrate resilience to storm surge forcing. Such insights help temper our expectations regarding the coastal erosion and flood risk reduction functions of gravel barriers in the face of global environmental change.

Recent projections suggest worst-case scenarios of more than six ft (1.8 m) of global mean sea-level rise by end of century, progressively making coastal flood events more frequent and more severe. The impact on transportation systems along coastal regions is likely to be substantial. An analysis of impacts for Atlantic and Cape May counties in southern New Jersey is conducted. The impact on accessibility to employment is analyzed using a dataset of sea-level increases merged with road network (TIGER) data and Census data on population and employment. Using measures of accessibility, it is shown how access will be reduced at the block-group level. An additional analysis of low and high income quartiles suggest that lower-income block groups will have greater reductions in accessibility. The implication is that increasing sea levels will have large impacts on people and the economy, and large populations will have access to employment disrupted well before their own properties or places of employment may begin to flood (assuming no adaptation).

Shoreline retreat along extended semi-arid areas of North African coasts are indicative of the imbalance of coastal sedimentary processes due to modern abrupt changes in precipitation patterns and urban growth. Monitoring of the diachronic shoreline position and land-use from 1952 to 2018 in the coast of the Hammamet Bay in central-east Tunisia, using both aerial and orbital photogrammetric scenes and the Digital Shoreline Analysis System from 1887 to 2018, suggests shoreline retreat rates ranging from −1.3 to −5.6 m/yr. Such rates are abnormal when compared to the average of −0.07 m/yr suggested by global-scale assessment modeling for sandy beach evolution. These abnormal erosions extend over 65 km of sandy beaches, resulting from a severe deficit of sediment transport caused primarily by rapid coastal urban growth that obstructs sediment flow to the shoreline. We suggest that the high retreat rates observed in the low-population period of 1884–1931 originated mainly from storm surges and tsunamis, or potentially subsidence in the coastal substratum. Moreover, our analysis of the salinity of shallow coastal aquifers and land coverage suggests that shoreline retreat coupled with rapid urban growth accelerated seawater intrusion ~5 km inland, causing soil desiccation, the development of salt lakes, and reduction of vegetation coverage by ~18%. These abrupt environmental changes have a severe, adverse impact on crop production and food security in these densely populated and economically important areas across significant parts of the North African coasts, sharing similar key environmental parameters with our study site. We conclude that anthropogenic drivers are the major source of shoreline retreat rather than natural ones.

The co-evolution of wetland loss and flood risk in the Mississippi River Delta is tested by contrasting the response of storm surge in coastal basins with varying historical riverine sediment inputs. A previously developed method to construct hydrodynamic storm surge models is employed to quantify historical changes in coastal storm surge. Simplified historical landscapes facilitate comparability while storm surge model meshes developed from historical data are incomparable due to the only recent (post-2000) extensive use of lidar for topographic mapping. Storm surge model meshes circa 1930, 1970 and 2010 are constructed via application of land to water (L:W) isopleths, lines that indicate areas of constant land to water ratio across coastal Louisiana. The ADvanced CIRCulation (ADCIRC) code, coupled with the Simulating WAves Nearshore (SWAN) wave model, is used to compute water surface elevations, time of inundation, depth-averaged currents and wave statistics from a suite of 14 hurricane wind and pressure fields for each mesh year. Maximum water surface elevation and inundation time differences correspond with coastal basins featuring historically negligible riverine sediment inputs and wetland loss as well as a coastal basin with historically substantial riverine inputs and wetland gain. The major finding of this analysis is maximum water surface elevations differences from 1970 to 2010 are 0.247 m and 0.282 m within sediment-starved Terrebonne and Barataria coastal basins, respectively. This difference is only 0.096 m across the adjacent sediment-abundant Atchafalaya-Vermilion coastal basin. Hurricane Rita inundation time results from 1970 to 2010 demonstrate an increase of approximately one day across Terrebonne and Barataria while little change occurs across Atchafalaya-Vermilion. The connection between storm surge characteristics and changes in riverine sediment inputs is also demonstrated via a sensitivity analysis which identifies changes in sediment inputs as the greatest contributor to changes in storm surge when compared with historical global mean sea level (GMSL) rise and the excavation of major navigation waterways. Results imply the magnitude of the challenge of preparing this area for future subsidence and GMSL rise.

Total water levels (TWLs) at the coast are driven by a combination of deterministic (e.g., tides) and stochastic (e.g., waves, storm surge, and sea level anomalies) processes. The contribution of each process to TWLs varies depending on regional differences in climate and framework geology, as well as local-scale variations in beach morphology, coastal orientation, and shelf bathymetry. Large-scale changes to the climate altering the frequency, direction, and intensity of storms, may therefore propagate to the nearshore differently, amplifying or suppressing local coastal hazards and changing the exposure of coastal communities to extreme TWLs. This study investigates the hydrodynamic and geomorphologic factors controlling local TWLs along high-energy United States coastlines where wave-influences dominate TWLs. Three study sites in the states of Washington, Oregon, and California are chosen to explore how regional and local differences in beach topography and wave transformation over shelf bathymetry drives variations in the magnitude and impacts of extreme TWLs. Results indicate that TWLs are most influenced by wave transformation processes in locations with steep beach slopes and complex offshore bathymetry, while beach topography influences the severity of coastal impacts. Once the relative morphologic controls on TWLs are better understood, hypothetical future climate scenarios are explored to assess how changes to the average deepwater wave climate (height, period, and direction) may alter local TWLs when compared to estimates of likely sea level rise and future coastal management strategies. Changes to the wave climate are found to be as detrimental to the coastline as sea level rise in some locations, where small variations of the TWL drive large, nonlinear changes in hours of impact to the backshore beach. Overall, this study develops an approach for quantifying the range of hydrodynamic and morphologic controls on the magnitude of TWLs which will ultimately better prepare coastal communities for uncertain changes to the global climate.

Recent hurricane events have exposed the susceptibility of petrochemical facilities to severe transportation network disruptions due to flooding or storm surge. Network disruptions can result in cascading impacts or amplify the consequences of damage to petrochemical infrastructure due to delayed emergency response and limited access to the site. This study presents a scenario-based framework to assess the accessibility of petrochemical facilities by emergency responders and workers during storm surge events. First, the framework couples storm surge modeling with aboveground storage tank fragility models to determine the locations where natural hazard-triggered technological (NaTech) events could occur. Then, storm surge modeling is coupled with bridge fragility models and geographic system analysis to evaluate the potential for network disruptions such as bridge failures and road inundations. Finally, probabilistic network analyses are performed to evaluate the time-evolving accessibility of NaTech sites to emergency responders and facility workers. As a proof of concept, the framework is applied to a case study area. Results for the case study area demonstrate that the proposed framework is a powerful tool to quantify the accessibility of potential NaTech events, facilitate mitigation and emergency activities, and improve the management of critical resources and personnel during and after a storm.

Mangrove forests are productive ecosystems but are vulnerable to tropical cyclones. In this study, we quantified the damage of mangroves from Hurricane Irma at a large-scale using Landsat data, and modeled the risk of mangroves to hurricanes using three internal/physical metrics (a vegetation index, canopy height, and distance to open ocean) and two external/hurricane-related metrics (hurricane track and storm surge inundation). Four machine learning techniques including Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and k-Nearest Neighbor (k-NN) were examined and compared with the Multiple Linear Regression (MLR) method to identify the best risk model for damage projection from future hurricanes. The models were calibrated and validated using data before and after Hurricane Irma. Machine learning algorithms had a better performance than the linear model, and RF achieved the best result with a correlation coefficient (r) of 0.84 in predicting mangrove damages. The model also produced an encouraging result to hindcast mangrove damages from Hurricane Wilma. We applied object-based modeling and mapping techniques and produced mangrove damage maps from Irma and a worst-case scenario hurricane with an intensity of Category 5 and a track along the mangrove distribution. A total of 332 km2 of mangroves were severely damaged from Irma, and 635 km2 would be devastated from the modeled scenario. The techniques developed here can be used for other mangrove forests exposed to tropical cyclones.

The Bahamas or Lucayan Archipelago located in the western North Atlantic Ocean is highly susceptible to impact of hurricanes considering its location along the major pathways of Atlantic hurricanes and increased storminess in the Atlantic basin. The hydrodynamics of the narrow and steep carbonate continental shelf of Bahamas archipelago provides a stark contrast to the east coast of the United States by means of distinct interaction of shelves with hurricane induced waves, storm tide and currents. The present study implements a coupled ADCIRC-SWAN model to investigate the surge and wave dynamics along the coasts of Bahamas archipelago during Hurricane Joaquin, using multiple reanalyzed wind products. The analysis is focused on the hydrodynamic response of the archipelago considering its varying coastal bathymetry, slope and arching coastlines. Model computed a maximum significant wave height of 15 m, storm surge 1.5 m and coastal currents of 4 m/s during Hurricane Joaquin. Moreover, validation study also shows very good agreement with the buoy observations from the region. Spatio-temporal variability of storm tide and waves along with nonlinear impacts of wave setup and setdown highlights the dominance of waves with moderate influence of storm tides along the coastal zone of the island chain. The study also evaluated interaction of coastal currents with the arching coastlines of the Bahamas. In addition, wave parameters attributed to the sinking of the cargo ship El-Faro during the Hurricane Joaquin have been examined. Significant wave heights exceeding 12.5 m with wave period of 12.5 s and the reversing wave direction during Hurricane Joaquin might have resulted in the capsize of the cargo ship.

Storm surge is a critical component in the evolution of barrier island systems, eroding the shoreface and depositing sediment landward as overwash deposits; this “rollover” process enables barrier islands to migrate landward during periods of rising sea level. However, cyclonic storms may also generate seaward-directed flow and sediment transport, which is not typically accounted for in barrier island modeling. A strong outflow occurred at Port Aransas, Texas during Hurricane Harvey in 2017, as evidenced from field observations, satellite photos, and tide data; modeling indicates that outflow was forced by offshore winds to the left of landfall. To investigate the impact of this event on the barrier system, we collected post-storm multibeam bathymetry data and sediment samples within Aransas Pass and Lydia Ann Channel, important conduits linking the bays to the Gulf of Mexico, and where such data were previously collected in 2009 and 2012. The 2009–2012 comparison provides a baseline against which to ascertain the storm impact contained in the 2012–2017 comparison. Both land- and marine-based evidence indicate that significant erosion accompanied the outflow event, focused at the edges of the Corpus Christi ship channel and Lydia Ann Channel. Large quantities of sand, up to 6.5 m thick, also accumulate in deeps of Aransas Pass and Lydia Ann Channel, presumably as the outflow event waned in strength. We infer that the outflow event transported a large amount of barrier system sands offshore, but do not have sufficient constraints at this time to quantify it.

The amount and extent of coastal flooding caused by hurricanes can be sensitive to the timing or speed of the storm. For storms moving parallel to the coast, the hazards can be stretched over a larger area. Hurricane Matthew was a powerful storm that impacted the southeastern U.S. during October 2016, moving mostly parallel to the coastline from Florida through North Carolina. In this study, three sources for atmospheric forcing are considered for a simulation of Matthew's water levels, which are validated against extensive observations, and then the storm's effects are explored on this long coastline. It is hypothesized that the spatial variability of Matthew's effects on total water levels is partly due to the surge interacting nonlinearly with tides. By changing the time of occurrence of the storm, differences in storm surge are observed in different regions due to the storm coinciding with other periods in the tidal cycles. These differences are found to be as large as 1 m and comparable to the tidal amplitude. A change in forward speed of the storm also should alter its associated flooding due to differences in the duration over which the storm impacts the coastal waters. With respect to the forward speed, the present study contributes to established results by considering the scenario of a shore-parallel hurricane. A faster storm caused an increase in peak water levels along the coast but a decrease in the overall volume of inundation. On the other hand, a slower storm pushed more water into the estuaries and bays and flooded a larger section of the coast. Implications for short-term forecasting and long-term design studies for storms moving parallel to long coastlines are discussed herein.

Frequent storm surges often cause catastrophic impacts on human lives and the global economy; however, these phenomena are not well understood. In this study, a regional storm reconstruction is performed based on a grain-size analysis and stratigraphic modelling of the accelerator mass spectrometry radiocarbon dates of benthic foraminifera from two neighbouring lagoon cores from Lingyang Reef in the Xisha Islands located in the northern South China Sea of the western Pacific. The dating results from the lagoon cores reveal a ~3500-year depositional history. Three different depositional units are recognized based on a time series of distinct grain-size variations that correspond to the following three stages of storm activity: intense and frequent storms from ~3500 to 3100 cal yr BP and ~1800 cal yr BP to present and weak and infrequent storms from ~3100 to 1800 cal yr BP. A high sedimentation rate remarked by reverse and chaos age is observed from ~2800 to 2600 cal yr BP in both cores, and it was likely associated with a tsunami event. In addition, grain-size variability may be associated with changes over time caused by the synchronous Asian monsoon and may also be correlated with climate records retrieved from the ice cores from Greenland; thus, this variability could indicate pervasive global climatic teleconnections. The overall temporal patterns of the isolated coral branches and shells from the sediment sequences are well correlated with the high sea surface temperatures in the western tropical Pacific. We suggest that increasing sea surface temperatures in the future may lead to more intense storm activity in the western Pacific warm pool as the planet warms.

Anthropogenic climate change is considered as one of the greatest environmental, social and economic threats to the future world. Low lying deltas all over the world are increasingly subjected to multidimensional risk of sea level rise, cyclone, surges and salinisation. The life and livelihood of the communities of such deltas are endangered due to climate change acting as risk multiplier. The Mahanadi delta in the state of Odisha, India is one of the such populous deltas with estimated 8 million population in 2011 with a density of 613 persons/km2. Over the past decades, it experienced major climatic threats in the form of cyclone, surge inundation and flooding with variable intensities and impacts along and across the coast. The present research assessed the risk of climatic extreme events and their variability in the delta, with an intention of mitigation or adaptation to possible impacts in specific region. Synthetic Aperture Radar (SAR) data and daily rainfall data were used to extract flood inundation. Tropical Cyclone Risk Model (TCRM) along with surge decay function was used to estimate cyclonic wind speed and surge inundation and risk indices were computed using fuzzy logic based approach. The result shows that in the coastal districts, risk of severe cyclones rank above the heavy floods. Agriculture, the main livelihood of these districts (71%) is impacted adversely making the delta community vulnerable to such extreme events. Kendrapara followed by Bhadrak and Jagasinghpur districts appear to be most risk prone segment in the delta making the northern part comparatively more risk prone where focused mitigation and adaptation actions are needed.

Unlike inundation from a tsunami, inundation originating from a tropical cyclone is rather complex since it is usually accompanied by torrential rain. Runoff in the vicinity of an estuarine outlet may thus incur additional inundation damage. In this study, a modeling system is proposed that considers the river discharge effect in addition to tides and surges to enhance the modeling accuracy of storm-induced inundation in coastal areas. The hydrodynamic model (Delft3D) and hydrological model (HEC-HMS) were coupled to account for all the flooding drivers, such as tides, storm surges, river discharges, and their interactions. In the coupled model, Delft3D was responsible for tidal and storm-induced surging motions, while HEC-HMS was used to calculate the river discharge at the downstream outlet of basins. Typhoon Maemi, which caused severe inundation damage to the Korean peninsula in 2003, was simulated by the model with a focus on the localized inundation process. The increase in inundation risk caused by river discharge was of particular interest and was assessed through a comparison of two different cases: Case ST (Storm-Tide) and Case STR (Storm-Tide-Riverine flow). The results clearly show that the case considering the rainfall-runoff process in the storm surge simulation outperforms that in which storm surge is not considered. A further detailed investigation of the inundation depth and coverage of both cases revealed several findings. The proposed model is expected to be of great aid in producing the flood hazard mapping with enhanced accuracy.

Human presence, coastal erosion, and tourism activities are increasing the attention to coastal flooding risk. To perform risk assessments, long time series of observed or hindcast wave parameters and tide levels are then necessary. In some cases, only a few years of observation are available, so that observed extreme data are not always representative and reliable. A hindcast system aimed to reconstruct long time series of total tide levels may be of great help to perform robust extreme events analysis and then to protect human life, activities as well as to counteract coastal erosion by means of risk assessments. This work aims to propose a simplified method to hindcast storm surge levels time series in semi-enclosed basins with low computational costs. The method is an extension of a previous work of some of the authors and consists of a mixed approach in which the estimation of storm surge obtained by using the theory of linear dynamic system is corrected by using a statistical method. Both steps are characterized by low computational costs. Nevertheless, the results may be considered reliable enough also in view of the simplicity of the approach. The proposed method has been applied to the Manfredonia case study, a small village located in the Southern Adriatic Italian coast and often prone to coastal flooding events. The comparison of extreme events estimated on the basis of hindcast levels time series is satisfactorily similar to those estimated on the basis of observed tide series.

The interaction of tides and storm surges can significantly modify the final levels reached by storm surges that threaten coastal areas. In this paper, numerical experimental results are presented that examine tidal influence on storm surges. This is done using a two-dimensional ADCIRC (Advanced Circulation Model) applied to the effects of Typhoon Rammasun (July 2014) on Tieshan Bay, China. The results show that, without considering tidal forcing, there is an underestimation of positive surge levels, while negative surge levels are overestimated. It is also shown that the prevailing wind direction and shape of Tieshan Bay affect the distribution of storm surges. The nonlinear residual levels caused by tide-surge interaction can reach 0.94 m at the top of the bay when peak negative storm surge levels occur, with nonlinear levels increasing from the outside to the head of the bay. Through the derivation of mathematical terms, a direct relationship between the nonlinear residual levels and the dynamic influencing factors is established. Further, it is demonstrated that the combination of wind stress and bottom friction terms and advection terms play leading roles in the derivations, whereas terms related to local acceleration and Coriolis force contribute little to the nonlinear levels. The combination of wind stress and bottom friction terms and advection terms show complex spatial and temporal variation.

In this work, we develop a high-resolution oceanographic database, suitable for marine renewable energy (MRE) applications. We apply downscaling techniques, using ROMS numerical model, to generate a 29-year (1985–2013), high-resolution (325 m), hourly sea level and currents (10 vertical levels) hindcast that reproduces storm surge and astronomical tide dynamics at a MRE test site (BiMEP) in the Bay of Biscay. The results are fully validated using instrumental data. We also analyze the result sensitivity to the open boundary conditions. We find that using boundary conditions from a baroclinic reanalysis, reproducing a wide range of physical processes, does not give more accurate results than a barotropic reanalysis, reproducing storm surge and astronomical tides, the main forcings at the study area. This analysis also leads us to address the importance of the temporal extent in the databases used for MRE applications. Finally, the generated hindcast is used to analyze normal and extreme currents and sea level regimes in BiMEP, following the internationally accepted standards for the design of MRE converters. The generated database offers MRE converter developers an alternative to the often-proposed empirical formulae for the definition of the design cases to consider in the loads and safety analysis of their devices.

Coastal bridges are susceptible to severe damage due to wave-induced forces during extreme events such as coastal flooding, hurricanes, storm surges and tsunamis. As a direct impact of climate change, the frequency and intensity of these events are also expected to increase in the future. This paper presents a comprehensive review of a four-phase resilience assessment of coastal bridge structures, namely, (i) characterization of external wave-induced forces, (ii) structural response of bridges, (iii) vulnerability assessment of damaged components, and (iv) post-disaster recovery. The four comprehensive modules are adopted from the classic framework of PEER PBEE and constitute the integrated knowledge needed for the prediction of the resilience of infrastructure under extreme wave-induced loads. The study also presents new expressions for resilience restoration that simultaneously account for the time, resources (cost) and environmental impacts of different recovery options with variable importance levels to different stakeholders.

Healthy salt marshes are known to provide protection from extreme events, such as storm surge. However, such systems are vulnerable to sea level rise, anthropological modifications that alter circulation, and decreasing sediment supply. Here, circulation in an anthropologically modified salt marsh, the Milford Neck Conservation Area, near Milford, DE, USA, is examined during typical and extreme event conditions. Two month-long deployments were used to assess the tidal circulation within the system and develop, calibrate, and validate to within 10% a numerical hydrodynamic model (CMS, Coastal Modeling System). Areas of tidal choking (rapid loss of tidal energy) are identified as contributing to poor circulation within large upland areas. Modeling results for existing tidal conditions and a 20-year storm surge event show that by removing constrictions and improving circulation, large ponded areas can become intertidal, which would allow for marsh re-colonization and reduction in open water areas.

The Typhoon Kai-tak that occurred in August 2012 produced strong winds, heavy rain, extreme wave, and storm surge, which also had a significant impact on the coastal areas of China and Vietnam. Studying the formation and tracking the movement mechanism of this typhoon will help reduce future coastal disasters, as well as have important scientific significance. The impact of a typhoon creates strong mass transport and energy exchange between the atmosphere and the ocean which produces a strong interaction between the wind field and the flow field. A coupled atmosphere-ocean model in the South China Sea was established based on the mesoscale atmospheric model WRF and the regional ocean model ROMS. Typhoon Kai-tak was simulated using this model. The simulation results show that the coupled WRF-ROMS model indicate high simulation accuracy with respect of storm surge in the South China Sea under the influence of Typhoon Kai-tak. The simulation results also reveal the temporal and spatial distribution of Typhoon Kai-tak's field, storm surge, and wind-induced flow fields. The spatial asymmetry and time lag in the spatial–temporal distribution of sea surface temperature during Typhoon Kai-tak have been discussed. The heat exchange at the air-sea interface was very strong under the influence of Typhoon Kai-tak, and the latent heat generated by water vapor evaporation plays a dominant role in the heat exchange at the air-sea interface, which shows that the heat carried by the vaporization of the sea surface is one of the important factors for the decrease of sea temperature under the influence of a typhoon.

This study assesses the coastal flooding risk of Kenitra coast (Morrocan Atlantic) consisting of rectilinear beaches backed by dunes and crossed by the mouth of Sebou river. A Differential Global Positioning System (DGPS) topographic survey of the study area was carried out in order to analyse shore and backshore morphology. Total water levels (TWL) are empirically calculated and statistically analysed, taking into account the tide data, wave runup and projection IPCC sea level rise. The TWL estimation method is adapted taking into account the differences of coast morphology: natural beaches exposed directly to the Atlantic waves, and sheltered urban areas protected by a dike inside the Sebou estuary. Projections of extreme TWL on topography of the study area were performed in order to map floodable areas. The results show that the Kenitra coast is not secured against the risk of coastal flooding during extreme storms. The most vulnerable areas are located near the jetties of the mouth north of Mehdia beach and south of Chlihat beach. The extension of flooded areas is between about 402 500 m2 and 647 900 m2 for the 25 and 100 years water levels, respectively. However, the operations of sand nourishment and reprofiling beach in these low areas can protect backshore from expected risk of storm surges.

Global sea level rise (SLR) rates are accelerating, and abnormal weather is occurring more frequently due to global warming and climate change. SLR could intensify coastal disasters and concerns of an increase in storminess. In this study, a two-dimensional advanced circulation model (ADCIRC) was used to simulate tides and storm surges around the Taiwan coast. The model was calibrated and verified using observed tides and storm surges at four tidal gauge stations, including Taipei Tamsui, Taichung Harbor, Kaohsiung Harbor, and Hualien Harbor, based on historical typhoon events. The root mean square error and skill value of the differences between the computed and observed water levels for model calibration and validation were in the range of 0.08–0.27 m and 0.92–0.99, respectively. The results showed a reasonable agreement between the simulated and observed tidal levels and surge heights. The validated model was then used to assess the impact of SLR on the tides and surge heights. Four typical typhoon events under present-day sea level conditions and under SLR conditions of 0.87 m and 1.9 m were used for the model simulations. The simulated results show that the largest differences in water levels and surge heights between present-day conditions and SLR of 0.87 m and 1.9 m are found at Taichung Harbor compared to other three-gauge stations. The changes in M2 tidal amplitude are less than 1 cm due to sea level rise. Moreover, the timing of the M2 tide was earlier by approximately 4.7 min and 9 min under SLR 0.87 m and 1.9 m, respectively, at Taichung Harbor. The maximum increases in water level ranged from 9.2 cm to 13.7 cm under SLR of 0.87 m and from 19.2 cm to 24.8 cm under SLR of 1.9 m at Taichung Harbor. The peak water level can significantly increase as a result of the SLR. All of these characteristics respond to an SLR with nonlinear and nonuniform behavior.

In coastal areas, flood events can result from the interaction of several factors such as rainfall, river flow and the classical tidal asymmetry to mention but a few. Therefore, flood risk assessment in these areas involves not only the estimation of the extreme values of each variable, but also their probability of occurring simultaneously. This study investigates the combined effect and dependence between a “heavy” rainfall with a high tidal levels forcing on the occurrence and severity of floods in the urban neighborhood close to the estuary of the Bouregreg River (Morocco). The methodology used for this analysis is based on a bivariate copula model to evaluate the joint risk probability of flood events. The estimated joint probability is used to define the boundary conditions for a hydraulic model to quantify the water levels and the extent of floods caused by the combination of both extreme rainfall and storm surge. The considered variables reveal a not negligible correlation, and the copula approach seems to be suitable and enough flexible, for analyzing separately marginal distributions of the source variables and their structure of dependence. Results show that the joint probability of rainfall and tide both exceeding their critical thresholds remains low to moderate, and the biggest threat to this area might be caused by heavy rainfall. However, high tide adds an extra risk by reducing the capacity of the urban drainage in absorbing storm water; especially when rainfall intensity exceeds 100 years return period. Although rainfall and tide introduce a wide range of time scale meteorological forcing, this won’t prevent storm surge and extreme rainfall events resulting from climate change, to take place in the future, on the same day leading to some of the most critical flooding scenarios in this area.

Dune erosion exposes coastal communities to greater risks of sea level rise, severe storm surge impact, flooding and property damage. This study evaluated the contribution of vegetation roots to dune erosion volume reduction using an analytical solution of a wave impact model. A resistance coefficient obtained from direct field measurements of dune shear strength and root density at South Padre Island, Texas, U.S.A was introduced into the analytical solution. Findings show that resistance of coastal dunes to erosion depends on vegetation type; the average in-situ shear strength of dunes vegetated with monocot species (sea oats) was 41.7 ± 6.1 KPa which was significantly higher than those vegetated with dicot species (railroad vines, gulf croton and camphor weed) at 22.2 ± 4.8 KPa. The measured in-situ shear strength of dunes vegetated with sea oats also showed a positive correlation with root density for a limited number of samples. A range of values for a proposed new coefficient of 0.2–0.8 was estimated from the ratio of in-situ shear strength of bare dunes to the shear strength of dunes vegetated with sea oats and proposed for consideration in the wave impact model When applied to the analytical solution of the wave impact model in the collision regime, a lower coefficient value resulted in lower predicted erosion volumes while higher values resulted in higher erosion volume. The results from this study emphasized the importance of suitable dune vegetation for an overall resilient coastal dune system for protection against erosion and this work suggests an approach to help quantify the benefits of the vegetation on erosion mitigation, which was validated through a comparison with field measurements.

How does physical history of flood-related hazards affect individuals’ perceptions? The present study represents a unique effort to understand perceptions of flood hazards in light of the geographic background. Situated in Alabama, the United States, the cities of Mobile and Huntsville display two different physical geographic contexts. Despite one being a coastal city (Mobile) and the other being an inland city, both are similarly vulnerable to flooding. We first present results of historical analyses of heavy precipitation in both cities and analysis of storm surge history in the city of Mobile. We then report results of both descriptive statistical and inferential statistical analyses based on a two-city residents’ survey that was conducted in the spring of 2016. We find that residents in both cities are able to connect the particular natural hazard of flooding with their physical environments. Residents in both cities are influenced by their perceptions of precipitation when making assessments of flooding. Despite the fact that Huntsville has not experienced heavy precipitation events as much as Mobile in recent history, residents of Huntsville tend to link heavy rainfall – the most frequent cause of flooding in that city, with flooding. In contrast, residents of Mobile tend to link hurricanes, more particularly hurricane number, with flooding. These results show that people are attuned to their physical environments and take into consideration their personal observations when forming perceptions of natural hazards. More studies need to be conducted to further investigate the dynamics of physical exposure to hazards and risk perceptions in other geographic areas.

Multi-hazard assessment is receiving increasing attention as often commonly occurring hazards may contain a second or even a third associated hazard. Generally, multi-hazards could be joint hazards (i.e. these hazards occur at the same time), for example, a hurricane usually comes with strong wind, storm surge, and heavy rainfall. They can also be one hazard preceding another, for example, an earthquake generating a tsunami. The jointly occurring hazards in some cases can be more devastating than a single hazard. This paper will describe the assessment of two jointly occurring hazards, wind and ice formation by using an advance numerical simulation. First, multivariate (hourly wind, temperature and precipitation) simulation for many years in the Midwestern US is undertaken. By setting a condition for freezing rain, these parameters were input into a simple ice-accretion model to estimate ice-thickness. A joint hazard curve for wind and ice was then constructed and compared to the existing prescribed treatment of these two hazards in design loading guidelines, such as ASCE 7 in the United States, ISO 12494 (International Standard); and the results from our previous model.

Design practices for aquaculture systems in northeastern US estuarine areas have evolved over time based on experience of operators and on project economics in an increasingly competitive market. There has been growing awareness among aquaculture practitioners of the need to evaluate the integrity of their designs under increasing severity and/or frequency of extreme environments, such as winter storms and hurricanes. A parametric study is conducted in this paper to assess the adequacy of mooring ropes for oyster cages under severe environmental conditions, including high tides, storm surges and 100-year extreme wave heights. The test site for this study, comprising of 1080 cages arranged in 24 rows, is located in the upstream estuarine area of the Damariscotta River along the coast of Maine, where significant aquaculture farming takes place. Field measurements were conducted on the main mooring lines at three different locations, by using several load cells and custom-designed data acquisition systems. Environmental data at the site were collected from oceanographic buoys, as well as from local tidal and wind stations. Statistical results of the field data show that the measured mooring tensions are strongly correlated with tide-induced water level variations. While current is not the dominating contributor to mooring tension at high tide, it is a dominant force for rope tension at low to mid tidal level. Also notable is the effect of reduced current on the mooring load as the flow passes through the net cages at the front and back of the farm. The mooring tensions at the front (seaward direction) are observed to be 30–50% larger than the back (landward) loads. In addition, wind gust load also constitutes a significant contribution to mooring tension. At low and high tides, it can add up to 200% and 30%, respectively, to the total mooring load. Formulations commonly used in offshore engineering were applied to evaluate the environmental forcing and the line tensions. By employing recommended inertia and drag coefficients, good agreement with measured data were obtained. These formulations are subsequently used to evaluate the safety factor of the under various scenarios, including larger farm sizes, shorter rope lengths, and effects of extreme storm surge conditions and 100-year return wave height.

Roads in poor road condition disrupt emergency operations in disaster-prone areas during emergency periods. Prolonged inundation of pavements from storm surge accelerates deterioration of pavements and increases maintenance cost. The objective of this study is to propose an optimized decision support system for pavement maintenance and rehabilitation (MR community, structure and infrastructure vulnerabilities; and damage indices. Linear programming was applied to optimize M&R strategies to ensure good pavement condition for all roads at a minimum M&R budget. Lifecycle optimization of M&R operations estimated that USD 2.49 million is the minimum annual budget that ensures having good average road’s condition in the study area. Most of the annual M&R budget will be invested for overlay and resealing treatments on the roads at high and medium GEOPHRIV areas. This study helps transportation authorities to identify deteriorated pavement sections, maintain the pavement periodically to prevent or minimize damage before storm surge, and allocate resources for M&R operations.

Assessment of vulnerability to storm surge flood is not only significant for the survival of the exposed communities but also for adaptation. Defining vulnerability as the function of exposure, sensitivity and resilience capacity, we propose a composite vulnerability index (CVI) to assess village- level vulnerability to storm surge flood in the Sundarban Biosphere Reserve (SBR), India. The composite vulnerability index based analysis revealed that of the total villages (1063) located in SBR; nearly half of the villages are highly and very highly vulnerable with least capacity to cope with any kind of extreme event. The villages located in the southern parts and adjacent to coast were found more vulnerable to storm surge while those located at higher elevation in the central part showed low vulnerability. Some villages in northern part of the region were under high and very high vulnerability due to presence of low lying and waterlogged wetlands. The findings of the study may have implications for developing resilience capacity in response to storm surge flooding. Thus, the methodology can help the local policymakers in integrating local multi-hazards knowledge and in making information actionable for mitigation and adaptation of storm surge flood hazard.

Coastal flooding due to storm surge and sea-level rise (SLR) affects seawater intrusion (SWI) in aquifers. Under coastal flooding events, SWI from both sea boundary and land-surface is expected to increase. SWI in coastal aquifers is also strongly influenced by geological heterogeneity characteristics. In this study, the combined impacts of fully geological heterogeneity and coastal flooding on SWI is quantified in a two-dimensional unconfined coastal aquifer. Three indices including the seawater toe location ( x toe ), the mixing volume ( v mv ) and the SWI volume ( v swiv ) are used to assess the vulnerability to the intrusion of the seawater. A series of 50 log-normally distributed random hydraulic conductivity with a spherical correlation function is generated using the GCOSIM3D code. Then, numerical simulations of transient, saturated-unsaturated variable-density flow and solute transport, SUTRA, are performed in a stochastic Monte Carlo framework to understand how coastal flooding and geological heterogeneity effects can change the groundwater salinity. During storm surge events, seawater penetrates into the aquifer and leads to reduce temporary of the freshwater quality. The results indicate that the storm surge has a short-term impact on fresh groundwater. The aquifer is significantly influenced by SLR as a long-term effect while it causes a larger x toe in comparison with pre-flooding events’ conditions. Also, the results obtained under gradual and instantaneous assumption of SLR show that the gradual assumption leads to a smaller x toe which is more realistic. Comparison of the homogeneous and heterogeneous scenarios indicates the heterogeneity affects SWI status both in the presence and the absence of coastal flooding events. It causes reduction in x toe and v swiv as well as increase in v mv . This study shows the significant value of considering a wide range of variations due to heterogeneity, in order to better manage the coastal fresh groundwater aquifers.

In this paper, the trivariate frequency analysis method for joint probability assessment of typhoon-induced storm surges and rainstorms is presented. The proposed method includes three major processes. The first process is to the find the best fitted marginal cumulative distributions for wind speeds (W), storm surges (S) and rainstorms (R), respectively. It is found that the Lognormal distribution is more suitable for storm surges and rainstorms, and Weibull distribution is more suitable for wind speeds. The second process is to estimate the joint probability distributions of W, S and R using four trivariate copulas, namely, Gumbel, Clayton, Frank and AMH. It is found that the joint probability can be best modeled by Gumbel copula. The last process is to calculate the conditional joint distributions of typhoon-induced storm surges and rainstorms which is useful for government agencies for improving disaster system management during typhoon events. An effective Particle Swarm Optimization (PSO) is proposed for to estimate the parameters of marginal cumulative distributions and copula functions. Analysis results based on the maximum likelihood method (MLM) and log-likelihood function (LLF) demonstrate the effectiveness of the PSO.

The coastal region of Bangladesh is highly vulnerable due to its low adaptive capacity, dense population, flat topography and exposure to various natural disasters such as cyclone, storm surges, sea level rise, tidal floods, bank erosion etc. In addition to present vulnerability, climate change will bring detrimental impact on socio-economic performance, health, and livelihood of the coastal population. This study has been conducted to assess the vulnerabilities of the coastal region of Bangladesh by considering the IPCC framework of vulnerability studies and using multivariate statistical techniques. A total of 31 indicators have been used of which 24 are socio-economic and 7 are natural (exposure) indicators and these indicators have been retrieved from the secondary source. Principal Component Analysis (PCA) has been applied to find unequal weights of all indicators. Afterward, 7 vulnerability groups (Principal Components - PCs) have been retained which eigenvalue greater than one in accordance with Kaiser Criterion. Demographic Vulnerability (PC1), Economic Vulnerability (PC2), Agricultural Vulnerability (PC3), Water Vulnerability (PC4), Health Vulnerability (PC5), Climate Vulnerability (PC6) and Infrastructural Vulnerability (PC7) are the principle vulnerable groups considering both present (2013) and the future (2050) climate change scenarios. Spatial maps of each group have been generated to assess the regional variation of above mentioned multispectral vulnerability profile across the coastal region of Bangladesh. Climate change will change dramatically the future vulnerability profile which will be alarming for agro-ecological systems of that region. The findings of this study might be useful for policy makers as well as planners.

The impacts of a major hurricane on residential real estate can be devastating. Hurricane Sandy in New York City (NYC) is among the examples of how flooding can unexpectedly extend beyond FEMA flood zones. Such surprises or negative shocks can provide property owners—especially those not flooded—with new information about future flood risks, based on the difference of the property distance from the flood zone and the distance to the actual locations of flooding. We use a difference-in-differences approach to quantify the effects of these shocks on residential property values for non-flooded NYC properties after Sandy. The short-run negative “surprise” effect was lower NYC housing prices by about 6%-7% for each mile (or about 2% per standard deviation) difference between the property distance from the flood zone and the distance to the actual locations of flooding. The corresponding positive “surprise” effect is insignificant. The long-term “surprise” effects of flood risk on housing prices tend to disappear, as residents’ memories of the “surprise” fade and they seem to only recall the actual storm surge several years after the hurricane.

Coastal areas globally suffer from serious erosion and sedimentation problems. The assessment of coastal erosion risk is fundamental for better coastal management. The main goal of the current study was to enhance coastal management by identifying the coastal erosion risk and suggest possible mitigation measures. The study was developed for the Egyptian Northern Coast. MIKE 21 was used to evaluate the erosion and test the proposed measures. First, a bathymetric survey of the study area was conducted. Then the tidal data, storm surge, and global sea rise data were collected. The offshore wave data, shoreline data were compiled. And then, the different nearshore wave modeling and wave propagation were modeled. The model was calibrated using measured data in 2014 and validated using measured data in 2016. Future shoreline changes for the years 2029, 2039, and 2049 were depicted. A suitable mitigation measure was used and tested for the same years. The groins with a specific size and arrangement were tested. The main goal of the study is to find a suitable solution to protect the coast and investigate its impact on the shoreline in the next 30 years. The proposed mitigation measure minimized the coastal erosion of the study area rigorously.

Background: Climate change impacts are felt disproportionately in developing countries, and in particular Southern Asia experiences the most damaging hydrometeorological events in the world, with loss of life from past cyclones in the hundreds of thousands. Despite this, the Bay of Bengal cyclone basin receives far less research attention than many of the others around the world. Here, we study the historical and future impacts of Super Cyclone Amphan, which made landfall in May 2020, bringing storm surges of 2-4 meters to coastlines of India and Bangladesh. Methods: In this modelling study, we combine projections of sea level rise from the Coupled Model Intercomparison Projection, phase 6 (CMIP6), with estimates of storm surge using a dynamic storm surge model. Sampling the spectrum of possible sea level rises, we consider a low, medium and high scenario, based on projections in 2100. We then feed these into a flood inundation model to simulate storm surge-induced flooding, had Cyclone Amphan occurred in these future worlds. Finally, we consider the change in future population growth and urbanisation, thereby calculating the change in population exposure to these future flooding events. Our approach is that of the extreme event attribution community, but projecting into the future rather than interrogating the past. Findings: We find that in 2100, the local sea level rise in the Bay of Bengal during the pre-monsoon cyclone season is between 0.32-0.84 m, depending on which emissions scenario is followed. If a Cyclone Amphan-scale storm surge occurred on top of that sea level rise, the future population of both India and Bangladesh will be more exposed, with India showing >200% increased exposure to extreme (>3 m) and moderate (>1 m) flooding under a high emissions scenario, and Bangladesh showing ~60-80% increased exposure to the same scenarios. The majority of this change in both countries comes from sea level rise rather than population changes, and in Bangladesh the future population change contributes negatively to the change in exposure, as more citizens migrate further inshore. However, if we follow an emissions scenario consistent with meeting the upper Paris Agreement climate goal, we project very little change in exposure. Interpretation: There is an urgent need to reduce carbon emissions to net zero, to prevent the negative impacts of climate change. By far the majority of cyclone research has been undertaken for countries such as America and Japan, with less resilient countries such as those in South Asia, which are more sensitive to changes in climate, seeing far less attention. With Cyclone Amphan occurring at the height of the COVID-19 crisis, we highlight how the risk was compounded and recommend that future climate risk assessments explicitly account for these potential non-linearities. Funding Statement: The main funding is from the Natural Environment Research Council. Declaration of Interests: The authors declare no competing interests.

Polders (enclosed coastal embankments) are often constructed to protect river and coastal floodplains in deltas. In Bangladesh, a total of 139 polders have been constructed between the 1960s and 1980s to safeguard agricultural lands from potential damage due to tidal floods, storm surge floods, and salinity intrusion. Whilst such flood control measures reduce the probability of flooding, they have had complex impacts on geomorphological and hydrological processes with consequence for human wellbeing. This legacy of interventions in the coastal system and subsequent human adaptations, now makes decision making even more challenging at a time of increasing environmental pressures. This thesis analyses historical floods in the coastal zone in Bangladesh, diagnosing whether the floods were attributable to monsoonal precipitation (pluvial flooding), high upstream river discharge into the tidal delta (fluvio-tidal flooding), or cyclone-induced storm surges. It quantifies polders’ effectiveness by modelling different forms of inundation to estimate what flooding might have been had the polders not been constructed. Considering the societal impacts of flooding, the effects of changing land-use and flood risk on poverty are quantified. The results answer the questions of (i) how the pattern of land use/land cover (LULC) change influences flood risk at present and continue to do so in the future; (ii) how LULC change and flood risk impact poverty spatially. The last section of the thesis focuses on estimating the impacts of potential Tidal River Management (TRM) on elevating the floodplains and reducing the annual probability of flooding. It identifies suitable TRM sites to model sediment deposition in those areas. The potential impact of TRM on flooding is investigated by comparing flood susceptibility ‘before and after’ the implementation of TRM. By analyzing complex coastal flood processes and adaptation options spatially and quantitatively, this thesis provides new evidence to the effectiveness of the past (polders), and potential future (TRM) adaptation options. It also presents a new approach to flood risk estimation, considering the societal impacts of flooding. The results of this thesis could be of importance both in research and practice for making scientifically informed decisions on coastal flood risk management, particularly in Bangladesh.

Nowadays, most coastal cities have complex drainage systems (i.e., rivers and pipelines) connected to the sea, affecting the flooding during the co-occurrence of rain and storm surges. In this study, this compound flooding is studied by developing a coupled model based on a one-dimensional (1D) hydrological model SWMM and a two-dimensional (2D) hydrodynamic model ADCIRC. The coupling is achieved by setting the 1D model as a subroutine of the 2D model while the parallel computing scheme of the 2D model is kept using the Message Passing Interface (MPI). The coupled model is applied in Xiangshan, Zhejiang Province, along the eastern coast of China. The model accurately ensures water conservation and reproduces the observed tidal elevation, storm surge, and river water stages during Typhoons Haikui (2012) and Fitow (2013). A series of simulations are carried out to quantify the influences of a coastal dam, drainage system, control of tide gates, rain, and storm surge on the compound flooding. The results show that the drainage system enhances the connectivity between the land and the sea no matter whether the coastal dam exists, leading to faster flooding and draining. Furthermore, when a storm surge occurs, the high surge level can significantly reduce the drainage efficiency of the inland flooding during rain and thus causes more severe flooding hazards. The simulation results also suggest that urban pipelines play an important role in preventing urban flooding caused by rain. And for the prevention of storm surge inundation, an effective gate control strategy is suggested that the gates should be closed when the water levels on both sides of the dam are equal for the first time before the peak of the storm surge and are open when the water levels are equal again. Finally, the flooded area can be divided into the tidal zone, the hydrologic zone, and the transition zone to identify different flood mitigation strategies.

Flood risk management (FRM) in coastal cities is a challenging task due to uncertain climate hazards under sea-level rise (SLR) and large-scale vulnerable buildings within in the floodplain. This study presents a building-level adaptation framework to evaluate alternative community adaptation strategies relying on cloud computing. We incorporated multiple sources of model uncertainties and randomly generated storm surges in each year of simulation using the extreme value distribution (GEV) theory. Based on a case study in Miami-Dade County, Florida, four adaptation scenarios were designed to evaluate their effectiveness in adaptation. Our sensitivity analysis suggested a positive linear relationship between community flood risk reduction and total community adaptation costs in the life-cycle cost-benefit (LCCB) model. Our results showed that uncertainties of the total community damage based on the LCCB model ranges from $ 221 million to $ 2.75 billion. However, when considering social vulnerability, the total community damage increased substantially, ranging from $ 244 million to $ 3.44 billion. Nevertheless, a 6ft public seawall based on the upper bound of the GEV distribution with the enforced building elevation policy in flood zones could substantially reduce community flood damage under uncertain sea-level rises.

In September 2018 Hurricane Florence had severe impacts on the lower Neuse River and Neuse estuary, North Carolina, despite the fact that it was a minor storm in terms of traditional indicators of storm intensity. The storm was consistent with recent trends and predictions of tropical cyclone activity driven by Anthropocene climate warming. However, its impacts in the Neuse area were also conditioned by idiosyncratic aspects of the geographic setting and the synoptic situation. Geomorphic changes examined here include erosion of estuarine shoreline bluffs, geomorphic transformations of small freshwater swamps, and effects on the river and floodplain upstream of the estuary. The shoreline changes caused by Florence were unique with respect to previous tropical cyclones and ongoing episodic erosion, due to the extraordinarily high and unusually long duration of storm surge. Transformations of the “ravine swamps”—mainly associated with deposition of >0.6 m of sand on organic muck and open water surfaces—were similarly unprecedented. Despite high river discharges (third highest on record) and the high storm surge, fluvial impacts in the lower river and fluvial-estuarine transition zone were minimal. This is attributable to the morphology of the channel-floodplain system, adapted to Holocene sea-level rise and preserved by wetlands protection programs. The large area of the storm, slow forward movement, and extreme rainfall of Florence are likely indicative of a “new normal” with respect to tropical cyclones in the region. However, the geomorphic impacts in the lower Neuse were largely determined by particulars of the Neuse estuary and Florence's storm track. An exception is the limited impacts on the lower fluvial portion of the river and the fluvial-estuarine transition zone, where there exists a complex mosaic of channels and flowing wetlands capable of accommodating extreme discharges.

Using geological evidence to extend the history of typhoon activity beyond the instrumental period and understand the possible linkage between future climate change and increasing storm intensity is of great significance in preparing for coastal risks in a warming world. In this study, an extreme storm event that occurred on the southern Yangtze coast, East China, during the latter stage of Neolithic Liangzhu Culture were estimated based on sedimentary records and numerical modeling. We first investigated the spatial distribution of peat layers formed during the time of the Liangzhu Culture to produce a high-resolution map of the paleo-coastline of the Ningbo Plain. Inverse modeling using the grain size of storm deposits recovered at the end of Liangzhu Culture at the Neolithic Yushan site was applied to calculate the instantaneous water level including wave run-up and storm surge caused by the extreme event. Numerical simulations of multiple typhoon scenarios combined with precipitation and sea-level rise constrained by the paleo-coastline and paleo-topography were then used to estimate the storm surge and inundation on the coast of Hangzhou Bay. Through comparison of results between the inverse model and numerical simulations, we infer that the intensity of the storm recorded at the Yushan site was likely greater than any typhoon in the local instrumental records and that the storm deposits were formed by a Super Typhoon, which moved close to or made landfall directly on the southeast coast of Hangzhou Bay. Our modeling further suggests that the extreme storm event was coupled with an abrupt relative sea-level rise at ca. 4.5 cal kyr BP, which indicates a warmer west Pacific Ocean at that time.