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Feiyun River (Rui'an section) is a tidal reach, and the design water levels within different return periods are difficult to determine. Peaks-over-threshold (POT) analysis methods were used to study the water level maximums of the river section. The study results indicate that skew surges have a measurable impact on extreme water levels and are characterized by a sharp increase in wind speeds at the estuary, followed by a sudden decrease, leading to a significant storm surge event. When the return periods are 50, 100 and 200 years, the corresponding water levels of Feiyun River (Rui'an section) are 5.59, 6.04 and 6.49 m, respectively. The proportion of skew surges in extreme water levels increases with the return period length, and it exceeds 50% when the return period is 200 years. The calculation results based on skew surges are often more reasonable in long return periods. [ABSTRACT FROM AUTHOR]

The tidal section of the Feiyun River is affected by the dual effects of the upstream flood discharge and downstream tidal uplift, resulting in complex water level changes. To determine the extreme water levels of the tidal section, the methods of the statistical analysis, harmonic calculation and joint probability analysis are utilized to study the correlation between the water level changes and the downstream estuarine tides and upstream floods based on the observation data and explore the extreme water level characteristics caused by flood-tide encounters. The study results indicate that the interannual water level correlation between Rui'an Hydrological Station and the up-downstream is not significant, but the correlation of their monthly water levels is enhanced. During the rainy season, there is a positive correlation between the daily average water levels of the upstream and Rui'an Hydrological Station. The water levels at Feiyun River (Rui'an section) are more affected by the combined influence of the astronomical tides and storm surges than by the upstream runoffs and water levels. The main contributing factor to the extreme skew surges at Rui'an Hydrological Station is the offshore storm surges. There is a significant time difference between the upstream flood peaks and the skew surge peaks at Rui'an Hydrological Station. The skew surge peaks at Rui'an Hydrological Station are at the forefront of the flood peaks superimposed by the extreme skew surges of the storm surges. The combined maximum total water levels for 1 year, 5 years, 10 years and 50 years calculated by the joint probability analysis method are 4.16 m, 4.44 m, 4.59 m and 4.90 m, respectively, which are basically consistent with the analysis results of measured data in the past 50 years. According to the joint probability distribution of the storm surges and astronomical tides, the reliability of short period calculation results is relatively high. [ABSTRACT FROM AUTHOR]

Coastal flooding compound events can be caused by climate-driven extremes of storm surges and waves. To assess the risk associated with these events in the context of climate variability, the bivariate extremes of skew surge (S) and significant wave height (HS) are modeled in a nonstationary framework using physical atmospheric/oceanic parameters as covariates (atmospheric pressure, wind speed and sea surface temperature). This bivariate nonstationary distribution is modeled using a threshold-based approach for the margins of S and HS and a dynamic copula for their dependence structure. Among the covariates considered, atmospheric pressure and related wind speed are primary forcings for the margins of S and HS, but temperature is the main positive forcing of their dependence. This latter relation implies an increasing risk of compound events of S and HS for the studied site in the context of increasing global temperature. [ABSTRACT FROM AUTHOR]

Extreme sea level estimates are fundamental for mitigating coastal flooding as they provide insight for defence engineering. As the global climate changes, rising sea levels combined with increases in storm intensity and frequency pose an increasing risk to coastline communities. We present a new method for estimating extreme sea levels that accounts for the effects of climate change on extreme events that are not accounted for by mean sea level trends. We follow a joint probabilities methodology, considering skew surge and peak tides as the only components of sea levels. We model extreme skew surges using a non-stationary generalised Pareto distribution (GPD) with covariates accounting for climate change, seasonality and skew surge–peak tide interaction. We develop methods to efficiently test for extreme skew surge trends across different coastlines and seasons. We illustrate our methods using data from four UK tide gauges and estimate sea level return levels when accounting for these long-term trends. [ABSTRACT FROM AUTHOR]

State‐of‐the‐art flood hazard maps in coastal cities are often obtained from simulating coastal or pluvial events separately. This method does not account for the seasonality of flood drivers and their mutual dependence. In this article, we include the impact of these two factors in a computationally efficient probabilistic framework for flood risk calculation, using Ho Chi Minh City (HCMC) as a case study. HCMC can be flooded subannually by high tide, rainfall, and storm surge events or a combination thereof during the monsoon or tropical cyclones. Using long gauge observations, we stochastically model 10,000 years of rainfall and sea level events based on their monthly distributions, dependence structure and cooccurrence rate. The impact from each stochastic event is then obtained from a damage function built from selected rainfall and sea level combinations, leading to an expected annual damage (EAD) of $1.02 B (95th annual damage percentile of $2.15 B). We find no dependence for most months and large differences in expected damage across months ($36–166 M) driven by the seasonality of rainfall and sea levels. Excluding monthly variability leads to a serious underestimation of the EAD by 72–83%. This is because high‐probability flood events, which can happen multiple times during the year and are properly captured by our framework, contribute the most to the EAD. This application illustrates the potential of our framework and advocates for the inclusion of flood drivers' dynamics in coastal risk assessments. Plain Language Summary: In coastal cities, floods can result from different drivers such as intense rainfall and extreme sea levels. In order to estimate the expected annual damage (EAD) from flooding, it is important to correctly quantify the chance of these events happening and their impacts. Commonly, only the maximum value for a flood driver each year is taken, ignoring its seasonality; and these maxima are assumed to either never or always happen at the same time of the year. These assumptions become problematic when pluvial and coastal floods can occur at different times of the year and sometimes at the same time, such as in Ho Chi Minh City (HCMC). In this paper, we develop a framework to account for the seasonality of flood drivers and their mutual dependencies. Using statistical and hydrodynamic modeling, we generate the equivalent of 10,000 years of rainfall and sea level events and estimate their impact. We find the EAD for HCMC to be $1.02 B. Neglecting the seasonality of rainfall and sea level leads to an underestimation of the EAD by 72–83%. This application illustrates the potential of our framework and advocates for the inclusion of flood drivers' dynamics in coastal risk assessments. Key Points: We develop a flood risk framework based on monthly time series that includes the seasonality and the dependence between flood driversNot accounting for seasonality underestimates the expected annual damage (EAD) in Ho Chi Minh City by 72–83%Rainfall and storm surge are independent for most months but, under the assumption of full correlation, EAD would increase by 15% [ABSTRACT FROM AUTHOR]

Abstract Using high‐frequency tide gauge observations from 1980 to 2017, we analyzed changes in extreme sea levels (ESLs) along the Chinese coast to examine whether extreme sea‐level rise acceleration could be observed. The results indicated that the ESL has risen with fluctuations along the Chinese coast. The ESL also featured significant decadal variabilities. The ESL rise was accelerated at most tide gauges throughout the whole study period, especially after the 1980s, while the acceleration patterns varied with station location. The mean sea level (MSL) change was confirmed as the major driver of the ESL change according to the analysis. However, the skew surge may also have affected the extremes at many of the tide gauges, which was observed after detrending. The extreme/MSL had a significant positive correlation with the Atlantic Multidecadal Oscillation, which is supposed to affect the MSL through a combination of variation in sea surface temperature, pressure system, and wind. That sea level oscillation is dominated by Atlantic Multidecadal Oscillation should be taken into consideration when studying accelerations in the rate of ESLs and of MSLs along the Chinese coast.

Extreme value statistics applied to positive storm surges (PSS) is a necessary tool for coastal management adaptation and decision-making. Generally, when extreme values of PSS are calculated, the maximum height of PSS or the skew surge (SK) for each event is used. In this paper, a comparison of the results obtained by applying the generalized extreme value (GEV) distribution to series of maximum PSS and SK (GEV-MPSS and GEV-MSK, respectively), observed in two port areas with different hydrodynamic and tidal characteristics, is performed for the period from 1956 to 2012. The sites chosen are Buenos Aires and Mar del Plata. The first one is located at the Río de la Plata Estuary, with PSS that tripled the height of the astronomical tide. The second is located on the Atlantic coast of Buenos Aires Province, with PSS that often reach the amplitude of the astronomical tide. The GEV distribution parameters are calculated by the maximum likelihood method, and estimated heights are obtained using MPSS and MSK for return periods up to 500 years. Results show that estimated heights calculated using GEV-MPSS or GEV-MSK differ from one to another for both locations. GEV-MPSS appears to overestimate the meteorological effect in some events, while GEV-MSK appears to underestimate this effect on others. It is also shown that both methodologies are not applicable to all events at the same location. An alternative to obtain a more representative dataset of meteorological action would be using both methodologies, selecting the MSK or the MPSS that identify the maximum wind effect for each event. [ABSTRACT FROM AUTHOR]

Using high‐frequency tide gauge observations from 1980 to 2017, we analyzed changes in extreme sea levels (ESLs) along the Chinese coast to examine whether extreme sea‐level rise acceleration could be observed. The results indicated that the ESL has risen with fluctuations along the Chinese coast. The ESL also featured significant decadal variabilities. The ESL rise was accelerated at most tide gauges throughout the whole study period, especially after the 1980s, while the acceleration patterns varied with station location. The mean sea level (MSL) change was confirmed as the major driver of the ESL change according to the analysis. However, the skew surge may also have affected the extremes at many of the tide gauges, which was observed after detrending. The extreme/MSL had a significant positive correlation with the Atlantic Multidecadal Oscillation, which is supposed to affect the MSL through a combination of variation in sea surface temperature, pressure system, and wind. That sea level oscillation is dominated by Atlantic Multidecadal Oscillation should be taken into consideration when studying accelerations in the rate of ESLs and of MSLs along the Chinese coast. Key Points: The acceraction of the extreme sea level along the Chinese coast is analyzed in the paper for the first timeWe found that the Atlantic Multidecadal Oscillation (AMO) significantly affect the mean sea levels and extreme sea levels along the Chinese coast [ABSTRACT FROM AUTHOR]

Based on previous studies of tide‐gauge records from locations with semidiurnal tidal regimes, extreme skew surges are always assumed independent of the high water (HW). However, differences in water depth between HW peaks of semidiurnal tidal regimes can be much lower than those in mixed semidiurnal regimes, where one daily HW is higher than the other. We statistically analyze tide‐gauge records of 15 sites worldwide with a mixed semidiurnal regime and find that for approximately half of these sites extreme skew surges occur more often during smaller HWs. This dependence is not caused by seasonality effects, and the places that show dependence are all located in areas with a shallow continental shelf, thus indicating possible tide‐skew surge interactions. In those cases where dependence exists, using the skew surge does not seem to offer any advantages over the nontidal residual. Plain Language Summary: The water level during storms (i.e., storm surges) in coastal areas largely depends on the level of the tide. This effect can be more noticeable in places with a mixed semidiurnal regime, which is characterized by two high water peaks per day, with one high water peak being larger than the other. Knowledge of this effect can help forecasting and prevention of flooding events in these regions. We statistically analyze water level records of 15 sites worldwide with a mixed semidiurnal regime and find that in around half of these sites storm surges occur more often at lower high water levels. These places are all located in areas with a shallow continental shelf, such as estuaries or closed seas. Key Points: Extreme skew surges are not independent of the high water level in some sites with mixed tidal regimeExtreme skew surges occur more often during lower high tidal waters in the sites that show dependenceThe dependence observed between extreme skew surges and high waters does not arise from seasonality effects [ABSTRACT FROM AUTHOR]

Storm surges and the resulting extreme high sea levels are among the most dangerous natural disasters and are responsible for widespread social, economic and environmental consequences. Using a set of 220 tide gauges, this paper investigates the temporal variations in storm surges around the world and the spatial coherence of its variability. We compare results derived from two parameters used to represent storm surge: skew surge and the more traditional, non-tidal residual. We determine the extent of tide-surge interaction, at each study site, and find statistically significant (95% confidence) levels of tide-surge interaction at 59% of sites based on tidal level and 81% of sites based on tidal-phase. The tide-surge interaction was strongest in regions of shallow bathymetry such as the North Sea, north Australia and the Malay Peninsula. At most sites the trends in the skew surge time series were similar to those of non-tidal residuals, but where there were large differences in trends, the sites tended to have a large tidal range. Only 13% of sites had a statistically significant trend in skew surge, and of these approximately equal numbers were positive and negative. However, for trends in the non-tidal residual there are significantly more negative trends. We identified 8 regions where there were strong positive correlations in skew surge variability between sites, which meant that a regional index could be created to represent these groups of sites. Despite, strong correlations between some regional skew surge indices, none are significant at the 95% level, however, at the 80% level there was significant positive correlation between the north-west Atlantic - south and the North Sea. Correlations between the regional skew surge indices and climate indices only became significant at the 80% level, where Nińo 4 was positively correlated with the Gulf of Mexico skew surge index and negatively correlated with the east Australia skew surge index. The inclusion of auto-correlation in the calculation of correlation greatly reduced their significance, especially in the short time-series used for the regional skew surge indices.

Abstract: The impacts of storm surges represent an increasing risk to the world's coastlines. Coastal planners require accurate estimates of flood risk in order to provide suitable defensive measures. Therefore a reliable methodology is required for the estimation of extreme sea-level probabilities at high spatial resolution along coastlines. This paper describes a new method for estimating these probabilities, with application to the UK coastline. The method consists of two components: the estimation of extreme sea-levels by applying a newly developed statistical method, termed the Skew Surge Joint Probability Method, with tide gauge records, and the use of hindcast sea-levels to dynamically interpolate these estimates around complex coastlines. The skew surge parameter is a more reliable indicator of meteorological impacts on sea-level than the non-tidal residual used in the Revised Joint Probability Method, as previously used in the United Kingdom. The method has been applied to the UK coastline to provide a database of extreme sea-level probabilities for the Environment Agency for England and Wales and the Scottish Environment Protection Agency. The database will be used to inform coastal defense strategy, flood mapping and forecasting and to support policy, implementation and operational decision-making. [Copyright &y& Elsevier]

Abstract: Autoregressive (AR) models have been widely used in several geophysical applications, as they represent a simple and practical option for modeling stochastic series. In this paper, we show that AR models can be adapted and are useful for the description of skew surge (i.e., a surge occurring at the time of a high tide) series. Namely, seasonal AR models of skew surge series are built on 35 sites located along the coasts of the European Atlantic Ocean, the English Channel and the Southern part of the North Sea. These models are presented and discussed. The estimation of the distribution of the residuals, modeled using a Normal Inverse Gaussian (NIG) distribution, is also discussed. AR models are advantageous for a number of reasons: (i) they provide information on the correlation length of the surge phenomena, (ii) they can be used to forecast short-term surge occurrences based on a limited set of past observations and (iii) they provide plausible information about longer series, which may have larger extremes than what is observed, permitting a statistical description of simulated extremes. These three characteristics and benefits are examined and discussed for a selected site, the Saint-Nazaire harbor (France), with respect to the storm surge that occurred during the Xynthia storm of February 2010. [Copyright &y& Elsevier]

• The skew surge is more suitable than the residual water level for surge risk assessment frameworks. • The residual water level may be a better metric for capturing the relationship between storm surges and climate changes. A better understanding of the storm surge phenomenon is essential for coastal protection, future planning, and coastal ecosystem conservation. Using hourly sea level data from 15 tide gauges along the coastline of China the metrics, skew surge and residual water level, which are used to represent storm surges, are compared in this study. The relationship between residual water level, skew surge and predicted high tide were analyzed using two statistical measurements. The results showed that unlike the annual maximum residual water level, the annual maximum skew surge and the astronomical high tide tended to coincide more frequently (more than 50% of the annual maximum skew surges occurred at high tide). Thus, the skew surge was more suitable than the residual water level for use in risk-based coastal planning frameworks. Using the monthly maximum value and indices of the storm surge (storm surge number, duration and intensity), we compared the performances of skew surge and residual water level in expressing changes of storm surges. These two metrics can both capture changes in storm surge activities on seasonal, decadal and long-term scales, and correlation coefficients of storm surge intensity between residual water level and skew surge were greater than 0.80 at 11 tide gauges. At most tide gauges, the skew surge was significantly correlated with 4–5 nearby tide gauges while the residual water level was correlated with only 1–2 tide gauges, the skew surge may be a better metric for risk-based coastal planning frameworks if the interpolation method is used. The El Niño-Southern Oscillation (ENSO) can affect the storm surge frequency along the coastline of China. The effects of the ENSO were more obvious when the residual water level was selected. In conclusion, the skew surge can be selected for use in risk-based coastal planning frameworks, while the residual water level may be a better metric for capturing the relationship between storm surges and climate changes. [ABSTRACT FROM AUTHOR]