This paper describes a framework in which artificial extreme sea levels (ESLs) can be generated for use in flood risk analyses. Such analyses require large numbers of events to accurately assess the risk associated with certain return water levels and quantify uncertainties surrounding the temporal variability of ESL events. Stochastic models satisfy this requirement as they are computationally inexpensive, and thus, many thousands of events may be generated over a very short period of time. As a case study, we have developed a stochastic model for the German Baltic Sea coast capable of simulating the temporal behavior of ESLs. To do this, high‐resolution water level data from 45 tide‐gauges have been used as model input. At each location, observed ESLs are identified and parameterized. Artificial ESLs are generated using Monte Carlo simulations based on the parametric distribution functions fitted to the parameterized observed ESLs. We show that the method outlined here provides an accurate representation of ESLs at all tide‐gauges tested. However, the model is limited by the availability, length, and quality of high‐resolution water level data. Due to the rarity of ESLs in the German Baltic Sea, including historical measurements into the stochastic procedure allows for the generation of artificial ESLs more in‐line with past extremes.
Managed realignment (MR) involves the landward relocation of sea defences to foster the (re)creation of coastal wetlands and achieve nature-based coastal protection. The wider application of MR is impeded by knowledge gaps related to lacking data on its effectiveness under extreme surges and the role of changes in vegetation cover, for example due to sea-level rise. We employ a calibrated and validated hydrodynamic model to explore relationships between surge attenuation, MR width(/area) and vegetation cover for the MR site of Freiston Shore, UK. We model a range of extreme water levels for four scenarios of variable MR width. We further assess the effects of reduced vegetation cover for the actual MR site and for the scenario of the site with the largest width. We show that surges are amplified for all but the largest two site scenarios, suggesting that increasing MR width results in higher attenuation rates. Substantial surge attenuation (up to 18 cm km−1) is only achieved for the largest site. The greatest contribution to the attenuation in the largest site scenario may come from water being reflected from the breached dike. While vegetation cover has no statistically significant effect on surge attenuations in the original MR site, higher coverage leads to higher attenuation rates in the largest site scenario. We conclude that at the open coast, only large MR sites (> 1148 m width) can attenuate surges with return periods > 10 years, while increased vegetation cover and larger MR widths enable the attenuation of even higher surges.
Assessments of flood exposure and risk are usually conducted for individual events with a specific peak water level and hydrograph, without considering variations in the temporal evolution (duration and intensity) of storm surges. Here we investigate the influence of temporal variability of storm surge events on flood characteristics in coastal zones, namely flood extent and inundation depth, and assess the associated flood exposure in terms of affected properties for the case of the municipality of Eckernförde, Germany. We use a nested hydrodynamic model to simulate five physically plausible, stochastically simulated storm surge events, with peak water levels corresponding to a univariate return period of 200 years and varying intensities. In a second step, the events are also combined with high-end sea-level rise projections corresponding to the RCP 8.5 scenario to analyze if the influence of temporal variability changes with rising sea-levels. Results show differences exceeding 5% in flood extent when comparing storm surges with the highest and lowest intensities. The number of properties exposed differs by approximately 20%. Differences in mean and maximum inundation depths are approximately 5%, both with and without sea-level rise. However, deviations in flood extent increase by more than 20%, depending on the sea-level rise projection, whereas differences in the number of exposed properties decrease. Our findings indicate that the temporal variability of storm surges can have considerable influence on flood extent and exposure in the study area. Taking into account that flood extent increases with rising sea-levels, we recommend that uncertainty related to the temporal variability of storm surges is represented in future flood risk assessments to ensure efficient planning and to provide a more comprehensive assessment of exposed infrastructure and assets.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.