A Spatial Structure Variable Approach to Characterize Storm Events for Coastal Flood Hazard Assessment
TL;DR: In this paper, the authors address the problem of defining credible joint statistics of significant wave heights Hs and water levels ζ, focusing on the selection of the sample pair that characterizes each sea storm, to evaluate the occurrence probability of extreme events.
Abstract: Over the last decades, the evaluation of hazards and risks associated with coastal flooding has become increasingly more important in order to protect population and assets. The general purpose of this research was to assess reliable coastal flooding hazard maps due to overflow and wave overtopping. This paper addresses the problem of defining credible joint statistics of significant wave heights Hs and water levels ζ, focusing on the selection of the sample pair that characterizes each sea storm, to evaluate the occurrence probability of extreme events. The pair is selected maximizing a spatial structure variable, i.e., a linear combination of Hs and Relaix, F., Zammit, P.S. Satellite cells are essential for skeletal muscle, specific to each point of the area at risk. The structure variable is defined by the sensitivity of the flooding process to Hs and ζ, as found by analyzing a set of inundation maps produced through a Simplified Shallow-Water numerical model (SSW). The proposed methodology is applied to a coastal stretch in the Venetian littoral (Italy), by means of a 30 year-long time series recorded at the “Acqua Alta” oceanographic research tower, located in the Northern Adriatic Sea in front of the Venetian lagoon. The critical combination of Hs and ζ forming the structure variable is presented in a map, and it can be related to the topography and the presence of mitigation measures. The return period associated with the two recent large storms that occurred in this area in 2018 and 2019 is also investigated. The proposed procedure gives credible occurrence probabilities for these events, whereas other approaches would consider them extremely unlikely.
Citations
More filters
TL;DR: There were two typos in the original publication of this article as discussed by the authors , and two more typos were found in the follow-up publication of the same article, in 2012.
Abstract: There were two typos in the original publication [...]
TL;DR: In this article , a comparison of different monitoring strategies and methodologies that have been integrated into repeated surveys in order to evaluate the performance of a new camera system is presented, based on Raspberry Pi.
Abstract: Coastal monitoring is strategic for the correct assessment of nearshore morphodynamics, to verify the effects of anthropogenic interventions for the purpose of coastal protection and for the rapid assessment of flooding vulnerability due to severe events. Remote sensing and field surveys are among the main approaches that have been developed to meet these necessities. Key parameters in the assessment and prevision of coastal flooding extensions, beside meteomarine characteristics, are the topography and slope of beaches, which can be extremely dynamic. The use of continuous monitoring through orthorectified video images allows for the rapid detection of the intertidal bathymetry and flooding threshold during severe events. The aim of this work was to present a comparison of different monitoring strategies and methodologies that have been integrated into repeated surveys in order to evaluate the performance of a new camera system. We used a low-cost camera based on Raspberry Pi called VISTAE (Video monitoring Intelligent STAtion for Environmental applications) for long-term remote observations and GNSS-laser tools for field measurements. The case study was a coastal tract in Riccione, Italy (Northern Adriatic Sea), which is the seat of nourishment interventions and of different types of underwater protection structures to combat coastal erosion. We performed data acquisition and analysis of the emerged beach and of the swash zone in terms of the intertidal bathymetry and shoreline. The results show a generally good agreement between the field and remote measurements through image processing, with a small discrepancy of the order of ≈0.05 m in the vertical and ≈1.5 m in the horizontal in terms of the root mean square error (RMSE). These values are comparable with that of current video monitoring instruments, but the VISTAE has the advantages of its low-cost, programmability and automatized analyses. This result, together with the possibility of continuous monitoring during daylight hours, supports the advantages of a combined approach in coastal flooding vulnerability assessment through integrated and complementary techniques.
References
More filters
TL;DR: In this article, a fundamental analysis of the meaning of second-moment reliability in multivariate problems is presented, and the format described is entirely derived from one basic assumption concerning the measurement of reliability.
Abstract: A fundamental analysis of the meaning of second-moment reliability in multivariate problems is presented. The format described is entirely derived from one basic assumption concerning the measurement of reliability. All formulations are exact, and approximations involving the assumption of small variance are only introduced to simplify practical equations. The format is fully invariant under any change of formulation of the failure criteria consistent with the laws of algebra and mechanics.
2,702 citations
2,623 citations
TL;DR: In this paper, the authors apply univariate extreme value theory to quantify the risk of failure due to extreme levels of some environmental process and demonstrate how these ideas can be exploited as part of the design process.
Abstract: For many structural design problems univariate extreme value theory is applied to quantify the risk of failure due to extreme levels of some environmental process. In practice, many forms of structure fail owing to a combination of various processes at extreme levels. Recent developments in statistical methodology for multivariate extremes enable the modelling of such behaviour. The aim of this paper is to demonstrate how these ideas can be exploited as part of the design process
315 citations
TL;DR: In this article, the authors focus on the multidimensional frequency analysis of sea storm significant wave height (H), storm duration (D), storm direction (A), and storm interarrival time (I) (i.e., the calm period separating two successive storms).
194 citations
01 Jan 2002
TL;DR: In this paper, a method for joint probability analysis, using a Monte Carlo simulation approach, based on distributions fitted to water level, wave height and wave steepness, and to the dependence between them, is presented.
Abstract: On coasts with high tidal ranges, or subject to high surges, both still water levels and waves can be important in assessing flood risk; their relative importance depends on location and on the type of sea defence. The simultaneous occurrence of large waves and a high still water level is therefore important in estimating their combined effect on sea defences. Wave period can also be important in assessing run-up and overtopping, and so it is useful also to have information on the joint distribution of wave height and period. Unless the variables are either completely independent or completely dependent, multivariate extremes are difficult to predict directly from observational data, as there may be too few events of the relevant type amongst the observations. In the past, the fitting and extrapolation of the dependence functions between the variables has often involved complicated and/or subjective approaches. This paper presents a method for joint probability analysis, using a Monte Carlo simulation approach, based on distributions fitted to water level, wave height and wave steepness, and to the dependence between them. RESUME
179 citations