A long-term equilibrium beach planform model for coastal work design

Traditional models usually allow fitting the equilibrium beach planform of crenulated beaches knowing wave climate characteristics at a control point. However, sometimes there are shoals or bars in the surf zone which affect surf zone dynamics and longshore sediment distribution, and it is difficult to take into account these elements using those traditional models. A long-term equilibrium beach planform model is proposed here based on sediment transport equations. This model takes into account the sediment transport due to oblique wave incidence and that due to wave height gradient. Two case studies have been studied: a simple pocket beach and a beach which is sheltered by a sandstone bar. Results show the model fits reasonably well the equilibrium beach planform to the shorelines of those beaches. This model is more suitable than traditional models when there are elements affecting surf zone dynamics

Beach memory

A new concept of beach memory is investigated in this research. Using a Beach Evolution Model developed for beach rotation, we define a function of beach memory able to describe the weight of the preceding wave conditions and their contribution in the current beach response. The time beach memory time is also defined as the period of time required for the beach memory function to be dissipated in the previous time to negligible values. The Beach Memory Function and the Beach Memory Time can be used to determine the influence of the preceding energy in the current coastal changes. Both new concepts were applied to quantify the Weighted Energy Flux Direction required for the beach planform to be estimated based on the parabolic approximations. Modeled results reproduce successfully observed planform positions

Integrated tsunami vulnerability and risk assessment: application to the coastal area of El Salvador

ABSTRACT. Advances in the understanding and prediction of tsunami impacts allow for the development of risk reduction strategies for tsunami-prone areas. This paper presents a tsunami vulnerability and risk assessment for the case study of El Salvador, the applied methodology dealing with the complexity and variability of coastal zones by means of (i) an integral approach to cover the entire risk-related process from the hazard, vulnerability and risk assessments to the final risk management; (ii) an integrated approach to combine and aggregate the information stemming from the different dimensions of coupled human and natural systems; and (iii) a dynamic and scale-dependent approach to integrate the spatiotemporal variability considerations. This work also aims at establishing a clear connection to translate the vulnerability and risk assessment results into adequate target-oriented risk reduction measures, trying to bridge the gap between science and management for the tsunami hazard. The approach is applicable to other types of hazards, having been successfully applied to climate-change-related flooding hazard

Tsunami evacuation modelling as a tool for risk reduction: application to the coastal area of El Salvador

ABSTRACT. Advances in the understanding and prediction of tsunami impacts allow the development of risk reduction strategies for tsunami-prone areas. This paper presents an integral framework for the formulation of tsunami evacuation plans based on tsunami vulnerability assessment and evacuation modelling. This framework considers (i) the hazard aspects (tsunami flooding characteristics and arrival time), (ii) the characteristics of the exposed area (people, shelters and road network), (iii) the current tsunami warning procedures and timing, (iv) the time needed to evacuate the population, and (v) the identification of measures to improve the evacuation process. The proposed methodological framework aims to bridge between risk assessment and risk management in terms of tsunami evacuation, as it allows for an estimation of the degree of evacuation success of specific management options, as well as for the classification and prioritization of the gathered information, in order to formulate an optimal evacuation plan. The framework has been applied to the El Salvador case study, demonstrating its applicability to sitespecific response times and population characteristics