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- Biotic and abiotic factors governing dune response to storm eventsPublication . Garzon, Juan L.; Costas, Susana; Ferreira, OscarThe alongshore response of dunes to storm events can be extremely variable and,consequently, their capacity to maintain their services, including the protection ofhinterland communities. In this study, the role of biotic and abiotic factors determin-ing the magnitude of dune retreat driven by a severe storm along a 60 km barrierisland system was investigated. Data from high-resolution satellite imagery, digitalterrain models, and wave propagation models were used in this assessment. Theassessed abiotic factors included the backshore volume, dune height, downdrift inletdistance, and incident wave power. The evaluated biotic factor was the vegetationcover, characterized by a vegetation index retrieved from the multispectral imagery.The results revealed large alongshore variability on dune retreat, ranging from negli-gible impact to ca. 40 m of retreat. All combined factors allowed us to explain up to70% of the dune retreat variability through a multi-regression analysis. Among allinvestigated factors, the major contributor controlling the magnitude of dune retreatwas the backshore volume (more robust berms reduced the retreat) followed by thewave power (normal and longitudinal components). Moreover, the removal of localsalient features in the dune line caused the straightening of the coastline, highly con-tributing to the development of dune retreat hotspots. The other evaluated factorshad a smaller influence on reducing coastal retreat, including the vegetation, whosecontribution to dune protection was around one order of magnitude lower than thatprovided by the backshore volume. The results highlight the importance of regionalassessments to understand the causes behind the large alongshore variability ofstorm impacts at dunes. They also state the relatively low influence of the vegetationfrom this climatic region to enhance dune resistance to storms.
- Uncertainty analysis related to beach morphology and storm duration for more reliable early warning systems for coastal hazardsPublication . Garzon, Juan L.; Plomaritis, T. A.; Ferreira, OscarEarly warning systems (EWSs) for coastal erosion are highly cost-effective instruments for disaster risk reduction. Among other aspects, an adequate pre-storm beach morphology and the storm characteristic definition are relevant in determining EWSs prediction reliability. Here, XBeach simulations were used to investigate the beach-dune response to different storm events with varying duration and pre-storm morphologies. Severity was defined using wave height return periods (from 5 to 50 years) and duration variability was established by confidence intervals after an adjustment with wave height. Beach morphology variability included different berm morphologies, including erosional and accretional conditions. Three erosion indicators were used: remaining berm width, dune retreat, and eroded volume. Regarding the pre-storm morphology variability: i) pre-storm conditions highly determined the final berm width for the 5 and 10-year events; ii) antecedent morphology affected dune retreat variability mostly for the 50 year events, and; iii) eroded volume depended on the pre-storm conditions, but the percentage of the eroded volume, relative to the initial conditions, was similar regardless of the morphology. Regarding the storm duration effect: i) this variable had a limited impact on the remaining berm width for the 5-year event; ii) storm duration influenced dune retreat mainly for the 50-year event, determining dune breaching occurrence, and; iii) eroded volume response to changes in duration was similar regardless of storm intensity, except for the 50-year event. According to the obtained results, the implementation of reliable EWSs for coastal erosion needs to assess the uncertainties related to initial/forcing conditions, namely pre-storm morphology and storm duration.
- Modeling of coastal erosion in exposed and groin-protected steep beachesPublication . Garzon, Juan L.; Ferreira, Oscar; Plomaritis, Theocharis A.Process-based models are suitable tools for reproducing storm-driven erosion. However, their performance has been mainly examined on mild-slope sandy beaches and their use on steep beaches still represents a challenge. Here, open-source process-based model XBeach experiments were combined with topographical measurements collected for two storms (16- and 5-year return period) to obtain a reliable model. The model parameters “facua” (parameterized wave asymmetry and skewness sediment transport component), “bermslope” (upslope transport term for semireflective beaches), and “wetslope” (critical avalanching submerged slope) were utilized for calibration and validation. The 16-year storm simulations on an exposed beach revealed that whether bermslope increased and “facua” must be reduced, and vice versa, to properly simulate erosion. Adding bermslope provided excellent results for these storms when using facua and wetslope values close to the recommended values. In a groin-protected site, XBeach was successfully calibrated and validated for the tested storms using these parameters, although with different values. These experiments demonstrated that the appropriate use of these parameters can satisfactorily simulate morphological changes on steep beaches for different hydrodynamic conditions and coastal settings (exposed and groin protected).
- Early Warning System development: Quarteira and Praia de FaroPublication . Garzon, Juan L.; Zozimo, Catarina; Ferreira, Andreia M. Marques; Ferreira, Oscar; Fortes, Conceição Juana; Reis, Maria TeresaMany coastal zones worldwide are heavily populated and host very important socio-economic sectors. Portugal is a good example of countries whose economy is highly dependent on tourism activities, especially those sea-related activities. The two sites selected in this project (Quarteira and Faro) receive thousands of national and international visitors annually, not only during the summertime but also in the rest of the seasons because of the favorable weather conditions. However, these sites have been acknowledged as coastal risk hotspots due to their exposure to wave-induced flooding and erosion. Under this threat, the implementation of effective disaster risk reduction (DRR) plans is vital for minimizing damages in occupied areas. In this regard, Early Warning Systems (EWSs) play an important role in allowing for preparedness, namely, timely site evacuation or effective intervention prior to the approaching storm. The successful implementation of EWSs is one of the most cost-effective and efficient measures for disaster risk reduction and the saving of lives. EWSs can rely on complex tools such as process-based models to simulate coastal hazards namely erosion and flooding. However, they are normally highly time-consuming and this aspect might represent a major limitation for operational systems. Conversely, Bayesian Networks (BNs) can provide risk probabilities instantly after being trained and they have been successfully used to make predictions of storm impacts in several coastal applications. The main disadvantage of Bayesian Networks is that they are data-intensive, requiring large input information in order to derive the probabilistic relationships used in their predictions. Under the lack of field observations, process-based models can be used to generate this required information. Once trained, the BN can be used as a surrogate for a process-based model in an EWS.