Browsing by Author "Andriolo, Umberto"
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- Field measurements and hydrodynamic modelling to evaluate the importance of factors controlling overwashPublication . Matias, Ana; Carrasco, A.R.; Loureiro, Carlos; Masselink, Gerd; Andriolo, Umberto; McCall, Robert; Ferreira, Oscar; Plomaritis, Theocharis; Pacheco, André; Guerreiro, MarthaOverwash hydrodynamic datasets are mixed in quality and scope, being difficult to obtain due to fieldwork experimental limitations. Nevertheless, these measurements are crucial to develop reliable models to predict overwash. Aiming to overcome such limitations, this work presents accurate fieldwork data on overwash hydrodynamics, further exploring it to model overwash on a low-lying barrier island. Fieldwork was undertaken on Barreta Island (Portugal) in December 2013, during neap tides and under energetic conditions, with significant wave height reaching 2.6 m. During approximately 4 h, more than 120 shallow overwash events were measured with a video-camera, a pressure transducer and a current-meter. This high-frequency fieldwork dataset includes runup, overwash number, depth and velocity. Fieldwork data along with information from literature were used to implement XBeach model in non-hydrostatic mode (wave-resolving). The baseline model was tested for six verification cases; and the model was able to predict overwash in five. Based in performance metrics and the verification cases, it was considered that the Barreta baseline overwash model is a reliable tool for the prediction of overwash hydrodynamics. The baseline model was then forced to simulate overwash under different hydrodynamic conditions (waves and lagoon water level) and morpho-sedimentary settings (nearshore topography and beach grain-size), within the characteristic range of values for the study area. According to the results, the order of importance of factors controlling overwash predictability in the study area are: 1st) wave height (more than wave period) can promote overwash 3–4 times more intense than the one recorded during fieldwork; 2nd) nearshore bathymetry, particularly shallow submerged bars, can promote an average decrease of about 30% in overwash; 3rd) grain-size, finer sediment produced an 11% increase in overwash due to reduced infiltration; and 4th) lagoon water level, only negligible differences were evidenced by changes in the lagoon level. This implies that for model predictions to be reliable, accurate wave forecasts are necessary and topo-bathymetric configuration needs to be monitored frequently.
- Performance of intertidal topography video monitoring of a meso-tidal reflective beach in South PortugalPublication . Vousdoukas, Michalis; Ferreira, P. M.; Almeida, Luis Pedro; Dodet, Guillaume; Psaros, Fotis; Andriolo, Umberto; Taborda, Rui; Silva, Ana Nobre; Ruano, Antonio; Ferreira, ÓscarThis study discusses site-specific system optimization efforts related to the capability of a coastal video station to monitor intertidal topography. The system consists of two video cameras connected to a PC, and is operating at the meso-tidal, reflective Faro Beach (Algarve coast, S. Portugal). Measurements from the period February 4, 2009 to May 30, 2010 are discussed in this study. Shoreline detection was based on the processing of variance images, considering pixel intensity thresholds for feature extraction, provided by a specially trained artificial neural network (ANN). The obtained shoreline data return rate was 83%, with an average horizontal cross-shore root mean square error (RMSE) of 1.06 m. Several empirical parameterizations and ANN models were tested to estimate the elevations of shoreline contours, using wave and tidal data. Using a manually validated shoreline set, the lowest RMSE (0.18 m) for the vertical elevation was obtained using an ANN while empirical parameterizations based on the tidal elevation and wave run-up height resulted in an RMSE of 0.26 m. These errors were reduced to 0.22 m after applying 3-D data filtering and interpolation of the topographic information generated for each tidal cycle. Average beach-face slope tan(β) RMSE were around 0.02. Tests for a 5-month period of fully automated operation applying the ANN model resulted in an optimal, average, vertical elevation RMSE of 0.22 m, obtained using a one tidal cycle time window and a time-varying beach-face slope. The findings indicate that the use of an ANN in such systems has considerable potential, especially for sites where long-term field data allow efficient training.