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    Tytuł:
    The impact of tides and waves on near-surface suspended sediment concentrations in the English Channel
    Autorzy:
    Guillou, N.
    Rivier, A.
    Chapalain, G.
    Gohin, F.
    Powiązania:
    https://bibliotekanauki.pl/articles/48548.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Instytut Oceanologii PAN
    Tematy:
    suspended sediment concentration
    spatial variability
    temporal variability
    coastal water
    English Channel
    bathymetry
    numerical modelling
    ROMS model
    MERIS data
    Opis:
    Numerous ecological problems of continental shelf ecosystems require a refined knowledge of the evolution of suspended sediment concentrations (SSC). The present investigation focuses on the spatial and temporal variabilities of near-surface SSC in coastal waters of the English Channel (western Europe) by exploiting numerical predictions from the Regional Ocean Modeling System ROMS. Extending previous investigations of ROMS performances in the Channel, this analysis refines, with increased spatial and temporal resolutions, the characterization of near-surface SSC patterns revealing areas where concentrations are highly correlated with evolutions of tides and waves. Significant tidal modulations of near-surface concentrations are thus found in the eastern English Channel and the French Dover Strait while a pronounced influence of waves is exhibited in the Channel Islands Gulf. Coastal waters present furthermore strong SSC temporal variations, particularly noticeable during storm events of autumn and winter, with maximum near-surface concentrations exceeding 40 mg l1 and increase by a factor from 10 to 18 in comparison with time-averaged concentrations. This temporal variability strongly depends on the granulometric distribution of suspended sediments characterized by local bimodal contributions of silts and sands off coastal irregularities of the Isle of Wight, the Cotentin Peninsula and the southern Dover Strait.
    Źródło:
    Oceanologia; 2017, 59, 1
    0078-3234
    Pojawia się w:
    Oceanologia
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Machine learning methods applied to sea level predictions in the upper part of a tidal estuary
    Autorzy:
    Guillou, N.
    Chapalain, G.
    Powiązania:
    https://bibliotekanauki.pl/articles/2078822.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Instytut Oceanologii PAN
    Tematy:
    multiple regression model
    artificial neural network
    multilayer perceptron
    regression function
    machine learning algorithm
    sea level
    Opis:
    Sea levels variations in the upper part of estuary are traditionally approached by relying on refined numerical simulations with high computational cost. As an alternative efficient and rapid solution, we assessed here the performances of two types of machine learning algorithms: (i) multiple regression methods based on linear and polynomial regression functions, and (ii) an artificial neural network, the multilayer perceptron. These algorithms were applied to three-year observations of sea levels maxima during high tides in the city of Landerneau, in the upper part of the Elorn estuary (western Brittany, France). Four input variables were considered in relation to tidal and coastal surge effects on sea level: the French tidal coefficient, the atmospheric pressure, the wind velocity and the river discharge. Whereas a part of these input variables derived from large-scale models with coarse spatial resolutions, the different algorithms showed good performances in this local environment, thus being able to capture sea level temporal variations at semi-diurnal and spring-neap time scales. Predictions improved furthermore the assessment of inundation events based so far on the exploitation of observations or numerical simulations in the downstream part of the estuary. Results obtained exhibited finally the weak influences of wind and river discharges on inundation events.
    Źródło:
    Oceanologia; 2021, 63, 4; 531-544
    0078-3234
    Pojawia się w:
    Oceanologia
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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