Improving Estuarine Hydrodynamic Forecasts Through Numerical Model Ensembles

• Tipo: Artigo em Revista Científica Internacional
• Data: 2022

Autores

Isabel Iglesias (Autor) ICBAS; José Luís Pinho (Autor) Outra; Paulo Avilez Valente (Autor) FEUP; William Melo (Autor) Outra; Ana Bio (Autor) Outra; Ana Gomes (Autor) Outra; José Vieira (Autor) Outra; Luísa Bastos (Autor) FCUP; Fernando Veloso Gomes (Autor) FEUP

Revista

Título: Frontiers in Marine Science

Vol. 11

Página Inicial: 18

ISSN: 2296-7745

Editora: Frontiers Media

Indexação

ISI Web of Knowledge - 3 Citações

Scopus - 3 Citações

Outras Informações

ID Authenticus: P-00W-6QD

DOI: 10.3389/fmars.2022.812255

Abstract (EN): Numerical models are essential tools for the study and analysis of the hydrodynamics of estuarine systems. However, the model results contain uncertainties, which need to be minimized to increase the accuracy of predictions. In this work, the ensemble technique is proposed as a solution to improve hydrodynamic forecasts for estuarine regions. Two numerical models, openTELEMAC-MASCARET and Delft3D, were considered for the application of this technique to two Portuguese estuaries. Superensembles for three scenarios (summer, winter, and extreme event) were built to assess the effectiveness of the technique in improving water level prediction. Various weighing techniques were tested in the construction of the ensembles. Weighing techniques that consider the previous performance of each model alone outperformed other techniques. This was observed for all scenarios considered, at all sampling points and in both studied estuaries. The effect of the ensemble size was also analyzed. It was found that the size of the set is directly related to the prediction accuracy, with the best results provided by the superensembles with the highest number of elements. It is concluded that the combined use of several hydrodynamic models reduces the uncertainty of the results and increases the reliability and consistency of predictions for estuarine regions.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 18