Coastal forecast through coupling of Artificial Intelligence and hydro-morphodynamical modelling
Coastal forecast through coupling of Artificial Intelligence and hydro-morphodynamical modelling
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DOI：
10.1080/21664250.2023.2233724
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发表时间：
2023-07
影响因子：
2.4
通讯作者：
Pavitra Kumar;N. Leonardi
中科院分区：
文献类型：
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作者：
Pavitra Kumar;N. Leonardi
摘要随着全球海岸线气候驱动风险的增加，了解和预测形态变化以及开发有效的海岸预测系统已成为适应气候变化的首要任务。人工智能是一种强大的技术，近年来发展迅速，可以为沿海科学领域提供新的分析手段。然而，相对于其他科学领域，这些技术在沿海地貌学方面的潜力仍然相对未被探索。本文研究了人工神经网络和贝叶斯网络与完全耦合的水动力学和形态模型（Delft3D）相结合，用于预测形态变化和沉积物输运沿着海岸系统。测试了两组人工智能模型，一组依赖于本地化建模输出或本地化数据源，另一组具有减少的建模输出依赖性，并且一旦训练，仅依赖于边界条件和海岸线几何形状。第一组模型分别为训练和测试提供大于0.95和0.86的回归值。第二组简化依赖性模型分别为训练和测试提供大于0.84和0.76的回归值。我们的研究结果突出了人工智能和统计模型在沿海应用中的潜力。
ABSTRACT As climate-driven risks for the world’s coastlines increase, understanding and predicting morphological changes as well as developing efficient systems for coastal forecast has become of the foremost importance for adaptation to climate change. Artificial Intelligence is a powerful technology that has been rapidly evolving recently and can offer new means of analysis for the coastal science field. Yet, the potential of these technologies for coastal geomorphology remains relatively unexplored with respect to other scientific fields. This article investigates the use of Artificial Neural Networks and Bayesian Networks in combination with fully coupled hydrodynamics and morphological models (Delft3D) for predicting morphological changes and sediment transport along coastal systems. Two sets of Artificial Intelligence models were tested, one set relying on localized modeling outputs or localized data sources and another set having reduced dependency from modeling outputs and, once trained, solely relying on boundary conditions and coastline geometry. The first set of models provides regression values greater than 0.95 and 0.86 for training and testing, respectively. The second set of reduced dependency models provides regression values greater than 0.84 and 0.76 for training and testing, respectively. Our results highlight the potential of AI and statistical models for coastal applications.