Fully-Lagrangian three-dimensional modelling of river ice jam initiation

漂浮的河流冰块的积聚和堵塞，称为冰塞，是加拿大河流洪水的重要原因。因此，预测何时何地可能发生冰堵，对于估计潜在的洪水、评估相关的风险和规划应对措施至关重要。然而，即使在计算技术和数值模型方面取得了最新的进步，这种预测仍然超出了现有预测工具的能力。这是由于冰塞的复杂性质以及引发和形成冰塞的条件，这取决于许多因素，包括冰的特性以及水道的水动力、热力学和地形。因此，拟议的项目旨在开发一个复杂的数值模式，能够预测冰塞的形成，并将其应用于研究在适用于加拿大(特别是魁北克)河流的范围内导致冰塞形成的临界条件。所提出的模型将基于三维高性能混合无网格拉格朗日技术，该技术以处理高度动态的多物理问题而闻名，因此能够再现冰-水相互作用和冰塞形成的详细物理过程。模型结果与实验数据相结合，有望建立冰塞形成与冰的大小和浓度、河流形态和水流条件等关键有效参数的临界值之间的关系。因此，建议的研究将提供一个新的理解，否则很难预测堵塞的启动。这将大大提高冰塞的可预测性，这对于预防和减轻与拥堵和由此产生的洪水及其破坏性的社会经济影响有关的风险，特别是在加拿大和魁北克河，具有至关重要的作用。

Accumulation and blockage of floating river ice parcels, called ice jam, is a significant cause of flooding in Canadian rivers. Therefore, prediction of where and when the ice jam may happen is essential for estimation of the potential flooding, assessment of the associated risk, and planning responses. Nevertheless, even with the latest advancement in computational techniques and numerical models, such prediction is still beyond the capabilities of existing predictive tools. This is due to the complex nature of ice jams and the conditions leading to its initiation and formation, which depend on a large number of factors including the ice characteristics, and the hydrodynamic and thermodynamic and morphology of the watercourse. The proposed project, therefore, aims at developing a sophisticated numerical model, capable of predicting the ice jam formation and applying it for investigating the critical conditions leading to jam initiation over ranges applicable to Canadian (esp., Quebec) rivers. The proposed model will be based on a three-dimensional high-performance hybrid mesh-free Lagrangian technique, which is known for its ability to deal with highly dynamic multi-physics problems, and hence is capable of reproducing the detailed physics of ice-water interactions and ice jam initiation and formation. The model outcomes, in combination with the experimental data, are expected to establish the relationship between the ice jam initiation and the critical value of the key effective parameters such as ice size and concentration, river morphology, and flow conditions. Therefore, the proposed research will provide a new understanding of the otherwise difficult to predict jam initiation. This will significantly improve the ice jams predictability, which has a crucial role in the prevention and mitigation of the risks associated with the jams and resulting floods and their devastating socio-economic impacts, particularly in Canadian and Quebec rivers.