Alpine mass movements can generate process cascades involving different materials including rock, ice, snow, and water. Numerical modelling is an essential tool for the quantification of natural hazards. Yet, state-of-the-art operational models are based on parameter back-calculation and thus reach their limits when facing unprecedented or complex events. Here, we advance our predictive capabilities for mass movements and process cascades on the basis of a three-dimensional numerical model, coupling fundamental conservation laws to finite strain elastoplasticity. In this framework, model parameters have a true physical meaning and can be evaluated from material testing, thus conferring to the model a strong predictive nature. Through its hybrid Eulerian–Lagrangian character, our approach naturally reproduces fractures and collisions, erosion/deposition phenomena, and multi-phase interactions, which finally grant accurate simulations of complex dynamics. Four benchmark simulations demonstrate the physical detail of the model and its applicability to real-world full-scale events, including various materials and ranging through five orders of magnitude in volume. In the future, our model can support risk-management strategies through predictions of the impact of potentially catastrophic cascading mass movements at vulnerable sites.

高山质量运动可以产生涉及不同材料的过程级联，包括岩石、冰、雪和水。数值模拟是量化自然灾害的重要工具。然而，最先进的操作模型基于参数反算，因此在面临前所未有或复杂的事件时会达到其极限。在这里，我们在三维数值模型的基础上提高了对质量运动和过程级联的预测能力，将基本守恒定律与有限应变弹塑性相结合。在这个框架中，模型参数具有真正的物理意义，可以通过材料测试进行评估，从而赋予模型强大的预测性。通过其混合欧拉-拉格朗日特征，我们的方法自然地再现了断裂和碰撞，侵蚀/沉积现象和多相相互作用，最终可以准确模拟复杂的动力学。四个基准模拟展示了模型的物理细节及其对真实世界全尺度事件的适用性，包括各种材料，体积范围为五个数量级。未来，我们的模型可以通过预测脆弱地点潜在的灾难性级联大规模运动的影响来支持风险管理策略。