  The use of Internet of Things (IoT) technologies is becoming a preferred
solution for the assessment of tailings dams' safety. Real-time sensor
monitoring proves to be a key tool for reducing the risk related to these
ever-evolving earth-fill structures, that exhibit a high rate of sudden and
hazardous failures. In order to optimally exploit real-time embankment
monitoring, one major hindrance has to be overcome: the creation of a
supporting numerical model for stability analysis, with rapid-enough response
to perform data assimilation in real time. A model should be built, such that
its response can be obtained faster than the physical evolution of the analyzed
phenomenon. In this work, Reduced Order Modelling (ROM) is used to boost
computational efficiency in solving the coupled hydro-mechanical system of
equations governing the problem. The Reduced Basis method is applied to the
coupled hydro-mechanical equations that govern the groundwater flow, that are
made non-linear as a result of considering an unsaturated soil. The resulting
model's performance is assessed by solving a 2D and a 3D problem relevant to
tailings dams' safety. The ROM technique achieves a speedup of 3 to 15 times
with respect to the full-order model (FOM) while maintaining high levels of
accuracy.

Computational Engineering, Finance, and Science