The failure of a large gravity dam might have catastrophic effects putting a large number of human lives at risk, not counting the considerable economic consequences. Most of dams are prone to natural hazards, with particular regard to flood and earthquake, so the structural control and the evaluation of the dam fragility assume great importance both to apply early warning procedure and to enhance the resilience of the system. Numerical models assume great importance in order to predict the seismic behaviour of the complex dam-soil-reservoir interacting system, nevertheless they are affected by different sources of uncertainty. The effects of uncertainties can be reduced by exploiting all available information about the structure in order to calibrate finite element models. In this scenario, measurements acquired by a monitoring system and in-situ tests take on a major role as important sources of information. This paper investigates the effect of the uncertainties in the static and dynamic analysis of existing concrete gravity dams by means of two case studies. The general Polynomial Chaos Expansion (gPCE) technique makes possible the uncertainties propagation through numerical models even without High Performance Computing (HPC). This way, the effects of the uncertainties can be quantified in terms of model output. Hybrid-predictive models based on the gPCE allow reducing the computational burden in the solution of the inverse problem and in the structural control as well
