During strong earthquakes, the seismic wave propagation in soils involves nonlinear behaviors strongly depending on the strain level. Indeed, for small strain (typically <10^{-6}), a linear constitutive law (modulus and damping independent on the load level) can reproduce the experimental observations on site. However, for larger strains, a nonlinear hysteretic constitutive law is needed to describe the evolution of stiffness and energy dissipation during seismic loading. In addition, as strong earthquakes are characterized by larger amplitudes and durations, the role of pore pressure cannot be neglected for saturated soils. Indeed pore water pressure controls phenomena such as cyclic mobility and liquefaction due to the loss of soil strength. This can lead to a fast decrease of effective stresses and permanent deformations in the soil causing severe damage to structures. This work extends the applicability of existing calculation models for a more detailed analysis of seismic risk. Starting from a FEM approach describing the propagation of seismic waves in the vertical direction, taking into account 3D loading (so-called "1D-3C" approach: 1 direction - 3 components) in nonlinear dry soils, new strategies to consider the role of water are developed. The model is based on the relationship between the pore pressure and the shear work. The three-dimensional stress state of the material is considered. The model is validated by comparison with experimental results. The "1D-3C" approach was used to model the response of soils for four real earthquakes: the Superstition Hills earthquake in 1987 in the United States (M_{w}=6.7), the Tohoku earthquake in 2011 in Japan (M_{w}=9.1), the Kushiro earthquake in Japan in 1993 (M_{w}=7.8) and the Emilia Romagna earthquake in Italy in 2012 (M_{w}=5.9). For the first three earthquakes, records at depth and on the surface are available. The study of the first three cases makes possible the validation of the model by comparing the calculated accelerations on the surface with the available records. The model can then be considered as an advanced tool for the prediction of the seismic soil response
