Non-Gaussian non-stationary models for natural hazard modeling

This paper addresses the construction of probabilistic models for time or space dependent natural hazards. The proposed method uses Karhunen-Loève expansion in order to construct an empirical model matching the non-stationarity and the randomness of natural phenomena such as earthquakes or other complex environmental processes. The terms of the Karhunen-Loève expansion are identified directly from measured data. The approach is illustrated and its performance assessed through two academic examples. It is then applied to seismic ground motion modeling using recorded data.