Modelling the Space-Time Field of Tectonic Stresses in the Area of Unlimited Space for Seismic Safety

The research is aimed at the structurally similar geodynamical model building for a selective diagnosis of seismic hazard and territorial seismic zoning refinement. For the first time the article presents the territorial geodynamic model developed on the basis of a structural mask method for geographic energy fields as a result of reading of the historical information about the structure of earthquake-provoking energy flows, which is enclosed in the Earth’s crust objects. A vector space-time field structurally similar to a territorial tectonic stress field is calculated via the largest differential layer power gradient between the basic terrain surfaces indicating a vertical territory displacement over a period of time passed between formations of adjacent valleys. As a result of the research we have defined the space-time differentiation of relative velocity and movement direction of the territorial tectonic elements in the period from the Pliocene through the Quaternary. We also have defined the concentration areas and the types of tectonic stress generated by compression and tension. The correspondence has been established between the calculated tectonic stress concentration areas and seismic events. A satisfactory degree of conjugation between the modeled vertical tectonic movement velocities was determined in a studied area for the Quaternary period and the re-leveling results for the 20th century. It was proved that the developed geodynamical model of the studied territory is structurally similar to the corresponding geophysical field of tectonic stresses. The largest differential layer power gradient, being an integrated measure of the comparative velocity and direction of movement of tectonic elements, as well as their rheological properties and the tectonic stress value, can be used for point diagnostics of the seismic hazard and territorial seismic zoning refinement and serve as an earthquake forecasting predictor.