2.4.3. Synergy between Analogue and Numerical Modelling
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| Fig. 26. Schematic diagram showing the added value of a coupled analogue-numerical modelling system (Persson et al., 2004). The analogue modelling facilities are used to simulate upper crustal deformation and its dynamic response to surface erosion and sedimentation predicted by the developed numerical models. The scanner is used to transmit the surface topography of the analogue model to the numerical model. The displayed image shows the drainage system of the Ebro river (NE Spain) (Garcia-Castellanos et al., 2003). Subsequently, the calculated erosion/deposition is manually applied to the analogue model. |
Novel tectonic modelling concepts and their implementation in numerical modelling software provide new opportunities for quantifying the interplay between stresses and rheology during deformation of the lithosphere. Computer simulations will focus on the links between mountain-forming and basin-forming processes, basin geometries and vertical motions in space and time. Furthermore, thermo-mechanical numerical modelling schemes, accounting for the physics of strain localization in the lithosphere and its consequence for poly-phase deformation and associated vertical motions, can be designed and implemented.
Analogue modelling will provide independent validation of numerical models and will be particularly useful in complex settings, such as those with pronounced 3-D geometries (e.g. strike-slip systems and compressional mountain belts). Various scales can be handled: shallow to deep, local to regional with advantages of analogue modelling in terms of complexity and proximity to geological observations and advantage of numerical modelling in terms of physical clarity and higher potential for sensitivity studies and parameter variation (Fig. 26). In analogue experiments, geomechanical boundary conditions and material properties will be dynamically scaled to simulate lithospheric conditions.
With respect to modelling techniques, ever-faster computer systems and ever-larger datasets result in vast improvements in modelling capabilities. A transition to true 4-D modelling has been achieved during the last years. However, modelling approaches to different problems are still developed on an ad-hoc basis.