TOOLBOX FOR ANALYSIS OF FLEXURAL ISOSTASY (TAFI) – A MATLAB® TOOLBOX FOR MODELING FLEXURAL DEFORMATION OF THE LITHOSPHERE

Flexural deformation due to vertical tectonic loads emplaced on the lithosphere and corresponding gravity variations are commonly modelled by treating the lithosphere as a thin elastic plate overlying an inviscid fluid asthenosphere. These models are essential to understanding the isostatic response of a plate and flexural basin evolution history. For such modeling, we designed a new interactive Matlab® toolbox called Toolbox for Analysis of Flexural Isostasy (TAFI). This toolbox supports 2-D and 3-D forward modeling of lithospheric flexure and the corresponding gravity anomaly. TAFI computes Green's Functions for flexure of the elastic plate subjected to point or line loads, and an analytical solution for harmonic loads. Flexure due to non-impulsive, distributed 2-D or 3-D loads are computed by convolving the appropriate Green's function with a spatially discretized load function read from a user-supplied file. The gravity anomalies associated with each density interface within the lithosphere are calculated by using the Fourier Transform of flexural deflection of these interfaces and estimating the gravity in the wavenumber domain. All models created in TAFI use Matlab's intrinsic functions, and do not require any other specialized toolbox, functions or libraries except those distributed with TAFI. The modeling functions within TAFI can be called from the Matlab workspace, from within user-written programs, or from a Graphical User Interface (GUI) provided with TAFI. The Graphical User Interface of the toolbox provides interactive flexural modeling of lithosphere enabling real time comparison of model fits with observed gravity data and data constraining the flexural subsidence and uplift, thus facilitating a rapid search for the best fitting flexural model. TAFI’s GUI also provides platform for teaching the principals of isostasy by creating an interactive learning environment in which users can readily see the effects of changes in model parameters.