Least squares collocation method in Moho depth determination in Iran using gravity gradient data

In this study, an approach using gravity observations utilizing the Least Squares Collocation (LSC) method is developed with the aim of mapping the depth spatial variability of the Mohorovičić discontinuity. This approach is based on a spherical two-layer isostatic model where the exterior gravity field only varies because of the shifting topographic masses and the related isostatic adjustment since it is believed that the Earth's core has a uniform density distribution. Assuming mass conservation between the Moho column of height $$ with respect to $$ representing the mean Moho and following a Helmert condensation approach, the relationship between the surface layer density to the potential $$ can be obtained and $$ can be estimated via LSC from observed values of any functional derived from $$. With such approach, the depth of Moho in the Iranian Plateau is estimated from $$ data generated by GOCO06S model reduced by topography, bathymetry and sediments effects by considering GEBCO2021 and CRUST1.0 models. The needed a-priori assumptions on $$ and the density contrast $$ are tuned so to obtain the best fit with seismic Moho depths reported by literature. 73 stations were matched with 3 km of standard deviation, which is coherent with the expected accuracy of the benchmark values. The remaining greater discrepancies showed to be clustered in defined areas like the Zagros chain and the reliefs along the Caspian coastline and the East borders.