Estimation of Moho Depth Beneath Southern Indian Shield by Inverting Gravity Anomalies Constrained by Seismic Data

This study presents a high‐resolution 3D Moho structure beneath southern India and its surrounding regions from observed gravity anomalies. The global gravity disturbance model (XGM2019e) with a grid resolution of 0.1° is considered for this study. The extended Bott's inversion algorithm and Gauss‐Fast Fourier Transform based forward model are adopted to invert for the Moho undulations beneath the Indian peninsula. The inversion algorithm is tested for a synthetic model having a predefined density contrast and mean Moho depth. The robustness of this inversion algorithm is further tested for noise‐incorporated gravity data. The control points are required for estimating two hyper‐parameters, viz. density contrast, and reference depth, which play a crucial role in the precise estimation of Moho depth. In real case study, the inverted Moho depth of Southern India and its surrounding regions by seismic constraint receiver function‐driven control points show a very complex architecture of Moho topography. The observed average crustal thickness in the study region is 35.35 km, corroborating with the previously reported Moho depths. The maximum crustal thickness is 53.04 km beneath the southern part of Archean Western Dharwar Craton and west of Salem block, around 44–47 km Moho depth is observed at the south of Salem block into Madurai block till Achankovil Shear Zone, which suggests the possible continuation of the Achaean crust of Palghat‐Cauvery Shear Zone System. The lowest crustal thickness values are observed along the eastern margin of the Cuddapah basin, which overlaps with the Proterozoic Krishna basin of the Eastern Ghats Mobile belt. Plain Language Summary Earth's crust and mantle boundary is known as Mohorovičić discontinuity or Moho. Estimation of the accurate 3D architecture of Moho has various applications in geodynamic modeling, tectonic deformation study, etc. Deep seismic refraction and receiver functions analysis are the main geophysical techniques for imaging Moho topography. Seismic‐driven Moho estimations are very accurate and station dependent, however, sparsely distributed due to cost compulsion. Contrarily, high‐resolution gravity data are readily available due to modern satellite gravimetry with a limitation of lack of unique interpretation of the estimated structure. In the present study, the seismic constraint gravity inversion algorithm is developed and applied to the Southern peninsula of India for high‐resolution Moho topography est