Comparative analysis of Vening-Meinesz Moritz isostatic models using the constant and variable crust-mantle density contrast - A case study of Zealandia

Mohammad Bagherbandi, Robert Tenzer

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)


We compare three different numerical schemes of treating the Moho density contrast in gravimetric inverse problems for finding the Moho depths. The results are validated using the global crustal model CRUST2.0, which is determined based purely on seismic data. Firstly, the gravimetric recovery of the Moho depths is realized by solving Moritz's generalization of the Vening-Meinesz inverse problem of isostasy while the constant Moho density contrast is adopted. The Pratt-Hayford isostatic model is then facilitated to estimate the variable Moho density contrast. This variable Moho density contrast is subsequently used to determine the Moho depths. Finally, the combined least-squares approach is applied to estimate jointly the Moho depths and density contract based on a priori error model. The EGM2008 global gravity model and the DTM2006.0 global topographic/bathymetric model are used to generate the isostatic gravity anomalies. The comparison of numerical results reveals that the optimal isostatic inverse scheme should take into consideration both the variable depth and density of compensation. This is achieved by applying the combined least-squares approach for a simultaneous estimation of both Moho parameters. We demonstrate that the result obtained using this method has the best agreement with the CRUST2.0 Moho depths. The numerical experiments are conducted at the regional study area of New Zealand's continental shelf.
Original languageEnglish
Pages (from-to)339-348
Number of pages10
JournalJournal of Earth System Science
Issue number2
Publication statusPublished - 1 Jan 2013
Externally publishedYes


  • Crust
  • Gravity
  • Isostatic model
  • Moho interface

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

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