4.7 Article

Probing the Southern African Lithosphere With Magnetotellurics-Part I: Model Construction

Journal

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2021JB023117

Keywords

magnetotellurics; lithosphere; southern Africa

Funding

  1. German Research Foundation, DFG [MO 2265/4-1]
  2. Australian Research Council [FT150100541]
  3. Projekt DEAL
  4. Australian Research Council [FT150100541] Funding Source: Australian Research Council

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The Southern African Magnetotelluric Experiment (SAMTEX) collected data at over 700 sites in southern Africa and presented the first 3D inversions of the full dataset. The study focused on comparing different inversion codes and subsets of data to assess the robustness of the 3D models. Results showed that all inversions imaged the main conductive and resistive features, but differences existed between the models.
The Southern African Magnetotelluric Experiment (SAMTEX) involved the collection of data at over 700 sites in Archean to Proterozoic southern Africa, spanning features including the Kalahari Craton, Bushveld Complex, and voluminous kimberlites. Here, we present the first 3D inversions of the full SAMTEX data set. In this paper, we focus on assessing the robustness of the 3D models by comparing two different inversion codes, jif3D and ModEM, and two different subsets of the data, one containing all acceptable data and the other containing a smaller selection of undistorted, high-quality data. Results show that the main conductive and resistive features are imaged by all inversions, including deep resistive features in the central Kaapvaal Craton and southern Congo Craton and a lithospheric-scale conductor beneath the Bushveld Complex. Despite this, differences exist between the jif3D and ModEM inverse models that derive mainly from the differences in regularization between the models, with jif3D producing models that are very smooth laterally and with depth, while ModEM produces models with more discrete conductive and resistive features. Analysis of the differences between these two inversions can provide a good indication of the model resolution. More minor differences are apparent between models run with different subsets of data, with the models containing all acceptable data featuring higher wavelength conductivity variations than those run with fewer stations but also demonstrating poorer data fit.

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