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Density perturbations in the subsurface are the main driver of mantle convection and can contribute to lithospheric deformation. However, in many places the density structure in the subsurface is poorly constrained. Most geodynamic models rely on simplified equations of state or use linear seismic velocity perturbations to density conversions. In this study, we investigate the density structure beneath the Rungwe Volcanic Province (RVP), which is the southernmost volcanic center in the Western Branch of the East African Rift (EAR). We use shear-wave velocity perturbations ( dlnv(s) ) as a reference model to perform constrained inversions of satellite gravity data centered on the RVP. We use the code jif3D with a dlnv(s) -density coupling criterion based on mutual information to generate a 3D density model beneath the RVP up to a depth of 660 km. Our results reveal a conspicuous negative density anomaly (& SIM;-200 kg/m(3)) in the sublithospheric mantle (at depths ranging from similar to 100 km to similar to 250 km) beneath the central part of the Malawi Rift extending to the west, beneath the Niassa Craton, coincident with locations with positive shear-wave velocity perturbations (+7%). We calculate a 3D model of the velocity-to-density conversion factor (f) and find negative f-values beneath the Niassa Craton which suggests the observed negative density anomaly is mostly due to compositional variations. Apart from the Niassa Craton, there are generally positive f-values in the study area, which suggest dominance of temperature control on the density structure. Although the RVP generally shows negative density anomalies and positive f-values, at shallow depths (< 120 km), f asymptotic to 0, which suggests important contributions of both temperature and composition on the density structure possibly due to the presence of plume material. The negative buoyancy of the Niassa Craton contributes to its long stability, while constituting a barrier to the southward flow of

When interpreting geophysical models, we need to establish a link between the models’ physical parameters and geological units. To define these connections, it is crucial to consider and compare geophysical models with multiple, independent parameters. Particularly in complex geological scenarios, such as the rifted passive margin offshore Namibia, multi-parameter analysis and joint inversion are key techniques for comprehensive geological inferences. The models resulting from joint inversion enable the definition of specific parameter combinations, which can then be ascribed to geological units. Here we perform a user-unbiased clustering analysis of the parameters electrical resistivity and density from two models derived in a joint inversion along the Namibian passive margin. We link the resulting parameter combinations to break-up related lithology, and infer the history of margin formation. This analysis enables us to clearly differentiate two types of sediment cover. Namely, one of near-shore, thick, clastic sediments, and a second one of further offshore located, more biogenic, marine sediments. Furthermore, we clearly identify areas of interlayered massive, and weathered volcanic flows, which are usually only identified in reflection seismic studies as seaward dipping reflectors. Lastly, we find a distinct difference in the signature of the transitional crust south of- and along the supposed hot-spot track Walvis Ridge. We ascribe this contrast to an increase in magmatic activity above the volcanic centre along Walvis Ridge, and potentially a change in melt sources or depth of melting. This characterizes a rift-related southern complex, and a plume-driven Walvis Ridge regime. All of these observations demonstrate the importance of multi-parameter geophysical analysis for large-scale geological interpretations. Furthermore, our results may improve future joint inversions using direct parameter coupling, by providing a guideline for the complex passive margins

When interpreting geophysical models, we need to establish a link between the models’ physical parameters and geological units. To define these connections, it is crucial to consider and compare geophysical models with multiple, independent parameters. Particularly in complex geological scenarios, such as the rifted passive margin offshore Namibia, multi-parameter analysis and joint inversion are key techniques for comprehensive geological inferences. The models resulting from joint inversion enable the definition of specific parameter combinations, which can then be ascribed to geological units. Here we perform a user-unbiased clustering analysis of the parameters electrical resistivity and density from two models derived in a joint inversion along the Namibian passive margin. We link the resulting parameter combinations to break-up related lithology, and infer the history of margin formation. This analysis enables us to clearly differentiate two types of sediment cover. Namely, one of near-shore, thick, clastic sediments, and a second one of further offshore located, more biogenic, marine sediments. Furthermore, we clearly identify areas of interlayered massive, and weathered volcanic flows, which are usually only identified in reflection seismic studies as seaward dipping reflectors. Lastly, we find a distinct difference in the signature of the transitional crust south of- and along the supposed hot-spot track Walvis Ridge. We ascribe this contrast to an increase in magmatic activity above the volcanic centre along Walvis Ridge, and potentially a change in melt sources or depth of melting. This characterizes a rift-related southern complex, and a plume-driven Walvis Ridge regime. All of these observations demonstrate the importance of multi-parameter geophysical analysis for large-scale geological interpretations. Furthermore, our results may improve future joint inversions using direct parameter coupling, by providing a guideline for the complex passive margins

Integration of multiple geophysical data is a key practice to reduce model uncertainties and enhance geological interpretations. Electrical resistivity models resulting from inversion of marine magnetotelluric (MT) data, often lack depth resolution of lithological boundaries and distinct information for shallow model parts. This is due to the diffusive nature of electromagnetic fields, enhanced by deficient data sampling and model regularization during inversion. Thus, integrating data or models to constrain layer thicknesses or structural boundaries is an effective approach to derive better constrained and more detailed resistivity models. We investigate the different impacts of three cross-gradient coupled constraints on 3D MT inversion of data from the Namibian passive continental margin. The three constraints are a) coupling with a fixed structural density model; b) coupling with satellite gravity data; c) coupling with a fixed gradient velocity model. Here we show that coupling with a fixed model (a and c) improves the resistivity model the most. Shallow conductors imaging sediment cover are confined to a thinner layer in the resulting resistivity models compared to the MT-only model. Additionally, these constraints help to suppress vertical smearing of a conductive anomaly attributed to a fracture zone, and clearly show that the seismically imaged Moho is not accompanied by a change in electrical resistivity. All of these observations help to derive an Earth model, which will form the basis for future interpretation of the processes that lead to continental break-up during the early Cretaceous.

Combined analysis of multiple geophysical methods is a key practice to reduce model uncertainties and improve geological interpretations. Various approaches to combine several data sets or physical models in joint inversion have different advantages and challenges. We present a comparison of two ways to integrate marine magnetotelluric (MT) with gravity data along the Namibian passive continental margin and also compare them to a single-method MT inversion. This study area offers an excellent setting, because multiple tectonic processes (e.g. rifting, magmatism, post-breakup sedimentation) lead to various lithological units with distinct physical properties (e.g. continental-, transitional-, and oceanic crust, fault systems or sedimentary depocenters). The two joint inversions are a cross-gradient coupled 3D inversion of marine magnetotelluric data with a fixed structural density model based on gravity modeling, and a joint inversion of the same MT data with satellite gravity data. Structural coupling with the blocky density model enforces harsh resistivity changes in an otherwise smooth model and helps reducing excessively smeared inversion artifacts. Although the edge-like features complicate direct model interpretation, they indicate alternative ways to fit the MT data, while simultaneously matching seismic observations integrated in the density cross-model. For the second approach, the large solution space of the satellite gravity data inversion limits the improvements through joint inversion compared to a single method MT inversion. The resulting joint inversion resistivity model differs only marginally from the single-method resistivity model, while the joint density model inherits some of the rather questionable resistivity model features. Our study demonstrates how joint inversion of multiple data aids model interpretation. The resulting resistivity models provide equally well-fitting alternatives to single-method evaluation, and additionally fit other geoph

Geophysical inversion always faces the problem of ambiguity, where several earth models can describe the same data. To tackle this issue, additional information can be integrated by joint inversion of different data sets (Heincke et al., 2017; Moorkamp, 2017; Moorkamp et al., 2011), or by cooperative inversion through relating physical models derived from independent data (Bedrosian, 2007; Gallardo, 2004; Haber & Oldenburg, 1997; Lines et al., 1987; Paasche & Tronicke, 2007).Here we present our recent results of joint- and cooperative inversions along the Namibian passive continental margin and Walvis Ridge investigating break-up related magmatism. Jegen et al. (2016), presents a resistivity model derived from Magnetotelluric data acquired in 2011 (SAMPLE project). We reevaluate this data due to a previous rotation error, and implement three additional set ups, wherea)MT data inversion is constrained by a geological model derived from gravity modeling (Maystrenko et al., 2013)b)marine MT- and satellite gravity data are jointly inverted with a common objective functionc)a 2D velocity model (Fromm et al., 2017) is used as a structural constraint in 3D MT inversion