Geodetic Evidence for a Buoyant Mantle Plume Beneath the Eifel Volcanic Area, NW Europe

Abstract

The volcanism of the Eifel volcanic field (EVF), in west-central Germany, is often considered an example of hotspot volcanism given its geochemical signature and the putative mantle plume imaged underneath. EVF’s setting in a stable continental area provides a rare natural laboratory to image surface deformation and test the hypothesis of there being a thermally buoyant plume. Here we use Global Positioning System (GPS) data to robustly image vertical land motion (VLM) and horizontal strain rates over most of intraplate Europe. We find a spatially-coherent positive VLM anomaly over an area much larger than the EVF and with a maximum uplift of ~1 mm yr−1 at the EVF (when corrected for glacial isostatic adjustment). This rate is considerably higher than averaged over the Late-Quaternary. Over the same area that uplifts, we find significant horizontal extension surrounded by a radial pattern of shortening, a superposition that strongly suggests a common dynamic cause. Besides the Eifel, no other area in NW Europe shows significant positive VLM coupled with extensional strain rates, except for the much broader region of glacial isostatic adjustment. We refer to this 3D deformation anomaly as the Eifel Anomaly. We also find an extensional strain rate anomaly near the Massif Central volcanic field surrounded by radial shortening, but we do not detect a significant positive VLM signal there. The fact that the Eifel Anomaly is located above the Eifel plume suggests the plume causes the anomaly. Indeed, we show that buoyancy forces induced by the plume at the bottom of the lithosphere can explain this remarkable surface deformation. Plume-induced deformation can also explain the relatively high rate of regional seismicity, particularly along the Lower Rhine Embayment.

Lithospheric Sill Intrusions and Present‐Day Ground Deformation at Rhenish Massif, Central Europe

“…The retrieved opening rate spatial distribution is mostly consistent across the three data sets reaching highest values (∼0.8-1.3 mm/yr) at the center of RHM. In particular, for GPS-sites and gridded-std1 cases the highest opening rate is mostly concentrated slightly to the north-west of the Quaternary EVF activity location (Figures 2a.1 and 2b.1) and produces a horizontal velocity pattern mostly compatible with the area of significant dilatation rate (Kreemer et al, 2020) (Figures 2a.2 and 2b.2). In the gridded-std2 case, instead, the highest opening rate coincides with the Quaternary EVF activity location, where the highest uplift is observed (Figure 2c.1).…”

“…Thus, magma emplacement becomes localized, inducing, or contributing to, lithosphere deformation (Figure 1b). Melt accumulation in the litosphere might be needed in the buoyant-body model by Kreemer et al (2020), since it does not entirely reproduce the shape of the highest uplift area and it implies a buoyancy force distribution over a 150-180 km radius area, much larger than the imaged ∼60 km diameter plume stem below RHM (Ritter, 2007;Ritter et al, 2001).…”

“…Since GIA was not previously removed from the provided vertical velocities at GPS sites, we derived the GIA correction from the difference between the provided corrected and non-corrected gridded velocities and removed it from the vertical GPS velocities (Figure S1 in Supporting Information S1). The vertical data show a spatially coherent uplift area over the Rhenish Massif region with highest values (∼1-3 mm/yr) at EVF (Figures 1d and 1f), while subsidence is probably related to noise and/or residual trends at continental scale (Kreemer et al, 2020).…”

“…In general, the horizontal velocities are lower than the vertical ones (∼0.33 mm/yr of maximum horizontal separation rate across the uplift anomaly) and show a less clear pattern (Figure 1c). However, they reveal an extension region slightly offset north-west from the highest uplift area (Kreemer et al, 2020) (gray line in Figure 1; Figure S2 in Supporting Information S1).…”

“…We discuss the feasibility, limitations and possible interpretations of the resulting models. Kreemer et al (2020) computed velocities from position time-series between January 2000 and October 2019, both at available GPS sites and as gridded values (at 0.1° steps, i.e., ∼10 km) obtained after data post-processing. This involves steps of despeckling velocities computed at GPS sites (i.e., leveling out velocity values against outliers) and subsequent gridding.…”