The Federal Institute for Geosciences and Natural Resources (Bundesanstalt für Geowissenschaften und Rohstoffe or BGR) is a German agency within the Federal Ministry of Economics and Technology. It acts as a central geoscience consulting institution for the German federal government. The headquarters of the agency is located in Hanover and there is a branch in Berlin. Early 2013, the BGR employed a total of 795 employees. The BGR, the State Authority for Mining, Energy and Geology and the Leibniz Institute for Applied Geophysics form the Geozentrum Hanover. All three institutions have a common management and infrastructure, and complement each other through their interdisciplinary expertise.Headquarters in Hannover.
Recent advances in artificial intelligence (AI), in particular foundation models, have improved the state of the art in many application domains including geosciences. Some specific problems, however, could not benefit from this progress yet. Soil horizon classification, for instance, remains challenging because of its multimodal and multitask characteristics and a complex hierarchically structured label taxonomy. Accurate classification of soil horizons is crucial for monitoring soil condition, which directly impacts agricultural productivity, food security, ecosystem stability and climate resilience. In this work, we propose SoilNet - a multimodal multitask model to tackle this problem through a structured modularized pipeline. In contrast to omnipurpose AI foundation models, our approach is designed to be inherently transparent by following the task structure human experts developed for solving this challenging annotation task. The proposed approach integrates image data and geotemporal metadata to first predict depth markers, segmenting the soil profile into horizon candidates. Each segment is characterized by a set of horizon-specific morphological features. Finally, horizon labels are predicted based on the multimodal concatenated feature vector, leveraging a graph-based label representation to account for the complex hierarchical relationships among soil horizons. Our method is designed to address complex hierarchical classification, where the number of possible labels is very large, imbalanced and non-trivially structured. We demonstrate the effectiveness of our approach on a real-world soil profile dataset and a comprehensive user study with domain experts. Our empirical evaluations demonstrate that SoilNet reliably predicts soil horizons that are plausible and accurate. User study results indicate that SoilNet achieves predictive performance on par with or better than that of human experts in soil horizon classification. All code and experiments can be found in our repository: https://github.com/calgo-lab/BGR/.
Chromite ore processing residue (COPR) has caused large-scale Cr(VI) contamination of soil and groundwater worldwide. In Kanpur, India, vast quantities are generated during the production of Cr-based leather tanning salts and often deposited on open landfills. We previously hypothesized that under such conditions COPR naturally sequester CO2, which might promote additional Cr(VI) release. Here, we tested this in accelerated carbonation experiments on fresh and aged COPR. After quantifying the CO2 uptakes, native and carbonated COPR were tested for Cr(VI) mobility by aqueous batch leaching. To unravel the effects of CO2 uptake on COPR, we further conducted pH-adjusted and Na2CO3-spiked leaching. Mineralogical changes were assessed by thermogravimetry-mass spectrometry (TG-MS). Unlike the aged, hence naturally carbonated COPR, the fresh COPR showed high CO2 uptakes of up to 5.6 wt.-%, causing a pH drop and increasing Cr(VI) leachability by up to 450 mg & sdot; L- 1. '32- had a much stronger effect on Cr(VI) release than pH drop. TG-MS indicated that upon carbonation, calcite and hydrotalcite precipitated by consuming hydrocalumite and katoite, thus liberating their hosted Cr(VI) and shifting the mineralogy of the fresh COPR towards the aged material. Ongoing carbonation likely exacerbates groundwater pollution at COPR dumpsites, precluding natural attenuation.
Abstract Understanding the coastal zone of the Antarctic Ice Sheet (AIS), where it interacts with the Southern Ocean and warmer air masses, is crucial for predicting Antarctica's influence on the global climate and sea level. This region has multiple tipping mechanisms that could trigger large, rapid, and potentially irreversible changes in the AIS, the Southern Ocean and their global connections in the coming centuries. The AIS remains the largest source of uncertainty in future sea‐level projections. Bed topography beneath the ice shelves and the coastal ice sheet is not yet well documented, and is a major source of this uncertainty. This review assesses current knowledge of the coastal zone and highlights methods to investigate it, including aerogeophysical surveys, ground‐ and ship‐based measurements, satellite observations, and computer modeling. An ensemble analysis of published bed topography data sets identifies significant data gaps and their regional distribution, framed in the context of current ice‐sheet behavior and potential instability. We propose scientific priorities and guidelines for future aerogeophysical surveys, advocating for a comprehensive, coordinated international effort to build a next‐generation data set of Antarctic bed properties. Such an initiative would significantly advance understanding of the role of coastal processes in ice‐sheet dynamics, reducing uncertainties in sea‐level rise projections and improving predictions of future ocean and climate changes.
The Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), has conducted airborne radar campaigns since 1994 across Antarctica and Greenland, utilizing six different radar systems to study ice sheets and their interactions with climate, ocean and the solid Earth. Over the past three decades, AWI has collected more than one million profile-kilometres of radar data, covering approximately one quarter of the Antarctic and the Greenland Ice Sheet, respectively. In this review article, we describe AWI's airborne radar systems and their deployments over the Greenland and Antarctic Ice Sheet. Moreover, we summarize application and usage of AWI's radar systems, which provided crucial insights into e.g., ice dynamics, mass balance, and ancient landscapes buried beneath the ice. The integration of radar data with other geophysical methods has enhanced bathymetric models, improving predictions of ice–ocean interactions and ice-shelf stability and contributed to a better understanding of crustal and geological evolution of the Antarctic continent. As part of this paper, and to support scientific progress, AWI made its airborne radar data publicly accessible through the Radar Data over Polar Ice Sheets viewer hosted by the Marine Data Portal (https://marine-data.de/viewers/, last access: 19 April 2026) and PANGAEA (https://doi.org/10.1594/PANGAEA.972094; Eisen et al., 2024), ensuring compliance with FAIR (Findable, Accessible, Interoperable, Reusable) data principles. Future research will expand on these contributions, focusing on refining ice-sheet models and exploring new areas of glaciological and geological interest.
