ALBERT

Description: Main aim of the project was to investigate the local seismicity (distribution and kinematics) within and around the Fergana basin and the Southern Tien Shan in Southern Kyrgistan. In order to achieve this goal a temporary local network was installed between 2009 and 2010. The results derived from this project contributed to decipher the relationship between geodynamics, neotectonic block structures and the occurrence of landslides in this region.

Description: This data publication provides a European assessment of building exposure, organized country-by-country. The dataset provides information about the number of buildings; the number of occupants; structural information and structural costs of buildings per geographical area. The main purpose of this data collection is risk assessment for natural hazards, however it can be used by anyone in need of a building exposure dataset. The data holds information about single buildings, with global estimates of built-up area on 10m x 10m pixels and exposure information per district. All OpenStreetMap (OSM) buildings existing in an OSM excerpt from 1 July 2023, 00:00 UTC (OpenStreetMap contributors, 2023), all buildings from the Global ML Building Footprint (GMLBF, Microsoft, 2023) dataset have been processed and for each building the occupancy type and number of stories have been identified based on data in OSM, such as land use and points of interest. The Global Human Settlement Built-up Characteristics 2022A Layer has been used as initial distribution of built area (Pesaresi, 2022). Aggregated exposure information, including the structural information and the number of occupants, stems the ESRM20 (Crowley et al., 2020). The resulting dataset is distributed per country as an SQLite/SpatiaLite database. Each database contains three tables and one view. The database is organized around three key concepts, that each have their own table. An Entity is a geographical unit that contains exposure. In this dataset, the entities are tiles in a multi-resolution grid, according to the Quad tree structure (Finkel & Bentley, 1974), with the tiles projected using the Web Mercator projection (EPSG:3857). The zoom-level of the Quadkeys inside the grid varies from level-15 to level-18, depending on the number of buildings inside each tile to preserve privacy-sensitive information. Practically, the size of the tiles varies between around 100m x 100m and 1km x 1km. Each entity consists of one or more Assets, defining the number of buildings of a particular structural type and their population and structural value. The structural type is described using a taxonomy string, describing for example structural properties, occupancy type and the expected number of stories. The exact definition of a taxonomy that is used in this dataset is described in the GEM Building Taxonomy v2.0 (Brzev et al., 2013). On top of the tables, one key view has been defined too. A view is essentially a query on the table that give some insights into the data. The `key_values_per_tile` provides the total number of buildings, total number of occupants at night and total structural costs summed over all assets in one tile entity.

Description: The dataset presents the greenhouse gas production (CO2 and CH4) from sediment of a terrestrial permafrost outcrop (Byk14-A-1; 71.85175°N, 129.350883°E), the thermokarst lake Goltsovoye (PG2412 (TKL), 71.74515°N, 129.30217°E), the nearly-closed Polar Fox Lagoon (PG2411 (LAG1), 71.743056°N, 129.337778°E) and the semi-open Uomullyakh Lagoon (PG2410-1 (LAG1), 71.730833°N, 129.2725°E). We incubated the samples anaerobically at 4 °C under fresh (c=0 g/L), brackish (c=13g/L) and marine (36g/L) conditions for one year and measured carbon dioxide (CO2) and methane (CH4) concentrations regularly in a 250 µL subsample using gas chromatography with an Agilent GC 7890A equipped with an Agilent HP-PLOT Q column. Cumulative CO2 and CH4 concentrations and production rates per day are given over time for all samples with three replicates each per gram of dry weight and normalised to gram of soil organic carbon (SOC).

Description: Groundwater contamination of the fractured aquifers by agricultural pollutants has been happening worldwide since more than a century, boosting the scientific research to develop new modelling approaches for reactive transport simulation in aquifers. Spatially implicit methods like travel time approaches have been gaining interest, attracting by their lower computational demand and flexibility. At the same time, detailed mechanistic models of reactive transport in the fractured systems allow percipient understanding of underlying geochemical processes and provide veritable quantification of the latter. In this work, we connect a spatially explicit model of denitrification and isotope transport, and analytical solutions of atrazine transport in the fractured system, with a spatially implicit travel time approach. The work aims to study reactive behaviour of agriculturally produced contaminants on the catchment scale and quantify the fractured system parameters of the Muschelkalk aquifer. Reactive transport modelling was employed for this purpose with MIN3P and analytical solutions for a single fracture. Reactive transport models included advective flow in the fracture as well as possible (multicomponent) diffusive exchange with the rock matrix and redox processes taking place along the flow path. Determination of the travel times and transport parameters is done by direct modelling of tritium, helium, radiogenic helium, and argon-39 isotopes and accounting for multicomponent diffusion and radioactive decay within the streamline. Stochastic simulations of the atrazine transport under parametric uncertainty were employed for predictive quantification of travel time-dependent groundwater vulnerability. Conceptual model selection of denitrification and investigation of the redox evolution on the catchment scale was done with the MIN3P code. Results were verified with observations made across the Ammer catchment. The gained knowledge highlights the significance of comprehensive process-based hydrogeochemical modelling along with an uncertainty assessment on the catchment scale. It also demonstrates the relevance of reactive transport modelling for correct calibration as a prerequisite for prediction of the long-term evolution and transport of solutes in groundwater.

Description: This data publication provides the results of the investigations and measurements of thermal rock properties conducted on site in the Tournemire field laboratory and at the Thermal Petrophysics Lab at GFZ. The thermal characterization of the clayey Jurassic (Upper Toarcian, ca. 180 My old) is contributing to the site characterization of the Tournemire Underground Research Lab (URL), located in Southern France. This URL is installed in a former railway tun-nel to better understand the physical processes resulting from thermal and hydrau-lic loading in a small fault zone in a highly consolidated shale formation (Bonnelye et al., 2023). At the Tournemire site, faults and fractures of different sizes extend from the surface (sedimentary cover) to the crystalline basement. At one specific gallery (Gallery East 03) installed in the former tunnel, thermally controlled in-situ fluid injection experiments are scheduled on a strike-slip fault zone outcropping at the URL (Bonnelye et al., 2023). In 2022, we visited the URL for baseline characteri-zation of thermal properties and to study the heterogeneity of the clay-dominated formation. Therefore, we took the chance to collect data and samples for a laborato-ry measurement campaign and to measure thermal conductivity in-situ in the tun-nel wall of Gallery East 03. The thermal data shall provide the baseline for the pa-rameterization of future numerical 3D models to better understand the thermal-hydraulic processes related to the experiment. This data publication provides the results of the investigations and measurements conducted on-site in the field la-boratory and at the Thermal Petrophysics Lab at GFZ.

Description: The open source Video In Situ Snowfall Sensor (VISSS) is a novel instrument for the characterization of particle shape and size in snowfall. The VISSS consists of two cameras with LED backlights and telecentric lenses that allow accurate sizing and combine a large observation volume with relatively high resolution and a design that limits wind disturbance. Here, movies and images of falling precipitation particles are provided for station Ny-Ålesund from July 2022 to December 2023. For further details on the VISSS Sensor see Maahn et al. (2024).