Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ
Recent publications
The modern, over 250-m-deep basin of Lake Constance represents the underfilled northern part of an over 400-m-deep, glacially overdeepened trough, which reaches well into the Alps at its southern end. The overdeepening was formed by repeated glacial advance-retreat cycles of the Rhine Glacier throughout the Middle to Late Pleistocene. A seismic survey of Lake Constance revealed a Quaternary sediment fill of more than 150 m thickness representing at least the last glacial cycle. The stratified sedimentary fill consists at the base of ice-contact deposits on top of the molasse bedrock, overlain by glaciolacustrine to lacustrine sediments. During the successful field test of a newly developed, mid-size coring system ("HIPERCORIG"), the longest core (HIBO19) ever taken in Lake Constance was retrieved with an overall length of 24 m. The sediments recovered consist of a nearly continuous succession of lacustrine silts and sands including more than 12 m of Late Glacial sediment at the base. 14 lithotypes were identified through petrophysical and geochemical analyses. In combination with a ¹⁴ C- and OSL-based age-depth model, the core was divided into three main chronostratigraphic units. The basal age of ~ 13.7 ka BP dates the base of the succession back to the Bølling-Allerød interstadial, with overlying strata representing a complete and thick Younger-Dryas to Holocene succession. The sediments offer a high-resolution insight into the evolution of paleo-Lake Constance from a cold, postglacial to a more productive and warmer Holocene lake. The Late Glacial succession is dominated by massive, m-thick sand beds reflecting episodic sedimentation pulses. They are most likely linked to a subaquatic channel system originating in the river Seefelder Aach, which is, despite the Holocene drape, still apparent in today’s lake bathymetry. The overlying Holocene succession reveals a prominent, several cm-thick, double-turbiditic event layer representing the most distal impact of the Flimser Bergsturz, the largest known rockslide of the Alps that occurred over 100 km upstream the river Rhine at ~ 9.5 ka BP. Furthermore, lithologic variations in the Holocene succession document the varying sediment loads of the river Rhine and the endogenic production representing a multitude of environmental changes.
Real-Time Kinematic Precise Point Positioning (PPP–RTK) is inextricably linked to external ionospheric information. The PPP–RTK performances vary much with the accuracy of ionospheric information, which is derived from different network scales, given different prior variances, and obtained under different disturbed ionospheric conditions. This study investigates the relationships between the PPP–RTK performances, in terms of precision and convergence time, and the accuracy of external ionospheric information. The statistical results show that The Time to First Fix (TTFF) for the PPP–RTK constrained by Global Ionosphere Map (PPP–RTK-GIM) is about 8–10 min, improved by 20%–50% as compared with that for PPP Ambiguity Resolution (PPP-AR) whose TTFF is about 13–16 min. Additionally, the TTFF of PPP–RTK is 4.4 min, 5.2 min, and 6.8 min, respectively, when constrained by the external ionospheric information derived from different network scales, e.g. small-, medium-, and large-scale networks, respectively. To analyze the influences of the optimal prior variances of external ionospheric delay on the PPP–RTK results, the errors of 0.5 Total Electron Content Unit (TECU), 1 TECU, 3 TECU, and 5 TECU are added to the initial ionospheric delays, respectively. The corresponding convergence time of PPP–RTK is less than 1 min, about 3, 5, and 6 min, respectively. After adding the errors, the ionospheric information with a small variance leads to a long convergence time and that with a larger variance leads to the same convergence time as that of PPP-AR. Only when an optimal prior variance is determined for the ionospheric delay in PPP–RTK model, the convergence time for PPP–RTK can be shorten greatly. The impact of Travelling Ionospheric Disturbance (TID) on the PPP–RTK performances is further studied with simulation. It is found that the TIDs increase the errors of ionospheric corrections, thus affecting the convergence time, positioning accuracy, and reliability of PPP–RTK.
Current methods for estimating ion density on Swarm rely on the assumption of 100% O + and no along-track ion velocity flows. These assumptions are routinely violated, particularly on the nightside and during high-latitude and polar cap traversals, compromising the accuracy of the measurements. The use of faceplate current data along with the Langmuir probe ion admittance measurements, and orbital-motion limited (OML) theory, make it possible to relax some of the assumptions inherent in current ESA Swarm density estimates. This further yields along-track ion drift and effective ion mass estimates. This paper describes the theoretical basis for estimating revised ion density, providing a new estimate for effective ion mass, as well as an alternative way of estimating along-track ion drift. The complete Swarm historical data set has been generated and validated using empirical models (International Reference Ionosphere, and an empirical electric field model), as well as ground-spacecraft conjunctions. Case studies and statistical results reveal clear geophysical signatures in the new product of light ions at low- and mid-latitudes and along-track ion drift at high latitudes, and their response to space weather. Graphical Abstract
In recent years, there has been a substantial increase in the induced seismicity associated with geothermal systems. However, understanding and modeling of injection-induced seismicity have still remained as a challenge. This paper presents a two-dimensional fully thermo-hydro-mechanical (THM) coupled boundary element approach to characterize the fault response to forced fluid injection and assess the effect of different injection protocols on seismic risk mitigation as well as permeability enhancement. The laboratory-derived rate-and-state friction law was used to capture the frictional paradigm observed in mature faults produced in granite rocks. All phases of stick-slip cycles, including aseismic slip, propagation of dynamic rupture, and interseismic periods, were simulated. The modeling results showed that the residual values of effective normal stress and static shear stress after a particular event completely dominate the constitutive behavior of fault friction during the next seismic event. The seismic energy analyses indicated that there is a negative correlation between the seismic magnitude and the total injected volume, such that a prolonged monotonic injection eventually results in the steady slip, rather than the seismic slip. Several fluid injection protocols were designed based on a volume-controlled (VC) approach and traffic light systems (TLS) to explore their effectiveness on the seismic risk mitigation and permeability enhancement. The results showed that cyclic injection based on TLS is the most effective approach for irreversible permeability enhancement of faults through promoting slow and steady slips. Our numerical simulations also revealed that fluid extraction (backflow-fixing bottom hole pressure at atmospheric pressure), regardless of the injection style, can considerably reduce the seismicity-related risks by preventing the fast-accelerated fracture slip during the post-injection stage. This study presents novel insights into modeling the rate-and-state governed faults exposed to forced fluid injection, and provides useful approaches for shear stimulation of faults with reduced seismic risks.
This study uses an integrated approach to characterize the dynamic evolution of the power-producing high-enthalpy geothermal system of Lahendong, North-Sulawesi, Indonesia. Lahendong has two primary reservoirs, the southern and the northern, which have been utilised for electricity production for more than twenty years. The main focus of this study is the characterisation of heat and mass flows in the system with respect to geological structures and permeability distribution. Also, it delineates how the geothermal system has evolved and the spatial variation of the response resulting from prolonged utilization of the reservoirs. This research implemented geological structure analysis on recent surface fault mapping and pre-existing fault studies from literature. Further, the study analysed well data comprising well pressure, enthalpy, drilling program reviews and tracer tests. Hydrochemical investigation compiled new and old surface and subsurface hydrochemical evolution in both the temporal and spatial domain. The results confirm several fault trends in the study area: NE-SW and NW-SE are the major striking directions, while E-W and N-S are less dominant. The most apparent trends are NE-SW striking strike-slip faults, NW-SE thrust faults and N-S and E-W striking normal faults. The faults compartmentalize the reservoir. A comparison of the southern and the northern reservoir shows that the southern one is more controlled by faults; both reservoirs rely on fractures as permeability provider and are controlled by shallow hydrogeology, as derived from the integrated analysis of transient well data. Geochemical analysis shows that the reservoir fluids have generally a higher eelectrical conductivity and are closer to fluid-rock equilibrium, probably due to boiling, compared to spring waters. Spring waters have generally become more acidic, which is an expected result of reservoir boiling and increased steam input to near-surface waters. The spatial distribution of changes shows a permeability evolution over time and also the role of structural permeability in response to changing reservoir conditions. Observing and recording reservoir data is highly important to understand the reservoir response to production and ensure the long-term sustainability of the system. Additionally, the data is critical for making a major difference in the reservoir management strategy.
Calibration and validation of aboveground biomass (AGB) (AGB) products retrieved from satellite-borne sensors require accurate AGB estimates across hectare scales (1 to 100 ha). Recent studies recommend making use of non-destructive terrestrial laser scanning (TLS) based techniques for individual tree AGB estimation that provide unbiased AGB predictors. However, applying these techniques across large sites and landscapes remains logistically challenging. Unoccupied aerial vehicle laser scanning (UAV-LS) has the potential to address this through the collection of high density point clouds across many hectares, but estimation of individual tree AGB based on these data has been challenging so far, especially in dense tropical canopies. In this study, we investigated how TLS and UAV-LS can be used for this purpose by testing different modelling strategies with data availability and modelling framework requirements. The study included data from four forested sites across three biomes: temperate, wet tropical, and tropical savanna. At each site, coincident TLS and UAV-LS campaigns were conducted. Diameter at breast height (DBH) and tree height were estimated from TLS point clouds. Individual tree AGB was estimated for ≥170 trees per site based on TLS tree point clouds and quantitative structure modelling (QSM), and treated as the best available, non-destructive estimate of AGB in the absence of direct, destructive measurements. Individual trees were automatically segmented from the UAV-LS point clouds using a shortest-path algorithm on the full 3D point cloud. Predictions were evaluated in terms of individual tree root mean square error (RMSE) and population bias, the latter being the absolute difference between total tree sample population TLS QSM estimated AGB and predicted AGB. The application of global allometric scaling models (ASM) at local scale and across data modalities, i.e., field-inventory and light detection and ranging LiDAR metrics, resulted in individual tree prediction errors in the range of reported studies, but relatively high population bias. The use of adjustment factors should be considered to translate between data modalities. When calibrating local models, DBH was confirmed as a strong predictor of AGB, and useful when scaling AGB estimates with field inventories. The combination of UAV-LS derived tree metrics with non-parametric modelling generally produced high individual tree RMSE, but very low population bias of ≤5% across sites starting from 55 training samples. UAV-LS has the potential to scale AGB estimates across hectares with reduced fieldwork time. Overall, this study contributes to the exploitation of TLS and UAV-LS for hectare scale, non-destructive AGB estimation relevant for the calibration and validation of space-borne missions targeting AGB estimation.
Antimony (Sb)-rich geothermal deposits have been observed in many geothermal power plants worldwide. They occur as red-colored, sulfidic precipitates disturbing energy-harvesting by clogging the geothermal installations. In order to prevent the formation of this scale, information on its physicochemical features is needed. For this purpose, Sb-rich sulfide-based deposits were synthesized at controlled conditions in a pressurized glass reactor at geothermal conditions (135 °C and 3.5 bar). Various polymeric antiscalants with different functional groups, such as acrylic acid, sulphonic acid, and phosphonic acid groups were tested for their effect on Sb sulfide solubility. An additional computational study was performed to determine the binding energy of Sb and S atoms to these groups. The results suggest that sulfonic acid groups are the most affective. Therefore, it was concluded that these macromolecule containing sulfonic acid groups and poly (vinyl sulfonic acid) derivatives could potentially act as antiscalants for the formation of antimony sulfide.
Freshwater microbes play a crucial role in the global carbon cycle. Anthropogenic stressors that lead to changes in these microbial communities are likely to have profound consequences for freshwater ecosystems. Using field data from the coordinated sampling of 617 lakes, ponds, rivers, and streams by citizen scientists, we observed linkages between microbial community composition, light and chemical pollution, and greenhouse gas concentration. All sampled water bodies were net emitters of CO2, with higher concentrations in running waters, and increasing concentrations at higher latitudes. Light pollution occurred at 75% of sites, was higher in urban areas and along rivers, and had a measurable effect on the microbial alpha diversity. Genetic elements suggestive of chemical stress and antimicrobial resistances (IntI1, blaOX58) were found in 85% of sites, and were also more prevalent in urban streams and rivers. Light pollution and CO2 were significantly related to microbial community composition, with CO2 inversely related to microbial phototrophy. Results of synchronous nationwide sampling indicate that pollution-driven alterations to the freshwater microbiome lead to changes in CO2 production in natural waters and highlight the vulnerability of running waters to anthropogenic stressors.
Flooding is the most costly natural hazard in Europe. Climatic and socioeconomic change are expected to further increase the amount of loss in the future. To counteract this development, policymaking, and adaptation planning need reliable large-scale risk assessments and an improved understanding of potential risk drivers. In this study, recent datasets for hazard and flood protection standards are combined with high resolution exposure projections and attributes of vulnerability derived from open data sources. The independent and combined influence of exposure change and climate scenarios rcp45 and rcp85 on fluvial flood risk are evaluated for three future periods centered around 2025, 2055 and 2085. Scenarios with improved and neglected private precaution are examined for their influence on flood risk using a probabilistic, multivariable flood loss model — BN-FLEMOps — to estimate fluvial flood losses for residential buildings in Europe. The results on NUTS-3 level reveal that urban centers and their surrounding regions are the hotspots of flood risk in Europe. Flood risk is projected to increase in the British Isles and Central Europe throughout the 21st century, while risk in many regions of Scandinavia and the Mediterranean will stagnate or decline. Under the combined effects of exposure change and climate scenarios rcp45, rcp85, fluvial flood risk in Europe is estimated to increase seven-fold and ten-fold respectively until the end of the century. Our results confirm the dominance of socioeconomic change over climate change on increasing risk. Improved private precautionary measures would reduce flood risk in Europe on an average by 15%. The quantification of future flood risk in Europe by integrating climate, socioeconomic and private precaution scenarios provides an overview of risk drivers, trends, and hotspots. This large-scale comprehensive assessment at a regional level resolution is valuable for multi-scale risk-based adaptation planning.
Previous studies have revealed that hydraulic fracturing behavior in crystalline rock (e.g., granite) is highly dependent on mineral content, grain size, and heterogeneity and is therefore quite different from the behavior observed in sedimentary rock (e.g., sandstone). We investigated hydraulic fracture paths generated via cyclic and monotonic injection in Pocheon granite, Gonghe granite, and gray sandstone. The gray sandstone has a porosity of 9.0% and its anisotropy was not considered in this study. The effect of cyclic injection on the reduction of hydraulic fracturing breakdown pressure was more significant in the two granites compared with that in the sandstone. Computed tomography images were obtained on fractured specimens for a quantitative evaluation of hydraulic fractures that included fracture length, fracture aperture, and tortuosity. Minerals along hydraulic fractures in the two granites were identified via an analysis of thin section collages from microscopic observations. We analyzed the role of different minerals (i.e., quartz and biotite) and pre-existing defects – such as microcracks and natural fractures – in controlling hydraulic fracture propagation in monotonic and cyclic injections.
The recently observed slow transients in the Sea of Marmara are important to quantify the seismic hazard and risk for the greater Istanbul metropolitan region. In this study, we analyze and characterize a slow slip event that occurred in the Eastern Sea of Marmara in 2016. To characterize the temporal history and the location of this event, we combine for the first time in this region different types of geodetic data (strainmeters and GNSS stations) and seismicity. We propose two interpretations to explain the observations: either the slow event initiated on the western part of the Armutlu fault and then propagated approximately 40 km eastward, or it initiated on the western section of the Armutlu fault, and then jumped onto a perpendicular fault after propagating ca. 15 km. We deduce these interpretations from forward modeling of the strain and displacement data. In addition, our results also suggest that this slow event triggered seismicity on a neighboring perpendicular fault.
We investigate whether the distribution of maximum seasonal streamflow is significantly affected by catchment or climate state of the season/month ahead. We fit the Generalized Extreme Value (GEV) distribution to extreme seasonal streamflow for around 600 stations across Europe by conditioning the GEV location and scale parameters on 14 indices, which represent the season-ahead climate or catchment state. The comparison of these climate-informed models with the classical GEV distribution, with time-constant parameters, suggests that there is a substantial potential for seasonal forecasting of flood probabilities. The potential varies between seasons and regions. Overall, the season-ahead catchment wetness shows the highest potential, although climate indices based on large-scale atmospheric circulation, sea surface temperature or sea ice concentration also show some skill for certain regions and seasons. Spatially coherent patterns and a substantial fraction of climate-informed models are promising signs towards early alerts to increase flood preparedness already a season ahead.
Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing³. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change³.
If life exists on Mars, it would face several challenges including the presence of perchlorates, which destabilize biomacromolecules by inducing chaotropic stress. However, little is known about perchlorate toxicity for microorganism on the cellular level. Here we present the first proteomic investigation on the perchlorate‐specific stress responses of the halotolerant yeast Debaryomyces hansenii and compare these to generally known salt stress adaptations. We found that the responses to NaCl and NaClO4‐induced stresses share many common metabolic features, e.g., signaling pathways, elevated energy metabolism, or osmolyte biosynthesis. Nevertheless, several new perchlorate‐specific stress responses could be identified, such as protein glycosylation and cell wall remodulations, presumably in order to stabilize protein structures and the cell envelope. These stress responses would also be relevant for life on Mars, which ‐ given the environmental conditions ‐ likely developed chaotropic defense strategies such as stabilized confirmations of biomacromolecules and the formation of cell clusters. This article is protected by copyright. All rights reserved.
Purpose Soil erosion by water yields sediment to surface reservoirs, reducing their storage capacities, changing their geometry, and degrading water quality. Sediment reuse, i.e., fertilization of agricultural soils with the nutrient-enriched sediment from reservoirs, has been proposed as a recovery strategy. However, the sediment needs to meet certain criteria. In this study, we characterize sediments from the densely dammed semiarid Northeast Brazil by VNIR-SWIR spectroscopy and assess the effect of spectral resolution and spatial scale on the accuracy of N, P, K, C, electrical conductivity, and clay prediction models. Methods Sediment was collected in 10 empty reservoirs, and physical and chemical laboratory analyses as well as spectral measurements were performed. The spectra, initially measured at 1 nm spectral resolution, were resampled to 5 and 10 nm, and samples were analysed for both high and low spectral resolution at three spatial scales, namely (1) reservoir, (2) catchment, and (3) regional scale. Results Partial least square regressions performed from good to very good in the prediction of clay and electrical conductivity from reservoir (< 40 km ² ) to regional (82,500 km ² ) scales. Models for C and N performed satisfactorily at the reservoir scale, but degraded to unsatisfactory at the other scales. Models for P and K were more unstable and performed from unsatisfactorily to satisfactorily at all scales. Coarsening spectral resolution by up to 10 nm only slightly degrades the models’ performance, indicating the potential of characterizing sediment from spectral data captured at lower resolutions, such as by hyperspectral satellite sensors. Conclusion By reducing the costly and time-consuming laboratory analyses, the method helps to promote the sediment reuse as a practice of soil and water conservation.
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656 members
Cécile Lara Blanchet
  • Section paleoclimate and landscape evolution
Mathias Bochow
  • Division of Remote Sensing
Marco De Lucia
  • Fluid Systems Modeling
Luca C Malatesta
  • Division of Earth Surface Process Modelling
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