Institut für Geowissenschaften
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Ground motion with strong-velocity pulses can cause significant damage to buildings and structures at certain periods; hence, knowing the period and velocity amplitude of such pulses is critical for earthquake structural engineering.
However, the physical factors relating the scaling of pulse periods with magnitude are poorly understood.
In this study, we investigate moderate but damaging earthquakes (M-w 6-7) and characterize ground- motion pulses using the method of Shahi and Baker (2014) while considering the potential static-offset effects.
We confirm that the within-event variability of the pulses is large. The identified pulses in this study are mostly from strike-slip-like earthquakes. We further perform simulations using the freq uency-wavenumber algorithm to investigate the causes of the variability of the pulse periods within and between events for moderate strike-slip earthquakes.
We test the effect of fault dips, and the impact of the asperity locations and sizes. The simulations reveal that the asperity properties have a high impact on the pulse periods and amplitudes at nearby stations.
Our results emphasize the importance of asperity characteristics, in addition to earthquake magnitudes for the occurrence and properties of pulses produced by the forward directivity effect.
We finally quantify and discuss within- and between-event variabilities of pulse properties at short distances.
Wetlands are dynamic ecosystems that require continuous monitoring and assessment of degradation status to design strategies for their sustainable management. While hydrology provides the primary functional control for the wetland ecosystem, the loss of landscape connectivity influences wetland degradation in a major way as it leads to fragmentation. This article aims to integrate hydrogeomorphic and ecological concepts for the assessment of degradation status and its causal factors for a large wetland in the western Ganga plains, India, the Haiderpur, using a wetlandscape approach. We have used a remote-sensing-based approach, which offers a powerful tool for assessing and linking cross-scale structures, functions, and controls in a wetlandscape. The Haiderpur, a Ramsar site since December 2021, is an artificial wetland located on the right bank of the Ganga River wherein the inflows are controlled by a barrage constructed on the Ganga River apart from smaller tributaries flowing in from the north. A novel aspect of this work is the integration of river dynamics and its connectivity to the wetlandscape to understand the spatiotemporal variability in the waterspread area in the wetland. In this work, we have developed an integrated wetlandscape assessment approach by evaluating wetland's geomorphic and hydrological connectivity status for the period 1993-2019 (25 years) across three different spatial scales - regional, catchment, and wetland. We have highlighted the ecological implications of connectivity and patch dynamics for developing sustainable wetland management plans.
Groundwater is critical in supporting current and future reliable water supply throughout Africa. Although continental maps of groundwater storage and recharge have been developed, we currently lack a clear understanding on how the controls on groundwater recharge vary across the entire continent. Reviewing the existing literature, we synthesize information on reported groundwater recharge controls in Africa. We find that 15 out of 22 of these controls can be characterised using global datasets. We develop 11 descriptors of climatic, topographic, vegetation, soil and geologic properties using global datasets, to characterise groundwater recharge controls in Africa. These descriptors cluster Africa into 15 Recharge Landscape Units for which we expect recharge controls to be similar. Over 80% of the continents land area is organized by just nine of these units. We also find that aggregating the Units by similarity into four broader Recharge Landscapes (Desert, Dryland, Wet tropical and Wet tropical forest) provides a suitable level of landscape organisation to explain differences in ground-based long-term mean annual recharge and recharge ratio (annual recharge / annual precipitation) estimates. Furthermore, wetter Recharge Landscapes are more efficient in converting rainfall to recharge than drier Recharge Landscapes as well as having higher annual recharge rates. In Dryland Recharge Landscapes, we found that annual recharge rates largely varied according to mean annual precipitation, whereas recharge ratio estimates increase with increasing monthly variability in P-PET. However, we were unable to explain why ground based estimates of recharge signatures vary across other Recharge Landscapes, in which there are fewer ground based recharge estimates, using global datasets alone. Even in dryland regions, there is still considerable unexplained variability in the estimates of annual recharge and recharge ratio, stressing the limitations of global datasets for investigating ground-based information.
On 7 January 2020, an M-w 6.4 earthquake occurred in the northeastern Caribbean, a few kilometers offshore of the island of Puerto Rico. It was the mainshock of a complex seismic sequence, characterized by a large number of energetic earthquakes illuminating an east-west elongated area along the southwestern coast of Puerto Rico. Deformation fields constrained by Interferometric Synthetic Aperture Radar and Global Navigation Satellite System data indicate that the coseismic movements affected only the western part of the island. To assess the mainshock's source fault parameters, we combined the geodetically derived coseismic deformation with teleseismic waveforms using Bayesian inference. The results indicate a roughly east-west oriented fault, dipping northward and accommodating similar to 1.4 m of transtensional motion. Besides, the determined location and orientation parameters suggest an offshore continuation of the recently mapped North Boqueron Bay-Punta Montalva fault in southwest Puerto Rico. This highlights the existence of unmapped faults with moderate-to-large earthquake potential within the Puerto Rico region.
Efforts have been made in the past to enhance building exposure models on a regional scale with increasing spatial resolutions by integrating different data sources. This work follows a similar path and focuses on the downscaling of the existing SARA exposure model that was proposed for the residential building stock of the communes of Valparaiso and Vina del Mar (Chile). Although this model allowed great progress in harmonising building classes and characterising their differential physical vulnerabilities, it is now outdated, and in any case, it is spatially aggregated over large administrative units. Hence, to more accurately consider the impact of future earthquakes on these cities, it is necessary to employ more reliable exposure models. For such a purpose, we propose updating this existing model through a Bayesian approach by integrating ancillary data that has been made increasingly available from Volunteering Geo-Information (VGI) activities. Its spatial representation is also optimised in higher resolution aggregation units that avoid the inconvenience of having incomplete building-by-building footprints. A worst-case earthquake scenario is presented to calculate direct economic losses and highlight the degree of uncertainty imposed by exposure models in comparison with other parameters used to generate the seismic ground motions within a sensitivity analysis. This example study shows the great potential of using increasingly available VGI to update worldwide building exposure models as well as its importance in scenario-based seismic risk assessment.
It is widely recognized that collisional mountain belt topography is generated by crustal thickening and lowered by river bedrock erosion, linking climate and tectonics(1-4). However, whether surface processes or lithospheric strength control mountain belt height, shape and longevity remains uncertain. Additionally, how to reconcile high erosion rates in some active orogens with long-term survival of mountain belts for hundreds of millions of years remains enigmatic. Here we investigate mountain belt growth and decay using a new coupled surface process(5,6) and mantle-scale tectonic model(7). End-member models and the new non-dimensional Beaumont number, Bm, quantify how surface processes and tectonics control the topographic evolution of mountain belts, and enable the definition of three end-member types of growing orogens: type 1, non-steady state, strength controlled (Bm > 0.5); type 2, flux steady state(8), strength controlled (Bm approximate to 0.4-0.5); and type 3, flux steady state, erosion controlled (Bm < 0.4). Our results indicate that tectonics dominate in Himalaya-Tibet and the Central Andes (both type 1), efficient surface processes balance high convergence rates in Taiwan (probably type 2) and surface processes dominate in the Southern Alps of New Zealand (type 3). Orogenic decay is determined by erosional efficiency and can be subdivided into two phases with variable isostatic rebound characteristics and associated timescales. The results presented here provide a unified framework explaining how surface processes and lithospheric strength control the height, shape, and longevity of mountain belts.
Seismology, like many scientific fields, e.g., music information retrieval and speech signal pro- cessing, is experiencing exponential growth in the amount of data acquired by modern seismo- logical networks. In this thesis, I take advantage of the opportunities offered by "big data" and by the methods developed in the areas of music information retrieval and machine learning to predict better the ground motion generated by earthquakes and to study the properties of the surface layers of the Earth. In order to better predict seismic ground motions, I propose two approaches based on unsupervised deep learning methods, an autoencoder network and Generative Adversarial Networks. The autoencoder technique explores a massive amount of ground motion data, evaluates the required parameters, and generates synthetic ground motion data in the Fourier amplitude spectra (FAS) domain. This method is tested on two synthetic datasets and one real dataset. The application on the real dataset shows that the substantial information contained within the FAS data can be encoded to a four to the five-dimensional manifold. Consequently, only a few independent parameters are required for efficient ground motion prediction. I also propose a method based on Conditional Generative Adversarial Networks (CGAN) for simulating ground motion records in the time-frequency and time domains. CGAN generates the time-frequency domains based on the parameters: magnitude, distance, and shear wave velocities to 30 m depth (VS30). After generating the amplitude of the time-frequency domains using the CGAN model, instead of classical conventional methods that assume the amplitude spectra with a random phase spectrum, the phase of the time-frequency domains is recovered by minimizing the observed and reconstructed spectrograms. In the second part of this dissertation, I propose two methods for the monitoring and characterization of near-surface materials and site effect analyses. I implement an autocorrelation function and an interferometry method to monitor the velocity changes of near-surface materials resulting from the Kumamoto earthquake sequence (Japan, 2016). The observed seismic velocity changes during the strong shaking are due to the non-linear response of the near-surface materials. The results show that the velocity changes lasted for about two months after the Kumamoto mainshock. Furthermore, I used the velocity changes to evaluate the in-situ strain-stress relationship. I also propose a method for assessing the site proxy "VS30" using non-invasive analysis. In the proposed method, a dispersion curve of surface waves is inverted to estimate the shear wave velocity of the subsurface. This method is based on the Dix-like linear operators, which relate the shear wave velocity to the phase velocity. The proposed method is fast, efficient, and stable. All of the methods presented in this work can be used for processing "big data" in seismology and for the analysis of weak and strong ground motion data, to predict ground shaking, and to analyze site responses by considering potential time dependencies and nonlinearities.
The 100 km wide Merida Andes extend from the Colombian/Venezuelan border to the Coastal Cordillera. The mountain chain and its associated major strike-slip fault systems in western Venezuela formed due to oblique convergence of the Caribbean with the South American Plates and the north-eastwards expulsion of the North Andean Block. Due to the limited knowledge of lithospheric structures related to the formation of the Merida Andes research projects have been developed to illuminate this zone with deep geophysical data. In this study, we present three-dimensional inversion of broadband magnetotelluric data, collected along a 240 km long profile crossing the Merida Andes and the Maracaibo and Barinas-Apure foreland basins. The distribution of the stations limits resolution of the model to off-profile features. Combining 3D inversion of synthetic data sets derived from 3D modelling with 3D inversion of measured data, we could derive a 10 to 15 km wide corridor with good lateral resolution to develop hypotheses about the origin of deep-reaching anomalies of high electrical conductivity. The Merida Andes appear generally as electrically resistive structures, separated by anomalies associated with the most important fault systems of the region, the Bocono and Valera faults. Sensitivity tests suggest that the Valera Fault reaches to depths of up to 12 km and the Bocono Fault to more than 35 km depth. Both structures are connected to a sizeable conductor located east of the profile at 12-15 km depth. We propose that the high conductivity associated with this off-profile conductor may be related to the detachment of the Trujillo Block. We also identified a conductive zone that correlates spatially with the location of a gravity low, possibly representing a SE tilt of the Maracaibo Triangular Block under the mountain chain to great depths (>30 km). The relevance of these tectonic blocks in our models at crustal depths seems to be consistent with proposed theories that describe the geodynamics of western Venezuela as dominated by floating blocks or orogens. Our results stress the importance of the Trujillo Block for the current tectonic evolution of western Venezuela and confirm the relevance of the Bocono Fault carrying deformation to the lower crust and upper mantle. The Barinas-Apure and the Maracaibo sedimentary basins are imaged as electrically conductive with depths of 4 to 5 km and 5 to 10 km, respectively. The Barinas-Apure basin is imaged as a simple 1D structure, in contrast to the Maracaibo Basin, where a series of conductive and resistive bodies could be related to active deformation causing the juxtaposition of older geological formations and younger basin sediments.
The stabilizing properties of mineral-organic carbon (OC) interactions have been studied in many soil environments (temperate soils, podzol lateritic soils, and paddy soils). Recently, interest in their role in permafrost regions is increasing as permafrost was identified as a hotspot of change. In thawing ice-rich permafrost regions, such as the Yedoma domain, 327-466 Gt of frozen OC is buried in deep sediments. Interactions between minerals and OC are important because OC is located very near the mineral matrix. Mineral surfaces and elements could mitigate recent and future greenhouse gas emissions through physical and/or physicochemical protection of OC. The dynamic changes in redox and pH conditions associated with thermokarst lake formation and drainage trigger metal-oxide dissolution and precipitation, likely influencing OC stabilization and microbial mineralization. However, the influence of thermokarst processes on mineral-OC interactions remains poorly constrained. In this study, we aim to characterize Fe, Mn, Al, and Ca minerals and their potential protective role for OC. Total and selective extractions were used to assess the crystalline and amorphous oxides or complexed metal pools as well as the organic acids found within these pools. We analyzed four sediment cores from an ice-rich permafrost area in Central Yakutia, which were drilled (i) in undisturbed Yedoma uplands, (ii) beneath a recent lake formed within Yedoma deposits, (iii) in a drained thermokarst lake basin, and (iv) beneath a mature thermokarst lake from the early Holocene period. We find a decrease in the amount of reactive Fe, Mn, Al, and Ca in the deposits on lake formation (promoting reduction reactions), and this was largely balanced by an increase in the amount of reactive metals in the deposits on lake drainage (promoting oxidation reactions). We demonstrate an increase in the metal to C molar ratio on thermokarst process, which may indicate an increase in metal-C bindings and could provide a higher protective role against microbial mineralization of organic matter. Finally, we find that an increase in mineral-OC interactions corresponded to a decrease in CO2 and CH4 gas emissions on thermokarst process. Mineral-OC interactions could mitigate greenhouse gas production from permafrost thaw as soon as lake drainage occurs.
Boreal forests cover over half of the global permafrost area and protect underlying permafrost. Boreal forest development, therefore, has an impact on permafrost evolution, especially under a warming climate.
Forest disturbances and changing climate conditions cause vegetation shifts and potentially destabilize the carbon stored within the vegetation and permafrost. Disturbed permafrost-forest ecosystems can develop into a dry or swampy bush- or grasslands, shift toward broadleaf- or evergreen needleleaf-dominated forests, or recover to the pre-disturbance state.
An increase in the number and intensity of fires, as well as intensified logging activities, could lead to a partial or complete ecosystem and permafrost degradation. We study the impact of forest disturbances (logging, surface, and canopy fires) on the thermal and hydrological permafrost conditions and ecosystem resilience.
We use a dynamic multilayer canopy-permafrost model to simulate different scenarios at a study site in eastern Siberia. We implement expected mortality, defoliation, and ground surface changes and analyze the interplay between forest recovery and permafrost. We find that forest loss induces soil drying of up to 44%, leading to lower active layer thicknesses and abrupt or steady decline of a larch forest, depending on disturbance intensity.
Only after surface fires, the most common disturbances, inducing low mortality rates, forests can recover and overpass pre-disturbance leaf area index values. We find that the trajectory of larch forests after surface fires is dependent on the precipitation conditions in the years after the disturbance. Dryer years can drastically change the direction of the larch forest development within the studied period.