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The 2015 magnitude 7.8 Gorkha earthquake and its aftershocks weakened mountain slopes in Nepal. Co- and postseismic landsliding and the formation of landslide-dammed lakes along steeply dissected valleys were widespread, among them a landslide that dammed the Kali Gandaki River. Overtopping of the landslide dam resulted in a flash flood downstream, though casualties were prevented because of timely evacuation of low-lying areas. We hindcast the flood using the BREACH physically based dam-break model for upstream hydrograph generation, and compared the resulting maximum flow rate with those resulting from various empirical formulas and a simplified hydrograph based on published observations. Subsequent modeling of downstream flood propagation was compromised by a coarse-resolution digital elevation model with several artifacts. Thus, we used a digital-elevation-model preprocessing technique that combined carving and smoothing to derive topographic data. We then applied the 1-dimensional HEC-RAS model for downstream flood routing, and compared it to the 2-dimensional Delft-FLOW model. Simulations were validated using rectified frames of a video recorded by a resident during the flood in the village of Beni, allowing estimation of maximum flow depth and speed. Results show that hydrological smoothing is necessary when using coarse topographic data (such as SRTM or ASTER), as using raw topography underestimates flow depth and speed and overestimates flood wave arrival lag time. Results also show that the 2-dimensional model produces more accurate results than the 1-dimensional model but the 1-dimensional model generates a more conservative result and can be run in a much shorter time. Therefore, a 2-dimensional model is recommended for hazard assessment and planning, whereas a 1-dimensional model would facilitate real-time warning declaration.
Earthquakes occurring close to hydrocarbon fields under production are often under critical view of being induced or triggered. However, clear and testable rules to discriminate the different events have rarely been developed and tested. The unresolved scientific problem may lead to lengthy public disputes with unpredictable impact on the local acceptance of the exploitation and field operations. We propose a quantitative approach to discriminate induced, triggered, and natural earthquakes, which is based on testable input parameters. Maxima of occurrence probabilities are compared for the cases under question, and a single probability of being triggered or induced is reported. The uncertainties of earthquake location and other input parameters are considered in terms of the integration over probability density functions. The probability that events have been human triggered/induced is derived from the modeling of Coulomb stress changes and a rate and state-dependent seismicity model. In our case a 3-D boundary element method has been adapted for the nuclei of strain approach to estimate the stress changes outside the reservoir, which are related to pore pressure changes in the field formation. The predicted rate of natural earthquakes is either derived from the background seismicity or, in case of rare events, from an estimate of the tectonic stress rate. Instrumentally derived seismological information on the event location, source mechanism, and the size of the rupture plane is of advantage for the method. If the rupture plane has been estimated, the discrimination between induced or only triggered events is theoretically possible if probability functions are convolved with a rupture fault filter. We apply the approach to three recent main shock events: (1) the M-w 4.3 Ekofisk 2001, North Sea, earthquake close to the Ekofisk oil field; (2) the M-w 4.4 Rotenburg 2004, Northern Germany, earthquake in the vicinity of the Sohlingen gas field; and (3) the M-w 6.1 Emilia 2012, Northern Italy, earthquake in the vicinity of a hydrocarbon reservoir. The three test cases cover the complete range of possible causes: clearly human induced, not even human triggered, and a third case in between both extremes.
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.
The seismicity of the Dead Sea fault zone (DSFZ) during the last two millennia is characterized by a number of damaging and partly devastating earthquakes. These events pose a considerable seismic hazard and seismic risk to Syria, Lebanon, Palestine, Jordan, and Israel. The occurrence rates for large earthquakes along the DSFZ show indications to temporal changes in the long-term view. The aim of this thesis is to find out, if the occurrence rates of large earthquakes (Mw ≥ 6) in different parts of the DSFZ are time-dependent and how. The results are applied to probabilistic seismic hazard assessments (PSHA) in the DSFZ and neighboring areas. Therefore, four time-dependent statistical models (distributions), including Weibull, Gamma, Lognormal and Brownian Passage Time (BPT), are applied beside the exponential distribution (Poisson process) as the classical time-independent model. In order to make sure, if the earthquake occurrence rate follows a unimodal or a multimodal form, a nonparametric bootstrap test of multimodality has been done. A modified method of weighted Maximum Likelihood Estimation (MLE) is applied to estimate the parameters of the models. For the multimodal cases, an Expectation Maximization (EM) method is used in addition to the MLE method. The selection of the best model is done by two methods; the Bayesian Information Criterion (BIC) as well as a modified Kolmogorov-Smirnov goodness-of-fit test. Finally, the confidence intervals of the estimated parameters corresponding to the candidate models are calculated, using the bootstrap confidence sets. In this thesis, earthquakes with Mw ≥ 6 along the DSFZ, with a width of about 20 km and inside 29.5° ≤ latitude ≤ 37° are considered as the dataset. The completeness of this dataset is calculated since 300 A.D. The DSFZ has been divided into three sub zones; the southern, the central and the northern sub zone respectively. The central and the northern sub zones have been investigated but not the southern sub zone, because of the lack of sufficient data. The results of the thesis for the central part of the DSFZ show that the earthquake occurrence rate does not significantly pursue a multimodal form. There is also no considerable difference between the time-dependent and time-independent models. Since the time-independent model is easier to interpret, the earthquake occurrence rate in this sub zone has been estimated under the exponential distribution assumption (Poisson process) and will be considered as time-independent with the amount of 9.72 * 10-3 events/year. The northern part of the DSFZ is a special case, where the last earthquake has occurred in 1872 (about 137 years ago). However, the mean recurrence time of Mw ≥ 6 events in this area is about 51 years. Moreover, about 96 percent of the observed earthquake inter-event times (the time between two successive earthquakes) in the dataset regarding to this sub zone are smaller than 137 years. Therefore, it is a zone with an overdue earthquake. The results for this sub zone verify that the earthquake occurrence rate is strongly time-dependent, especially shortly after an earthquake occurrence. A bimodal Weibull-Weibull model has been selected as the best fit for this sub zone. The earthquake occurrence rate, corresponding to the selected model, is a smooth function of time and reveals two clusters within the time after an earthquake occurrence. The first cluster begins right after an earthquake occurrence, lasts about 80 years, and is explicitly time-dependent. The occurrence rate, regarding to this cluster, is considerably lower right after an earthquake occurrence, increases strongly during the following ten years and reaches its maximum about 0.024 events/year, then decreases over the next 70 years to its minimum about 0.0145 events/year. The second cluster begins 80 years after an earthquake occurrence and lasts until the next earthquake occurs. The earthquake occurrence rate, corresponding to this cluster, increases extremely slowly, such as it can be considered as an almost constant rate about 0.015 events/year. The results are applied to calculate the time-dependent PSHA in the northern part of the DSFZ and neighbouring areas.
Rapidly uplifting coastlines are frequently associated with convergent tectonic boundaries, like subduction zones, which are repeatedly breached by giant megathrust earthquakes. The coastal relief along tectonically active realms is shaped by the effect of sea-level variations and heterogeneous patterns of permanent tectonic deformation, which are accumulated through several cycles of megathrust earthquakes. However, the correlation between earthquake deformation patterns and the sustained long-term segmentation of forearcs, particularly in Chile, remains poorly understood. Furthermore, the methods used to estimate permanent deformation from geomorphic markers, like marine terraces, have remained qualitative and are based on unrepeatable methods. This contrasts with the increasing resolution of digital elevation models, such as Light Detection and Ranging (LiDAR) and high-resolution bathymetric surveys.
Throughout this thesis I study permanent deformation in a holistic manner: from the methods to assess deformation rates, to the processes involved in its accumulation. My research focuses particularly on two aspects: Developing methodologies to assess permanent deformation using marine terraces, and comparing permanent deformation with seismic cycle deformation patterns under different spatial scales along the M8.8 Maule earthquake (2010) rupture zone. Two methods are developed to determine deformation rates from wave-built and wave-cut terraces respectively. I selected an archetypal example of a wave-built terrace at Santa Maria Island studying its stratigraphy and recognizing sequences of reoccupation events tied with eleven radiocarbon sample ages (14C ages). I developed a method to link patterns of reoccupation with sea-level proxies by iterating relative sea level curves for a range of uplift rates. I find the best fit between relative sea-level and the stratigraphic patterns for an uplift rate of 1.5 +- 0.3 m/ka.
A Graphical User Interface named TerraceM® was developed in Matlab®. This novel software tool determines shoreline angles in wave-cut terraces under different geomorphic scenarios. To validate the methods, I select test sites in areas of available high-resolution LiDAR topography along the Maule earthquake rupture zone and in California, USA. The software allows determining the 3D location of the shoreline angle, which is a proxy for the estimation of permanent deformation rates. The method is based on linear interpolations to define the paleo platform and cliff on swath profiles. The shoreline angle is then located by intersecting these interpolations. The
accuracy and precision of TerraceM® was tested by comparing its results with previous assessments, and through an experiment with students in a computer lab setting at the University
of Potsdam.
I combined the methods developed to analyze wave-built and wave-cut terraces to assess regional patterns of permanent deformation along the (2010) Maule earthquake rupture. Wave-built terraces are tied using 12 Infra Red Stimulated luminescence ages (IRSL ages) and shoreline angles in wave-cut terraces are estimated from 170 aligned swath profiles. The comparison of coseismic slip, interseismic coupling, and permanent deformation, leads to three areas of high permanent uplift, terrace warping, and sharp fault offsets. These three areas correlate with regions of high slip and low coupling, as well as with the spatial limit of at least eight historical megathrust ruptures (M8-9.5). I propose that the zones of upwarping at Arauco and Topocalma reflect changes in frictional properties of the megathrust, which result in discrete boundaries for the propagation of mega earthquakes.
To explore the application of geomorphic markers and quantitative morphology in offshore areas I performed a local study of patterns of permanent deformation inferred from hitherto unrecognized drowned shorelines at the Arauco Bay, at the southern part of the (2010) Maule earthquake rupture zone. A multidisciplinary approach, including morphometry, sedimentology, paleontology, 3D morphoscopy, and a landscape Evolution Model is used to recognize, map, and assess local rates and patterns of permanent deformation in submarine environments. Permanent deformation patterns are then reproduced using elastic models to assess deformation rates of an active submarine splay fault defined as Santa Maria Fault System. The best fit suggests a reverse structure with a slip rate of 3.7 m/ka for the last 30 ka. The register of land level changes during the earthquake cycle at Santa Maria Island suggest that most of the deformation may be accrued through splay fault reactivation during mega earthquakes, like the (2010) Maule event. Considering a recurrence time of 150 to 200 years, as determined from historical and geological observations, slip between 0.3 and 0.7 m per event would be required to account for the 3.7 m/ka millennial slip rate. However, if the SMFS slips only every ~1000 years, representing a few megathrust earthquakes, then a slip of ~3.5 m per event would be required to account for the long- term rate. Such event would be equivalent to a magnitude ~6.7 earthquake capable to generate a local tsunami.
The results of this thesis provide novel and fundamental information regarding the amount of permanent deformation accrued in the crust, and the mechanisms responsible for this accumulation at millennial time-scales along the M8.8 Maule earthquake (2010) rupture zone. Furthermore, the results of this thesis highlight the application of quantitative geomorphology and the use of repeatable methods to determine permanent deformation, improve the accuracy of marine terrace assessments, and estimates of vertical deformation rates in tectonically active coastal areas. This is vital information for adequate coastal-hazard assessments and to anticipate realistic earthquake and tsunami scenarios.
Most of the deformation associated with the seismic cycle in subduction zones occurs offshore and has been therefore difficult to quantify with direct observations at millennial timescales. Here we study millennial deformation associated with an active splay-fault system in the Arauco Bay area off south central Chile. We describe hitherto unrecognized drowned shorelines using high-resolution multibeam bathymetry, geomorphic, sedimentologic, and paleontologic observations and quantify uplift rates using a Landscape Evolution Model. Along a margin-normal profile, uplift rates are 1.3m/ka near the edge of the continental shelf, 1.5m/ka at the emerged Santa Maria Island, -0.1m/ka at the center of the Arauco Bay, and 0.3m/ka in the mainland. The bathymetry images a complex pattern of folds and faults representing the surface expression of the crustal-scale Santa Maria splay-fault system. We modeled surface deformation using two different structural scenarios: deep-reaching normal faults and deep-reaching reverse faults with shallow extensional structures. Our preferred model comprises a blind reverse fault extending from 3km depth down to the plate interface at 16km that slips at a rate between 3.0 and 3.7m/ka. If all the splay-fault slip occurs during every great megathrust earthquake, with a recurrence of similar to 150-200years, the fault would slip similar to 0.5m per event, equivalent to a magnitude similar to 6.4 earthquake. However, if the splay-fault slips only with a megathrust earthquake every similar to 1000years, the fault would slip similar to 3.7m per event, equivalent to a magnitude similar to 7.5 earthquake.
In many procedures of seismic risk mitigation, ground motion simulations are needed to test systems or improve their effectiveness. For example they may be used to estimate the level of ground shaking caused by future earthquakes. Good physical models for ground motion simulation are also thought to be important for hazard assessment, as they could close gaps in the existing datasets. Since the observed ground motion in nature shows a certain variability, part of which cannot be explained by macroscopic parameters such as magnitude or position of an earthquake, it would be desirable that a good physical model is not only able to produce one single seismogram, but also to reveal this natural variability.
In this thesis, I develop a method to model realistic ground motions in a way that is computationally simple to handle, permitting multiple scenario simulations. I focus on two aspects of ground motion modelling. First, I use deterministic wave propagation for the whole frequency range – from static deformation to approximately 10 Hz – but account for source variability by implementing self-similar slip distributions and rough fault interfaces. Second, I scale the source spectrum so that the modelled waveforms represent the correct radiated seismic energy. With this scaling I verify whether the energy magnitude is suitable as an explanatory variable, which characterises the amount of energy radiated at high frequencies – the advantage of the energy magnitude being that it can be deduced from observations, even in real-time.
Applications of the developed method for the 2008 Wenchuan (China) earthquake, the 2003 Tokachi-Oki (Japan) earthquake and the 1994 Northridge (California, USA) earthquake show that the fine source discretisations combined with the small scale source variability ensure that high frequencies are satisfactorily introduced, justifying the deterministic wave propagation approach even at high frequencies. I demonstrate that the energy magnitude can be used to calibrate the high-frequency content in ground motion simulations.
Because deterministic wave propagation is applied to the whole frequency range, the simulation method permits the quantification of the variability in ground motion due to parametric uncertainties in the source description. A large number of scenario simulations for an M=6 earthquake show that the roughness of the source as well as the distribution of fault dislocations have a minor effect on the simulated variability by diminishing directivity effects, while hypocenter location and rupture velocity more strongly influence the variability. The uncertainty in energy magnitude, however, leads to the largest differences of ground motion amplitude between different events, resulting in a variability which is larger than the one observed.
For the presented approach, this dissertation shows (i) the verification of the computational correctness of the code, (ii) the ability to reproduce observed ground motions and (iii) the validation of the simulated ground motion variability. Those three steps are essential to evaluate the suitability of the method for means of seismic risk mitigation.
Detecting whether and how river discharge responds to strong earthquake shaking can be time-consuming and prone to operator bias when checking hydrographs from hundreds of gauging stations. We use Bayesian piecewise regression models to show that up to a fifth of all gauging stations across Chile had their largest change in daily streamflow trend on the day of the M-w 8.8 Maule earthquake in 2010. These stations cluster distinctly in the near field though the number of detected streamflow changes varies with model complexity and length of time window considered. Credible seismic streamflow changes at several stations were the highest detectable in eight months, with an increased variance of discharge surpassing the variance of discharge following rainstorms. We conclude that Bayesian piecewise regression sheds new and unbiased insights on the duration, trend, and variance of streamflow response to strong earthquakes, and on how this response compares to that following rainstorms.
The Cheb Basin (CZ) is a shallow Neogene intracontinental basin located in the western Eger Rift. The Cheb Basin is characterized by active seismicity and diffuse degassing of mantle-derived CO2 in mofette fields. Within the Cheb Basin, the Hartoušov mofette field shows a daily CO2 flux of 23–97 tons. More than 99% of CO2 released over an area of 0.35 km2. Seismic active periods have been observed in 2000 and 2014 in the Hartoušov mofette field. Due to the active geodynamic processes, the Cheb Basin is considered to be an ideal region for the continental deep biosphere research focussing on the interaction of biological processes with geological processes.
To study the influence of CO2 degassing on microbial community in the surface and subsurface environments, two 3-m shallow drillings and a 108.5-m deep scientific drilling were conducted in 2015 and 2016 respectively. Additionally, the fluid retrieved from the deep drilling borehole was also recovered. The different ecosystems were compared regarding their geochemical properties, microbial abundances, and microbial community structures. The geochemistry of the mofette is characterized by low pH, high TOC, and sulfate contents while the subsurface environment shows a neutral pH, and various TOC and sulfate contents in different lithological settings. Striking differences in the microbial community highlight the substantial impact of elevated CO2 concentrations and high saline groundwater on microbial processes. In general, the microorganisms had low abundance in the deep subsurface sediment compared with the shallow mofette. However, within the mofette and the deep subsurface sediment, the abundance of microbes does not show a typical decrease with depth, indicating that the uprising CO2-rich groundwater has a strong influence on the microbial communities via providing sufficient substrate for anaerobic chemolithoautotrophic microorganisms. Illumina MiSeq sequencing of the 16S rRNA genes and multivariate statistics reveals that the pH strongly influences the microbial community composition in the mofette, while the subsurface microbial community is significantly influenced by the groundwater which motivated by the degassing CO2. Acidophilic microorganisms show a much higher relative abundance in the mofette. Meanwhile, the OTUs assigned to family Comamonadaceae are the dominant taxa which characterize the subsurface communities. Additionally, taxa involved in sulfur cycling characterizing the microbial communities in both mofette and CO2 dominated subsurface environments.
Another investigated important geo–bio interaction is the influence of the seismic activity. During seismic events, released H2 may serve as the electron donor for microbial hydrogenotrophic processes, such as methanogenesis. To determine whether the seismic events can potentially trigger methanogenesis by the elevated geogenic H2 concentration, we performed laboratory simulation experiments with sediments retrieved from the drillings. The simulation results indicate that after the addition of hydrogen, substantial amounts of methane were produced in incubated mofette sediments and deep subsurface sediments. The methanogenic hydrogenotrophic genera Methanobacterium was highly enriched during the incubation. The modeling of the in-situ observation of the earthquake swarm period in 2000 at the Novy Kostel focal area/Czech Republic and our laboratory simulation experiments reveals a close relation between seismic activities and microbial methane production via earthquake-induced H2 release. We thus conclude that H2 – which is released during seismic activity – can potentially trigger methanogenic activity in the deep subsurface. Based on this conclusion, we further hypothesize that the hydrogenotrophic early life on Earth was boosted by the Late Heavy Bombardment induced seismic activity in approximately 4.2 to 3.8 Ga.
Earthquakes deform Earth's surface, building long-lasting topographic features and contributing to landscape and mountain formation.
However, seismic waves produced by earthquakes may also destabilize hillslopes, leading to large amounts of soil and bedrock moving downslope. Moreover, static deformation and shaking are suspected to damage the surface bedrock and therefore alter its future properties, affecting hydrological and erosional dynamics. Thus, earthquakes participate both in mountain building and stimulate directly or indirectly their erosion. Moreover, the impact of earthquakes on hillslopes has important implications for the amount of sediment and organic matter delivered to rivers, and ultimately to oceans, during episodic catastrophic seismic crises, the magnitude of life and property losses associated with landsliding, the perturbation and recovery of landscape properties after shaking, and the long term topographic evolution of mountain belts. Several of these aspects have been addressed recently through individual case studies but additional data compilation as well as theoretical or numerical modelling are required to tackle these issues in a more systematic and rigorous manner.
This dissertation combines data compilation of earthquake characteristics, landslide mapping, and seismological data interpretation with physically-based modeling in order to address how earthquakes impact on erosional processes and landscape evolution. Over short time scales (10-100 s) and intermediate length scales (10 km), I have attempted to improve our understanding and ability to predict the amount of landslide debris triggered by seismic shaking in epicentral areas. Over long time scales (1-100 ky) and across a mountain belt (100 km) I have modeled the competition between erosional unloading and building of topography associated with earthquakes. Finally, over intermediate time scales (1-10 y) and at the hillslope scale (0.1-1 km) I have collected geomorphological and seismological data that highlight persistent effects of earthquakes on landscape properties and behaviour.
First, I compiled a database on earthquakes that produced significant landsliding, including an estimate of the total landslide volume and area, and earthquake characteristics such as seismic moment and source depth. A key issue is the accurate conversion of landslide maps into volume estimates. Therefore I also estimated how amalgamation - when mapping errors lead to the bundling of multiple landslide into a single polygon - affects volume estimates from various earthquake-induced landslide inventories and developed an algorithm to automatically detect this artifact. The database was used to test a physically-based prediction of the total landslide area and volume caused by earthquakes, based on seismological scaling relationships and a statistical description of the landscape properties. The model outperforms empirical fits in accuracy, with 25 out of 40 cases well predicted, and allows interpretation of many outliers in physical terms. Apart from seismological complexities neglected by the model I found that exceptional rock strength properties or antecedent conditions may explain most outliers.
Second, I assessed the geomorphic effects of large earthquakes on landscape dynamics by surveying the temporal evolution of precipitation-normalized landslide rate. I found strongly elevated landslide rates following earthquakes that progressively recover over 1 to 4 years, indicating that regolith strength drops and recovers. The relaxation is clearly non-linear for at least one case, and does not seem to correlate with coseismic landslide reactivation, water table level increase or tree root-system recovery. I suggested that shallow bedrock is damaged by the earthquake and then heals on annual timescales. Such variations in ground strength must be translated into shallow subsurface seismic velocities that are increasingly surveyed with ambient seismic noise correlations. With seismic noise autocorrelation I computed the seismic velocity in the epicentral areas of three earthquakes where I constrained a change in landslide rate. We found similar recovery dynamics and timescales, suggesting that seismic noise correlation techniques could be further developed to meaningfully assess ground strength variations for landscape dynamics. These two measurements are also in good agreement with the temporal dynamics of post-seismic surface displacement measured by GPS. This correlation suggests that the surface healing mechanism may be driven by tectonic deformation, and that the surface regolith and fractured bedrock may behave as a granular media that slowly compacts as it is sheared or vibrated.
Last, I compared our model of earthquake-induced landsliding with a standard formulation of surface deformation caused by earthquakes to understand which parameters govern the competition between the building and destruction of topography caused by earthquakes. In contrast with previous studies I found that very large (Mw>8) earthquakes always increase the average topography, whereas only intermediate (Mw ~ 7) earthquakes in steep landscapes may reduce topography. Moreover, I illustrated how the net effect of earthquakes varies with depth or landscape steepness implying a complex and ambivalent role through the life of a mountain belt. Further I showed that faults producing a Gutenberg-Richter distribution of earthquake sizes, will limit topography over a larger range of fault sizes than faults producing repeated earthquakes with a characteristic size.