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The creation of building exposure models for seismic risk assessment is frequently challenging due to the lack of availability of detailed information on building structures. Different strategies have been developed in recent years to overcome this, including the use of census data, remote sensing imagery and volunteered graphic information (VGI). This paper presents the development of a building-by-building exposure model based exclusively on openly available datasets, including both VGI and census statistics, which are defined at different levels of spatial resolution and for different moments in time. The initial model stemming purely from building-level data is enriched with statistics aggregated at the neighbourhood and city level by means of a Monte Carlo simulation that enables the generation of full realisations of damage estimates when using the exposure model in the context of an earthquake scenario calculation. Though applicable to any other region of interest where analogous datasets are available, the workflow and approach followed are explained by focusing on the case of the German city of Cologne, for which a scenario earthquake is defined and the potential damage is calculated. The resulting exposure model and damage estimates are presented, and it is shown that the latter are broadly consistent with damage data from the 1978 Albstadt earthquake, notwithstanding the differences in the scenario. Through this real-world application we demonstrate the potential of VGI and open data to be used for exposure modelling for natural risk assessment, when combined with suitable knowledge on building fragility and accounting for the inherent uncertainties.
Earthquake site responses or site effects are the modifications of surface geology to seismic waves. How well can we predict the site effects (average over many earthquakes) at individual sites so far? To address this question, we tested and compared the effectiveness of different estimation techniques in predicting the outcrop Fourier site responses separated using the general inversion technique (GIT) from recordings. Techniques being evaluated are (a) the empirical correction to the horizontal-to-vertical spectral ratio of earthquakes (c-HVSR), (b) one-dimensional ground response analysis (GRA), and (c) the square-root-impedance (SRI) method (also called the quarter-wavelength approach). Our results show that c-HVSR can capture significantly more site-specific features in site responses than both GRA and SRI in the aggregate, especially at relatively high frequencies. c-HVSR achieves a "good match" in spectral shape at similar to 80%-90% of 145 testing sites, whereas GRA and SRI fail at most sites. GRA and SRI results have a high level of parametric and/or modeling errors which can be constrained, to some extent, by collecting on-site recordings.
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.
Evaluation of a novel application of earthquake HVSR in site-specific amplification estimation
(2020)
Ground response analyses (GRA) model the vertical propagations of SH waves through flat-layered media (1DSH) and are widely carried out to evaluate local site effects in practice. Horizontal-to-vertical spectral ratio (HVSR) technique is a cost-effective approach to extract certain site-specific information, e.g., site fundamental frequency (f(0)), but HVSR values cannot be directly used to approximate the levels of S-wave amplifications. Motivated by the work of Kawase et al. (2019), we propose a procedure to correct earthquake HVSR amplitudes for direct amplification estimations. The empirical correction compensates HVSR by generic vertical amplification spectra categorized by the vertical fundamental frequency (f(0v)) via kappa-means clustering. In this investigation, we evaluate the effectiveness of the corrected HVSR in approximating observed linear amplifications in comparison with 1DSH modellings. We select a total of 90 KiK-net (Kiban Kyoshin network) surface-downhole sites which are found to have no velocity contrasts below their boreholes and thus of which surface-to-borehole spectral ratios (SBSRs) can be taken as their empirical transfer functions (ETFs). 1DSH-based theoretical transfer functions (TTFs) are computed in the linear domain considering uncertainties in Vs profiles through randomizations. Five goodness-of-fit metrics are adopted to gauge the closeness between observed (ETF) and predicted (i.e., TTF and corrected HVSR) amplifications in both amplitude and spectral shape over frequencies from f(0) to 25 Hz. We find that the empirical correction to HVSR is highly effective and achieves a "good match" in both spectral shape and amplitude at the majority of the 90 KiK-net sites, as opposed to less than one-third for the 1DSH modelling. In addition, the empirical correction does not require a velocity model, which GRAs require, and thus has great potentials in seismic hazard assessments.
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.
We address the question of whether all large-magnitude earthquakes produce an erosion peak in the subaerial components of fluvial catchments. We evaluate the sediment flux response to the Maule earthquake in the Chilean Andes (Mw 8.8) using daily suspended sediment records from 31 river gauges. The catchments cover drainage areas of 350 to around 10,000 km(2), including a wide range of topographic slopes and vegetation cover of the Andean western flank. We compare the 3- to 8-year postseismic record of sediment flux to each of the following preseismic periods: (1) all preseismic data, (2) a 3-year period prior to the seismic event, and (3) the driest preseismic periods, as drought conditions prevailed in the postseismic period. Following the earthquake, no increases in suspended sediment flux were observed for moderate to high percentiles of the streamflow distribution (mean, median, and >= 75th percentile). However, more than half of the examined stations showed increased sediment flux during baseflow. By using a Random Forest approach, we evaluate the contributions of seismic intensities, peak ground accelerations, co-seismic landslides, hydroclimatic conditions, topography, lithology, and land cover to explain the observed changes in suspended sediment concentration and fluxes. We find that the best predictors are hillslope gradient, low-vegetation cover, and changes in streamflow discharge. This finding suggests a combined first-order control of topography, land cover, and hydrology on the catchment-wide erosion response. We infer a reduced sediment connectivity due to the postseismic drought, which increased the residence time of sediment detached and remobilized following the Maule earthquake.
The impressive number of stream gauges in Chile, combined with a suite of past and recent large earthquakes, makes Chile a unique natural laboratory to study several streams that recorded responses to multiple seismic events. We document changes in discharge in eight streams in Chile following two or more large earthquakes. In all cases, discharge increases. Changes in discharge occur for peak ground velocities greater than about 7-11cm/s. Above that threshold, the magnitude of both the increase in discharge and the total excess water do not increase with increasing peak ground velocities. While these observations are consistent with previous work in California, they conflict with lab experiments that show that the magnitude of permeability changes increases with increasing amplitude of ground motion. Instead, our study suggests that streamflow responses are binary. Plain Language Summary Earthquakes deform and shake the surface and the ground below. These changes may affect groundwater flows by increasing the permeability along newly formed cracks and/or clearing clogged pores. As a result, groundwater flow may substantially increase after earthquakes and remain elevated for several months. Here we document streamflow anomalies following multiple high magnitude earthquakes in multiple streams in one of the most earthquake prone regions worldwide, Chile. We take advantage of the dense monitoring network in Chile that recorded streamflow since the 1940s. We show that once a critical ground motion is exceeded, streamflow responses to earthquakes can be expected.
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.
Along a subduction zone, great megathrust earthquakes recur either after long seismic gaps lasting several decades to centuries or over much shorter periods lasting hours to a few years when cascading successions of earthquakes rupture nearby segments of the fault. We analyze a decade of continuous Global Positioning System observations along the South American continent to estimate changes in deformation rates between the 2010 Maule (M8.8) and 2015 Illapel (M8.3) Chilean earthquakes. We find that surface velocities increased after the 2010 earthquake, in response to continental-scale viscoelastic mantle relaxation and to regional-scale increased degree of interplate locking. We propose that increased locking occurs transiently during a super-interseismic phase in segments adjacent to a megathrust rupture, responding to bending of both plates caused by coseismic slip and subsequent afterslip. Enhanced strain rates during a super-interseismic phase may therefore bring a megathrust segment closer to failure and possibly triggered the 2015 event.
Die genauen Einsatzzeiten seismischer P-Phasen von Erdbeben werden in SeisComP3 und anderen Auswerteprogrammen standardmäßig und in Echtzeit automatisch bestimmt. S-Phasen stellen dagegen eine weit größere Herausforderung dar. Nur mit genauen Picks der P- bzw. S-Phasen können die Erdbebenlokationen korrekt und stabil bestimmt werden. Darum besteht erhebliches Interesse, diese mit hoher Genauigkeit zu bestimmen. Das Ziel der vorliegenden Bachelorarbeit war es, vier verschiedene, bereits vorhandene S-Phasenpicker auf ausgewählte Parameter optimal zu konfigurieren, auf Testdaten anzuwenden und deren Leistungsfähigkeit objektiv zu bewerten. Dazu wurden ein S-Picker (S-L2) aus dem OpenSource SeisComp3-Programmpaket, zwei S-Picker (S-AIC, S-AIC-V) als kommerzielles Modul der Firma gempa GmbH für SeisComP3 und ein S-Picker (Frequenzband) aus dem OpenSource PhasePaPy-Paket ausgewählt. Die Bewertung erfolgte durch Vergleich automatischer Picks mit manuell bestimmten Einsatzzeiten. Alle vier Picker wurden separat konfiguriert und auf drei verschiedene Datensätze von Erdbeben in N-Chile und im Vogtland, Deutschland, angewandt. Dazu wurden regional bzw. lokal typische Erdbeben zufällig ausgewählt und die P- und S-Phasen manuell bestimmt. Mit den zu testenden S-Pickeralgorithmen wurden dieselben Daten durchsucht und die Picks automatisch bestimmt. Die Konfigurationen der Picker wurden gleichzeitig automatisch und objektiv durch iterative Anpassung optimiert. Ein neu erstelltes Bewertungssystem vergleicht die manuellen und die automatisch gefundenen S-Picks anhand von definierten Qualitätsfaktoren. Die Qualitätsfaktoren sind: der Mittelwert und die Standardabweichung der zeitlichen Differenzen zwischen den S-Picks, die Anzahl an übereinstimmenden S-Picks, die Prozentangaben über mögliche S-Picks und die benötigt Rechenzeit. Die objektive Bewertung erfolgte anhand eines Scores. Der Scorewert ergibt sich aus der gewichteten Summe folgender normierter Qualitätsfaktoren: Standardabweichung (20%), Mittelwert (20%) und Prozentangabe über mögliche S-Picks (60%). Konfigurationen mit hohem Score werden bevorzugt. Die bevorzugten Konfigurationen der verschiedenen Picker wurden miteinander verglichen, um den am besten geeigneten S-Pickeralgorithmus zu bestimmen. Allgemein zeigt sich, dass der S-AIC Picker für jeden der drei Datensätze die höchsten Scores und damit die besten Ergebnisse liefert. Dabei wurde für jeden Datensatz ein andere Konfiguration der Parameter des S-AIC Pickers als die am besten geeignete bezeichnet. Daher ist für jede Erdbebenregion eine andere Konfigurationen erforderlich, um optimale Ergebnisse mit diesem S-Picker zu bekommen.