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Enero de 2023
Machine Learning Developments and Applications in Solid-Earth Geosciences: Fad or Future?
Authors: Yunyue Elita Li, Daniel O’Malley et al
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After decades of low but continuing activity, applications of machine learning (ML) in solid Earth geoscience have exploded in popularity. This special collection provides a snapshot of those applications, which range from data processing to inversion and interpretation, for which ML appears particularly well

suited. Inevitably, there are variations in the degree to which these methods have been developed. We hope that the progress seen in some areas will inspire efforts in others. Challenges remain, including the formidable task of how geoscience can keep pace with developments in ML while ensuring the scientific rigor that our field depends on, but with improvements in sensor technology and accelerating rates of data accumulation, the methods of ML seem poised to play an important role for the foreseeable future.

Enero de 2023
Estimating geomagnetically induced currents in southern Brazil using 3-D Earth resistivity model
Authors: Karen V. Espinosa, Antonio L. Padilha et al
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Geomagnetically induced currents (GICs) result from the interaction of the time variation of ground magnetic field during a geomagnetic disturbance with the Earth’s deep electrical resistivity structure. In this study, we simulate induced GICs in a hypothetical representation of a low-latitude power transmission network located mainly over the large Paleozoic Paraná basin in southern Brazil. Two intense geomagnetic storms in June and December 2015 are chosen and geoelectric fields are calculated by convolving a 3-D Earth resistivity model with recorded geomagnetic variations. The dB/dt proxy often used to characterize GIC activity fails during the June storm mainly due to the relationship

of the instantaneous geoelectric field to previous magnetic field values. Precise resistances of network components are unknown, so assumptions are made for calculating GIC flows from the derived geoelectric field. The largest GICs are modeled in regions of low conductance in the 3-D resistivity model, concentrated in an isolated substation at the northern edge of the network and in a cluster of substations in its central part where the E-W oriented transmission lines coincide with the orientation of the instantaneous geoelectric field. The maximum magnitude of the modeled GIC was obtained during the main phase of the June storm, modeled at a northern substation, while the lowest magnitudes were found over prominent crustal anomalies along the Paraná basin axis and bordering the continental margin. The simulation results will be used to prospect the optimal substations for installation of GIC monitoring equipment.

Enero de 2023
Induced Seismicity by Groundwater Extraction at the Dead Sea Fault, Jordan
Authors: E. Shalev, N. Wetzler et al
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The earthquake sequence, with a maximum earthquake magnitude of MW 3.8, that occurred during January–February 2022 at the northern Dead Sea fault, is shown to be induced by extensive groundwater abstraction in Wadi Al-Arab basin. Wadi Al-Arab basin, which is bordered in the west by the Dead Sea fault, has been overexploited by extensive groundwater abstraction causing significant drawdowns. Relative earthquake relocation indicates an elongated S-N sequence subparallel to the Dead Sea fault. We simulate the three-dimensional hydraulic head changes in the past 40 years at Wadi al Arab basin. Results show that the drawdowns at

the Dead Sea fault wells reached a value greater than 180 m. We use these results to further model the poroelastic effects of the drawdown on the stability of the Dead Sea fault using a typical fault architecture including fault core surrounded by damage zone. Upward groundwater drainage through the permeable damage zone leads to compaction and strengthening. Failure on the Dead Sea fault is expected to occur on the impermeable fault core or at the protholith where weakening is expected. Groundwater abstraction in Wadi Al-Arab basin cause changes of a few MPa in the Coulmb Failure Stress (ΔCFS) and trigger seismicity in these sections. This is the second location along the Dead Sea fault where groundwater abstraction was shown to recently induce earthquakes. With growing demand for water and long lasting droughts in the Middle East, seismicity induced by groundwater abstraction might reoccur in the near future.

Enero de 2023
The 2013 slab-wide Kamchatka earthquake sequence
Authors: B. Rousset, M. Campillo et al
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Studies of initiation of large earthquakes are usually focused on frictional instabilities occurring in the near vicinity of the future rupture. Possible contributions of long-distance interactions with large-scale tectonic instabilities remain unknown. Here we analyze seismic catalogs and geodetic time series during a few months preceding the 2013 M = 8.3 deep-focus Okhotsk earthquake. This deep-focus event is

preceded by four intense seismic clusters in the seismogenic zone. GNSS time series in Kamchatka revealed a transient landward motion episode one month prior to the mainshock, consistent with an increase of seismogenic zone loading. This transient loading episode is accompanied by a doubling of the intermediate depth seismicity rate suggesting a transient slab pull as the origin. These observations question the constant subducting velocity hypotheses and may have implications in the understanding of the long-distance along-slab stress interactions and in their contribution to initiation of large deep-focus earthquakes.

Diciembre de 2022
Violent Groundwater Eruption Triggered by a Distant Earthquake
Authors: Xin Yan, Zheming Shi et al
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It is now well established that earthquakes cause various hydrogeological responses at distances thousands of kilometers from the epicenter. What remains unexplained is the large amplitude and intensity of some responses. Following the 2004 Mw 9.1 Sumatra earthquake, groundwater 3,200 km from the epicenter erupted violently from a well and formed

a water fountain reaching a height exceeding 60 m. We model the relevant processes by combining tidal analysis of groundwater level with numerical simulations using a two-dimensional finite-element model. We suggest that the eruption resulted from a combination of factors, including a rapid increase of crustal permeability and runaway CO2 exsolution and bubble nucleation induced by the passage of seismic waves. Our results may have implications for some engineering applications such as oil production and CO2 sequestration, and the eruption of hydrothermal features such as geysers.

Diciembre de 2022
Modeling Viscosity of Volcanic Melts With Artificial Neural Networks
Authors: D. Langhammer, D. Di Genova et al
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Viscosity is of great importance in governing the dynamics of volcanoes, including their eruptive style. The viscosity of a volcanic melt is dominated by temperature and chemical composition, both oxides and water content. The changes in melt structure resulting from the interactions between the various chemical components are complex, and the construction of a physical viscosity model that depends on composition has not yet been achieved. We therefore train an artificial neural network (ANN) on a large database of measured compositions, including water, and viscosities that spans virtually the entire chemical space of terrestrial magmas, as

well as some technical and extra-terrestrial silicate melts. The ANN uses composition, temperature, a structural parameter reflecting melt polymerization and the alkaline ratio as input parameters. It successfully reproduces and predicts measurements in the database with significantly higher accuracy than previous global models for volcanic melt viscosities. Viscosity measurements are restricted to low and high viscosity ranges, which exclude typical eruptive temperatures. Without training data at such conditions, the ANN cannot reliably predict viscosities for this important temperature range. To overcome this limitation, we use the ANN to create synthetic viscosity data in the high and low viscosity range and fit these points using a physically motivated, temperature-dependent viscosity model. Our study introduces a synthetic data approach for the creation of a physically motivated model predicting volcanic melt viscosities based on ANNs.

Diciembre de 2022
Secular Evolution of Continents and the Earth System
Authors: Peter A. Cawood, Priyadarshi Chowdhury et al
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Understanding of secular evolution of the Earth system is based largely on the rock and mineral archive preserved in the continental lithosphere. Based on the frequency and range of accessible data preserved in this record, we divide the secular evolution into seven phases: (a) “Proto-Earth” (ca. 4.57–4.45 Ga); (b) “Primordial Earth” (ca. 4.45–3.80 Ga); (c) “Primitive Earth” (ca. 3.8–3.2 Ga); (d) “Juvenile Earth” (ca. 3.2–2.5 Ga); (e) “Youthful Earth” (ca. 2.5–1.8 Ga); (f) “Middle Earth” (ca. 1.8–0.8 Ga); and (g) “Contemporary Earth” (since ca. 0.8 Ga). Integrating this record with knowledge of secular cooling of the mantle and lithospheric rheology

constrains the changes in the tectonic modes that operated through Earth history. Initial accretion and the Moon forming impact during the Proto-Earth phase likely resulted in a magma ocean. The solidification of this magma ocean produced the Primordial Earth lithosphere, which preserves evidence for intra-lithospheric reworking of a rigid lid, but which also likely experienced partial recycling through mantle overturn and meteorite impacts. Evidence for craton formation and stabilization from ca. 3.8 to 2.5 Ga, during the Primitive and Juvenile Earth phases, likely reflects some degree of coupling between the convecting mantle and a lithosphere initially weak enough to favor an internally deformable, squishy-lid behavior, which led to a transition to more rigid, plate like, behavior by the end of the early Earth phases. The Youthful to Contemporary phases of Earth, all occurred within a plate tectonic framework with changes between phases linked to lithospheric behavior and the supercontinent cycle.

Diciembre de 2022
A Pore-Throat Segmentation Method Based on Local Hydraulic Resistance Equivalence for Pore-Network Modeling
Authors: Yang Liu, Wenbo Gong, Yu Zhao et al
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The pore network is an approximate representation of the void space of porous materials, such as rocks and soil, via pores (corresponding to large cavities) and throats (narrow constrictions). During extraction of networks from real void space, ambiguous definitions or determinations of pores and throats may cause significant errors in the prediction of single/multi-phase transport properties. Meanwhile, the pore-throat segmentation needs to exclude non-physical parameters as much as possible. In this work, we propose a pore-throat segmentation method based on local hydraulic resistance

equivalence between the real void space and the simplified pore-throat geometry. Each pore-throat interface is carefully determined at the position where the simplified tubes preserve the local hydraulic resistance of the real space best. This local segmentation method ensures equivalency between extracted pore network and real pore space without any empirical or non-physical parameters. After validations of accuracy and reliability by benchmarks, this method is applied to real porous materials including spherical pack, sand pack, sandstone, limestone, and carbonate. The single/two-phase transport properties predicted by the new method agree well with the experimental data and the direct simulation results. The proposed method improves the accuracy of pore network model (PNM) predictions significantly with a slight increase in computational cost. This local pore-throat segmentation method may enhance the capability of PNM for more complicated applications.

Noviembre de 2022
Linking Upper-Plate Fault Reactivation With the Megathrust Earthquake Cycle: The Case of the Northern Chile Outer Forearc (19°S–23°S)
Authors: J. Cortés-Aranda, J. González et al
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Although smaller and less recurrent than earthquakes occurring on the interplate contact of subduction margins, seismic events on crustal faults (fault reactivation) may cause severe damage for inhabited areas in the vicinity. Former studies suggest that fault reactivation may occur during the interseismic phase (the time period between two successive earthquakes) of the subduction cycle or following megathrust earthquakes. This is, both phases may induce stress perturbations on crustal

faults and, eventually, produce their reactivation. Herein, we calculate the stress perturbations induced by interseismic and coseismic scenarios on seismogenic crustal faults in the northern Chile outer forearc (19°S–23°S). These faults occur directly above a subduction segment that contained the great 1877 Iquique Earthquake. Our results suggest that both interseismic and coseismic stages of the megathrust cycle may produce fault reactivation; nevertheless, each stage favors specific fault types. Furthermore, our results indicate that a great megathrust earthquake in the area could promote the reactivation of most of the upper crustal faults, increasing the seismic hazard in the region. This study is relevant when considering the interaction between interplate processes and crustal fault reactivation to better assess the seismic hazard in this and other subduction zones.

Noviembre de 2022
Powering Earth's Ancient Dynamo With Silicon Precipitatione
Authors: Alfred J. Wilson, Monica Pozzo et al
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The iron core at the center of the Earth presently has a molten outer shell and solid inner region which is growing as the Earth cools. This inner core (IC) growth provides power to the outer core (OC) because elements excluded from the IC are light and rise to the top of the OC. Today, this power drives the Earth's magnetic field but was not available before the IC began to freeze 1 billion years ago. Despite

this, the rock record shows that the magnetic field has been extant for 4 billion years, raising the question of how it was powered before the IC formed. Here, we perform calculations of the constituent liquid iron alloys in the core to understand the conditions which allow silicon to be dissolved into the core. We find that for a low oxygen condition, silicon can be dissolved into the hot ancient core and then released as the Earth cools, leaving behind dense, iron rich liquids which sink providing an alternate source of convective power. We show that this process could have powered the magnetic field before the IC formed and might constrain the core composition.

Noviembre de 2022
The 2021 “Complex Systems” Nobel Prize: The Climate, With and Without Geocomplexity
Author: S. Lovejoy
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One half of 2021s Nobel Physics prize was awarded to statistical physicist Giorgio Parisi and the other—the first in geophysics in 75 years—to climate scientists Syukoro Manabe and Klaus Hasselmann, the former for pioneering General Circulation Models and the latter (primarily) for proposing a statistical model explaining the climate as a slowly varying state driven by random weather noise. However, the Nobel committee recognized the climate laureates' work almost exclusively from the 1960s and 1970s. We update their report with the contributions from nonlinear geophysics and discuss the implications

for the unity of geoscience, and for future climate modeling.
Complexity science in general—and geocomplexity in particular—emerged in the wake of the 1980s nonlinear revolution: notably deterministic chaos, fractals, nonlinear waves, self organized criticality and somewhat later, network theory. Complexity physics took shape in the 1990s (see the review, Nicolis & Nicolis, 2012) whereas nonlinear geoscience can be roughly dated from the workshops on Nonlinear VAriability in Geophysics (NVAG 1–4, 1986–1997), the establishment of the Nonlinear Processes division at the European Geophysical Society (now European Geophysical Union, EGU, 1989), the Nonlinear Geophysics focus group at the American Geophysical Union (AGU, 1997) and in 2009, an AGU session with accompanying geocomplexity workshop (Lovejoy et al., 2009).

Noviembre de 2022
Forecasting the Geomagnetic Activity Several Days in Advance Using Neural Networks Driven by Solar EUV Imaging
Authors: Guillerme Bernoux, Antoine Brunet et al
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The Sun is an active star that constantly emits particles in all directions, including toward the Earth. This flow of charged particles (called solar wind) interacts with and disturbs the Earth's magnetic field, resulting in so-called geomagnetic storms. Geomagnetic storms, and generally speaking Sun-Earth interactions, can have dramatic consequences on spacecrafts, aircrafts (and their passengers), and electrical power grids. That is why it is essential to be

able to accurately forecast the state of disturbance of the Earth's magnetosphere. Most current models rely on in-situ near-Earth measurements of the solar wind to forecast the geomagnetic activity up to a few hours in advance. In order to extend the forecasting horizon, we investigate the direct use of solar imaging to drive an artificial intelligence-based model designed to forecast the geomagnetic activity up to a few days in advance. To do so, we design SERENADE, a prototype model able to partially capture the geomagnetic dynamics at least 2 days ahead, which shows that our approach is very promising. Our model is one of the first of its kind and, although it is not yet ready to be used in an operational context, it opens the way to future developments.

Noviembre de 2022
Fluid-Induced Fault Reactivation Due To Brucite + Antigorite Dehydration Triggered the Mw7.1 September 19th Puebla-Morelos (Mexico) Intermediate-Depth Earthquake
Authors: F. Gutiérrez-Aguilar, D. Hernández-Uribe et al
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The Puebla-Morelos (central Mexico) Mw7.1 earthquake occurred in an uncommon locality in Mexico compared to most of the catastrophic earthquakes that have occurred in this part of the world—it nucleated ∼250 km inland, almost below

Mexico City. In this paper, we explore the role of mineralogical changes occurring in the Cocos tectonic plate, which is currently descending below the North America plate. Our model tracked the changes in the minerals within the rocks and show that the earthquake might have been triggered by the physical changes associated with the mineral reaction: brucite + antigorite = olivine + H2O. We suggest that this mineral reaction primarily occurred along faults in the subducting oceanic floor along which the mantle lithosphere was hydrated prior to subduction. The brucite + antigorite dehydration reaction may be key for intermediate seismicity worldwide.

Noviembre de 2022
Supervised Machine Learning of High Rate GNSS Velocities for Earthquake Strong Motion Signals
Authors: T. Dittmann, Y. Liu et al
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Continuously operating, high sample rate Global Navigation Satellite System (GNSS) sensors that experience ground shaking from an earthquake can provide valuable data regarding the nature of the ground motion. If this data is streamed in real-time, these observations can complement existing traditional seismic infrastructure measurements that are used for earthquake early warning or rapid ground motion assessments. However, the data from these sensors can be noisy and have non-

earthquake artifacts that are difficult to tell apart from true seismic signals. In this work we used a nearly 20-years archive of high sample rate GNSS velocities occurring during known seismic events to train, validate and test a machine learning model for earthquake detection. This machine learning approach is taken from existing algorithms used for a wide variety of challenging classification problems where a label can be applied to a sample. We demonstrate that this data-driven method, without any external information, is more likely to detect these signals with less false alarms when compared to existing methods. The added confidence this algorithm provides will allow these valuable measurements to be included in operational seismic assessment and warning decision criteria.

Noviembre de 2022
Oscillations of the Ionosphere Caused by the 2022 Tonga Volcanic Eruption Observed With SuperDARN Radars
Authors: Jiaojiao Zhang, Jiyao Xu et al
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On 15 January 2022, an underwater volcano on the southwest Pacific island of Tonga erupted, triggering significant disturbances on the surface and in the ionosphere that propagated worldwide. The oscillation features of the ionosphere caused by the volcanic eruption have not been identified. The volcanic eruption caused numerous irregularities in the ionosphere. These irregularities move with the

ionosphere similar to how leaves move in a rough sea. In this study, the ionospheric irregularities were observed and employed as tracers to analyze the ionospheric oscillations. Different features of ionospheric oscillations, including the maximum line-of-sight (LOS) velocity, the altitude of the maximum LOS velocity, and the propagation direction, were observed before and after the arrival of the surface air pressure waves. The amplitudes of the LOS velocities of the ionospheric fluctuations approached 150 m/s, and a maximum upward displacement of 100 km, which is the strongest ionospheric fluctuation caused by geological hazards ever observed.

Noviembre de 2022
Tsunami Early Warning From Global Navigation Satellite System Data Using Convolutional Neural Networks
Authors: Donsub Rim, Robert Baraldi et al
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Producing rapid real-time forecasts for tsunamis in the first few minutes of an earthquake is a challenging problem. Accurate forecasts often rely on direct measurements of the tsunami, which are only available at sparse locations, and only after the tsunami has passed the sensors. Real-time numerical modeling of the tsunami is also time consuming. This work attempts to bypass these difficulties by considering a model that can forecast

tsunami wave heights based only on Global Navigation Satellite System (GNSS) data, which is available within minutes from an extensive network of stations. We present some initial results using this approach for hypothetical tsunamis originating from the Cascadia Subduction Zone, with forecast locations in Puget Sound. We show that this approach gives comparable results to earlier work based on observing tsunami waveforms for 30 or 60 min, but now using only a few minutes of GNSS data. We explore varying the number of GNSS stations and find that the model yields accurate forecasts when as few as 20 GNSS stations are used, and outperforms our previous model when additional stations are used. The model performs well even when only the initial 4 min of GNSS data is used.

Octubre de 2022
Linking Earthquake Magnitude-Frequency Statistics and Stress in Visco-Frictional Fault Zone Models
Authors: Adam Beall, Martijn van den Ende et al
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The ability to estimate the likelihood of given earthquake magnitudes is critical for seismic hazard assessment. Earthquake magnitude-recurrence statistics are empirically linked to stress, yet which fault-zone processes explain this link remains debated. We use numerical models to reproduce the interplay between viscous creep and frictional sliding of a fault-zone, for which inter-seismic locking

becomes linked to stress. The models reproduce the empirical stress-dependent earthquake magnitude distribution observed in nature. Stress is related to the likelihood a fault section is near frictional failure, influencing likely rupture lengths. An analytical model is derived of a fault consisting of identical patches, each with a probability of inter-seismic locking. It reproduces a similar magnitude-recurrence relationship, which may therefore be caused by probabilistic clustering of locked fault patches. Contrasts in earthquake statistics between regions could therefore be explained by stress variation, which has future potential to further constrain statistical models of regional seismicity.

Octubre de 2022
This lagoon is effectively a person, says Spanish law that’s attempting to save it
Author: Erik Stokstad
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Only a few years ago, the clear, shallow waters of Mar Menor, a saltwater lagoon off eastern Spain that is Europe’s largest, hosted a robust population of the highly endangered fan mussel, a meter-long bivalve. But in 2016, a massive algal bloom, fueled by fertilizer washing off farm fields, sucked up the lagoon’s oxygen and killed 98% of the bivalves, along with seahorses, crabs, and other marine life.
The suffocating blooms struck again and again, and

millions of dead fish washed onto shore. By last year, local residents—some of whom benefit from tourism to the lagoon—had had enough. Led by a philosophy professor, activists launched a petition to adopt a new and radical legal strategy: granting the 135-square-kilometer lagoon the rights of personhood. Nearly 640,000 Spanish citizens signed it, and on 21 September, Spain’s Senate approved a bill enshrining the lagoon’s new rights.
The new law doesn’t regard the lagoon and its watershed as fully human. But the ecosystem now has a legal right to exist, evolve naturally, and be restored. And like a person, it has legal guardians, including a scientific committee, which will give its defenders a new voice.

Octubre de 2022
Earthquake Focal Mechanisms as a Stress Meter of Active Volcanoes
Author: Yosuke Aoki
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The orientation of faulting associated with volcano-tectonic earthquakes follows the stress field there, as with tectonic earthquakes. Therefore, stress changes associated with volcanic activity change fault orientations or focal mechanisms. Zhan et al. observed temporal changes of focal mechanisms associated with volcanic unrest. They decomposed

the stress field into the ambient differential stress, volcano loading, and the stress change by the dike intrusion; they then evaluated their relative contributions to constrain the magnitude of the ambient differential stress that is consistent with the observation. This study indicates that focal mechanisms can be used to monitor the stress state of an active volcano. Combining focal mechanisms with other geophysical observables, such as seismic anisotropy and geodetic measurements, will give us more precise assessments of the stress state, leading to better forecasts of volcanic activity.

Septiembre de 2022
Glacier Contributions to River Discharge During the Current Chilean Megadrought?
Authors: Michael McCarthy, Fabienne Meier et al
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The current Chilean megadrought has led to acute water shortages in central Chile since 2010. Glaciers have provided vital fresh water to the region's rivers, but the quantity, timing and sustainability of that provision remain unclear. Here we combine in-situ, remote sensing and climate reanalysis data to show that from 2010 to 2018 during the megadrought, unsustainable imbalance ablation of glaciers (ablation not balanced by new snowfall) strongly buffered the late-summer discharge of the Maipo River, a primary source of water to Santiago. If there had been no glaciers, water availability would have been reduced from December through May, with a

31 ± 19% decrease during March. Our results indicate that while the annual contributions of imbalance ablation to river discharge during the megadrought have been small compared to those from precipitation and sustainable balance ablation, they have nevertheless been a substantial input to a hydrological system that was already experiencing high water stress. The water-equivalent volume of imbalance ablation generated in the Maipo Basin between 2010 and 2018 was 740 × 106 m3 (19 ± 12 mm yr−1), approximately 3.4 times the capacity of the basin's El Yeso Reservoir. This is equivalent to 14% of Santiago's potable water use in that time, while total glacier ablation was equivalent to 59%. We show that glacier retreat will exacerbate river discharge deficits and further jeopardize water availability in central Chile if precipitation deficits endure, and conjecture that these effects will be amplified by climatic warming.

Septiembre de 2022
Are Large Earthquakes Preferentially Triggered by Other Large Events?
Authors: Shyam Nandan, Guy Ouillon et al
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Fundamentally related to the ultraviolet (UV) divergence problem in physics, conventional wisdom in statistical seismology is that the smallest earthquakes, which are numerous and often go undetected, dominate the triggering of major earthquakes, making accurate forecasting of the latter difficult if not inherently impossible. Using the

general class of epidemic type aftershock sequence (ETAS) models and rigorous pseudo-prospective experiments, we show that ETAS models featuring a specific magnitude correlation between triggered and triggering earthquakes and a magnitude-dependent Omori kernel significantly outperform simpler ETAS models, in which these features are absent. Using the best forecasting model, we then show that large events preferentially trigger large earthquakes. These findings have far-reaching implications for short-term and medium-term seismic risk assessment and the development of a deeper theory without UV cut-off that is locally self-similar.

Septiembre de 2022
Regionalization in a Global Hydrologic Deep Learning Model: From Physical Descriptors to Random Vectors
Authors: Xiang Li, Ankush Khandelwal et al
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Streamflow prediction is a long-standing hydrologic problem. Development of models for streamflow prediction often requires incorporation of catchment physical descriptors to characterize the associated complex hydrological processes. Across different scales of catchments, these physical descriptors also allow models to extrapolate hydrologic information from one catchment to others, a process referred to as “regionalization”. Recently, in gauged basin scenarios, deep learning models have been shown to achieve state of the art regionalization performance by building a global hydrologic model. These models predict streamflow given catchment

physical descriptors and weather forcing data. However, these physical descriptors are by their nature uncertain, sometimes incomplete, or even unavailable in certain cases, which limits the applicability of this approach. In this paper, we show that by assigning a vector of random values as a surrogate for catchment physical descriptors, we can achieve robust regionalization performance under a gauged prediction scenario. Our results show that the deep learning model using our proposed random vector approach achieves a predictive performance comparable to that of the model using actual physical descriptors. The random vector approach yields robust performance under different data sparsity scenarios and deep learning model selections. Furthermore, based on the use of random vectors, high-dimensional characterization improves regionalization performance in gauged basin scenario when physical descriptors are uncertain, or insufficient.

Septiembre de 2022
Expand native vegetation in Chile’s cities
Authors: Juan L. Celis-Diez and Nélida Pohl
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Agosto de 2022
Could Kı̄lauea's 2020 Post Caldera-Forming Eruption Have Been Anticipated?
Authors: Paul Segall, Kyle Anderson et al
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In 2018 Kı̄lauea volcano erupted a decade's worth of basalt, given estimated magma supply rates, triggering caldera collapse. Yet, less than 2.5 years later Kı̄lauea re-erupted. At the 2018 eruption onset, pressure within the summit reservoir was 20 MPa above magmastatic. By the onset of collapse this

decreased by 17 MPa. Analysis of magma surges at the 2018 fissures, following collapse events, implies excess pressure at the eruption end of only 1 MPa. Given the new vent elevation, 11–12 MPa pressure increase was required to bring magma to the surface in December 2020. Analysis of Global Positioning System data between 8/2018 and 12/2020 shows there was a 73% probability that this condition was met at the onset of the 2020 eruption. Given a plausible range of possible vent elevations, there was a 40%–88% probability of sufficient pressure to bring magma to the surface 100 days before the eruption.

Agosto de 2022
Early Postseismic Deformation of the 2010 Mw 6.9 Yushu Earthquake and Its Implication for Lithospheric Rheological Properties
Authors: Yunguo Chen, Yan Hu et al
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We used the 250-day postseismic displacements derived from Global Positioning System data to explore various postseismic deformation processes of the 14 April 2010 Mw 6.9 Yushu earthquake, including the afterslip of the fault, viscoelastic relaxation in the lower crust and upper mantle, and

the poroelastic rebound. The preferred model shows that the afterslip of the fault decays rapidly with time. Viscoelastic relaxation in the lower crust and upper mantle decays slower with time but affects a broader area. Our results show that the range of the steady-state viscosity in the lower crust is 1019 Pa s. The optimal steady-state viscosity in the lower crust is ∼5 1018 Pa s. We simulate the deformation due to the poroelastic rebound in the top 10 km upper crust. Model results indicate that the poroelastic rebound only produces a few millimeters surface deformation and may be a secondary-order postseismic process.

Agosto de 2022
Deep-learning seismology
Authors: S. Mostafa Mousavi and Gregory C. Beroza
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Seismology is the study of seismic waves to understand their origin—most obviously, sudden fault slip in earthquakes, but also explosions, volcanic eruptions, glaciers, landslides, ocean waves, vehicular traffic, aircraft, trains, wind, air guns, and thunderstorms, for example. Seismology uses those same waves to infer the structure and properties of planetary interiors. Because sources can generate waves at any time, seismic ground

motion is recorded continuously, at typical sampling rates of 100 points per second, for three components of motion, and on arrays that can include thousands of sensors. Although seismology is clearly a data-rich science, it often is a data-driven science as well, with new phenomena and unexpected behavior discovered with regularity. And for at least some tasks, the careful and painstaking work of seismic analysts over decades and around the world has also made seismology a data label–rich science. This facet makes it fertile ground for deep learning, which has entered almost every subfield of seismology and outperforms classical approaches, often dramatically, for many seismological tasks.

Agosto de 2022
Groundwater Flow Rate Prediction From Geo-Electrical Features Using Support Vector Machines
Authors: Kouao Laurent Kouadio, Loukou Nicolas Kouame et al
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The electrical resistivity profiling and the vertical electrical sounding are cheap geophysical subsurface imaging methods. They are most preferred to find groundwater during the campaigns of drinking water supply, especially in developing countries. However, despite the use of both methods, the numerous unsuccessful drillings, due to their wrong locations, have considerably increased the budget of the project and thereby

limiting the number of boreholes previously intended for the population. To solve this problem, a technique was developed using one famous method of artificial intelligence called support vector machines to predict the flow rate (FR) before the drilling operations. To check the efficiency of the proposed approach, the technique was tested with data from a region in the northern part of Cote d’Ivoire (West Africa), which faced a considerable water shortage. The results show 77% capability to predict an accurate FR and 83% when the problem is addressed to the population living in a rural area. Henceforth, the proposed technique can be used to select the right locations expecting to give the recommended FR to minimize the rate of unsuccessful drillings, and indirectly reduce the problem of water scarcity.

Julio de 2022
A New Ocean State After Nuclear War
Authors: Cheryl S. Harrison, Tyler Rohr et al
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If nuclear arsenals were used accidentally or intentionally, they would produce dire consequences for all life on Earth. We simulated climate impacts of nuclear wars in a global Earth system model, focusing on marine impacts. We simulated a US-Russia war and several India-Pakistan wars. In all scenarios, firestorms from nuclear war would deliver soot to the upper atmosphere, blocking out the sun and causing global cooling. Impacts of the nuclear cooling event include expansion of sea ice

into populated coastal areas and decimation of ocean marine life. In all scenarios, the ocean cools rapidly but does not return to the pre-war state when the smoke clears. Instead, the ocean takes many decades to return to normal, and some parts of the ocean would likely stay in the new state for hundreds of years or longer. When the cooling event ends, Arctic sea ice is left in a new state, a sort of “Nuclear Little Ice Age.” Marine ecosystems would be highly disrupted by both the initial perturbation and the resulting new ocean state, resulting in impacts to ecosystem services worldwide, lasting for decades. This study underscores the danger of nuclear war and the long-term impacts to humans and our environment.

Julio de 2022
CREIME—A Convolutional Recurrent Model for Earthquake Identification and Magnitude Estimation
Authors: Megha Chakraborty, Darius Fenner et al
Link: Click here

The detection of earthquakes and rapid determination of parameters such as magnitude is crucial in Earthquake Monitoring and Earthquake Early Warning (EEW). Existing methods used to make such estimations are empirical and require expert analysts to define involved parameters, which is quite challenging. They are also sensitive to noise, which could lead to erroneous results. In this

paper, we propose the Convolutional Recurrent model for Earthquake Identification and Magnitude Estimation (CREIME) which is capable to detect an earthquake within 2 s of the first P wave arrival and provides a first estimate for its magnitude. We test the model on two independent data sets to demonstrate its generalizability. CREIME successfully discriminates between seismic events and noise with an average accuracy of 98% and can estimate first P-arrival time and local magnitude with average root mean squared errors of 0.13 s and 0.65 units, respectively. We also show that CREIME can perform better than traditional methods like STA/LTA and previously published deep learning architectures in the context of rapid characterization.

Julio de 2022
Combining Deep Learning With Physics Based Features in Explosion-Earthquake Discrimination
Authors: Qingkai Kong, Ruijia Wang et al
Link: Click here

This paper combines the power of deep-learning with the generalizability of physics-based features, to present an advanced method for seismic discrimination between earthquakes and explosions. The proposed method contains two branches: a deep learning branch operating directly on seismic waveforms or spectrograms, and a

second branch operating on physics-based parametric features. These features are high-frequency P/S amplitude ratios and the difference between local magnitude (ML) and coda duration magnitude (MC). The combination achieves better generalization performance when applied to new regions than models that are developed solely with deep learning. We also examined which parts of the waveform data dominate deep learning decisions (i.e., via Grad-CAM). Such visualization provides a window into the black-box nature of the machine-learning models and offers new insight into how the deep learning derived models use data to make decisions

Julio de 2022
Atmospheric waves and global seismoacoustic observations of the January 2022 Hunga eruption, Tonga
Authors: ROBIN S. MATOZA, DAVID FEE et al
Link: Click here

The 15 January 2022 climactic eruption of Hunga volcano, Tonga, produced an explosion in the atmosphere of a size that has not been documented in the modern geophysical record. The event generated a broad range of atmospheric waves observed globally by various ground-based and spaceborne instrumentation networks. Most .

prominent was the surface-guided Lamb wave (≲0.01 hertz), which we observed propagating for four (plus three antipodal) passages around Earth over 6 days. As measured by the Lamb wave amplitudes, the climactic Hunga explosion was comparable in size to that of the 1883 Krakatau eruption. The Hunga eruption produced remarkable globally detected infrasound (0.01 to 20 hertz), long-range (~10,000 kilometers) audible sound, and ionospheric perturbations. Seismometers worldwide recorded pure seismic and air-to-ground coupled waves. Air-to-sea coupling likely contributed to fast-arriving tsunamis. Here, we highlight exceptional observations of the atmospheric waves

Julio de 2022
Global fast-traveling tsunamis driven by atmospheric Lamb waves on the 2022 Tonga eruption
Authors: TATSUYA KUBOTA, TATSUHIKO SAITO et al
Link: Click here

On 15 January 2022, the Hunga Tonga-Hunga Ha‘apai volcano erupted, producing tsunamis worldwide including first waves which arrived more than 2 hours earlier than what is expected for conventional tsunamis. We investigated the

generation and propagation mechanisms of the tsunami “forerunner,” and our simulation found that fast-moving atmospheric Lamb waves drove the leading sea height rise whereas the scattering of the leading waves related to bathymetric variations in the Pacific Ocean produced subsequent long-lasting tsunamis. Tsunamis arriving later than the conventionally expected travel time are composed of various waves generated from both moving and static sources, which makes the tsunami, due to this eruption, much more complex and longer-lasting than ordinary earthquake-induced tsunamis.

Julio de 2022
Interplate Coupling and Seismic Potential in the Atacama Seismic Gap (Chile): Dismissing a Rigid Andean Sliver
Authors: V. Yáñez-Cuadra,F. Ortega-Culaciati et al
Link: Click here

We present a novel methodology to investigate the degree of coupling (a measure of the earthquake potential) along the plate interface in subduction zones. Here, we infer deformation and rotation of the continental plate together with the degree of coupling, all using Global Positioning System (GPS) measurements of continental surface deformation.

We apply this approach for the subduction margin formed by the convergence of Nazca and South-American plates, and located between the Chilean cities of Antofagasta and La Serena. We find three regions with high seismic potential, raising concerns for future occurrence of large tsunamigenic earthquakes. The first region is located westward of the rupture area of the 1995 (Mw8.0) Antofagasta earthquake, the second region extends for 200 km between the cities of Taltal and Copiapo and the third region extends for 100 km between the cities of Vallenar and La Serena. Our results highlight the importance of estimating continental strain jointly with coupling models.

Julio de 2022
Role of Poroelasticity During the Early Postseismic Deformation of the 2010 Maule Megathrust Earthquake
Authors: Carlos Peña,Sabrina Metzger et al
Link: Click aquí

Large earthquakes modify the state of stress and pore pressure in the upper crust and mantle. These changes induce stress relaxation processes and pore pressure diffusion in the postseismic phase. The two main stress relaxation processes are postseismic slip along the rupture plane of the earthquake and viscoelastic deformation in the rock volume. These processes decay with time, but can sustain over several years or decades, respectively. The other process that results in volumetric crusta

l deformation is poroelasticity due to pore pressure diffusion, which has not been investigated in detail. Using postseismic surface displacement data acquired by radar satellites after the 2010 Maule earthquake, we show that poroelastic deformation may considerably affect the vertical component of the observed geodetic signal during the first months. Poroelastic deformation also has an impact on the estimation of the postseismic slip, which in turn affects the energy stored at the fault plane that is available for the next event. In addition, shallow aftershocks within the continental crust show a good, positive spatial correlation with regions of increased postseismic pore-pressure changes, suggesting they are linked. These findings are thus important to assess the potential seismic hazard of the segment.

Julio de 2022
Testing of the Seismic Gap Hypothesis in a Model With Realistic Earthquake Statistics
Authors: G.Petrillo, A. Rosso et al
Link: Click here

The seismic gap hypothesis states that large earthquakes preferentially occur in seismogenic fault regions, accordingly termed gap regions, where no large earthquake has been observed for a long time. The validity of the hypothesis implies that it is possible to achieve some insights on the timing of the next large earthquake on the basis of the previous seismic history. However, since the 1990s numerous statistical tests have failed to support this

hypothesis and the current state of art is that many scientists consider the occurrence of large earthquakes fully unpredictable. In our study, we investigate the validity of the seismic gap hypothesis in a theoretical model which reproduces the main statistical features of real seismic occurrence in space, time, and magnitude. We show that, even if the model assumes a homogeneous and constant stress rate, the occurrence of large shocks is very irregular in time and space. Nonetheless, our findings support the hypothesis that an accurate monitoring of the shear stress rate on the fault and of previous seismic activity can be useful to identify the regions which have a higher probability to host the next big shock.

Julio de 2022
Inner Core Rotation Captured by Earthquake Doublets and Twin Stations
Authors: Yi Yang and Xiaodong Song
Link: Click here

The Earth's solid inner core (IC) is surrounded by the liquid outer core and plays an important role in the deep earth dynamics, especially the generation

of the Earth's magnetic field. It is still under debate whether the IC is rotating relative to the Earth's mantle and surface under the Earth's internal torques. Here we provided simple and direct observations that capture the relative rotation of the IC using a fortuitous combination of earthquakes and seismic stations. They allow us to determine the rotation rate as 0.13° per year (or 2.7 km per year at the equator of the IC boundary) faster than the mantle from 1991 to 2010.

Julio de 2022
Groundwater Flow Rate Prediction From Geo-Electrical Features Using Support Vector Machines
Authors: Kouao Laurent Kouadio,Loukou Nicolas Kouame et al
Link: Click here

The electrical resistivity profiling and the vertical electrical sounding are cheap geophysical subsurface imaging methods. They are most preferred to find groundwater during the campaigns of drinking water supply, especially in developing countries. However, despite the use of both methods, the numerous unsuccessful drillings, due to their wrong locations, have considerably increased the budget of the project and thereby

limiting the number of boreholes previously intended for the population. To solve this problem, a technique was developed using one famous method of artificial intelligence called support vector machines to predict the flow rate (FR) before the drilling operations. To check the efficiency of the proposed approach, the technique was tested with data from a region in the northern part of Cote d’Ivoire (West Africa), which faced a considerable water shortage. The results show 77% capability to predict an accurate FR and 83% when the problem is addressed to the population living in a rural area. Henceforth, the proposed technique can be used to select the right locations expecting to give the recommended FR to minimize the rate of unsuccessful drillings, and indirectly reduce the problem of water scarcity.

Julio de 2022
A Probabilistic View on Rupture Predictability: All Earthquakes Evolve Similarly
Authors: Jannes Münchmeyer, Ulf Leser et al
Link: Click here

Earthquakes are among the most destructive natural hazards known to humankind. While earthquakes can not be predicted, it is possible to record them in real-time and provide warnings to locations that the shaking has not reached yet. Warning times usually range from few seconds to tens of seconds. For very large earthquakes, the rupture itself, which is the process sending out the seismic waves, can have a similar duration. Whether the final size of the earthquake, its

magnitude, can be determined while the rupture is still ongoing is an open question. Here we show that this question is inherently probabilistic - how likely is an event to become large? We develop a formulation of rupture predictability in terms of conditional probabilities and a framework for estimating these from data. We apply our approach to two observables: moment rate functions, describing the energy release over time during a rupture, and seismic waveforms at distances of several thousand kilometers. The final earthquake magnitude can only be predicted after the moment rate peak, at approximately half the event duration. Even then, it is impossible to foresee future subevents. Our results suggests that ruptures exhibit a universal initiation behavior, independent of their size

Julio de 2022
Big Data Seismology
Authors: S. J. Arrowsmith,D. T. Trugman et al
Link: Click here

The discipline of seismology is based on observations of ground motion that are inherently undersampled in space and time. Our basic understanding of earthquake processes and our ability to resolve 4D Earth structure are fundamentally limited by data volume. Today, Big Data Seismology is an emergent revolution involving the use of large, data-dense inquiries that is providing new opportunities to make fundamental advances in these areas. This article reviews recent scientific advances enabled by Big Data Seismology through the context of three major drivers: the development of new data-dense sensor systems,

improvements in computing, and the development of new types of techniques and algorithms. Each driver is explored in the context of both global and exploration seismology, alongside collaborative opportunities that combine the features of long-duration data collections (common to global seismology) with dense networks of sensors (common to exploration seismology). The review explores some of the unique challenges and opportunities that Big Data Seismology presents, drawing on parallels from other fields facing similar issues. Finally, recent scientific findings enabled by dense seismic data sets are discussed, and we assess the opportunities for significant advances made possible with Big Data Seismology. This review is designed to be a primer for seismologists who are interested in getting up-to-speed with how the Big Data revolution is advancing the field of seismology.

Junio de 2021
Nuevo mapa de placas tectónicas y provincias geológicas
Fuente: Europapress.es
Link: Click aquí

Hay nuevo mapa global de provincias geológicas y placas tectónicas.
Nuevos modelos que muestran cómo se ensamblaron los continentes brindan más datos sobre la historia de la Tierra y ayudarán a comprender mejor peligros naturales como terremotos y volcanes. "Observamos el conocimiento actual de la configuración de las zonas límite de las placas y la construcción pasada de la corteza continental", dijo en un comunicado el doctor Derrick Hasterok, profesor del Departamento de Ciencias de la Tierra de la Universidad de Adelaide, quien dirigió el equipo que produjo los nuevos modelos...

Comunicado de la Universidad de Adelaida.

Updating our understanding of Earth’s architecture.
“We looked at the current knowledge of the configuration of plate boundary zones and the past construction of the continental crust,” said Dr Derrick Hasterok, Lecturer, Department of Earth Sciences, University of Adelaide who led the team that produced the new models.“The continents were assembled a few pieces at a time, a bit like a jigsaw, but each time the puzzle was finished it was cut up and reorganised to produce a new picture. Our study helps illuminate the various components so geologists can piece together the previous images. “We found that plate boundary zones account for nearly 16 per cent of the Earth's crust and an even higher proportion, 27 per cent, of continents.”

Mayo de 2022
Role of Poroelasticity During the Early Postseismic Deformation of the 2010 Maule Megathrust Earthquake
Authors Carlos Peña, Sabrina Metzger et al
Link: Click here

Large earthquakes modify the state of stress and pore pressure in the upper crust and mantle. These changes induce stress relaxation processes and pore pressure diffusion in the postseismic phase. The two main stress relaxation processes are postseismic slip along the rupture plane of the earthquake and viscoelastic deformation in the rock volume. These processes decay with time, but can sustain over several years or decades, respectively. The other process that results in volumetric crustal

deformation is poroelasticity due to pore pressure diffusion, which has not been investigated in detail. Using postseismic surface displacement data acquired by radar satellites after the 2010 Maule earthquake, we show that poroelastic deformation may considerably affect the vertical component of the observed geodetic signal during the first months. Poroelastic deformation also has an impact on the estimation of the postseismic slip, which in turn affects the energy stored at the fault plane that is available for the next event. In addition, shallow aftershocks within the continental crust show a good, positive spatial correlation with regions of increased postseismic pore-pressure changes, suggesting they are linked. These findings are thus important to assess the potential seismic hazard of the segment.

Mayo de 2022
How Credible Are Earthquake Predictions Based on TEC Variations?
Authors: R. Ikuta and R. Oba.
Link: Click here

Fluctuations in the ionospheric electron have been considered as a possible precursor of earthquakes. Papers by Liu et al. (2018, https://doi.org/10.3319/tao.2018.03.11.01) and Le et al. (2011, https://doi.org/10.1029/2010ja015781) are important as positive reports evaluating the precursory behavior from a statistical point of view. Liu et al. (2018, https://doi.org/10.3319/tao.2018.03.11.01) reported that the electrons increases/decreases at specific leading times before 62 large earthquakes occurred in China. Earthquake alarms based on these anomalies showed a good performance. Le et al. (2011, https://doi.org/10.1029/2010ja015781)

reported that rate of days with large fluctuation of electron contents increases before shallower and larger earthquakes, based on global 736 large earthquakes over 8 years. We test their methods by numerical experiments generating random earthquakes. Even for the random earthquakes never related to ionospheric processes, the method by Liu et al. (2018, https://doi.org/10.3319/tao.2018.03.11.01) achieves a high alarm performance comparable to their original paper. Regarding Le et al. (2011, https://doi.org/10.1029/2010ja015781), the rate of days with large electron fluctuation calculated by their equation increases before shallower and larger earthquakes even though the given rate is constant for all the earthquakes. These results show that the relation between ionospheric processes and earthquakes reported by the both studies should be artifact derived from the methodology.

Mayo de 2022
How Low Should We Alert? Quantifying Intensity Threshold Alerting Strategies for Earthquake Early Warning in the United States
Authors: Jessie K. Saunders, Sarah E. Minson et al
Link: Click here

In the ShakeAlert Earthquake Early Warning (EEW) System https://www.shakealert.org/, ground-motion models are used to rapidly calculate the distribution of shaking caused by an earthquake, where the resulting shaking distribution is used to determine the size of the EEW alert region. However, because these ground-motion models cannot account for shaking variabilities, if the EEW alert region is determined using the same shaking level as the

minimum shaking level that requires an alert (the target level), the alert region will be too small to include all locations that experience target level shaking, resulting in missed alerts. One solution is to expand the size of the alert region by using a shaking level that is lower than the target level in the alert region calculation. This action comes with a tradeoff: missed alerts cannot be decreased without also increasing over-alerting, that is, increasing alerts to locations that experience lower than target shaking levels. Here, we determine the preferred alerting levels for a range of target shaking levels by examining this tradeoff using a catalog of United States West Coast earthquakes. We find the preferred alerting levels can reduce missed alerts while keeping over-alerting to locations that will still feel some shaking from the earthquake.

Abril de 2022
Estimating Hydraulic Properties of the Shallow Subsurface Using the Groundwater Response to Earth and Atmospheric Tides: A Comparison With Pumping Tests
Authors: Rémi Valois, Gabriel C. Rau et al
Link: Click here

Estimating subsurface hydraulic properties using the groundwater (GW) response to Earth tides (ET) and atmospheric pressure is an alternative approach to pumping or slug tests (passive vs. active methods). Yet testing the applicability of models under different subsurface conditions and comparing results with traditional hydraulic methods are lacking. We first review the assumptions of analytical models used to evaluate the GW response to ET and their applicability in unconfined to confined conditions. Second, we develop a robust approach to select the right model based on amplitude and phase pattern of the diurnal and semi-diurnal tides. Third, based on earlier works we

develop an approach to derive the hydraulic conductivity of the screened interval using the GW response to atmospheric tides, here named “atmospheric slug test” (AST). We estimate transmissivity and storativity at three shallow aquifers in Cambodia and compare the results with subsurface properties derived from pumping tests (PT). Transmissivity values from AST and PT are in good agreement. However, we show that storativity values derived from ET show large discrepancies if borehole skin effects are ignored. Further, the GW response to ET exhibits a strong decay in amplitude with frequency while maintaining close to zero and positive phase shifts. When supplemented with the calculated transmissivity values, none of the analytical models was able to reproduce this frequency dependent behavior. Our work emphasizes the need for evaluating passive methods robustness under different subsurface conditions. Further work is required to understand the frequency dependent GW response to natural or artificial forces.

Abril de 2022
Comparison of Seven Weibull Distribution Models for Predicting Relative Hydraulic Conductivity
Authors:Jipeng Shan, Zhenlei Yang et al
Link: Click here

Modeling water flow in unsaturated soils requires accurate characterization of relative hydraulic conductivity (RHC) and water retention curve (WRC).
The overall objective of this study is to investigate the performances of seven Weibull distribution models for predicting RHC using the Assouline et al. (1998), WRC. Specifically, a new RHC model

was proposed via the approach of Assouline (2001),
with the assumptions of Burdine (1953). The proposed model, together with the other six models, was then compared with data from 40 soils to explore their predictive performances for RHC. The results showed that the proposed model provides the best agreement with measured data and yields a 16.1% improvement in RHC prediction compared to the widely used Assouline et al. (1998) model. The proposed model can be used as RHC parameterization for water flow modeling in the unsaturated zone.

Marzo de 2022
Volcano-tectonic control of Cumbre Vieja
Author: Pablo J. González
Link: Click here

The 2021 Cumbre Vieja volcano eruption started on 19 September 2021 and ended after 85 days and 8 hours, becoming La Palma’s longest and most voluminous (more than 200 million m3) eruption in historical times. Because of the good monitoring effort, this eruption will allow the testing of a wide range of scientific ideas, from the importance of a possible 436-year-long supercycle of duration-

decreasing eruptions to using the geophysical observations to understand how magma is stored and migrates within a vertically extended upper mantle and crustal magmatic system (1). These types of magmatic and volcanological information will transform volcano eruption hazard assessment and long-term planning (2). Moreover, a key research question remains as to why this eruption did not create a catastrophic volcano flank collapse as perhaps expected (3). The answer may be tied to its distinct volcano-tectonic features and, in particular, an unexpected fissure system that opened during the eruption’s last phase.

Marzo de 2022
Thermolab: A thermodynamics laboratory for non-linear transport processes in open systems
Authors: J. C. Vrijmoed and Y. Y. Podladchikov
Link: Click here

The behavior of Earth materials, rocks, minerals, melts, fluids and gases is important to predict physical processes in the Earth with computer models. The purpose of this is to study how the changes of variables such as fluid and solid composition influence the diffusion, fluid flow and reaction in rocks. Here we present a set of computer codes, called Thermolab, to calculate important physical properties such as density and chemical composition of solids, fluids and melts in chemical

equilibrium. The calculations are based on the Gibbs energy that exists for every material. We use computer codes, written in MATLAB/OCTAVE language, to show how this Gibbs energy is calculated and used to compute chemical equilibrium and find the physical properties such as density, and chemical composition. We discuss techniques for accurate calculation of chemical equilibrium and physical properties in real rocks. Finally, we use Thermolab to formulate a computer model of fluids reacting with rocks. We find that chemical composition of the fluid and rock strongly affect the speed and shape of the boundary between reacted and unreacted rock. Thermolab can be used in phase growth models to investigate the way in which rocks develop towards equilibrium.

Marzo de 2022
An End-to-End Earthquake Detection Method for Joint Phase Picking and Association using Deep Learning
Authors: Weiqiang Zhu,Kai Sheng Tai et al
Link: Click here

Earthquakes are monitored using multiple seismic stations in a seismic network. A typical earthquake detection workflow consists of two stages: first, earthquake signals are detected at each station; then these detections are associated across multiple stations to determine whether an earthquake occurred. These two stages are

independently optimized in conventional algorithms, thus the overall earthquake detection performance can be limited due to information loss between each stages jointly. In this work, we proposed an end-to-end approach to jointly optimize both stages (i.e., signal-station detection and multi-station association) inside one combined neural network architecture. The results on the 2019 Ridgecrest, CA earthquake sequence show that our end-to-end approach achieves earthquake detection accuracy rivaling that of other state-of-the-art approaches. Because our approach preserves information across tasks in the detection pipeline, it has the potential to outperform approaches that do not.

Marzo de 2022
The state of pore fluid pressure and 3D megathrust earthquake dynamics
Authors: Elizabeth H. Madden,Thomas Ulrich et al
Link: Click here

Large volumes of fluid can lead to high pressures that weaken rocks in fault zones and influence earthquake rupture. While fluids are critical to understanding behavior at subduction zones, where the largest earthquakes in the world occur and where tsunami generation increases hazard, measuring fluid and fluid pressure directly across

an entire megathrust currently is not possible. Here, we use supercomputers to model the devastating 2004 Mw 9.1 Sumatra-Andaman earthquake in 3D in order to isolate the role of fluid pressure on earthquake behavior. By first building a reliable base model and then varying fluid pressure to generate 6 earthquake scenarios, we find that fluid pressure is likely very high, and also that the way that fluid pressure varies with depth can greatly influences the earthquake and associated hazard. Fluid pressure controls location of the largest and fastest fault slip along the megathrust, and the possibility for a devastating tsunami.

Marzo de 2022
Spatiotemporal geostatistical analysis of groundwater level in aquifer systems of complex hydrogeology
Authors: Emmanouil A. Varouchakis, Carolina Guardiola-Albert et al
Link: Click here

A space-time data analysis was conducted to generate reliable spatial maps of groundwater level variability and to identify groundwater level patterns over the island of Crete, Greece. Two innovative tools were applied to find the optimal distance and interdependence between observations where hydro-geological discontinuities are present in the aquifer system. The first is an alternative to common

distance metric, which in everyday language is called the taxi-cab distance and the second is a function that identifies the number of the connected observations within the same distance creating a number of pairs with similar characteristics under a series of mathematical parameters that can model the increments and /or decrement of the physical variable values at that points. The outcome is a map that presents the variability of groundwater level in the entire island notifying areas under high risk of groundwater resources shortage. The presentation of groundwater level status in the entire island strengthens water resources planning and management and connection to hydro meteorological effects. The proposed methodology will be especially valuable in semi-arid areas where groundwater is the primary source of water.

Marzo de 2022
Experimental ELF/VLF Wave Communication with Excitation by Ionosphere Modulated Heating
Authors: Jutao Yang,Qingliang Li,Hong Lu et al
Link: Click here

In this study, we present experimental results from the European Incoherent Scatter Scientific Association for (EISCAT) communication using extremely low frequency/very low frequency (ELF/VLF) electromagnetic (EM) waves excited via amplitude-modulated auroral electrojet. Electromagnetic wave signals with modulation frequencies of 2017 Hz and 3517 Hz were encoded by quaternary phase shift keying (QPSK), and three

transmission rates (20 bps, 100 bps, and 400 bps) were selected. By analyzing the ELF/VLF EM wave intensity at the receiver, we found that the relationship between the ELF/VLF wave intensity and natural current intensity was affected by the background ionospheric state. Combined with previously published experimental results from High-frequency Active Auroral Research Program (HAARP) communications, the relationship between bit error rate (BER) and signal-to-noise ratio (Eb/N0) at the receiver was also analyzed. The results showed that when Eb/N0 > 8 dB, BER = 0 and when Eb/N0 < 8 dB, the relationship between BER and Eb/N0 satisfies the complementary error function, and the accurate relationship between them is given via experimental data fitting.

Marzo de 2022
How Low Should We Alert? Quantifying Intensity Threshold Alerting Strategies for Earthquake Early Warning in the United States
Authors: Jessie K. Saunders, Sarah E. Minson et al
Link: Click here

In the ShakeAlert Earthquake Early Warning (EEW) System, ground-motion models are used to rapidly calculate the distribution of shaking caused by an earthquake, where the resulting shaking distribution is used to determine the size of the EEW alert region. However, because these ground-motion models cannot account for shaking variabilities, if the EEW alert region is determined using the same shaking level as the minimum shaking level that requires an alert (the target level), the alert region

will be too small to include all locations that experience target level shaking, resulting in missed alerts. One solution is to expand the size of the alert region by using a shaking level that is lower than the target level in the alert region calculation. This action comes with a tradeoff: missed alerts cannot be decreased without also increasing over-alerting, that is, increasing alerts to locations that experience lower than target shaking levels. Here, we determine the preferred alerting levels for a range of target shaking levels by examining this tradeoff using a catalog of United States West Coast earthquakes. We find the preferred alerting levels can reduce missed alerts while keeping over-alerting to locations that will still feel some shaking from the earthquake.

Febrero de 2022
The Three Rs: Resolving Respiration Robotically in Shelf Seas
Authors: C. A. J. Williams, C. E. Davis et al
Link: Click here

Oxygen levels in the ocean are decreasing. Oxygen is needed by almost all life in the oceans, thus low oxygen levels can result in dramatic changes to marine ecosystems. The decrease in oxygen levels is particularly alarming in the coastal ocean or “shelf sea” (the region between the land and the deep open ocean), which supports the majority of global fisheries (over 90%). Therefore, there is both an urgent societal and an environmental need to better

understand processes influencing oxygen levels in the coastal ocean, such as physical water circulation and mixing, and biological oxygen production and consumption. Here we present turbulent mixing data collected over 40 days in a typical shelf sea using an unmanned, autonomous underwater vehicle (AUV) called an ocean glider. We use this data combined with oxygen data to calculate the contribution of physical oxygen fluxes to the observed change in oxygen, and from this deduce how much of the change was driven by biology. We prove that AUVs may be used as an effective method for monitoring oxygen dynamics and that this can aid responsible marine management in shelf seas.

Febrero de 2022
How Do Perceptions of Risk Communicator Attributes Affect Emergency Response? An Examination of a Water Contamination Emergency in Boston, USA
Authors: F. Aden-Antoniów, W. B. Frank et al
Link: Click here

Earthquakes rupture seismic faults when the fault can no longer support the stress built up by tectonic motion. Earthquake catalogs are thus a window into the tectonic processes that occur at depth. Background earthquakes occur spontaneously from tectonic stresses, creating a stress perturbation that generally triggers aftershocks. These aftershocks

can also trigger other aftershocks, creating aftershock sequences that may dominate earthquakes catalogs. The accurate determination of the background earthquakes' occurrence is crucial, as it directly relates to the fault's stress state and consequently favors a better understanding of the seismic hazard. To solve this problem, we develop and train a machine-learning model to classify background earthquakes and aftershocks in earthquake catalogs. After training our model on synthetic earthquakes catalogs, we apply it to several real cases from New Zealand and Southern California to show the effectiveness of our approach. Our results suggest that our method is adaptable to any region, independent of the style of seismicity or the catalog duration.

Febrero de 2022
Radiocarbon in the Land and Ocean Components of the Community Earth System Model
Authors: Tobias Frischknecht, Altug Ekici et al
Link: Click here

Large amounts of the carbon-isotope 14C, entering Earth's carbon cycle, were produced in the atmosphere by atomic bomb tests in the 1950s and 1960s. Here, we forced the ocean and land components of the Community Earth System Model with atmospheric 14CO2 over the historical period to constrain overturning time scales and fluxes. The uptake of bomb 14C by the land model is lower than observation-based estimates. This mismatch is likely linked to too-low 14C uptake by vegetation as the model overestimates 14C/C ratios of modern soils. This suggests model biases in forest productivity or wood carbon allocation and turnover,

and, in turn, a bias in the forest sink of anthropogenic carbon. The ocean model matches the observation-based global bomb 14C inventories when applying the quadratic relationship between gas transfer piston velocity and wind speed of Wanninkhof (2014), https://doi.org/10.4319/lom.2014.12.351 and the wind products from Large and Yeager or the Japanese Reanalysis Project. Simulated natural radiocarbon ages in the deep ocean are many centuries older than data-based estimates, indicating too slow deep ocean ventilation. The sluggish circulation causes large biases in biogeochemical tracers and implies a delayed deep ocean uptake of heat and carbon in global warming projections. Our study suggests that 14C observations are key to constrain carbon fluxes and transport timescales for improved representations of land and ocean biogeochemical cycles and Earth system model projections.

Febrero de 2022
A Simulation-Based Framework for Earthquake Risk-Informed and People-Centered Decision Making on Future Urban Planning
Authors: Gemma Cremen, Carmine Galasso et al
Link: Click here

Numerous approaches to earthquake risk modeling and quantification have already been proposed in the literature and/or are well established in practice. However, most of these procedures are designed to focus on risk in the context of current static exposure and vulnerability, and are therefore limited in their ability to support decisions related to the future, as yet partially unbuilt, urban landscape. We propose an end-to-end risk modeling framework that explicitly addresses this specific challenge. The framework is designed to consider the earthquake

(ground-shaking) risks of tomorrow's urban environment, using a simulation-based approach to rigorously capture the uncertainties inherent in future projections of exposure as well as physical and social vulnerability. The framework also advances the state-of-practice in future disaster risk modeling by additionally: (a) providing a harmonized methodology for integrating physical and social impacts of disasters that facilitates flexible characterization of risk metrics beyond physical damage/asset losses; and (b) incorporating a participatory, people-centered approach to risk-informed decision making. The framework is showcased using the physical and social environment of an expanding synthetic city. This example application demonstrates how the framework may be used to make policy decisions related to future urban areas, based on multiple, uncertain risk drivers.

Febrero de 2022
Lasting Effects of Soil Compaction on Soil Water Regime Confirmed by Geoelectrical Monitoring
Authors:
Alejandro Romero-Ruiz, Niklas Linde et al
Link: Click here

Despite its importance for hydrological and ecological soil functioning, characterizing, and quantifying soil structure in the field remains a challenge. Traditional characterization of soil structure often relies on point measurements, more recently, we advanced the use of minimally invasive geophysical methods that operate at plot-field scales and provide information under natural conditions. In this study, we expand the application using geoelectrical and time-domain reflectometry (TDR) monitoring of soil water dynamics to infer impacts of compaction on soil structure and function. We developed a modeling scheme combining a new pedophysical model of soil

electrical conductivity and a soil-structure-informed one-dimensional water flow and heat-transfer model. The model was used to interpret Direct Current (DC)-resistivity and TDR monitoring data in compacted soils at the Soil Structure Observatory (SSO) located in the vicinity of Zürich, Switzerland. We find that (1) soil compaction leads to a persistent decrease in soil electrical resistivity and (2) that compacted soils are typically drier than non-compacted soils during long drying events. The main decrease in electrical resistivity is attributed to decreasing macroporosity and increasing connectivity of soil aggregates due to compaction. Higher water losses in compacted soils are explained in terms of enhanced evaporation. Our work advances characterization of soil structure at the field scale with electrical methods by offering a physically based explanation of the impact of soil compaction on electrical properties and by interpreting DC-resistivity data in terms of soil water dynamics.

Febrero de 2022
Net-Zero CO2 Germany—A Retrospect From the Year 2050
Authors: Nadine Mengis, Aram Kalhori et al
Link: Click here

Here a net-zero-2050 Germany is envisioned by combining analysis from an energy-system model with insights into approaches that allow for a higher carbon circularity in the German system, and first results from assessments of national carbon dioxide removal potentials. A back-casting

perspective is applied on how net-zero Germany could look like in 2050. We are looking back from 2050, and analyzing how Germany for the first time reached a balance between its sources of CO2 to the atmosphere and the anthropogenic sinks created. This would consider full decarbonization in the entire energy sector and being entirely emission-free by 2050 within three priorities identified as being the most useful strategies for achieving net-zero: (a) Avoiding- (b) Reducing- (c) Removing emissions. This work is a collaboration of interdisciplinary scientists with the Net-Zero-2050 cluster of the Helmholtz Climate Initiative HI-CAM.

Enero de 2022
How Do Perceptions of Risk Communicator Attributes Affect Emergency Response? An Examination of a Water Contamination Emergency in Boston, USA
Authors: Amy Hyman, Sudha Arlikatti et al
Link: Click here

A water main break that contaminated the Boston area's water distribution system prompted a four-day “boil water” order. To understand risk communication during this incident, 600 randomly sampled residents were mailed questionnaires, yielding 110 valid responses. This article describes how perceptions of different social stakeholders influenced whether respondents complied with the Protective Action Recommendation—PAR (i.e., drank boiled water), took alternative protective actions (i.e., drank bottled water or/and self-

chlorinated water), or ignored the threat (i.e., continued to drink untreated tap water). Respondents perceived technical authorities (i.e., water utility, public health, and emergency management) to be higher on three social influence attributes (hazard expertize, trustworthiness, and protection responsibility) than public (i.e., news media, elected officials) and private (i.e., self/family, peers, and personal physicians) intermediate sources. Furthermore, respondents were most likely to comply with the PAR if they perceived authorities and public intermediates to be high on all three attributes and if they had larger households and lower income. Contrarily, they were more likely to take alternative actions if they were younger and had higher levels of income, risk perception, and emergency preparedness. These results underscore the need for technical authorities to develop credibility with their potential audiences before a crisis occurs.

Enero de 2022
On the relative temperatures of Earth’s volcanic hotspots and mid-ocean ridges
Authors: Xiyuan Bao, Carolina R. Lithgow-Bertelloni et al
Link: Click here

Volcanic hotspots are thought to be fed by hot, active upwellings from the deep mantle, with excess temperatures (Tex) ~100° to 300°C higher than those of mid-ocean ridges. However, Tex estimates are limited in geographical coverage and often

inconsistent for individual hotspots. We infer the temperature of oceanic hotspots and ridges simultaneously by converting seismic velocity to temperature. We show that while ~45% of plume-fed hotspots are hot (Tex ≥ 155°C), ~15% are cold (Tex ≤ 36°C) and ~40% are not hot enough to actively upwell (50°C ≤ Tex ≤ 136°C). Hot hotspots have an extremely high helium-3/helium-4 ratio and buoyancy flux, but cold hotspots do not. The latter may originate at upper mantle depths. Alternatively, the deep plumes that feed them may be entrained and cooled by small-scale convection.

Enero de 2022
Link: Click here


Enero de 2022
A Simulation-Based Framework for Earthquake Risk-Informed and People-Centered Decision Making on Future Urban Planning
Authors: Gemma Cremen, Carmine Galasso et al
Link: Click here

Numerous approaches to earthquake risk modeling and quantification have already been proposed in the literature and/or are well established in practice. However, most of these procedures are designed to focus on risk in the context of current static exposure and vulnerability, and are therefore limited in their ability to support decisions related to the future, as yet partially unbuilt, urban landscape. We propose an end-to-end risk modeling framework that explicitly addresses this specific challenge. The framework is designed to consider the earthquake

(ground-shaking) risks of tomorrow's urban environment, using a simulation-based approach to rigorously capture the uncertainties inherent in future projections of exposure as well as physical and social vulnerability. The framework also advances the state-of-practice in future disaster risk modeling by additionally: (a) providing a harmonized methodology for integrating physical and social impacts of disasters that facilitates flexible characterization of risk metrics beyond physical damage/asset losses; and (b) incorporating a participatory, people-centered approach to risk-informed decision making. The framework is showcased using the physical and social environment of an expanding synthetic city. This example application demonstrates how the framework may be used to make policy decisions related to future urban areas, based on multiple, uncertain risk drivers.

Enero, 2022
Terremoto de Valdivia de 1737, duración: 25 minutos
Por Reina Campos Caba - Meteored

Revelan enigmático evento ocurrido en Chile en el año 1737
De acuerdo a una reciente investigación que fue publicada por la revista Nature, Communications Earth & Environmental (NCEE), Valdivia fue azotada por un gran terremoto. Y no sólo eso, ya que tuvo la compañía de la erupción del volcán Osorno, en conjunto con hundimientos de tierra y desbordes de ríos.
Este descubrimiento es de suma relevancia, pues los registros históricos son la piedra angular para la predicción de la frecuencia con que ocurran los tsunamis en un lugar determinado. Hasta antes de esta investigación, sólo tres terremotos habían generado un tsunami en la zona sur de Chile desde la década de 1570.
¿Los resultados de la investigación cambian nuestra realidad como país ante este tipo de eventos naturales? La respuesta es sí, ya que esos datos revelan que hubo más tsunamis de lo que se pensaba. Eso cambia la frecuencia a una media estimada de ciento treinta años.
El equipo de investigación, integrado por las Universidades de York y Northumbria, Reino Unido, trabajaron con sedimentos. Específicamente, con las marismas de Chaihuín, ubicado cerca de Valdivia (epicentro del terremoto) ¿El día? fue un 24 de diciembre de 1737.
Hecho curioso de este terremoto: el evento principal, tuvo una duración de veinticinco minutos. El sólo hecho de imaginar todo el tiempo que estuvieron esas personas soportando la angustia del sismo, hace aún más relevante esta investigación.

Diciembre de 2021
Distribution and Dimethylsulfoniopropionate Degradation of Dimethylsulfoniopropionate-Consuming Bacteria in the Yellow Sea and East China Sea
Authors: Juan Yu, Sheng-Hui Zhang et al
Link: Click here

Bacterial catabolism of dissolved dimethylsulfoniopropionate (DMSP) (DMSPd) is an important sink of DMSP in seawater. There are two DMSPd consumption pathways (DMSP cleavage and demethylation), and the dimethylsulfide (DMS)-

producing (DMSP cleavage) pathway involves DMSP lyase activity (DLA). In this study, we evaluated the DMS, DMSP, DMSP-consuming bacteria (DCB) abundance, and DLA distributions in the seawater of the Yellow Sea and East China Sea. DCB in the seawater were isolated and identified. The degradation of DMSPd by and the bioavailability of the other five organic carbon analog of DMSP (including glycine betaine, acrylic acid, dimethylsulfoxide, monomethylamine, and dimethylamine) to DCB Bacillus sp. YES023 were investigated.

Diciembre de 2021
Design of a low-cost electrical resistivity meter for near surface surveys
Authors: M. de la Vega, M. V. Bongiovanni et al
Link: Click here

A programmable automated electrical resistivity meter was designed and constructed. The device was created to perform near surface studies, particularly for archaeogeophysical target characterization. Real field and laboratory model studies can be performed changing the current input of the device. The equipment consists of two independent devices, each one with its own microcontroller platform. They are interconnected through serial data transfer protocol. The first device, works as a resistivity meter where the ABMN

electrode positions are programmed and permits the interaction with the user. The second one, connects the current and voltage channels to the programmed electrode positions.
A physical model and field measurements were performed with different electrode configurations such as Dipole-Dipole, Werner-Schlumberger and Wenner γ112 in order to verify the performance of the automated electrical resistivity meter. The measurements give mean relative standard deviation values between 0.6% and 5.5% and data inversion convergence between 1.3% and 7.2%.
Even though this open source and low cost electrical resistivity meter was design primarily for archaeogeophysical studies, it could be adapted to other geophysical issues such as contamination plumes detection and characterization, tunnel detection, etc.

Diciembre de 2021
Explore Spatio-Temporal Learning of Large Sample Hydrology Using Graph Neural Networks
Authors: Alexander Y. Sun, Peishi Jiang et al
Link: Click here

Streamflow forecasting represents a long-standing problem in water resources management. Only a small fraction of river segments around the world are gauged. Hydrologists typically rely on other readily available catchment attributes (e.g., elevation, slope, climatology, and vegetation) to establish hydrological similarity between gauged and ungauged basins, and then "transfer" the information through a model to predict flow in ungauged basins. This work explores the use of graph neural networks (GNNs) to perform end-to-

end streamflow forecasting for both gauged and ungauged basins. GNN is a type of machine learning algorithm that uses nodes and edges to represent physical entities. Specifically, GNNs provide an effective means for representing and learning unstructured data sets (e.g., data sets from monitoring networks). We formulated GNN models to perform end-to-end spatiotemporal learning, which generates streamflow forecast at all basins. We demonstrated the feasibility of using GNN for prediction at ungauged basins, which remains one of the challenging problems in hydrology. Our systematic benchmarking results, including a large number of sensitivity studies, show that GNN models performed well on a large sample hydrology data set. An Explainable AI technique is used to interpret the learned results.

Diciembre de 2021
Mean Squared Error, Deconstructed
Authors: Timothy O. Hodson, Thomas M. Over et al
Link: Click here

Models are essential scientific tools for explaining and predicting phenomena ranging from weather and climate, to health outcomes, to economic development, to the origins of the universe, and testing competing models is one of the most basic scientific activites. Yet, how scientists evaluate and justify their models can be inconsistent or even

arbitrary. Traditionally, one performance metric—such as mean squared error—is used to identify the best model, but one metric provides little insight into what aspects of a model are “good” or “bad.” This paper proposes a basic language for expressing different aspects of a model's performance. On one hand, this is useful for determining which aspects of model may require revision, but it also allows the modeler to separate out the best elements among several models and combine them to form an ensemble, analogous to how an audio engineer mixes together multiple tracks to form the best rendition of a musical piece.

Noviembre de 2021
Scaling Deep Decarbonization Technologies
Authors: K. J. Holmes,E. Zeitler et al
Link: Click here

The US and world economies must drastically lower or eliminate emission of greenhouse gases to keep the impacts of climate change manageable. Eliminating energy sector carbon dioxide emissions, the most important greenhouse gas, is required for approaching net-zero emissions. This is known as “deep decarbonization.” The development of new technologies emitting little or zero carbon dioxide may not be the most important

challenge to deep decarbonization. Rather, massive deployment of technologies and the wider policy and societal transformations linked to profound changes in the energy system are likely to pose greater challenges. To better understand these issues for the United States and needs for guidance on the topic, the National Academy of Sciences, Engineering, and Medicine gathered energy system modelers, business and technology leaders, social scientists, and policy experts at a workshop to discuss a broad spectrum of scale-up issues associated with this transformation. This study shares and expands on the learning at the workshop.

Noviembre de 2021
Microseismicity Appears to Outline Highly Coupled Regions on the Central Chile Megathrust
Authors: C. Sippl,M. Moreno et al
Link: Click here

We compiled a novel microseismicity catalog for the Central Chile megathrust (29°–35°S), comprising 8,750 earthquakes between April 2014 and December 2018. These events describe a pattern of three trenchward open half-ellipses, consisting of a continuous, coast-parallel seismicity band at 30–45 km depth, and narrow elongated seismicity clusters that protrude to the shallow megathrust and separate largely aseismic regions along strike. To

test whether these shapes could outline highly coupled regions (“asperities”) on the megathrust, we invert GPS displacement data for interplate locking. The best-fit locking model does not show good correspondence to seismicity, possibly due to lacking resolution. When we prescribe high locking inside the half-ellipses, however, we obtain models with similar data fits that are preferred according to the Bayesian Information Criterion (BIC). We thus propose that seismicity on the Central Chile megathrust may outline three adjacent highly coupled regions, two of them located between the rupture areas of the 2010 Maule and the 2015 Illapel earthquakes, a segment of the Chilean margin that may be in a late interseismic stage of the seismic cycle.

Noviembre de 2021
A Spherical Harmonic Model of Earth's Lithospheric Magnetic Field up to Degree 1050
Authors: E. Thébault,G. Hulot,B. Langlais et al
Link: Click here

The magnetic field of the Earth's results from the superposition of various internal and external fields. The field produced by magnetized rocks in the Earth's lithosphere brings essential constraints on the crust composition, dynamics, and history. Its

description requires magnetic measurements in all regions of the world at different altitudes. Satellite measurements detect well the large Earth's magnetic field structures but are too far to detect the smaller ones that are weak at high altitudes. Historical marine and airplane data can be used to complement the satellite observations. Considering all these data makes it possible to build a global model that represents the magnetic field generated within the Earth's crust with a global 40 km horizontal spatial resolution.

Noviembre de 2021
Local Hydraulic Resistance in Heterogeneous Porous Media
Authors: Quirine Krol,Itzhak Fouxon et al
Link: Click here

We examine the validity of the commonly used Hagen-Poiseuille model of local resistance of porous media using direct numerical simulations. We provide theoretical arguments that highlight possible limitations of this model and formulate a

new constitutive model that is based on the circularity of iso-pressure surfaces. We compare the performance of both models on three different three-dimensional artificial porous media. We show that the new model improves the root-mean-squared-relative error from x for the three porous media respectively. We anticipate that our approach may find broad application in network models of porous media that are typically build from 3D images with intricate pore geometries.

Octubre de 2021
Soil Classification: A New Approach for Grouping Soils Using Unsaturated Hydraulic Conductivity Data
Authors: Behzad Ghanbarian and Brandon A. Yokeley
Link: Click here

Grouping soils based on similarities in their textural, taxonomic, and/or structural properties has broad applications to pedology, hydrology, and soil science. In this study, we present a new approach for classifying soils using hydraulic conductivity data.

We apply concepts from critical path analysis and calculate critical pore sizes at various water saturations from the unsaturated hydraulic conductivity curves. Soils with similar critical pore size at the same effective water saturation are then grouped into the same class. To demonstrate the practical application of the proposed soil classification method, we use 102 samples including nine soil textures from the UNSODA database. Applying a curve clustering method, we find eight different soil classes within the studied data set.

Octubre de 2021
Deep Learning for Geophysics: Current and Future Trends
Authors: Siwei Yu and Jianwei Ma
Link: Click here

Recently deep learning (DL), as a new data-driven technique compared to conventional approaches, has attracted increasing attention in geophysical community, resulting in many opportunities and challenges. DL was proven to have the potential to predict complex system states accurately and relieve the “curse of dimensionality” in large temporal and spatial geophysical applications. We address the basic concepts, state-of-the-art literature, and future trends by reviewing DL

approaches in various geosciences scenarios. Exploration geophysics, earthquakes, and remote sensing are the main focuses. More applications, including Earth structure, water resources, atmospheric science, and space science, are also reviewed. Additionally, the difficulties of applying DL in the geophysical community are discussed. The trends of DL in geophysics in recent years are analyzed. Several promising directions are provided for future research involving DL in geophysics, such as unsupervised learning, transfer learning, multimodal DL, federated learning, uncertainty estimation, and active learning. A coding tutorial and a summary of tips for rapidly exploring DL are presented for beginners and interested readers of geophysics.

Septiembre de 2021
Can Deep Learning Predict Complete Ruptures in Numerical Megathrust Faults?
Authors: David Blank and Julia Morgan et al
Link: Click here

We propose a binary classification model rooted in state-of-the-art deep learning techniques to predict whether or not complete-interface rupture is imminent along a numerical megathrust fault. The models are trained on labeled 2D space-time input features taken from the synthetic fault system. We

contrast the performance of two neural networks trained on three types of data, to determine the relative predictive power of each. The neural networks are able to discriminate imminent complete rupture precursors from everything else, thus providing a relative size and time forecast. Vertical displacements along the fault demonstrate relatively good predictive power. The results confirm previous qualitative observations that precursory deformation scales with upcoming event size, consistent with the preslip model for earthquake nucleation. The methods we propose are adaptable and can be modified to use 3D data in the future.

Septiembre de 2021
Controlling Induced Earthquake Magnitude by Cycled Fluid Injection
Authors: J. B. Zhu, J. Q. Kang et al
Link: Click here

The possibility of controlling induced earthquake magnitude through managed metering of water injection has yet to be rationalized. Mechanisms of reducing magnitudes of induced events through cycled fluid injection remain unclear. To explore such mechanisms and this possibility, we report experiments with water injection into laboratory faults. Water injection results in early triggering for

both single and cycled injection. However, the maximum moment magnitude and total energy of the repeating induced earthquakes during cycled water injection are both lower than those of induced earthquakes induced with continuous injection and for natural earthquakes without water injection. Higher permeability of the host reduces the number of injection-induced earthquakes but increases their moment. With an increasing number of water injection cycles, both maximum moment and total energy decrease, particularly as permeability decreases, while the number of induced events increases. The moment magnitude of induced events can thereby be controlled through cycled fluid injection.

Septiembre de 2021
Global 3-D Electrical Conductivity Model of the World Ocean and Marine Sediments
Author: Alexander V. Grayver
Link: Click here

This study presents global 3-D electrical conductivity models of the world ocean and marine sediments. Electrical conductivity of the ocean was calculated by invoking the Equation of State of Seawater (TEOS-10) with temperature and salinity data retrieved from the World Ocean Atlas and a series of high-resolution regional ocean climatology data sets. The resolution of the ocean conductivity atlas varies

between x and y globally. The conductivity of marine sediments was estimated by using compaction and thermal gradient models constrained by real observations on a 5-arc-minute global marine sediment thickness grid. I present numerical simulations of electromagnetic (EM) induction responses that demonstrate a significant effect of 3-D electrical conductivity of the ocean and marine sediments on EM responses for a broad range of frequencies. I show that both marine and land-based surveys designed for subsurface conductivity imaging or Space Weather modeling will benefit from inclusion of more realistic conductivity models of the ocean and seabed sediments.

Septiembre de 2021
Are deep aquifers really confined?
Authors: Yan Zhang,Chi-Yuen Wang et al
Link: Click here

Many deep aquifers overlain by barrier formations in the continental US are used as geological repositories for wastewaters coproduced from hydrocarbon exploration. This practice is to protect shallow groundwater following the US Environmental Protection Agency's regulation. Implicit in such practice is the assumption that deep aquifers overlain by mudstones or shales are confined so that the injected fluids will not migrate upward to contaminate shallow groundwater. However, no systematic test of this hypothesis has been made. Here we invert the groundwater response to both the M2 and the O1 tides and to the

barometric pressure across a large (2.046×106 km2) geologic regime, the North China platform, to systematically evaluate the hydraulic parameters as functions of depth and time without a priori assumption. Our result, the first of such inversion, shows no depth dependence of aquifer confinement to a depth of 3400 m and that deep confined aquifers overlain by barrier formations may become leaky after distant earthquakes. It suggests that monitoring of aquifer confinement may be needed to ensure if the targeted deep aquifer for wastewater injection is really confined. The results may be timely and of global significance because the practice of hydrofracking for natural gas and the deep injection for the disposal of the coproduced wastewaters in the US may soon be adopted by other countries, such as China.

Septiembre de 2021
Characteristics of Foreshocks Revealed by an Earthquake Forecasting Method Based on Precursory Swarm Activity
Authors: F. Hirose, K. Tamaribuchi et al
Link: Click here

We have developed an empirical earthquake forecast method, Maeda's method, based on the statistical features of precursory seismic swarm activity, that is foreshocks, which sometimes appear before a mainshock, and issuing an alert of a mainshock occurrence within a certain period of time. In this study, we investigated the effectiveness of earthquake forecast of Maeda's method by applying it to seismicity under various tectonic environments of Japan such as regions characterized by interplate seismic activity, a tectonic fault line (concentrated deformation zone), and an island arc area of seismic and volcanic activity. As a result, we confirmed that Maeda's method yielded

generally higher scores than a forecast model based on a stationary space-time epidemic-type aftershock sequence (ETAS) model. We also found that foreshocks detected along the Japan Trench were distributed along the edges of low-velocity anomalies and among areas with background swarms related to slow slip events (SSEs). The foreshocks may have been caused by a heterogeneous stress distribution associated with the existence of a plate-bending axis and a subducted seamount. Foreshocks off Iwate prefecture, in particular, were excited by periodic SSEs. In an inland tectonic zone and an island arc, swarm activity associated with magmatic or fluid activity related to low-velocity anomalies tended to be followed by a mainshock. Maeda's method is a simple and efficient counting-number-based earthquake forecast model and may capture characteristics of foreshocks that reflect a physical phenomenon, such as a nucleation process involving precursory slip, which the stationary ETAS model is not able to represent.

Septiembre de 2021
Can Deep Learning Predict Complete Ruptures in Numerical Megathrust Faults?
Authors: David Blank and Julia Morgan
Link: Click here

We propose a binary classification model rooted in state-of-the-art deep learning techniques to predict whether or not complete-interface rupture is imminent along a numerical megathrust fault. The models are trained on labeled 2D space-time input features taken from the synthetic fault system. We contrast the performance of two neural networks

rained on three types of data, to determine the relative predictive power of each. The neural networks are able to discriminate imminent complete rupture precursors from everything else, thus providing a relative size and time forecast. Vertical displacements along the fault demonstrate relatively good predictive power. The results confirm previous qualitative observations that precursory deformation scales with upcoming event size, consistent with the preslip model for earthquake nucleation. The methods we propose are adaptable and can be modified to use 3D data in the future.

Septiembre de 2021
Dominga: Extractivist policies hurt Chile’s ecosystems
Authors: Mauricio A. Urbina, Pablo C. Guerrero et al
Link: Click here


Agosto de 2021
Beating 1 Sievert: Optimal Radiation Shielding of Astronauts on a Mission to Mars
Authors: M.I. Dobynde, Y.Y. Shprit et al
Link: Click here

Space particle radiation is one of the main concerns in planning long-term human space missions. There are two main types of hazardous particle radiation: 1) solar energetic particles (SEP) originating from the Sun and 2) galactic cosmic rays (GCR) that come from the distant galaxies in space. Fluxes in particles of solar origin maximize during solar maximum when particles originating from the distant galaxies are more efficiently deflected from

the solar system during times when the sun is active. Our calculations clearly demonstrate that the best time for a human space flight to Mars is during the solar maximum, as it is possible to shield from SEP particles. Our simulations show that an increase in shielding creates an increase in secondary radiation produced by the most energetic GCR, which results in a higher dose, introducing a limit to a mission duration. We estimate that a potential mission to Mars should not exceed approximately 4 years. This study shows that while space radiation imposes strict limitations and presents technological difficulties for the human mission to Mars, such a mission is still viable.

Agosto de 2021
Lightning Activity Over Chilean Territory
Authors:J. Montana, C. Morales et al
Link: Click here

This work presents the spatial distribution and temporal variability of lightning activity over the continental territory of Chile by means of Thunderstorms days (Td), on the basis of 7 years (2012–2018) of lightning measurement from World Wide Lightning Location Network (WWLLN). Td are obtained separately for the 15 geopolitical regions of Chile, reporting the higher lightning activity in the northeastern region of the country with 85 thunderstorms days per year. These values are mainly located in the mountains between 2,000 and 5,000 m.a.s.l. where extensive mining activity is located and there are electrical facilities of great importance for Chile. The Td values obtained in this study update the information presented by the World

Meteorological Organization (WMO) in 1953, so far the only one available for the entire Chilean territory. From the diurnal cycle analysis, there is a marked mono-modal behavior of lightning activity in the afternoon for latitudes between (regions XV, I, and II) and a different behavior of lightning activity over the region between (regions X, XI, and XII) known as Chilean Patagonia, due to special weather conditions in that area. Further more, the seasonal analysis showed that the highest lightning activity occurs in January and February and the lowest activity takes place between June and August. Once again, the Chilean Patagonia showed a different behavior because the highest activity is presented in May and August, and the lowest in September. The analysis and results presented here contribute to the knowledge of lightning activity in the region that has not been characterized before and can serve as a basis for future research to determine the behavior of this natural phenomenon.

Agosto de 2021
Longer days on early Earth set stage for complex life
Author: Elizabeth Pennisi
Link: Click here

Today, oxygen fuels much of life on Earth, but it wasn't always that way. Three billion years ago, this gas was scarce in the atmosphere and oceans. Knowing why oxygen became plentiful could illuminate the evolution of our planet's flora and fauna, but scientists have struggled to find an

explanation satisfying to all. Now, a research team has proposed a novel link between how fast our planet spun on its axis—which defines the length of a day—and the ancient production of additional oxygen. Their modeling of Earth's early days, which incorporates evidence from microbial mats coating the bottom of a shallow, sunlit sinkhole in Lake Huron, produced a surprising conclusion: As Earth's spin slowed and led to longer days, that could have triggered more photosynthesis from similar mats, allowing oxygen to build up in ancient seas and diffuse up into the atmosphere.

Agosto de 2021
Spectrum Monitoring of Radio Digital Video Broadcasting Based on an Improved Generative Adversarial Network
Authors: X. Y. Wang, J. J. Yang, L. Zhang et al
Link: Click here

Due to the inherent broadcast nature of wireless communication systems, instances of radio jamming are common, such as natural interference and man-made interference, resulting in increasing demands for radio monitoring. A spectrum monitoring method based on a generative adversarial network model that is one of the most

promising approaches of learning any kind of data distribution using unsupervised learning was proposed in this paper for the detection of anomaly spectrum with impulse noise. To validate the performance of the proposed model, both the simulated data set and the measured data set of radio digital video broadcasting were used to train and test the model. Experiments on the two data sets reached a consistent conclusion: as long as the energy of the interference is greater than a certain threshold, the detection accuracy increases with the increase of the interference power and pulse width. Compared with the existing anomaly detection models, our model was faster and more stable.

Agosto de 2021
A Laboratory Perspective on the Gutenberg-Richter and Characteristic Earthquake Models
Authors:Evangelos Korkolis, André R. Niemeijer et al
Link: Click here

Probabilistic seismic hazard analysis (PSHA) is the standard method used for designing earthquake-resistant infrastructure. In recent years, several unexpected and destructive earthquakes have sparked criticism of the PSHA methodology. The seismological part of the problem is the true frequency-magnitude distribution of regional seismicity. Two major models exist, the Gutenberg-Richter (G-R) and the Characteristic Earthquake (CE) model, but it is difficult to choose between them. That is because the instrumental, historical,

and paleoseimological data available are limited in many regions of interest. Here, we demonstrate how a friction experiment on aggregates of glass beads can produce both regular (CE equivalent) and irregular (G-R equivalent) stick-slip. Using a new rotary shear apparatus we produced and analyzed large catalogs of acoustic emission (AE) events related to stick-slip. The distributions of AE sizes, interevent times, and interevent distances were found to be sensitive to particle size and the applied normal stress, and, to a lesser degree, the stiffness of the loading apparatus. More importantly, the system spontaneously switched behavior for short periods of time. In the context of PSHA, if faults are able to switch behavior as our experimental system does, then justifying the choice of either the CE or the G-R model is impossible based on existing observations.

Julio de 2021
Structural Evolution of a Crustal-Scale Seismogenic Fault in a Magmatic Arc: The Bolfin Fault Zone (Atacama Fault System)
Authors: Simone Masoch, Rodrigo Gomila et al
Link: Click here

How major crustal-scale seismogenic faults nucleate and evolve in crystalline basements represents a long-standing, but poorly understood, issue in structural geology and fault mechanics. Here, we address the spatio-temporal evolution of the Bolfin Fault Zone (BFZ), a >40-km-long exhumed seismogenic splay fault of the 1000-km-long strike-slip Atacama Fault System. The BFZ has a sinuous fault trace across the Mesozoic magmatic arc of the Coastal Cordillera (Northern Chile) and formed during the oblique subduction of the Aluk plate

beneath the South American plate. Seismic faulting occurred at 5–7 km depth and ≤ 300°C in a fluid-rich environment as recorded by extensive propylitic alteration and epidote-chlorite veining. Ancient (125–118 Ma) seismicity is attested by the widespread occurrence of pseudotachylytes. Field geologic surveys indicate nucleation of the BFZ on precursory geometrical anisotropies represented by magmatic foliation of plutons (northern and central segments) and andesitic dyke swarms (southern segment) within the heterogeneous crystalline basement. Seismic faulting exploited the segments of precursory anisotropies that were optimal to favorably oriented with respect to the long-term far-stress field associated with the oblique ancient subduction. The large-scale sinuous geometry of the BFZ resulted from the hard linkage of these anisotropy-pinned segments during fault growth.

Julio de 2021
The Entire Crust can be Seismogenic: Evidence from Southern Malawi
Authors: V. L. Stevens, R. A. Sloan et al
Link: Click here

The Bilila-Mtakataka Fault (BMF), at the southern end of the western branch of the East African Rift System (EARS), has been used in various scaling relation studies and arguments about the strength of the lithosphere. We present evidence for a similar, though more degraded, frontal scarp on the graben-bounding synthetic Chirobwe-Ntcheu Fault (CNF), showing that this fault is active simultaneously with the BMF. We deployed 17 geophones for ∼60 days around the southern end of Lake Malawi, across the footwall and hangingwall of the BMF. Continuous microseismicity can be seen from the surface to ∼35 km depth highlighting a

plane dipping ∼42°E. Lower-crustal earthquakes have previously been found in the EARS, and based on location and focal mechanism have been hypothesized to occur on planes that line up with the surface traces of large faults. However, no previous study of the EARS has revealed a fault plane throughout the crust that shows seismicity along its full length from the surface to the base of the crust. Rather, the lack of seismicity seen at mid-lower crustal depths, has led some people to the “jelly sandwich” hypothesis. Our results show that the entire crust is seismogenic, so support the “crème brûlée” model. In our two month deployment we recorded 22 aftershocks ML ≥ 2 from the March 8th, 2018 earthquake 200 km south of our array, 7 months after the mainshock, confirming that aftershock sequences in regions of low strain have a long duration, and could be the main component of seismicity in slowly straining regions.

Julio de 2021
Misconception of Waveform Similarity in the Identification of Repeating Earthquakes
Authors: Dawei Gao, Honn Kao et al
Link: Click here

Identification of repeating earthquakes (repeaters) usually depends on waveform similarity expressed as the corresponding cross-correlation coefficient (CC) above a prescribed threshold, typically ranging in 0.70–0.98. However, the robustness and effectiveness of such a strategy have rarely been fully examined. In this study, we examine whether CC is a valid proxy for repeater identification through

both synthetic and real earthquake experiments. We reveal that CC is controlled by not only the interevent distance but also many other factors, including station azimuth, epicentral distance, and velocity structure. Consequently, CC lacks the resolution in identifying true repeaters. For reliable repeater identification, we should consider the interevent overlap. Specifically, we define an event pair to be true repeaters if their interevent separation is smaller than the source dimension of the larger event. Our results imply that a systematic recheck of previously identified repeaters and associated interpretations/hypotheses may be important and necessary.

Julio de 2021
Active Mars: A Dynamic Worldc
Authors: Colin M. Dundas, Patricio Becerra et al
Link: Click here

Mars exhibits diverse surface changes at all latitudes and all seasons. Active processes include impact cratering, aeolian sand and dust transport, a

variety of slope processes, changes in polar ices, and diverse effects of seasonal CO2 frost. The extent of surface change has been surprising and indicates that the present climate is capable of reshaping the surface. Activity has important implications for the Amazonian history of Mars: understanding processes is a necessary step before we can understand their implications and variations over time.

Julio de 2021
Toward Developing a Generalizable Pedotransfer Function for Saturated Hydraulic Conductivity Using Transfer Learning and Predictor Selector Algorithm
Authors: Suraj Jena, Binayak P. Mohanty et al
Link: Click here

Saturated hydraulic conductivity (Ks) is an indispensable parameter for investigating surface/sub-surface hydrologic processes. Pedotransfer function (PTF) is a reasonable alternative to the expensive and tedious direct measurement of Ks. This study augments the PTF-

based Ks estimation using machine learning (ML). We evaluated different ML algorithms and selected the random forest (RF) as the learning algorithm for Ks prediction. Moreover, the prediction ability of random forest was enhanced through the selection of pertinent predictors for Ks. A robust PTF for the reported study was developed using the selected learning algorithm and pertinent predictors. We also evaluated the developed PTF alongside the recently published and commonly used PTFs within and outside the study region and observed superior prediction proficiency by our PTF compare to others in both cases. The developed ML-based PTF may provide an excellent cost-effective estimation of Ks.

Julio de 2021
Predicting Water Temperature Dynamics of Unmonitored Lakes With Meta-Transfer Learning
Authors: Jared D. Willard, Jordan S. Read et al
Link: Click here

Most environmental data come from a minority of well-monitored sites. An ongoing challenge in the environmental sciences is transferring knowledge from monitored sites to unmonitored sites. Here, we demonstrate a novel transfer-learning framework that accurately predicts depth-specific temperature in unmonitored lakes (targets) by borrowing models from well-monitored lakes (sources). This method, meta-transfer learning (MTL), builds a meta-learning model to predict transfer performance from candidate source models to targets using lake attributes and candidates' past performance. We constructed source models at 145 well-monitored lakes using calibrated process-based (PB) modeling and a recently developed approach called

process-guided deep learning (PGDL). We applied MTL to either PB or PGDL source models (PB-MTL or PGDL-MTL, respectively) to predict temperatures in 305 target lakes treated as unmonitored in the Upper Midwestern United States. We show significantly improved performance relative to the uncalibrated PB General Lake Model, where the median root mean squared error (RMSE) for the target lakes is 2.52°C. PB-MTL yielded a median RMSE of 2.43°C; PGDL-MTL yielded 2.16°C; and a PGDL-MTL ensemble of nine sources per target yielded 1.88°C. For sparsely monitored target lakes, PGDL-MTL often outperformed PGDL models trained on the target lakes themselves. Differences in maximum depth between the source and target were consistently the most important predictors. Our approach readily scales to thousands of lakes in the Midwestern United States, demonstrating that MTL with meaningful predictor variables and high-quality source models is a promising approach for many kinds of unmonitored systems and environmental variables.

Julio de 2021
Architecture, Kinematics, and Tectonic Evolution of the Principal Cordillera of the Andes in Central Chile (∼33.5°S): Insights From Detrital Zircon U-Pb Geochronology and Seismotectonics Implications
Authors: Verónica Mardones, Matías Peña et al
Link: Click here

We assess the role of inherited structures on the Meso-Cenozoic tectonic evolution of the main Andean Cordillera in central Chile (33°30′S-34°S). Based on extensive field mapping, U-Pb geochronology and palinspastic restorations along the Yeso and Volcán river valleys, we propose a tectono-stratigraphic model for the evolution of a hybrid fold-and-thrust belt, originated from the inversion of Mesozoic extensional basins. With these results, we highlight the structural graben configuration of the Yeguas Muertas and Nieves Negras depocenters, as evidenced by synextensional deposition of the Río Damas and Lo.

Valdés Formations, controlled by normal faulting The uppermost Cretaceous evolution can be approached through the analysis of the Las Coloradas Unit (ULC), which overlies the volcanic rocks of the upper Colimapu Formation and can be correlated, north of 32°S, with the Juncal Formation, and south of 35°S, with the Plan Los Yeuques Formation. The contractional Neogene-Quaternary deformation in the fold-and-thrust belt domain studied in this work, accommodated 27–28 km of minimum crustal shortening. The Neogene-Quaternary deformation that generated the final uplift of the Andes, has a close relationship with preexisting inverted Mesozoic structures. These structures deform the volcano-sedimentary Abanico Formation, deposited since the late Eocene, based on new U-Pb detrital zircon data. We propose that the active seismicity observed in the eastern border of the Principal Cordillera, located to the east of Santiago, can be associated with major crustal faults, as the Estero de Yeguas Muertas-Baños Colina fault system and the Chacayes-Yesillo fault.

Junio de 2021
Paleoseismic Evidence of a Mw 7 Pre-Hispanic Earthquake in the Peruvian Forearc
Authors: Carlos Benavente, Sam Wimpenny et al
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We present the results of a paleoseismic survey of the Incapuquio Fault System, a prominent transpressional fault system cutting the forearc of South Perú. High-resolution DEMs, optical satellite imagery, radiocarbon dating and paleoseismic trenching indicate that at least 2-3 m of net slip occurred on the Incapuquio Fault generating a complex, 100 km-long set of segmented fault scarps in the early 15th century (AD 1400-1440). We interpret the consistent along-strike pattern of fault scarp heights, geometries and kinematics to reflect a surface rupture generated by a single Mw 7.4-7.7 earthquake, suggesting that brittle failure of

the forearc poses a significant, yet mostly overlooked, seismic hazard to the communities in coastal areas of Perú. The timing of this earthquake coincides with the collapse of the Chiribaya civilization in AD 1360-1400, and we present evidence of damaged buildings along the fault trace that may be of Chirabayas age. Our surface faulting observations, when combined with observations of deformation in the forearc from geodesy and seismology, also demonstrate that the forearc in South Perú experiences a complex, time-varying pattern of permanent strain, with evidence for trench-parallel shortening, trench-parallel extension and trench-perpendicular shortening all in close proximinty but in different periods of the megathrust earthquake cycle. The kinematics of recent slip on the Incapuquio Fault are consistent with the sense of interseismic strain within the forearc measured by GPS, suggesting the fault is loaded towards failure between megathrust earthquakes.

Junio de 2021
Integrating Community Science Research and Space-Time Mapping to Determine Depth to Groundwater in a Remote Rural Region
Authors: A. M. Gómez, M. Serre et al
Link: Click here

Continuous depth to groundwater (DTG) data collection is challenging in remote regions. Community participation offers a way to both increase data collection and involves the local community in scientific projects. Local knowledge, which is often descriptive, can be difficult to include in quantitative analysis; however, it can increase scientists' ability to formulate hypotheses or identify relevant environmental processes. We show how Community Science Research can add useful descriptive information for a study based in rural Colombia. To estimate the spatiotemporal

distribution of DTG, the community collected water level measurements during a wet (La Niña) year and an average year. We built one spatial and two spatiotemporal models (with and without probabilistic data) using Bayesian Maximum Entropy. Due to the inclusion of local knowledge, the spatiotemporal model with probabilistic data reduced its mean square error by a factor of 15 compared to the spatial model. Using this model, we found that 13% of the study area has a high probability of very shallow DTG (<0.1 m) during an average year, whereas during La Niña, this area increases to 56%. The difference in shallow DTG between the average and wet year implies that after reaching a precipitation threshold, the study region may lose its flow regulation capacity, contributing to flooding during extreme precipitation events. Our approach presents a method to incorporate local knowledge in data-driven models by combining qualitative and quantitative information.

Junio de 2021
Data-Driven Clustering Reveals More Than 900 Small Magnitude Slow Earthquakes and Their Characteristics
Authors: C. Aiken and K. Obara et al
Link: Click here

Small magnitude slow earthquakes remain largely undetected in geodetic data due to noise levels. However, tremor and low-frequency earthquakes (LFE) may manifest slowly slipping fault motion as a cluster of events, i.e., a slow earthquake. Here, we identify >900 slow earthquakes in southwest Japan via data-driven clustering of tremor and LFE catalogs. We establish a more complete database

for slow earthquakes in southwest Japan and demonstrate their characteristics and long-term behavior. While sometimes sub-episodes of well-known episodic tremor and slip, the small slow earthquake clusters share similar scaling properties–energy, duration, and rupture area–with larger magnitude fast and slow earthquakes. The small slow earthquake clusters tend to rupture faster when migrating in their preferred rupture direction, but inter-event rupture speeds are on average similar to those of larger slow earthquakes. This suggests that rupture speed does not necessarily control slow earthquake spatial extent or eventual magnitude.

Junio de 2021
Finnigan Illsley-Kemp, Simon J. Barker
Authors: Siwei Yu, Jianwei Ma et al
Link: Click here

Taupō volcano, New Zealand, is a large caldera volcano that has been highly active through the Holocene. It most recently erupted ∼1,800 years ago but there have been multiple periods of historic volcanic unrest. We use seismological and geodetic analysis to show that in 2019 Taupō underwent a period of unrest characterized by increased seismic activity through multiple swarms and was accompanied by ground deformation within the

caldera. The earthquakes, which include non-double-couple events, serve to outline an aseismic zone beneath the most recent eruptive vents. This aseismic zone is coincident with an inflating source, based on forward modeling of ground deformation data. We infer that this aseismic and deforming region delineates the location of the present day magma reservoir that is ≥250 km3 in volume and has a melt fraction of >20%–30%, inhibiting seismic activity. Our analysis shows that the 2019 unrest at Taupō was volcanic in nature and origin, demonstrating that this is an active and potentially hazardous volcano, and that improving our monitoring and understanding of its behavior is important.

Junio de 2021
Misconception of Waveform Similarity in the Identification of Repeating Earthquakes
Authors: Dawei Gao, Honn Kao et al
Link: Click here

Identification of repeating earthquakes (repeaters) usually depends on waveform similarity expressed as the corresponding cross-correlation coefficient (CC) above a prescribed threshold, typically ranging in 0.70–0.98. However, the robustness and effectiveness of such a strategy have rarely been fully examined. In this study, we examine whether CC is a valid proxy for repeater identification through

both synthetic and real earthquake experiments. We reveal that CC is controlled by not only the inter-event distance but also many other factors, including station azimuth, epicentral distance, velocity structure, etc. Consequently, CC lacks the resolution in identifying true repeaters. For reliable repeater identification, we should consider the inter-event overlap. Specifically, we define an event pair to be true repeaters if their inter-event separation is smaller than the source dimension of the larger event. Our results imply that a systematic recheck of previously identified repeaters and associated interpretations/hypotheses may be important and necessary.

Junio de 2021
Relationships among Forearc Structure, Fault Slip, and Earthquake Magnitude: Numerical Simulations with Applications to the Central Chilean Margin
Authors: Xiaoyu Wang, Julia K. Morgan et al
Link: Click here

Two adjacent segments of the Chile margin exhibit significant differences in earthquake magnitude and rupture extents during the 1960 Valdivia and 2010 Maule earthquakes. We use the Discrete Element Method to simulate the upper plate as having an inner and outer wedge defined by different frictional domains along the decollement. We find that outer

wedge width strongly influences coseismic slip distributions. We use the published peak slip magnitudes to pick best fit slip distributions and compare our models to geophysical constraints on outer wedge widths for the margins. We obtain reasonable fits to published slip distributions for the 2010 Maule rupture. Our best-fit slip distribution for the 1960 Valdivia earthquake suggests that peak slip occurred close to the trench, differing from published models but being supported by new seismic interpretations along this margin. Finally, we also demonstrate that frictional conditions beneath the outer wedge can affect the coseismic slip distributions.

Junio de 2021
Learning the low frequency earthquake activity on the central San Andreas Fault
Authors: Christopher W. Johnson and Paul A. Johnson et al
Link: Click here

Low frequency earthquakes (LFEs) originating below the central San Andreas Fault are associated with slow-slip beneath the seismogenic zone within the more ductile portion of the crust. Monitoring efforts over 15 years detected > 1 million LFEs. We train a gradient boosted tree model using statistical features describing the seismic waveforms to

estimate the hourly LFE event count. The burst-like LFE behavior is reproduced, while lower amplitudes are predicted during the most active periods. The hourly event counts are up to 18% greater than the catalog. The ability to continuously monitor LFE activity provides insight to when geodetic measurements of slow slip are possible, without the need for developing a computational-intensive template-matching catalog. Similar waveform statistical features are found between detecting LFEs and tremors, which provides additional evidence tremors are composed of LFEs. The approach extracts information contained in continuous seismic waveforms that might benefit detecting precursory signals.

Junio de 2021
Identifying Key Drivers of Wildfires in the Contiguous US Using Machine Learning and Game Theory Interpretation
Authors: Sally S.-C. Wang, Yun Qian et al
Link: Click here

Understanding the complex interrelationships between wildfire and its environmental and anthropogenic controls is crucial for wildfire modeling and management. Although machine learning (ML) models have yielded significant improvements in wildfire predictions, their limited interpretability has been an obstacle for their use in advancing understanding of wildfires. This study builds an ML model incorporating predictors of local meteorology, land-surface characteristics, and socioeconomic variables to predict monthly burned area at grid cells of 0.25° × 0.25° resolution over the contiguous United States. Besides these predictors, we construct and include predictors representing the large-scale circulation patterns conducive to

wildfires, which largely improves the temporal correlations in several regions by 14%–44%. The Shapley additive explanation is introduced to quantify the contributions of the predictors to burned area. Results show a key role of longitude and latitude in delineating fire regimes with different temporal patterns of burned area. The model captures the physical relationship between burned area and vapor pressure deficit, relative humidity (RH), and energy release component (ERC), in agreement with the prior findings. Aggregating the contribution of predictor variables of all the grids by region, analyses show that ERC is the major contributor accounting for 14%–27% to large burned areas in the western US. In contrast, there is no leading factor contributing to large burned areas in the eastern US, although large-scale circulation patterns featuring less active upper-level ridge-trough and low RH two months earlier in winter contribute relatively more to large burned areas in spring in the southeastern US.

Junio de 2021
Deep Learning for Geophysics: Current and Future Trends
Authors: Siwei Yu, Jianwei Ma et al
Link: Click here

Recently deep learning (DL), as a new data-driven technique compared to conventional approaches, has attracted increasing attention in geophysical community, resulting in many opportunities and challenges. DL was proven to have the potential to predict complex system states accurately and relieve the “curse of dimensionality” in large temporal and spatial geophysical applications. We address the basic concepts, state-of-the-art literature, and future trends by reviewing DL

approaches in various geosciences scenarios. Exploration geophysics, earthquakes, and remote sensing are the main focuses. More applications, including Earth structure, water resources, atmospheric science, and space science, are also reviewed. Additionally, the difficulties of applying DL in the geophysical community are discussed. The trends of DL in geophysics in recent years are analyzed. Several promising directions are provided for future research involving DL in geophysics, such as unsupervised learning, transfer learning, multimodal DL, federated learning, uncertainty estimation, and active learning. A coding tutorial and a summary of tips for rapidly exploring DL are presented for beginners and interested readers of geophysics.

Junio de 2021
Seismic Slip-Pulse Experiments Simulate Induced Earthquake Rupture in the Groningen Gas Field
Authors: Luuk B. Hunfeld, Jianye Chen et al
Link: Click here

Rock materials show dramatic dynamic weakening in large-displacement (m), high-velocity (∼1 m/s) friction experiments, providing a mechanism for the generation of large, natural earthquakes. However, whether such weakening occurs during induced M3-4 earthquakes (dm displacements) is unknown. We performed rotary-shear experiments on simulated fault gouges prepared from the source-, reservoir-

and caprock formations present in the seismogenic Groningen gas field (Netherlands). Water-saturated gouges were subjected to a slip pulse reaching a peak circumferential velocity of 1.2–1.7 m/s and total displacements of 13–20 cm, at 2.5–20 MPa normal stress. The results show 22%–81% dynamic weakening within 5–12 cm of slip, depending on normal stress and gouge composition. At 20 MPa normal stress, dynamic weakening from peak friction coefficients of 0.4–0.9 to 0.19–0.27 was observed, probably through thermal pressurization. We infer that similar effects play a key role during induced seismic slip on faults in the Groningen and other reservoir systems.

Junio de 2021
Comparison of Current and Future PM2.5 Air Quality in China Under CMIP6 and DPEC Emission Scenarios
Authors: Jing Cheng, Dan Tong et al
Link: Click here

Global emission scenarios might be limited on regional-scale air quality projections because of inadequate consideration of local environmental policy. Here, we simulated China's air quality variations through 2050 with global emission data sets and local policy-based emission scenarios. Both global and local emissions can reasonably

estimate China's air quality; however, estimations with local emission scenarios are more correlated with surface observations and can better capture China's rapid air quality improvement during 2015–2019. Local policy deficiencies and current year bias further make future air quality projections driven by global emission scenarios 42%–73% higher than driven by local policy-based scenarios. Our findings could offer insights for the research community to incorporate more detailed regional information in future global scenario designs, which might help to better investigate the climate change impacts and improve global scenario applicability to regional scales

Junio de 2021
Deep Learning Can Predict Laboratory Quakes From Active Source Seismic Data
Authors: Parisa Shokouhi, Vrushali Girkar et al
Link: Click here

Small changes in seismic wave properties foretell frictional failure in laboratory experiments and in some cases on seismic faults. Such precursors include systematic changes in wave velocity and amplitude throughout the seismic cycle. However, the relationships between wave features and shear stress are complex. Here, we use data from lab friction experiments that include continuous

measurement of elastic waves traversing the fault and build data-driven models to learn these complex relations. We demonstrate that deep learning models accurately predict the timing and size of laboratory earthquakes based on wave features. Additionally, the transportability of models is explored by using data from different experiments. Our deep learning models transfer well to unseen datasets providing high-fidelity models with much less training. These prediction methods can be potentially applied in the field for earthquake early warning in conjunction with long-term time-lapse seismic monitoring of crustal faults, CO2 storage sites and unconventional energy reservoirs.

Junio de 2021
Subduction Polarity Reversal: Induced or Spontaneous?
Authors: Shengxing Zhang and Wei Leng
Link: Click here

Subduction polarity reversal (SPR) is the subduction initiation process following the arc-continent collision. Previous models emphasized the need for the external compressional force to induce it. However, the explanation of different geological structures in the reported SPR zones was poor. Based on our new thermomechanical model, we

confirm the possibility of establishing a spontaneous SPR system, which is self-sustained by negative buoyancy. The spontaneous SPR will occur when the whole overriding oceanic plate has a small plastic strength, while the arc-continent collision system with a strong overriding plate and a limited weak back-arc/arc structure prefers the compression-induced SPR. Moreover, a rather young oceanic plate (≤20 Ma) can trigger the SPR without any weak area. This study provides new insights into the different initiation mechanisms and evolutionary pathways of the potential Cenozoic SPR events in Ryukyu, Kamchatka, and New Hebrides.

Mayo de 2021
A Simple Model to Predict Hydraulic Conductivity in Medium to Dry Soil From the Water Retention Curves
Authors: Andre Peters, Tobias L. Hohenbrink et al.
Link: Click here

The mathematical representation of the soil hydraulic properties is of central importance for modeling water, solute and energy transport in soils. The established models of the water retention and hydraulic conductivity curves account for capillary water retention and conductivity, but neglect water adsorption and water flow in films and pore corners. They are therefore suited for modeling flow and transport processes in the medium to wet moisture range, but are susceptible to failure in dry soil. The model system developed by Peters and Iden and Durner (PDI in the following) is a simple parametric framework that overcomes these

structural shortcomings. However, it requires one additional parameter to scale the hydraulic conductivity curve in the moisture range where non-capillary flow dominates. Measured conductivity data are required to determine this scaling parameter and to compute the hydraulic conductivity over the complete moisture range. In this contribution, we first show that the original PDI model is in close agreement with a comprehensive model for film conductivity in porous media. We then derive a physically-based approach to predict the film conductivity from the water retention curve. This improved PDI model has the same number of parameters as established models and provides a complete prediction of the hydraulic conductivity curve including non-capillary flow if water retention data and the saturated conductivity are known. Application to literature data covering a broad range of textures shows an improvement of the conductivity prediction by the factor five if compared to the van Genuchten/Mualem model.

Mayo de 2021
Sensitivity of permeability changes to different earthquakes in a fault zone: Possible evidence of dependence on the frequency of seismic waves
Authors: Xin Liao, Yun Shi et al.
Link: Click here

Changes in the permeability of a fault zone are dependent upon the frequency of seismic waves, and is an important phenomenon whose mechanisms have not be completely elucidated to date. In this study, the tidal response of water level

in well Chuan06 was considered as an indicator of the permeability of the fault zone, and the sensitivity of permeability changes to earthquakes with different epicentral distances were investigated. The results suggested that the permeability change induced by seismic waves is frequency dependent. In addition, based on the mechanisms of permeability changes induced by the seismic waves, the difference in sensitivity may be attributed to the different sizes of the fractures in the fault zone. These findings are likely to contribute to an understanding of hydrogeological responses and seismic activity induced by the earthquakes.

Mayo de 2021
A Decade of Lessons Learned from the 2011 Tohoku oki Earthquake
Authors: N. Uchida and R. Bürgmann.
Link: Click here

The 2011 Mw 9.0 Tohoku oki earthquake is one of the world’s best recorded ruptures. In the aftermath of this devastating event, it is important to learn from the complete record. We describe the state of knowledge of the megathrust earthquake generation process before the earthquake, and what has been learned in the decade since the historic event. Prior to 2011, there were a number of studies suggesting the potential of a great megathrust earthquake in NE Japan from geodesy, geology, seismology, geomorphology, and paleoseismology, but results from each field were not enough to enable a consensus assessment of the hazard. A transient unfastening of interplate coupling and increased .

seismicity were recognized before the earthquake, but did not lead to alerts. Since the mainshock, follow up studies have (1) documented that the rupture occurred in an area with a large interplate slip deficit, (2) established large near‐trench coseismic slip, (3) examined structural anomalies and fault zone materials correlated with the coseismic slip, (4) clarified the historical and paleoseismic recurrence of M 9 earthquakes, and (5) identified various kinds of possible precursors. The studies have also illuminated the heterogeneous distribution of coseismic rupture, aftershocks, slow earthquakes and aseismic afterslip, and the enduring viscoelastic response, which together make up the complex megathrust earthquake cycle. Given these scientific advances, the enhanced seismic hazard of an impending great earthquake can now be more accurately established, although we do not believe such an event could be predicted with confidence

Mayo de 2021
Relationship Between Subduction Erosion and the Up Dip Limit of the 2014 Mw 8.1 Iquique Earthquake
Authors: Florian Petersen, Dietrich Lange et al.
Link: Click here

The aftershock distribution of the 2014 Mw 8.1 Iquique earthquake offshore northern Chile, identified from a long term deployment of ocean bottom seismometers installed eight months after the mainshock, in conjunction with seismic reflection imaging, provides insights into the processes regulating the updip limit of coseismic

rupture propagation. Aftershocks updip of the mainshock hypocenter frequently occur in the upper plate and are associated with normal faults identified from seismic reflection data. We propose that aftershock seismicity near the plate boundary documents subduction erosion that removes mass from the base of the wedge and results in normal faulting in the upper plate. The combination of very little or no sediment accretion and subduction erosion over millions of years has resulted in a very weak and aseismic frontal wedge. Our observations thus link the shallow subduction zone seismicity to subduction erosion processes that control the evolution of the overriding plate.

Mayo de 2021
Solar or Diesel: A Comparison of Costs for Groundwater Fed Irrigation in Sub Saharan Africa Under Two Energy Solutions
Authors:Hua Xie, Claudia Ringler et al.
Link: Click here

Sub Saharan Africa has long been beset with food insecurity and energy poverty. Expanding irrigated agriculture can help boost food production in the region, but this requires energy for accessing water, especially in groundwater fed irrigation. This paper compared economic performance of groundwater

pumping for irrigation under two energy solutions: solar photovoltaic (PV) and diesel fuel. We estimated the life cycle costs of the power units of two pumping systems for a range of crop and irrigation method scenarios and mapped their relative cost effectiveness over cropland in sub Saharan Africa. As a renewable and clean energy source, solar energy has attracted much attention and there is keen interest in investing in solar PV to support the development of irrigated agriculture. Results of this study provide insights into the prospects of promoting solar irrigation in sub Saharan Africa.

Abril de 2021
Flexural Control of Basal Crevasse Opening Under Ice Shelves
Authors: W. Roger Buck and Ching Yao Lai
Link: Click here

Classical analyses of basal crevasse opening do not account for the free surface of a floating ice layer. We describe a high resolution numerical treatment of the opening of a single crevasse in a finite thickness elastic layer floating on an inviscid substrate. For low extensional stress (less than about half of the expected maximum for a freely

floating shelf) the resulting crevasse height and width match previous studies. For larger magnitude applied extensional stresses, the new results predict basal crevasse widths an order of magnitude greater than the classical solution. An analysis using the thin layer approximation shows that the greatly increased predicted width of basal crevasse opening results from layer bending. Given that the height and width of basal crevasses are non linear functions of the stress experienced by an ice shelf, the new model results may enable better estimation of buttressing stresses for different parts of ice shelves.

Abril de 2021
Seismological Structures on Bimodal Distribution of Deep Tectonic Tremor
Authors: Yasunori Sawaki, Yoshihiro Ito et al.
Link: Click here

Deep tectonic tremors occur at the downdip extent of the seismogenic zone due to fluid processes. Beneath the northeastern Kii Peninsula, southwestern Japan, there is an along‐dip bimodal distribution of tremor. However, no constraint exists on the structures controlling that distribution. We extract detailed seismological structures from multi band receiver functions and evaluate conditional

differences in the distribution. To achieve high resolution images along the plate interface, we utilize records of regional deep focus earthquakes from the Pacific slab. Cross section images show the subducting oceanic plate with depth‐dependent phases along the bimodal distribution, revealing a conspicuous plate interface at the updip portion and an inconspicuous interface below the mantle wedge at the downdip portion. This indicates that episodic tremors occur in the high pore‐fluid plate interface below the impermeable forearc crust, and that continual tremors occur at the permeable mantle wedge corner, owing to continuous fluid supply from the oceanic crust.

Abril de 2021
A risk-based approach for managing hydraulic fracturing–induced seismicity
Authors: Ryan Schultz, Gregory C. Beroza et al.
Link: Click here

Risks from induced earthquakes are a growing concern that needs effective management. For hydraulic fracturing of the Eagle Ford shale in southern Texas, we developed a risk-informed strategy for choosing red-light thresholds that require immediate well shut-in. We used a combination of datasets to simulate spatially

heterogeneous nuisance and damage impacts. Simulated impacts are greater in the northeast of the play and smaller in the southwest. This heterogeneity is driven by concentrations of population density. Spatially varying red-light thresholds normalized on these impacts [moment magnitude (Mw) 2.0 to 5.0] are fairer and safer than a single threshold applied over a broad area. Sensitivity tests indicate that the forecast maximum magnitude is the most influential parameter. Our method provides a guideline for traffic light protocols and managing induced seismicity risks.

Abril de 2021
Diachronous Growth of the Northern Tibetan Plateau Derived From Flexural Modeling
Authors: Lin Wang, Feng Cheng et al.
Link: Click here

The early Cenozoic topography of the northern Tibetan plateau remains enigmatic because of the paucity of independent paleoelevation constraints. Long‐held views of northward propagating deformation imply a low Paleogene elevation, but this prediction is speculative. We apply flexural modeling to reconstructed Paleogene isopach data obtained from the Qaidam basin, which requires a

larger topographic load in the Qilian Shan and a smaller load in the Eastern Kunlun Shan. Incorporating knowledge of proto‐Paratethys marine incursions in the Paleogene Qaidam basin, we infer a topographically low (0.4–1.0 km) Eastern Kunlun Shan and a higher (0.4–1.5 km) Qilian Shan during the Paleogene. This implied paleo‐relief contrasts with previous predictions and suggests more recently, Neogene surface uplift in the Eastern Kunlun Shan has been more significant than in Qilian Shan, highlighting diachronous growth of the northern Tibetan plateau. The low moderate paleoelevation implies a warmer and more humid climate in Northern Tibet during the Paleogene.

Abril de 2021
Unraveling the Causes of the Seismicity Induced by Underground Gas Storage at Castor, Spain
Authors:Víctor Vilarrasa, Silvia De Simone et al.
Link: Click here

The offshore Castor Underground Gas Storage (UGS) project had to be halted after gas injection triggered three M4 earthquakes, each larger than any ever induced by UGS. The mechanisms that induced seismicity in the crystalline basement at 5–10 km depth after gas injection at 1.7 km depth remain unknown. Here, we propose a combination of mechanisms to explain the observed seismicity

First, the critically stressed Amposta fault, bounding the storage formation, crept by the superposition of well known overpressure effects and buoyancy of the relatively light injected gas. This aseismic slip brought an unmapped critically stressed fault in the hydraulically disconnected crystalline basement to failure. We attribute the delay between induced earthquakes to the pressure drop associated to expansion of areas where earthquakes slips cause further instabilities. Earthquakes occur only after these pressure drops have dissipated. Understanding triggering mechanisms is key to forecast induced seismicity and successfully design deep underground operations.

Abril de 2021
Analyzing Low Frequency Seismic Events at Cerberus Fossae as Long Period Volcanic Quakes
Authors: Sharon Kedar, Mark P. Panning et al.
Link: Click here

The InSight Mission began acquiring the first seismic data on Mars in early 2019 and has detected hundreds of events. The largest events recorded to date originate at Cerberus Fossae, a young volcanic region characterized by high volume, low viscosity lava flows. A handful of Low Frequency (LF) quakes that share key attributes of Long Period quakes recorded on Earth's volcanoes are also traced to Cerberus Fossae. This study explores whether a traditional volcanic source model that simulates the generation of tremor as pressurized fluid makes its way through a channel at depth, can explain these atypical LF events. We consider a

wide range of physical parameters including fluid viscosity, the ratio of driving pressure to lithostatic pressure, aspect ratio of the channel, and the equilibrium channel opening. We find that the model can produce the observed seismic signature, with a combination of low-viscosity magma and high volume flux of ~104 - 105 m3/s that are within an order-of-magnitude agreement with Cerberus Fossae lava flow properties deduced from analysis of lava flow dimensions. It is impossible, however, at this stage to conclude whether or not this is a likely explanation for Mars, as the model results in fluxes that are extreme for Earth yet are just within bounds of what has been inferred for Cerberus Fossae. We therefore conclude that we cannot rule out active magma flow as the mechanism responsible for the atypical LF events that likely originate from Cerberus Fossae.

Abril de 2021
Seismic Strain Rate and Flexure at the Hawaiian Islands Constrain the Frictional Coefficient
Authors: A. Bellas and S. J. Zhong
Link: Click here

Flexure occurs on intermediate geologic timescales (~1 Myr) due to volcanic-island building at the Island of Hawaii, and the deformational response of the lithosphere is simultaneously elastic, plastic, and ductile. At shallow depths and low temperatures, elastic deformation transitions to frictional failure on faults where stresses exceed a threshold value, and this complex rheology controls the rate of deformation manifested by earthquakes. In this study, we estimate the seismic strain rate based on earthquakes recorded between 1960 and 2019 at Hawaii, and the estimated strain rate with 10-18–10-15 s-1 in magnitude exhibits a local minimum or neutral bending plane at 15 km depth within the

lithosphere. In comparison, flexure and internal deformation of the lithosphere are modeled in 3D viscoelastic loading models where deformation at shallow depths is accommodated by frictional sliding on faults and limited by the frictional coefficient (µf), and at larger depths by low-temperature plasticity and high-temperature creep. Observations of flexure and the seismic strain rate are best-reproduced by models with µf = 0.3 ± 0.1 and modified laboratory-derived low-temperature plasticity. Results also suggest strong lateral variations in the frictional strength of faults beneath Hawaii. Our models predict a radial pattern of compressive stress axes relative to central Hawaii consistent with observations of earthquake pressure (P) axes. We demonstrate that the dip angle of this radial axis is essential to discerning a change in the curvature of flexure, and therefore has implications for constraining lateral variations in lithospheric strength.

Abril de 2021
Global groundwater wells at risk of running dry
AuthorsScott Jasechko and Debra Perrone
Link: Click here

Groundwater wells supply water to billions of people, but they can run dry when water tables decline. Here, we analyzed construction records for ~39 million globally distributed wells. We show that 6 to 20% of wells are no more than 5 meters deeper than the water table, implying that millions of wells

are at risk of running dry if groundwater levels decline by only a few meters. Further, newer wells are not being constructed deeper than older wells in some of the places experiencing significant groundwater level declines, suggesting that newer wells are at least as likely to run dry as older wells if groundwater levels continue to decline. Poor water quality in deep aquifers and the high costs of well construction limit the effectiveness of tapping deep groundwater to stave off the loss of access to water as wells run dry.

Abril de 2021
First Focal Mechanisms of Marsquakes
Authors: Nienke Brinkman, Simon C. Stähler et al.
Link: Click here

Since February 2019, NASA's InSight lander is recording seismic signals on the planet Mars, which, for the first time, allows to observe ongoing tectonic processes with geophysical methods. A number of Marsquakes have been located in the Cerberus Fossae graben system in Elysium Planitia and further west, in the Orcus Patera depression. We present a first study of the focal mechanisms of three well-recorded events (S0173a, S0183a, S0235b) to determine the processes dominating in the source region. We infer for all three events a predominantly extensional setting. Our method is

adapted to the case of a single, multicomponent receiver and based on fitting waveforms of P and S waves against synthetic seismograms computed for the initial crustal velocity model derived by the InSight team. We explore the uncertainty due to the single-station limitation and find that even data recorded by one station constrains the mechanisms (reasonably) well. For the events in the Cerberus Fossae region (S0173a, S0235b) normal faulting with a relatively steep dipping fault plane is inferred, suggesting an extensional regime mainly oriented E-W to NE-SW. The fault regime in the Orcus Patera region is not determined uniquely because only the P wave can be used for the source inversion. However, we find that the P and weak S waves of the S0183a event show similar polarities to the event S0173, which indicates similar fault regimes.

Abril de 2021
Seismological rockslide warnings in the Himalaya
Authors: N. Purnachandra Rao, Rajesh Rekapalli et al. | Edited by Jennifer Sills | Science Magazine
Link: Click here

On 7 February, a glaciated ridge of Ronti mountain in the western Himalaya faailed at 5600 m above sea level, causing a rocksslide that inducedd a debris flow and flooding in the tributaries of the river Ganga. The events destoyed two hydroelectric projects and claimed more 100 lives. Himalayan countries urgentrly need a robust early warning mechanism for rockslides aand triggered flow cascades such as debris...

Abril de 2021
Bayesian Integration Using Resistivity and Lithology for Improving Estimation of Hydraulic Conductivity
Authors: Shih-Yang Cheng and Kuo-Chin Hsu.
Link: Click here

The characterization of spatially heterogeneous hydraulic conductivity (K) is important in groundwater resources management. We propose a Bayesian statistical method that integrates multiple secondary data (continuous and category data) with primary data (K) to improve regional K field characterization. Considering the disparity of the data scale, spatial scarcity of primary and secondary data, and need for regional scale site characterization, the aquifer thickness is used as the scale for data integration. We transform the high resolution secondary data to the scale of K and perform linear/nonlinear regression analyses for the transformed secondary data and primary data. A Bayesian approach using

Metropolis within Gibbs sampling is developed for jointly integrating the primary and transformed secondary data without a limitation on the type of data attribute and the number of data set. A synthetic example is first presented to demonstrate the capability of the proposed method. Results show that the correlation strength, not the relation type, is the primary factor for improving the estimates. The Bayesian method is applied to Choushui River alluvial fan in Taiwan. Resistivity logs and a lithological description are first upscaled and then simultaneously integrated in the K estimation. Results indicate that the improvement of the K estimate obtained using resistivity data is higher in the proximal and mid fans but lower in the distal fan compared to that obtained using lithofacies data. Jointly integrating two attribute data outperforms using one or no secondary data set for K estimates. The proposed Bayesian integration method is thus versatile and suitable for large scale aquifer characterization.

Abril de 2021
Identification of Surface Deformation in InSAR Using Machine Learning
Authors: Clayton M. J. Brengman and William D. Barnhart
Link: Click here

The availability and frequency of synthetic aperture radar (SAR) imagery are rapidly increasing. This surge of data presents new opportunities to constrain surface deformation that spans various spatial and temporal scales. This expansion also introduces common challenges associated with large volumes of data, including best practices for analyzing these data. In recent years, machine learning techniques have been at the forefront of big data challenges, as an efficient methodology for automatically classifying large volumes of data. Convolutional Neural Networks (CNNs), in particular, have achieved strong levels of performance on image classification problems. Here we present SarNet, a CNN developed to

detect, locate, and classify the presence of co seismic like surface deformation within an interferogram. We trained SarNet using 4 × 106 synthetic interferograms, including both wrapped and unwrapped forward modeled co seismic like surface deformation with synthetic noise representative of the atmospheric and topographic noise found in interferograms. The results show that SarNet obtains an overall accuracy of 99.74% on a validation data set. We use class activation maps (CAMs) to show that SarNet returns the location of surface deformation within the interferogram. We employ a transfer learning method to translate the accuracy of SarNet trained on synthetic data to real interferograms with manually classified co‐seismic surface displacement. We train SarNet on 32 interferograms containing labeled co‐seismic surface deformation as well as noise. The results show that, through transfer learning, SarNet obtains an overall accuracy of 85.22% on a real InSAR data set, and that SarNet returns the location of the surface deformation within the interferogram.

Marzo de 2021
Injection induced seismicity size distribution dependent on shear stress
Authors: Y. Mukuhira, M. C. Fehler et al.
Link: Click here

Frequency magnitude distribution of a series of natural earthquakes and laboratory earthquakes correlates with the applied stress. However, the variation of the frequency magnitude distribution for injection-induced seismicity has not been

understood well since the stress state is rather constant in reservoir scale. This study investigates the stress state of the faults that caused the injection-induced seismicity. We found that the events that occurred from the fault that oriented to have relatively higher shear stress caused the b-value reduction. This finding provides the new perspective of the scaling law of frequency magnitude distribution for induced seismicity. This insight leads to seismic hazard mitigation due to fluid injection.

Marzo de 2021
Using array-derived rotational motion to obtain local wave propagation properties from earthquakes induced by the 2018 geothermal stimulation in Finland
Authors: G. Taylor, G. Hillers et al.
Link: Click here

Earthquakes generate seismic waves consisting of both translational (back and forth) and rotational ground motion. Translational motion is routinely measured by standard seismometers, but the observation of the rotational motion requires relatively expensive and rare instruments. In this study we estimate rotational ground motion caused by earthquakes using groups of translational seismometers. This technique—computing rotational motion from translational

seismometers—has been used before, but the novelty of our study is to use high quality recordings of earthquakes that were induced by the creation of a geothermal reservoir at 6 km depth in bedrock. We use our measurements of ground rotation to estimate the speed and direction in which the seismic waves are travelling when they reach the seismometers. We find that the direction in which the seismic waves travel usually points back to the earthquake location, but at some seismometers the waves arrive from a different direction. At these locations, it is likely that local geological features are altering the direction of the waves. We expect that our findings will provide access to approaches for determining earthquake characteristics and Earth structure that currently require highly specialised instruments.

Marzo de 2021
Investigating a tsunamigenic megathrust earthquake in the Japan Trench
Authors: Shuichi Kodaira, Takeshi Iinuma and Kentaro Imai.
Link: Click here

Ten years ago, the magnitude 9 Tohoku-oki earthquake rocked Japan and caused massive damage. The earthquake also generated a destructive tsunami, the impacts of which are still being managed today. Kodaira et al. review what was learned from the tremendous number of observations from the great earthquake that unexpectedly ruptured into a shallow part of the megathrust fault. Postseismic deformation is ongoing, as is the risk of another very large normal

fault earthquake seaward of the Japan Trench. Ten years have passed since the 2011 Tohoku-oki earthquake occurred in the Japan Trench, where the Pacific plate subducts beneath the continental plate. The earthquake and tsunami caused enormous damage along the coast of northeast Japan in the Tohoku region, and local communities are still recovering. Tsunami traces more than 10 m above sea level were observed along 530 km of coastline in central and northeast Japan, and runups higher than 20 m were observed over about 200 km of the Tohoku coast. The tsunami inundated an area of 561 km2, and its runup reached a maximum of 40 m in northern Tohoku. These statistics made it one of the largest tsunamis ever recorded in historical literature as well as in geological records...

Marzo de 2021
Evidence for the Innermost Inner Core: Robust Parameter Search for Radially Varying Anisotropy Using the Neighborhood Algorithm
Authors: J. Stephenson, H Tkalčić et al
Link: Click here

The model of cylindrical anisotropy in the inner core (IC) states that seismic rays traveling parallel to the Earth's rotational axis travel faster than those parallel to the equator. There have been continuing discrepancies in estimates of the strength and orientation of anisotropy, with some evidence suggesting that such a model may not be supported by available data. Here, we scrutinize the radial dependence of anisotropy within the IC, where the nature of anisotropy has been shown to change anywhere between a 300 and 800 km radius. We

use recent travel time data from the International Seismological Centre in conjunction with the neighborhood algorithm to provide a robust means of testing this idea, through examination of an ensemble of models that satisfactorily fit the data. This can be done with no explicit regularization and without the need for subjective choices associated with binning of phase data. In addition, uncertainty bounds are calculated for anisotropic parameters using a likelihood ratio approach. We find evidence to suggest that commonly employed spatial averaging (binning) methods may be detrimental to obtaining reliable results. We conclude that there is no significant change in the strength of anisotropy with depth in the IC. Instead, we find a change in the slow direction of anisotropy to 54° within the innermost IC at an ∼650 km radius with fast direction parallel to the Earth's rotational axis.

Febrero de 2021
A long lived planetesimal dynamo powered by core crystallization
Authors: Clara Maurel, James F. J. Bryson et al
Link: Click here

The existence of numerous iron meteorite groups indicates that some planetesimals underwent melting that led to metal‐silicate segregation, sometimes producing metallic cores. Meteorite paleomagnetic records suggest that crystallization of these cores led to the generation of dynamo magnetic fields. Here we describe the magnetic history of the partially differentiated IIE iron meteorite

parent body. This is the first planetesimal for which we have a time resolved paleomagnetic record constrained by 40Ar/39Ar chronometry spanning several tens of million years (Ma). We find that the core of the IIE parent body generated a dynamo, likely powered by core crystallization, starting before 78 ± 13 Ma after solar system formation and lasting at least 80 Ma. Such extended core crystallization suggests that the core composed a substantial fraction of the body (urn:x-wiley:00948276:media:grl61991:grl61991-math-000113 20% core to body radius ratio depending on the body's radius), indicating efficient core formation within some partially differentiated planetesimals.

Febrero de 2021
High Frequency Seismic Events on Mars Observed by InSight
Authors: Martin van Driel, Savas Ceylan et al
Link: Click here

The seismometer deployed on the surface of Mars as part of the InSight mission (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) has recorded several hundreds of marsquakes in the first 478 sols after landing. The majority of these are classified as high‐frequency (HF) events in the frequency range from approximately 1 to 10 Hz on Mars' surface. All the HF events excite a resonance around 2.4 Hz and show two distinct but broad arrivals of seismic energy that are separated by up to 450 s. Based on the

frequency content and vertical to horizontal energy ratio, the HF event family has been subdivided into three event types, two of which we show to be identical and only appear separated due to the signal‐to‐noise ratio. We show here that the envelope shape of the HF events is explained by guided Pg and Sg phases in the Martian crust using simple layered models with scattering. Furthermore, the relative travel times between these two arrivals can be related to the epicentral distance, which shows distinct clustering. The rate at which HF events are observed varies by an order of magnitude over the course of one year and cannot be explained by changes of the background noise only. The HF content and the absence of additional seismic phases constrain crustal attenuation and layering, and the coda shape constrains the diffusivity in the uppermost shallow layers of Mars.

Febrero de 2021
Bayesian integration using resistivity and lithology for improving estimation of hydraulic conductivity
Authors: Shih-Yang Cheng and Kuo-Chin Hsu
Link: Click here

The characterization of spatially heterogeneous hydraulic conductivity (K) is important in groundwater resources management. We propose a Bayesian statistical method that integrates multiple secondary data (continuous and category data) with primary data (K) to improve regional K field characterization. Considering the disparity of the data scale, spatial scarcity of primary and secondary data, and need for regional‐scale site characterization, the aquifer thickness is used as the scale for data integration. We transform the high-resolution secondary data to the scale of K and perform linear/nonlinear regression analyses for the transformed secondary data and primary data. A Bayesian approach using

Metropolis within Gibbs sampling is developed for jointly integrating the primary and transformed secondary data without a limitation on the type of data attribute and the number of data set. A synthetic example is first presented to demonstrate the capability of the proposed method. Results show that the correlation strength, not the relation type, is the primary factor for improving the estimates. The Bayesian method is applied to Choushui River alluvial fan in Taiwan. Resistivity logs and a lithological description are first upscaled and then simultaneously integrated in the K estimation. Results indicate that the improvement of the K estimate obtained using resistivity data is higher in the proximal and mid fans but lower in the distal fan compared to that obtained using lithofacies data. Jointly integrating two‐attribute data outperforms using one or no secondary data set for K estimates. The proposed Bayesian integration method is thus versatile and suitable for large-scale aquifer characterization.

Febrero de 2021
Real-time Earthquake Early Warning with Deep Learning: Application to the 2016 M 6.0 Central Apennines, Italy Earthquake
Authors: Xiong Zhang, Miao Zhang et al
Link: Click here

Earthquake early warning systems are required to report earthquake locations and magnitudes as quickly as possible before the damaging S wave arrival to mitigate seismic hazards. Deep learning techniques provide potential for extracting earthquake source information from full seismic waveforms instead of seismic phase picks. We developed a novel deep learning earthquake early

warning system that utilizes fully convolutional networks to simultaneously detect earthquakes and estimate their source parameters from continuous seismic waveform streams. The system determines earthquake location and magnitude as soon as very few stations receive earthquake signals and evolutionarily improves the solutions by receiving continuous data. We apply the system to the 2016 M 6.0 Central Apennines, Italy Earthquake and its first-week aftershocks. Earthquake locations and magnitudes can be reliably determined as early as four seconds after the earliest P phase, with mean error ranges of 8.5–4.7 km and 0.33–0.27, respectively.

Enero de 2021
Potential link between 2020 Mentone, West Texas M5 earthquake and nearby wastewater injection: implications for aquifer mechanical properties
Authors: Sui Tung, Guang Zhai et al
Link: Click here

The M5 Mentone earthquake that occurred on March 26, 2020, was the largest event recorded over the last two decades in West Texas within the Delaware Basin, a U.S. major petroleum producing area. Also, numerous hydrofracturing and wastewater disposal wells are spread across this region. Within

a 30 km distance to mainshock, eight class II injection wells for industrial wastewater disposal target the deep porous Ellenburger aquifer at an average rate of 1.36x106 BBL/mo during 2012-2020. Poroelastic models of fluid diffusion show these nearby injectors collectively imparted up to 80.5 kPa of Coulomb stress at the mainshock location, capable of triggering this M5 event. Assuming the Mentone event occurs when pore pressure increase is maximum, the time delay between peak injection and the M5 occurrence corresponds with an optimal permeability of 6.76x10-14 m2 for the Ellenburger aquifer layer, in agreement with independent estimates.

Enero de 2021
Tidal influence on seismic activity during the 2011-2013 El Hierro volcanic unrest
Authors: Luis Miguel Sanz, Pablo J. González et al
Link: Click here

The El Hierro volcanic unrest started in July 2011, with an increase in observed seismicity rates and surface deformation. After the initial onset, hypocenters migrated southward through September 2011, culminating in a submarine eruption beginning on October 10, 2011 and finishing in February 2012. The seismic activity continued, with remarkable periods of unrest through 2012 and 2013. The most significant episodes of seismic activity during this unrest are related to magma migration at depth. In this work, we compute tidal stress for each earthquake, at its

hypocenter depth, and assign them a tidal stress phase angle. We have found statistically significant correlations between the occurrence of earthquakes and tidal stress phase angles, corresponding mainly to increasing tidal stress change rates. We found primarily that the magnitude of vertical and E‐W horizontal tidal stress values and their changing rates with time were correlated with earthquake occurrence times. We also found that there is no correlation between tides and seismicity at times with no observed surface displacements, suggesting that tidal modulation might be related to overpressure during migration of magma. Tidal modulation changes with depth and the influence of ocean‐loading tides is stronger than the influence of solid Earth tides. Our results support the hypothesis that tidal stress may modulate the seismicity during volcanic unrest, particularly during shallow depth magma migration.

Diciembre de 2020
Probabilistic Geomagnetic Storm Forecasting via Deep Learning
Authors: Adrian Tasistro-Hart, Alexander Grayver et al
Link: Click here

Geomagnetic storms, which are governed by the plasma magnetohydrodynamics of the solar-interplanetary-magnetosphere system, entail a formidable challenge for physical forward modeling. Yet, the abundance of high quality observational data has been amenable for the application of data-hungry neural networks to geomagnetic storm forecasting. Almost all Geomagnetic storms, which are governed by the plasma magnetohydrodynamics of the solar-interplanetary-magnetosphere system, entail a formidable challenge for physical forward.

modeling. Yet, the abundance of high quality observational data has been amenable for the application of data-hungry neural networks to geomagnetic storm forecasting. Almost all applications of neural networks to storm forecasting have utilized solar wind observations from the Earth-Sun first Lagrangian point (L1) or closer and generated deterministic output without uncertainty estimates. Furthermore, forecasting work has focused on indices that are also sensitive to induced internal magnetic fields, complicating the forecasting problem with another layer of non-linearity. We address these points, presenting neural networks trained on observations from both the solar disk and the L1 point. Our architecture generates reliable probabilistic forecasts over Est, the external component of the disturbance storm time index, showing that neural networks can gauge confidence in their output.

Diciembre de 2020
Reconstruction of GRACE Total Water Storage Through Automated Machine Learning
Authors: Alexander Y. Sun, Bridget R. Scanlon et al
Link: Click here

The Gravity Recovery and Climate Experiment (GRACE) satellite mission and its follow-on, GRACE-FO, have provided unprecedented opportunities to quantify the impact of climate extremes and human activities on total water storage at large scales. The approximately one-year data gap between the two GRACE missions needs to be filled to maintain data continuity and maximize mission benefits. In this study, we applied an automated machine learning (AutoML) workflow to perform gridwise GRACE-like data reconstruction. AutoML represents a new paradigm for optimal algorithm selection, model structure selection, and hyperparameter tuning, addressing some of the most challenging issues

in machine learning applications. We demonstrated the workflow over the conterminous U.S. (CONUS) using six types of machine learning models and multiple groups of meteorological and climatic variables as predictors. Results indicate that the AutoML-assisted gap filling achieved satisfactory performance over the CONUS. On the testing data, the mean gridwise Nash-Sutcliffe efficiency is around 0.85, the mean correlation coefficient is around 0.95, and the mean normalized root-mean square error is about 0.09. Trained models maintain good performance when extrapolating to the mission gap and to GRACE-FO periods (after 2017/06). Results further suggest that no single algorithm provides the best predictive performance over the entire CONUS, stressing the importance of using an end-to-end workflow to train, optimize, and combine multiple machine learning models to deliver robust performance, especially when building large-scale hydrological prediction systems and when predictor importance exhibiting strong spatial variability.

Diciembre de 2020
Complex Basement-Involved Contractional Structures in the Pre-Andean Basins of Northern Chile: A Review from Seismic Data
Authors:F. Martínez, B. Muñoz et al
Link: Click here

For many years, the geometry, kinematic, and the age of the basement-involved structures of the Pre-Andean basins of northern Chile have been debated. Even, many tectonic models supported by surface geological data have ignored how is the continuity of these structures in the subsurface, and also their possible relation with ancient pre-orogenic structures, thus difficulting the understanding of the main tectonic mechanisms that acted during the Andean uplift. To solve this problem, we discussed in this study the geometry and timing of the basement-involved contractional structures present in the Pre-Andean basins of northern Chile. We present field and seismic evidences of different basement-involved structural styles, including reverse faults, inverted normal faults, basement thrust ramps, and rotated and reworked basin margins, and use it them to produce three large structural cross-sections showing the geometries and

distribution of structures along the inner forearc region. The structures are interpreted to have resulted from basin inversion, which was followed by large reverse faulting accumulating 43 km in the Salar de Atacama, 10 km in the Salar de Punta Negra and 27 km in the Salar de Pedernales. Major reverse faults are predominantly located along the western and eastern edges of the basins, whereas inverted normal faults, basement thrust ramps, and othe structures are confined to the central sections. In this context, large basement thrust ramps and reverse faults are the most effective structures for generating crustal thickening. Previous analyses (U-Pb dating) of synorogenic deposits over inverted structures and apatite fission track data from Paleozoic basement pre-rift rocks suggest that contraction in the region began in the Late Cretaceous-Paleocene and continued throughout the Cenozoic; however, basement rocks experienced rapid cooling due to tectonic uplift during the Eocene. Further, the results indicate that basement-involved contractional structures are not only generated by flat-slab subduction processes, as observed in other regions of northern Chile (e.g., Frontal Cordillera). Finally, we conclude that the observed structural complexity predominantly results from the initial distribution of pre-orogenic extensional structures.

Diciembre de 2020
Analytical Prediction of Seismicity Rate Due to Tides and Other Oscillating Stresses
Authors: Elías R. Heimisson, Jean-Philippe Avouac et al
Link: Click here

Oscillatory stresses are ubiquitous on Earth and other solid‐surface bodies. Tides and seasonal signals perpetually stress faults in the crust. Relating seismicity to these stresses offers fundamental insight into earthquake triggering. We present a simple model that describes seismicity rate due to perpetual oscillatory stresses. The model applies to large-amplitude,

nonharmonic, and quasiperiodic stressing. However, it is not valid for periods similar to the characteristic time ta. We show that seismicity rate from short‐period stressing scales with the stress amplitude, but for long periods with the stressing rate. Further, that background seismicity rate r is equal to the average seismicity rate during short‐period stressing. We suggest that Aσ0 may be underestimated if stresses are approximated by a single harmonic function. We revisit Manga et al. (2019, https://doi.org/10.1029/2019GL082892), which analyzed the tidal triggering of marsquakes and provide a rescaling of their seismicity rate response that offers a self‐consistent comparison of different hydraulic conditions.

Noviembre de 2020
A Machine Learning-Based Detection of Earthquake Precursors Using Ionospheric Data
Authors: A. A. Akyol, O. Arikan et al
Link: Click here

Detection of precursors of strong earthquakes is a challenging research area. Recently, it has been shown that strong earthquakes affect electron distribution in the regional ionosphere with indirectly observable changes in the ionospheric delays of GPS signals. Especially, the total electron content (TEC) estimated from GPS data can be used in the seismic precursor detection for strong earthquakes. Although physical mechanisms are not well understood yet, GPS‐based seismic precursors can be observed days prior to the occurrence of the earthquake. In this study, a novel machine learning‐based technique, EQ-PD, is proposed

for detection of earthquake precursors in near real time based on GPS‐TEC data along with daily geomagnetic indices. The proposed EQ‐PD technique utilizes support vector machine (SVM) classifier to decide whether an observed spatiotemporal anomaly is related to an earthquake precursor or not. The data fed to the classifier are composed of spatiotemporal variability map of a region. Performance of the EQ‐PD technique is demonstrated in a case study over a region covering Italy in between the dates of 1 January 2014 and 30 September 2016. The data are partitioned into three nonoverlapping time periods, that are used for training, validation, and test of detecting precursors of earthquakes with magnitudes above 4 in Richter scale. The EQ‐PD technique is able to detect precursors in 17 out of 21 earthquakes while generating 7 false alarms during the validation period of 266 days and 22 out of 24 earthquakes while generating 13 false alarms during the test period of 282 days.

Noviembre de 2020
Machine Learning-Based Analysis of Geological Susceptibility to Induced Seismicity in the Montney Formation, Canada
Authors: Paulina Wozniakowska and David W. Eaton
Link: Click here

We analyze data from 6,466 multistage horizontal hydraulic fracturing wells drilled into the Montney Formation over a large region in western Canada to evaluate the impact of geological, geomechanical, and tectonic characteristics on

the distribution of hydraulic fracturing-induced seismicity. Logistic regression was used to obtain a machine learning estimate of the seismogenic activation potential of each well. Our results fit the observed spatial variability, including an enigmatic change in seismicity at 120°W that does not correlate with any change in industrial activity. Feature importance analysis provides insight into data types that have the greatest impact on the results. Based on current data, seismogenic activation potential is most strongly influenced by depth of injection and distance of the well to the Cordilleran thrust belt.

Noviembre de 2020
Modern Meteoric 36Cl Deposition in the Atacama Desert, Chile
Authors: Fan Wang and Greg Michalski
Link: Click here

36Cl is a radioactive chlorine isotope found in the atmosphere and can be used in many ways, from determining ages of soils and groundwaters to tracing origins of salts and groundwater flow paths. In order to use meteoric 36Cl, we must know how much is deposited from the

atmosphere to the surface. There are only a few studies of 36Cl deposition in southern hemisphere, even less in extraordinarily dry environments, which hinders its use in desert regions south of the equator. We have measured the 36Cl deposition along a west‐east transect in the Atacama Desert in northern Chile and developed a simple explanation for our results. Future work will use this deposition rate to determine the duration of soil salt accumulation in the Atacama and understand changes in climate (precipitation) in the past.

 

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