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The increasing number of flood events combined with coastal urbanization has contributed to significant economic losses and damage to buildings and infrastructure. Development of higher resolution SAR flood mapping that accurately identifies flood features at all scales can be incorporated into operational flood forecasting tools, improving response and resilience to large flood events. Here, we present a comparison of several methods for characterizing flood inundation using a combination of synthetic aperture radar (SAR) remote sensing data and machine learning methods. We implement two applications with SAR GRD data, an amplitude thresholding technique applied, for the first time, to Sentinel-1A/B SAR data, and a machine learning technique, DeepLabv3+. We also apply DeepLabv3+ to a false color RGB characterization of dual polarization SAR data. Analyses at 10 m pixel spacing are performed for the major flood event associated with Hurricane Harvey and associated inundation in Houston, TX in August of 2017. We compare these results with high-resolution aerial optical images over this time period, acquired by the NOAA Remote Sensing Division. We compare the results with NDWI produced from Sentinel-2 images, also at 10 m pixel spacing, and statistical testing suggests that the amplitude thresholding technique is the most effective, although the machine learning analysis is successful at reproducing the inundation shape and extent. These results demonstrate the effectiveness of flood inundation mapping at unprecedented resolutions and its potential for use in operational emergency hazard response to large flood events. [ABSTRACT FROM AUTHOR]

Because of its proximity to the city of Naples and with a population of nearly 1 million people within its caldera, Campi Flegrei is one of the highest risk volcanic areas in the world. Since the last major eruption in 1538, the caldera has undergone frequent episodes of ground subsidence and uplift accompanied by seismic activity that has been interpreted as the result of a stationary, deeper source below the caldera that feeds shallower eruptions. However, the location and depth of the deeper source is not well-characterized and its relationship to current activity is poorly understood. Recently, a significant increase in the uplift rate has occurred, resulting in almost 13 cm of uplift by 2013 (De Martino et al., 2014; Samsonov et al., 2014b; Di Vito et al., 2016). Here we apply a principal component decomposition to high resolution time series from the region produced by the advanced Multidimensional SBAS DInSAR technique in order to better delineate both the deeper source and the recent shallow activity. We analyzed both a period of substantial subsidence (1993–1999) and a second of significant uplift (2007–2013) and inverted the associated vertical surface displacement for the most likely source models. Results suggest that the underlying dynamics of the caldera changed in the late 1990s, from one in which the primary signal arises from a shallow deflating source above a deeper, expanding source to one dominated by a shallow inflating source. In general, the shallow source lies between 2700 and 3400 m below the caldera while the deeper source lies at 7600 m or more in depth. The combination of principal component analysis with high resolution MSBAS time series data allows for these new insights and confirms the applicability of both to areas at risk from dynamic natural hazards. [ABSTRACT FROM AUTHOR]

Abstract: We present new results for shallow aseismic creep on the Hayward fault in California using a new DInSAR technique. This method not only provides, for the first time, the ability to map the displacement field on both sides of the fault, it does so over a much shorter time period than earlier results. The results provide a good match in the near-field to both the regional continuous GPS velocities and data from an alinement network that measures long-term creep along the fault. The average slip rate for the northern segment of the Hayward fault is ∼4.4mm/yr between 2008 and 2011, slightly less than that estimated for longer time periods, suggesting that the slip rate may not be constant. If the slip rate along the fault is variable on the decadal or longer scale, current estimates of its earthquake potential and the associated hazard associated with the slip rate deficit may need to be revised from previous estimates. We demonstrate the potential impact of this method to better define the spatial and temporal complexity of aseismic slip and estimate the accumulated elastic strain along one of the most significant sources of seismic hazard in the San Francisco Bay area. [Copyright &y& Elsevier]

Abstract: Earthquake fault systems interact over a broad spectrum of spatial and temporal scales and, in recent years, studies of the regional seismicity in a variety of regions have produced a number of new techniques for seismicity-based earthquake forecasting. While a wide variety of physical assumptions and statistical approaches are incorporated into the various methodologies, they all endeavor to accurately replicate the statistics and properties of both the historic and instrumental seismic records. As a result, the last ten years have seen significant progress in the field of intermediate- and short-term seismicity-based earthquake forecasting. These include general agreement on the need for prospective testing and successful attempts to standardize both evaluation methods and the appropriate null hypotheses. Here we differentiate the predominant approaches into models based upon techniques for identifying particular physical processes and those that filter, or smooth, the seismicity. Comparison of the methods suggests that while smoothed seismicity models provide improved forecast capability over longer time periods, higher probability gain over shorter time periods is achieved with methods that integrate statistical techniques with our knowledge of the physical process, such as the epidemic-type aftershock sequence (ETAS) model or those related to changes in the b-value, for example. In general, while both classes of seismicity-based forecasts are limited by the relatively short time period available for the instrumental catalog, significant advances have been made in our understanding of both the limitations and potential of seismicity-based earthquake forecasting. There is general agreement that both short-term forecasting, on the order of days to weeks, and longer-term forecasting over five-to-ten year periods, is within reach. This recent progress serves to illuminate both the critical nature of the different temporal scales intrinsic to the earthquake process and the importance of high quality seismic data for the accurate quantification of time-dependent earthquake hazard. [Copyright &y& Elsevier]

Abstract: Volcano flank instability has been recognized at many volcanoes around the globe. Structural, morphological, geodetic and geophysical evidence supports the continuous deformation of their flanks. While identification of instability has been recognized in well-documented examples, until recently the initial stages of such processes have been difficult to capture. Using a combination of geological, geodetic and geophysical data analysis, we study the stability of the Cumbre Vieja. New descending radar interferometric data, covering a volcanologically quiet period between 1992 and 2008 at Cumbre Vieja, indicate movement away from the satellite on the western volcano flank. Using an inversion of stacked velocity maps, we determine the geometry and slip for a near-horizontal dislocation beneath the western flank of Cumbre Vieja. Our ground deformation modelling results (position and depth) are in agreement with a low-density anomaly constrained by gravity data. The previously undetected intereruptive ground deformation at Cumbre Vieja volcano flanks was explained as an indicator of a kinematic passive response model of the flank, where the flanks were mobilized only during periods of magmatic activity (shallow dike intrusions) and remained stable and undeformed during intereruptive periods. Here, we present new results indicating that active creeping stress release due to gravitational loading is also a dominant deformation mechanism for (current) intereruptive periods at Cumbre Vieja, which would contribute positively to the stabilization of the edifice and reduce the associated hazard related to the volcano flank dynamics. This study at Cumbre Vieja can be considered as a prototype for similar volcanoes around the Macaronesian islands group (e.g., Fogo, Teide, El Hierro, Pico) and elsewhere. [ABSTRACT FROM AUTHOR]

In this work, we provide a joint study of the stress accumulation method (SAM) (K ing and B owman, 2003) and the Pattern Informatics (PI) index (T iampo et al., 2002b). We examine the theoretical underpinnings for the similarities between the two techniques, as well as the differences in their application. The SAM technique is employed to determine likely mechanisms for smaller areas of increased probability identified by the PI index, while a modified version of the PI index can be used to locate regions where the smaller magnitude associated with the anomaly is below the resolution of the SAM. Finally, we present three case studies from different regions of the San Andreas fault system to illustrate both their complementary nature, as well as the advantages to combining them in one synthesized analysis. [ABSTRACT FROM AUTHOR]

Abstract: A method for the computation and interpretation of gravity and height changes and vertical gravity gradients produced by magmatic intrusions in a layered elastic–gravitational medium is presented. The methodology assumes a planar medium geometry, which consists of welded layers overlying a half-space. The medium is elastic and gravitating. The intrusion is treated as a point source and can be located at any depth inside the medium. The theoretical elastic–gravitational model allows the computation of the so-called geometric and orthometric vertical displacements as well as gravity changes of different types. The corresponding vertical gravity gradients can also be computed. We present several examples of theoretical computations and study different types of these geometric and orthometric gravity gradients and the information we can get from the application of the methodology described. The results presented show that the use of these gradients is a useful tool to obtain information on the dynamics of the injection processes, including the detection of new magma recharge. We show that using the elastic–gravitational deformation model we can explain non-linear gravity–height relationships that appear in volcanic areas. We also present the application of the methodology to Mayon volcano, Philippines, delineating the intrusion of new magma, consistent with the produced eruptions after the observation period. [Copyright &y& Elsevier]

Examines viscoelastic displacement and gravity changes due to point magmatic intrusions in a gravitational layered solid Earth. Extension of a deformation model; Planar earth geometry of a model.

La Palma, Canary Islands, had its largest historical eruption in 2021. From January 2022 to May 2023 there were >2,100 seismic events, primarily at depths ≤20 km, prompting us to update the deformation and modeling study, using interferometric synthetic aperture radar observations and a last generation interpretation tool. We detect the evolution of the remaining magmatic body in the SW portion of the island, with arrival of new magma moving into the oceanic crust out to sea, and a pressurized zone in the central‐eastern area, at regions of structural weakness. The current source characteristics have some similarities to the early stage dynamics prior to the 2021 eruption. Operational and multidisciplinary studies must continue to monitor either their stabilization or growth and destabilization. The ability to identify magma ascent using only deformation data over short time periods allows us to characterize unrest patterns and provide new insights into volcanic processes. Plain Language Summary: Following the 2021 eruption at La Palma, Canary Islands, seismic activity has persisted that may be a precursor to future volcanic activity. Here we perform an updated deformation and modeling study that characterizes the evolution of the remaining magma in the SW area of the island. A fresh injection of magma occurs in the oceanic crust off the coast, along with a pressurized region in the central‐eastern area of the island where crustal weakness exists close to recent volcanic eruptions. The 2022–2023.4 process has similar characteristics to the evolution prior to the 2021 eruption. Ongoing studies should focus on monitoring the increase or decrease in this activity. Improved characterization of changing volcanic activity over short time periods can provide new insights into ongoing volcanic processes. Key Points: We determine the current unrest is similar to that prior to the 2021 eruption warranting attention by hazard response decision makersWe detect a shallow magmatic intrusion in the SW of the island migrating W into the submarine crust of the islandWe also detect a shallow pressurized zone located in the central eastern region of the island [ABSTRACT FROM AUTHOR]

As part of the collaborative GeoSciFramework project, we are establising a monitoring system for the Yellowstone volcanic area that integrates multiple geodetic and seismic data sets into an advanced cyber-infrastructure framework that will enable real-time streaming data analytics and machine learning and allow us to better characterize associated long- and short-term hazards. The goal is to continuously ingest both remote sensing (GNSS, DInSAR) and ground-based (seismic, thermal and gas observations, strainmeter, tiltmeter and gravity measurements) data and query and analyse them in near-real time. In this study, we focus on DInSAR data processing and the effects from using various atmospheric corrections and real-time orbits on the automated processing and results. We find that the atmospheric correction provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) is currently the most optimal for automated DInSAR processing and that the use of real-time orbits is sufficient for the early-warning application in question. We show analysis of atmospheric corrections and using real-time orbits in a test case over the Kilauea volcanic area in Hawaii. Finally, using these findings, we present results of displacement time series in the Yellowstone area between May 2018 and October 2019, which are in good agreement with GNSS data where available. These results will contribute to a baseline model that will be the basis of a future early-warning system that will be continuously updated with new DInSAR data acquisitions. [ABSTRACT FROM AUTHOR]

It is suggested that in addition to seismicity deep fluid injection may cause surface uplift and subsidence in oil and gas‐producing regions. This study uses the Raton Basin as an example to investigate the hydromechanical processes of surface uplift and subsidence during wastewater injection. The Raton Basin, in southern central Colorado and northern central New Mexico, has experienced wastewater injection related to coalbed methane and gas production starting in 1994. In this study, we estimate the extent and magnitude of total vertical deformation in the Raton Basin from 1994 to 2020 and incremental deformation between the years 2017 to 2020. Results indicate a modeled uplift as much as 15 cm occurring between 1994 and 2020. Between 2017 and 2020, up to 3 cm of uplift occurred, largely near the northwestern injection wells. Most modeled uplift between 1994 and 2020 occurred near the southern wells, where the greatest cumulative volume of wastewater was injected. However, modeled subsidence occurred around the southern and eastern wells between 2017 and 2020, after the rate of injection decreased. Modeling indicates that while the magnitude of modeled uplift corresponds to cumulative injection volume and maximum rate in the long‐term, short‐term incremental deformation (uplift or subsidence) is controlled by changes in the rate of injection. The number of yearly earthquake events follows periods of rapid modeled uplifting throughout the Basin, suggesting that measurable surface deformation may be caused by the same injection‐induced pore pressure perturbations that initiate seismicity. [ABSTRACT FROM AUTHOR]

Permafrost degradation in the Arctic is accelerating and affects northern communities, ecosystems, and global soil carbon storage. However, the extent, distribution, and rates of permafrost degradation in the pan-Arctic remain unknown, contributing to the challenges of mapping and monitoring it in a harsh and remote environment. We applied feature extraction, deep learning, and crowdsourcing to an open-access, high-resolution (2 m), and multi-temporal digital elevation models (i.e. ArcticDEM), to identify retrogressive thaw slumps (RTSs), a dynamic form of permafrost degradation widespread across the Arctic. Specifically, we (1) developed an automated pipeline to process approximately 200 TB of ArcticDEM data; (2) designed feature extractors (pixel-wise elevation differences, polygons of elevation reductions, lines of narrow-steep slopes, and RTS headwall lines) to identify slumps; (3) trained a super-efficient object detection algorithm based on deep learning (YOLOv4) and used it to locate RTSs from composite imagery derived from the ArcticDEM; (4) combined the extracted features and the bounding boxes output by YOLOv4 to obtain mapping results at a manageable level; and (5) developed a crowdsourcing system and invited volunteers to validate and refine the results. The final map included 2494 RTSs (actively expanding during ArcticDEM observation) across the Arctic. The results also show that (1) it is necessary to combine the extracted features and deep learning to remove many false positives in the scenario with limited training data, but large regions to map; (2) some hotspots of RTSs need further and detailed investigation, including an RTS cluster in Greenland; (3) the crowdsourcing system is useful for the validation of a large dataset, but responses to this work were limited, possibly because RTSs are a quite specific topic that not many people are familiar with. The results likely miss many RTSs due to the limitation in the method for identifying RTSs and uncertainties as well as short observation periods of ArcticDEM at many locations. This study provides data and serves as a starting point to develop a global inventory and better understand permafrost thaw in the pan-Arctic using very high resolution remote sensing. • First attempt to map RTSs at a near pan-Arctic scale using high resolution (2 m) data. • Developing an automated pipeline to process approximately 200 TB of data. • Combining feature extraction and deep learning to obtain results at a manageable level. • Developing a crowdsourcing system to bring efforts from the broader community. • Found a cluster of RTSs in Greenland where permafrost research is very limited. [ABSTRACT FROM AUTHOR]

The volcanic eruption at La Palma started on September 19, 2021. The eruption was preceded by a seismic swarm that began on September 11, although anomalous seismicity has been observed on the island since 2017. During the co-eruptive phase of the seismic activity, hypocenters depth was generally less than 15 km, save for the period between November 10 and November 27, when hypocenters ranged in the depth from 15 to 40 km. The eruption ended on December 13, 2021. We compute tidal stress for each earthquake at the hypocenter depth and find statistically significant correlations between the occurrence times of the earthquakes and the confining tidal stress values and stress rates. The correlation is depth-dependent, and ocean-loading tides have a stronger effect than body tides. We find that tidal stress variations contribute to the eruption onset and that certain explosive events, typical in Strombolian type volcanoes, seem to occur preferentially when the tidal stress rate is high. Our analysis supports the hypothesis that tides may modulate earthquake activity in volcanic areas, specifically during magma migration at shallow depths. A conceptual model is proposed, which could have a general application in the Canary Islands archipelago and other volcanic islands. [ABSTRACT FROM AUTHOR]

The Raton Basin of Southern Colorado and Northern New Mexico experienced a significant increase in seismicity over the last several decades, including two M5+ earthquakes. The increase in seismicity started soon after an increase in wastewater disposal associated with coal‐bed methane production. Twenty‐nine wastewater injection wells have operated in the Basin, with several high‐rate injectors located within a kilometer of the most seismically active regions. We developed a pore pressure model to investigate the relationship between pore pressure diffusion and onset of induced seismicity, with an emphasis on the Trinidad fault zones. Our model indicates that sufficient pore pressure increase had accumulated on the northern extent of the Trinidad fault zone to induce seismicity at the time of early‐stage seismic activity. The hydrogeologic architecture of the Basin played a key role in controlling pore pressure perturbation. The basal sedimentary interval with moderately low diffusivity restricted vertical pore pressure diffusion, creating a substantial lag time between wells becoming active and the expression of perturbation in the fault zones. The spatiotemporal relationship between early‐stage seismicity and wastewater injection in conjunction with modeled pore pressures suggests that the early‐stage seismicity in the Raton Basin was likely triggered by pore pressure diffusion. Plain Language Summary: In the Raton Basin, coal‐bed methane production sparked the need for deep wastewater disposal starting in 1994. Prior to wastewater injection few earthquakes were recorded within its boundaries but a large increase in earthquakes has been recorded over the last several decades. Pore pressure increase, caused by the deep wastewater injection, is thought to be the reason for the increase in local earthquakes. We developed a model to estimate pore pressure increases on several fault zones that have recently exhibited increased earthquake frequency. We found that wastewater injection produced increases in pore pressure on the fault zones large enough to cause earthquakes. This suggests that increased seismicity is, at least in part, the result of pore pressure change caused by deep wastewater injection. Key Points: Pore pressure change between 0.007 and 0.03 MPa initiates the onset of induced seismicity on the Trinidad fault zoneThe basal sedimentary interval restricted pore pressure diffusion, limiting the impact of high‐rate injection wells in the short termThe depth varying permeability of crystalline basement effects the manner and magnitude of pore pressure diffusion into basement faults [ABSTRACT FROM AUTHOR]

Sub-lithospheric stresses can be estimated by analysis of gravity field measurements. Depending on the measured gravimetric quantity, different methods can be employed to estimate those sub-lithospheric stresses. Here, we further develop the Runcorn’s theory for estimation of mantle stresses (1967) such that a Moho model and full topographic information are used to recover the function from which the stress can be computed by taking derivatives northwards and eastwards. We develop new integral equations for such a purpose and recover this function by solving those integral equations locally over the Indo-Pak (India-Pakistan) region from (1) a gravimetric Moho model computed from the SRTM (Shuttle Radar Topography Mission) and the Earth gravity model EGM2008, (2) SRTM and the seismic Moho model of CRUST1.0 and (3) data and measurements of the GOCE (Gravity field and steady-state Ocean Circulation Explorer) mission. Finally, we perform a joint inversion of seismic and GOCE data for the same purpose. The numerical results show that the use of a seismic Moho model recovers information about the stress field which is not seen in the results derived from a gravimetric Moho model. A combination of the seismic Moho model, SRTM and GOCE yields a better stress field than that of either the seismic and/or gravimetric data alone. The magnitudes of the sub-lithospheric stress are computed from the shear stress components over the area and good agreement is seen between the recovered combined stress field, the regional tectonic boundaries and the seismicity of the World Stress Map 2008 database. [ABSTRACT FROM AUTHOR]

Observations that unequivocally link seismicity and wastewater injection are scarce. Here we show that wastewater injection in eastern Texas causes uplift, detectable in radar interferometric data up to >8 kilometers from the wells. Using measurements of uplift, reported injection data, and a poroelastic model, we computed the crustal strain and pore pressure. We infer that an increase of >1 megapascal in pore pressure in rocks with low compressibility triggers earthquakes, including the 4.8–moment magnitude event that occurred on 17 May 2012, the largest earthquake recorded in eastern Texas. Seismic activity increased even while injection rates declined, owing to diffusion of pore pressure from earlier periods with higher injection rates. Induced seismicity potential is suppressed where tight confining formations prevent pore pressure from propagating into crystalline basement rocks. [ABSTRACT FROM AUTHOR]

La Palma, Canary Islands, underwent volcanic unrest which culminated in its largest historical eruption. We study this unrest along 2021 using Interferometric Synthetic Aperture Radar (InSAR) and a new improved interpretation methodology, comparing achieved results with the crustal structure. We reproduce the final phase of La Palma volcanic unrest, highligthing a shallow magma accumulation which begins about 3.5 months before the eruption in a crustal volume charactherized by low density and fractured rocks. Our modeling, together with our improved pictures of the crustal structure, allows us to explain the location and characteristics of the eruption and to detect failed eruption paths. These can be used to explain post-eruptive phenomena and hazards to the local population, such as detected gases anomalies in La Bombilla and Puerto Naos. Our results have implications for understanding volcanic activity in the Canaries and volcano monitoring elsewhere, helping to support decision-making and providing significant insights into urban and infrastructure planning in volcanic areas. [ABSTRACT FROM AUTHOR]

The 2019 Ridgecrest earthquake sequence manifested as one of the most complex fault surface ruptures observed in California in modern times. The M6.4 foreshock and M7.1 mainshock occurred on an intricate network of orthogonal and sub‐parallel faults resulting in observable surface displacement and surface rupture captured by geodetic data. Here we present the application of a high‐resolution 3D finite element model (FEM) approach to invert for the detailed fault slip of the entire sequence using complex rheology and fused coseismic Global Navigation Satellite System (GNSS) data with Sentinel‐1 differential interferometric synthetic aperture radar and pixel offset data. The heterogeneous FEM and the fused geodetic data set of pixel offsets, interferograms, and GNSS data results in our optimal inversion solution. This preferred solution is a complex, high‐resolution non‐planar slip model of both the M6.4 and M7.1 events that features three main regions of large slip (6.9+ m), with depths ranging from 2 to 10 km. The regions of slip are bounded by the mainshock hypocenter and the mainshock aftershocks and appear to be related to spatially varying rheological properties. We successfully reproduce a localized region of observed subsidence in the northern portion of the primary fault through the inclusion of a curved fault strand with a significant dip‐slip component. The curved fault strand is the site of our maximum slip of 7.4 m at a depth of 4.2 km. The results demonstrate a robust fit from a more complete, detailed model for the entire seismogenic zone with reasonable computational cost, providing new insights into the governing rheologic and structural processes. Plain Language Summary: The 2019 Ridgecrest, California earthquake sequence consisted of two main earthquakes: the M6.4 foreshock and the M7.1 mainshock. Understanding the structure and behavior of the faults responsible for these earthquakes is important to earthquake hazard and forecasting. We construct a complex 3D model representing the earth's interior at the location of the Ridgecrest earthquake using triangular building blocks. By combining Global Positioning System and different microwave remote sensing data, we produce a detailed map of how the ground deformed, even close to the faults. We use this deformation map to fine tune our 3D model and determine in which direction and by how much the faults moved during the M6.4 and M7.1 earthquakes. We find that the faults had large movement of almost 7 m in three regions at depths of 2–10 km. The largest movement of 7.4 m occurs north of the mainshock at an offshoot of the main fault where our mapped deformation shows the ground sinking. The locations of large fault movement coincide with regions of low aftershock activity and particular earth material. Key Points: High resolution finite element model with complex rheology and fused synthetic aperture radar‐Global Navigation Satellite System data produces a more complete fault slip model at all depthsMagnitude and extent of maximum slip regions surrounding the hypocenter persist for both homogeneous and heterogeneous rheology typesMaximum slip is bounded by mainshock hypocenter, aftershocks, decreased Poisson's ratio bodies, and the seismogenic zone [ABSTRACT FROM AUTHOR]

Deep learning has been used for mapping retrogressive thaw slumps and other periglacial landforms but its application is still limited to local study areas. To understand the accuracy, efficiency, and transferability of a deep learning model (i.e., DeepLabv3+) when applied to large areas or multiple regions, we conducted several experiments using training data from three different regions across the Canadian Arctic. To overcome the main challenge of transferability, we used a generative adversarial network (GAN) called CycleGAN to produce new training data in an attempt to improve transferability. The results show that (1) data augmentation can improve the accuracy of the deep learning model but does not guarantee transferability, (2) it is necessary to choose a good combination of hyper-parameters (e.g., backbones and learning rate) to achieve an optimal trade-off between accuracy and efficiency, and (3) a GAN can significantly improve the transferability if the variation between source and target is dominated by color or general texture. Our results suggest that future mapping of retrogressive thaw slumps should prioritize the collection of training data from regions where a GAN cannot improve the transferability. [ABSTRACT FROM AUTHOR]

Record-breaking avalanches generated by the dynamics of several driven nonlinear threshold models are studied. Such systems are characterized by intermittent behavior, where a slow buildup of energy is punctuated by an abrupt release of energy through avalanche events, which usually follow scale-invariant statistics. From the simulations of these systems it is possible to extract sequences of record-breaking avalanches, where each subsequent record-breaking event is larger in magnitude than all previous events. In the present work, several cellular automata are analyzed, among them the sandpile model, the Manna model, the Olami-Feder-Christensen (OFC) model, and the forest-fire model to investigate the record-breaking statistics of model avalanches that exhibit temporal and spatial correlations. Several statistical measures of record-breaking events are derived analytically and confirmed through numerical simulations. The statistics of record-breaking avalanches for the four models are compared to those of record-breaking events extracted from the sequences of independent and identically distributed (i.i.d.) random variables. It is found that the statistics of record-breaking avalanches for the above cellular automata exhibit behavior different from that observed for i.i.d. random variables, which in turn can be used to characterize complex spatiotemporal dynamics. The most pronounced deviations are observed in the case of the OFC model with a strong dependence on the conservation parameter of the model. This indicates that avalanches in the OFC model are not independent and exhibit spatiotemporal correlations. [ABSTRACT FROM AUTHOR]

Abstract: Any color may be represented in terms of three components (RGB or HSL) or four components (CMYK). For the four component color representation the use of quaternions, with one real and three imaginary components, is natural. By setting one component to zero, quaternions have been used in RGB or HSL representation of colors and color images. In this paper a new quantity, trinion, with one real and two imaginary components, is introduced and its use in color image representation is examined. The goal is to see if significant efficiencies in representation, analysis and computation involving three component color images accrue with the use of trinions. Two versions of the trinion Fourier transform (TFT) are introduced and it is shown that using TFT is preferable for combined analysis of three component color images rather than separate monochromatic analysis of each component and use of quaternions. Joint space-wavenumber localized trinion S (TS) transform with a two-dimensional Gaussian window function that scales with wavenumbers is also presented. Invertibility, rotation invariance, and computational aspects of the TS transform are discussed. [Copyright &y& Elsevier]

Abstract: Color images can be treated as two-dimensional quaternion functions. For analysis of quaternion images, a joint space-wavenumber localized quaternion S transform (QS) is presented in this study for a simultaneous determination of the local color image spectra. The QS transform uses a two-dimensional Gaussian localizing window that scales with wavenumbers. Rotation invariance, invertibility and computational aspects of the QS transform are discussed. The power map of the QS transform is presented here as a powerful tool in color image texture and pattern analysis. Examples are presented. [Copyright &y& Elsevier]

Differential interferometry is a very powerful tool for detecting changes in the Earth’s crust where coherence conditions are good, but is difficult to employ in some volcanic areas due to dense vegetation. We apply two differential InSAR methods using the time series associated with the interferograms to perform a phase analysis on a data set for La Palma island (Canary Islands) from the ERS-1 and ERS-2 European Space Agency (ESA) satellites for the time period 1992 to 2000. Both methods involve choosing a master image from the database and creating a series of interferograms with respect to this image. The “Coherent Pixel Time Series” (CPTS) technique chooses pixels with good average coherence, aligns the unwrapped interferograms with a stable area and then performs an inversion to calculate the linear velocity to quantify the deformation. The Coherent Target Modeling (CTM) method calculates the temporal coherence of each pixel to identify stable targets and then determines the best velocity for each pixel by using a linear fit that maximizes the temporal coherence. Using these two methods we have been able to detect deformation on La Palma Island that has been previously undetectable by conventional InSAR methods. There is a roughly circular region on the Southern part of the island that is actively deforming at ~ −4 to −8 mm/yr. This region is located near the Teneguia valcano, the host of the last known eruption on La Palma in 1971. A thorough investigation of the possible sources for this deformation revealed that it was most likely created by a subsurface thermal source. [ABSTRACT FROM AUTHOR]

We present an evaluation of residual vertical gravity–height change gradients obtained from gravimetric and elevation data between 1982 and 2000 at the Campi Flegrei caldera (CFc) in Italy. Spatial and temporal variations in the gradients are indicative of multiple causative sources during unrest, in particular for ground subsidence from 1988 onwards. Supported by results obtained from time-series inversion for the period 1988–2000 using a random search approach of a purely elastic earth model and a genetic algorithm accounting for elastic-gravitational effects, we propose a centre of dilatation undergoing predominantly pressure changes yet negligible mass changes as the dominant cause for caldera deflation. Mass fluctuations in randomly active secondary sources along the periphery of the CFc can be best explained by dynamic changes along the caldera boundary (ring) faults. [ABSTRACT FROM AUTHOR]

La Palma island is one of the highest potential risks in the volcanic archipelago of the Canaries and therefore it is important to carry out an in-depth study to define its state of unrest. This has been accomplished through the use of satellite radar observations and an original state-of-the-art interpretation technique. Here we show the detection of the onset of volcanic unrest on La Palma island, most likely decades before a potential eruption. We study its current evolution seeing the spatial and temporal changing nature of activity at this potentially dangerous volcano at unprecedented spatial resolutions and long time scales, providing insights into the dynamic nature of the associated volcanic hazard. The geodetic techniques employed here allow tracking of the fluid migration induced by magma injection at depth and identifying the existence of dislocation sources below Cumbre Vieja volcano which could be associated with a future flank failure. Therefore they should continue being monitored using these and other techniques. The results have implications for the monitoring of steep-sided volcanoes at oceanic islands. [ABSTRACT FROM AUTHOR]

Space-borne Synthetic Aperture Radar (SAR) provides an opportunity for monitoring ground deformation at active volcanoes with high temporal and spatial resolutions. Modern SAR satellites acquire very large volumes of data that no longer can be effectively and efficiently processed and interpreted manually. The development of novel automatic processing methodologies is warranted in order to fully utilize big data. The Multidimensional Small Baseline Subset (MSBAS) methodology is an example of the semi-automatic processing system for computing temporally dense two-dimensional, horizontal east-west and vertical time series of ground deformation from ascending and descending SAR imagery acquired by various satellites. Here MSBAS is used for mapping ground deformation at the Piton de la Fournaise volcano (La Réunion Island, France) during the February 2012–April 2016 period from RADARSAT-2 data. Five volcanic eruptions occurred during the June 2014–October 2015 period, producing over 60cm of horizontal and over 30cm of vertical ground deformation, well-resolved in the MSBAS-derived time series. Validation of DInSAR results by comparison with GNSS observations and modeling of the two last and largest eruptions was performed. Validation showed good overall agreement between DInSAR and GNSS observations while revealing the benefits and limitations of both techniques. Modeling of fault and dike geometries attempted to explain the dis-proportionally large eastward motion of the eastern flank of the Piton de la Fournaise volcano that occurred during these eruptions. We demonstrated that the simple elastic model consisting of two dikes and a sliding surface can account for the observed ground deformation. [ABSTRACT FROM AUTHOR]

The aim of the present study is to analyze the occurrences of future earthquakes using forecasting techniques from past seismicity in northeast India (latitude 20°N–31°N and longitude 87°E–97°E). The present study applies two types of retrospective binary forecasting. The first one is the pattern informatics (PI) method and the other is the Relative Intensity (RI) method. These techniques quantify the spatio-temporal seismicity rate changes in the historic seismicity of the study region. For this purpose, a uniform and complete earthquake catalogue in moment magnitude (Mw > 3) is prepared. The resulting binary forecasts are evaluated with the relative operating characteristics (ROC) diagram. The ROC diagram quantifies the results in terms of a hit rate (fraction of events that are successfully forecasted) versus a false alarm rate (no event occurs in a hotspot box). Evaluation of forecasting results using ROC diagram is more protective than maximum likelihood tests. The result gives a regional seismogenic map where earthquakes are likely to occur during a specified period in the future. The recent India–Nepal border earthquake of 18 September 2011 occurred in one of the forecasted regions. These techniques have been applied for the first time to the Indian subcontinent. [ABSTRACT FROM AUTHOR]

Montreal has significant seismic risk due to the combination of moderate seismicity, high population density, and vulnerable infrastructure. An important tool in damage and risk assessment is a scenario shakemap, which shows the expected ground shaking intensity distribution patterns. In this study, we use regional ground motion and site response evaluations to generate scenario shakemaps for Montreal. The impact of event location on expected ground motions and intensities was tested by considering the occurrence of a scenario (a given magnitude event) at various locations, where the scenarios are defined based on an analysis of the most likely future event locations. Variability in near surface geology plays an important role in earthquake ground shaking; we use microzonation information from Montreal to assess the expected site amplification effects. The results of this study may be used as input to seismic risk studies for Montreal. [ABSTRACT FROM AUTHOR]

On 17 October 2015, a large landslide entered the marine waters of Taan Fiord, Alaska, and generated a displacement wave with a 193 m runup. The wave scoured the surrounding hillslopes of soil and vegetation and deposited significant volumes of material into the fjord, onto hillslopes on the opposite side of the fjord, and on top of Tyndall Glacier. For this study, we generated six, 2-m posting Digital Surface Models (DSMs) using DigitalGlobe/Maxar satellite imagery acquired near-annually between 2012 and 2019, and the Surface Extraction with TIN-based Search-space Minimization (SETSM) high-performance computing algorithm. We aligned the DSMs to exposed bedrock in the 01 March 2014 DSM acquisition, and then used them to characterize topographic and volumetric changes from before and after the 2015 Taan Fiord rock avalanche. We find that the landslide mobilized roughly 77. 0 ± 0.9 Mm3 of material, of which approximately 56.3 Mm3 were deposited in the fjord waters. Furthermore, we quantified an additional 27.2 ± 3.8 Mm3 of material scoured from fjord-adjacent hillslopes and deposited in the fjord waters, providing new constraints on the subaqueous deposition. This is the first time that DSMs have been used to estimate the volume of scour caused by a tsunami and the subsequent changes in extent and volume with time. Our results for the landslide and runout are consistent with field measurements published previously. This study offers improved estimates of both subaerial and subaqueous deposition for the 2015 Taan Fiord landslide and describes additional regional environmental conditions. We identify precursory motion prior to the 2015 landslide, characterize several smaller-scale landslides in the larger Taan Fiord region, delineate terminus positions and associated ice dynamics of the Tyndall Glacier, and detail seasonal changes in vegetation growth and snow melt/accumulation. This work provides important new insights into the geomorphic features and dynamics of this landslide and subsequent tsunami. The interdisciplinary applications associated with DSMs and the accuracy of the measurements presented here demonstrate that these methods are an effective tool to improve our understanding of the pre- and post-landslide processes, for monitoring areas at risk for landslides and other natural hazards, and for rapid response to catastrophic events. • Differencing Digital Elevation Models to evaluate volumetric/geomorphic changes. • Subaerial erosion, deposition, and tsunami runup from the Taan Fiord landslide. • Detect precursor landslide motion, describe glacier dynamics and monitor vegetation. • Tsunami scour extent and volume at high spatial resolution using differenced DEMs. [ABSTRACT FROM AUTHOR]

Abstract: Rapidly accelerating ground subsidence in the south-western part of British Columbia, the third largest metropolitan area in Canada with over 2.3 million of inhabitants, is estimated using the Multidimensional Small Baseline Subset (MSBAS) advanced Differential Interferometric Synthetic Aperture Radar (DInSAR), an effective processing strategy for multi-mission, multi-temporal SAR data. The Synthetic Aperture Radar (SAR) data used in this study consists of seven independent data sets: one ascending and one descending ERS-1/2 and ENVISAT frames, together spanning July 1995–September 2010, and three RADARSAT-2 frames spanning February 2009–October 2012. During the July 1995–October 2012 period we observe fast ground subsidence with a maximum rate of about 2cm/year in the Greater Vancouver region that includes the Fraser River Delta and the cities of Burnaby, Richmond, Surrey, New Westminster and Vancouver. The rapidly accelerating subsidence is observed beneath the Vancouver International Airport, SkyTrain terminal as well as several agricultural and industrial locales. These time series suggest that the subsidence rate at the studied regions does not decrease with time, as suggested in previous studies, but remains steady or increases. These results also demonstrate the importance of acquiring and appropriately estimating longer time series, as previous studies on the same Greater Vancouver area may have misinterpreted the long term ground deformation rate and direction and underestimated the potential hazard. The long term impact of this subsidence on urban infrastructure can be significant and needs to be investigated further. [Copyright &y& Elsevier]

Many driven threshold systems display a spectrum of avalanche event sizes, often characterized by power-law scaling. An important problem is to compute probabilities of the largest events ("Black Swans"). We develop a data-driven approach to the problem by transforming to the event index frame, and relating this to Shannon information. For earthquakes, we find the 12-month probability for magnitude m > 6 earthquakes in California increases from about 30% after the last event, to 40%-50% prior to the next one. [ABSTRACT FROM AUTHOR]

The Regional Earthquake Likelihood Models (RELM) test of earthquake forecasts in California was the first competitive evaluation of forecasts of future earthquake occurrence. Participants submitted expected probabilities of occurrence of M ≥ 4.95 earthquakes in 0.1° × 0.1° cells for the period 1 January 1, 2006, to December 31, 2010. Probabilities were submitted for 7,682 cells in California and adjacent regions. During this period, 31 M ≥ 4.95 earthquakes occurred in the test region. These earthquakes occurred in 22 test cells. This seismic activity was dominated by earthquakes associated with the M = 7.2, April 4, 2010, El Mayor-Cucapah earthquake in northern Mexico. This earthquake occurred in the test region, and 16 of the other 30 earthquakes in the test region could be associated with it. Nine complete forecasts were submitted by six participants. In this paper, we present the forecasts in a way that allows the reader to evaluate which forecast is the most "successful" in terms of the locations of future earthquakes. We conclude that the RELM test was a success and suggest ways in which the results can be used to improve future forecasts. [ABSTRACT FROM AUTHOR]

SUMMARY We discuss the long-standing question of whether the probability for large earthquake occurrence (magnitudes m > 6.0) is highest during time periods of smaller event activation, or highest during time periods of smaller event quiescence. The physics of the activation model are based on an idea from the theory of nucleation, that a small magnitude earthquake has a finite probability of growing into a large earthquake. The physics of the quiescence model is based on the idea that the occurrence of smaller earthquakes (here considered as magnitudes m > 3.5) may be due to a mechanism such as critical slowing down, in which fluctuations in systems with long-range interactions tend to be suppressed prior to large nucleation events. To illuminate this question, we construct two end-member forecast models illustrating, respectively, activation and quiescence. The activation model assumes only that activation can occur, either via aftershock nucleation or triggering, but expresses no choice as to which mechanism is preferred. Both of these models are in fact a means of filtering the seismicity time-series to compute probabilities. Using 25 yr of data from the California-Nevada catalogue of earthquakes, we show that of the two models, activation and quiescence, the latter appears to be the better model, as judged by backtesting (by a slight but not significant margin). We then examine simulation data from a topologically realistic earthquake model for California seismicity, Virtual California. This model includes not only earthquakes produced from increases in stress on the fault system, but also background and off-fault seismicity produced by a BASS-ETAS driving mechanism. Applying the activation and quiescence forecast models to the simulated data, we come to the opposite conclusion. Here, the activation forecast model is preferred to the quiescence model, presumably due to the fact that the BASS component of the model is essentially a model for activated seismicity. These results lead to the (weak) conclusion that California seismicity may be characterized more by quiescence than by activation, and that BASS-ETAS models may not be robustly applicable to the real data. [ABSTRACT FROM AUTHOR]

In weather forecasting, current and past observational data are routinely assimilated into numerical simulations to produce ensemble forecasts of future events in a process termed “model steering”. Here we describe a similar approach that is motivated by analyses of previous forecasts of the Working Group on California Earthquake Probabilities (WGCEP). Our approach is adapted to the problem of earthquake forecasting using topologically realistic numerical simulations for the strike-slip fault system in California. By systematically comparing simulation data to observed paleoseismic data, a series of spatial probability density functions (PDFs) can be computed that describe the probable locations of future large earthquakes. We develop this approach and show examples of PDFs associated with magnitude M > 6.5 and M > 7.0 earthquakes in California. [ABSTRACT FROM AUTHOR]

Surface displacements and gravity changes due to volcanic sources are influenced by medium properties. We investigate topographic, elastic and self-gravitation interaction in order to outline the major factors that are significant in data modelling. While elastic-gravitational models can provide a suitable approximation to problems of volcanic loading in areas where topographic relief is negligible, for prominent volcanoes the rough topography could affect deformation and gravity changes to a greater extent than self-gravitation. This fact requires the selection, depending on local relief, of a suitable model for use in the interpretation of surface precursors of volcanic activity. We use the three-dimensional Indirect Boundary Element Method to examine the effects of topography on deformation and gravity changes in models of magma chamber inflation/deflation. Topography has a significant effect on predicted surface deformation and gravity changes. Both the magnitude and pattern of the geodetic signals are significantly different compared to half-space solutions. Thus, failure to account for topographic effects in areas of prominent relief can bias the estimate of volcanic source parameters, since the magnitude and pattern of deformation and gravity changes depend on such effects. [ABSTRACT FROM AUTHOR]

Tenerife is one of the most well monitored islands of the Canaries, but the surveillance generally is centred on Las Cañadas Caldera, where the Teide volcano is located. In the last 180 000 yr, the eruptions on Tenerife Island have never occurred in the same volcanic structure, except for the Teide and Pico Viejo central volcanic system, so that a complete monitoring network would have to cover the whole island. As a result, Synthetic Aperture Radar Interferometry (InSAR) is being used on Tenerife, because this space technique can provide a displacement map of the surface of the earth with centimetre precision. This paper presents the results obtained on Tenerife Island using 18 SAR images acquired by the ERS-1 and ERS-2 satellites during the period 1992–2000. Two important results have been obtained: no deformation on Las Cañadas Caldera, coinciding with results obtained using terrestrial techniques, and two subsidence episodes outside monitoring areas in the NW of the island, in the region of the last historic eruptions. These results show that InSAR is a useful technique for monitoring the entire island, thus allowing us to discover deformations in areas that are not routinely or easily monitored. This technique has been used in combination with Global Positioning System (GPS) observation of a global network on the island to define a new geodetic monitoring system. The possible causes of the deformations observed have been studied in an endeavour to discern if they might be of natural origin, in particular linked to a reactivation of prior volcanic activity. Examination of the geophysical observations on the island, human activities underway and the results of the modelling seem to indicate that at least part of the deformations may be caused by changes in the groundwater level and therefore are not linked to a volcanic reactivation. This result is important because it implies that, if geodetic volcano monitoring is to be performed on the island, the system used must be capable of discerning between various possible origins of the deformation by analysing their patterns and ancillary information from other sources. In this regard, InSAR is a basic tool on account of its unpaired wide area coverage and spatial density. [ABSTRACT FROM AUTHOR]

• New methodology constraining 3D volcanic sources using elementary sources aggregation. • It is effective in contexts where displacement is related to different sources. • No a-priori hypothesis about the causative sources is required. • The inversion process simultaneously inverts terrestrial and InSAR data. • It has been applied to the inversion of InSAR data for Mt. Etna during 2009-2013. Developments in Interferometric Synthetic Aperture Radar (InSAR) and GNSS (Global Navigation Satellite System) during the past decades have promoted significant advances in geosciences, providing high-resolution ground deformation data with dense spatio-temporal coverage. This large dataset can be exploited to produce accurate assessments of the primary processes occurring in geologically active areas. We present a new, original methodology to carry out a multi-source inversion of ground deformation data to better understand the subsurface causative processes. A nonlinear approach permits the determination of location, size and three-dimensional configuration, without any a priori assumption as to the number, nature or shape of the potential sources. The proposed method identifies a combination of pressure bodies and different types of dislocation sources (dip-slip, strike-slip and tensile) that represent magmatic sources and other processes such as earthquakes, landslides or groundwater-induced subsidence through the aggregation of elemental cells. This approach has the following features: (1) simultaneous inversion of the deformation components and/or line-of-sight (LOS) data; (2) simultaneous determination of diverse structures such as pressure bodies or dislocation sources, representing local and regional effects; (3) a fully 3D context; and (4) no initial hypothesis about the number, geometry or types of the causative sources is necessary. This methodology is applied to Mt. Etna (Southern Italy). We analyze the ground deformation field derived from a large InSAR dataset acquired during the January 2009 – June 2013 time period. The application of the inversion approach models several interesting buried structures as well as processes related to the volcano magmatic plumbing system, local subsidence within the Valle del Bove and seaward motion of eastern flank of the volcano. [ABSTRACT FROM AUTHOR]

The Cushing Hub in Oklahoma, one of the largest oil storage facilities in the world, is federally designated as critical national infrastructure. In 2014, the formerly aseismic city of Cushing experienced a Mw 4.0 and 4.3 induced earthquake sequence due to wastewater injection. Since then, an M4+ earthquake sequence has occurred annually (October 2014, September 2015, November 2016). Thus far, damage to critical infrastructure has been minimal; however, a larger earthquake could pose significant risk to the Cushing Hub. In addition to inducing earthquakes, wastewater injection also threatens the Cushing Hub through gradual surface uplift. To characterize the impact of wastewater injection on critical infrastructure, we use Differential Interferometric Synthetic Aperture Radar (DInSAR), a satellite radar technique, to observe ground surface displacement in Cushing before and during the induced Mw 5.0 event. Here, we process interferograms of Single Look Complex (SLC) radar data from the European Space Agency (ESA) Sentinel-1A satellite. The preearthquake interferograms are used to create a time series of cumulative surface displacement, while the coseismic interferograms are used to invert for earthquake source characteristics. The time series of surface displacement reveals 4–5.5 cm of uplift across Cushing over 17 months. The coseismic interferogram inversion suggests that the 2016 Mw 5.0 earthquake is shallower than estimated from seismic inversions alone. This shallower source depth should be taken into account in future hazard assessments for regional infrastructure. In addition, monitoring of surface deformation near wastewater injection wells can be used to characterize the subsurface dynamics and implement measures to mitigate damage to critical installations. [ABSTRACT FROM AUTHOR]