Western Indian Ocean basin shows one of the most complex signatures of the ocean floor anomalies by juxtaposition of the rapidly evolving, multiple spreading ridges, subduction systems and microcontinental slivers. This study based on ocean floor magnetic anomalies, gravity gradient map, tomographic profiles and geometrical kinematic models reports a significant westward drift of the Central Indian Ridge (CIR) segments. Documented precisely between the latitudes 17°S and 21°S the drift is coincident with the Deccan volcanism at ~65±2 Ma and we further explain its bearing on the Indian plate kinematics. The progressive stair-step trend of the ridge segments towards NE is marked by anomalous deflection to NW for a brief distance of ~217 km between these latitudes represented by the anomalies C30n-C29n. The observed length of the ridge segments moving NW at 17°S match the calculated NW drift rates of Indian plate (Bhagat et al., 2022). We infer that the NW drift and its restoration towards NE triggered short Plume Induced Subduction Initiation along the Amirante trench. Further a plume induced lithospheric tilt of the Indian plate (Sangode et al 2022) led to restoration of subduction along the Sunda trench at ~65 Ma imparting new slab pull force over the Indian subcontinent besides the NE trend for CIR. This episode resulted into anticlockwise rotation of the Indian plate along with accelerated drift rates due to vector addition of the plume push and the slab pull forces from Eurasian as well as Sunda subduction systems after 65 Ma. The Deccan eruption thus resulted in major geodynamic reorganization that altered the kinematics of Indian plate; and the signatures of which are well preserved over the ocean floor.

Self-organizing diffusion-reaction systems naturally form complex patterns under far from equilibrium conditions. A representative example is the rhythmic concentration pattern of Fe-oxides in Zebra rocks; these patterns include reddish-brown stripes, rounded rods, and elliptical spots. Similar patterns are observed in the banded iron formations which are presumed to have formed in the early earth under global glaciation. We propose that such patterns can be used directly (e.g., by computer-vision-analysis) to infer basic quantities relevant to their formation giving information on generalized chemical gradients. Here we present a phase-field model that quantitatively captures the distinct Zebra rock patterns based on the concept of phase separation that describes the process forming Liesegang stripes. We find that diffusive coefficients (i.e., the bulk self-diffusivities and the diffusive mobility of Cahn-Hilliard dynamics) play an essential role in controlling the appearance of regular stripe patterns as well as the transition from stripes to spots. The numerical results are carefully benchmarked with the well-established empirical spacing law, width law, timing law and the Matalon-Packter law. Using this model, we invert for the important process parameters that originate from the intrinsic material properties, the self-diffusivity ratio and the diffusive mobility of Fe-oxides, with a series of Zebra rock samples. This study allows a quantitative prediction of the generalized chemical gradients in mineralized source rocks without intrusive measurements, providing a better intuition for the mineral exploration space.

Freeboardelevation of a structure above the base flood elevation (BFE)is a critical component in mitigating or avoiding flood losses. However, the unrevealed benefits and savings of freeboard installation have prevented communities from adopting this approach. To improve decision-making for flood-vulnerable communities and enhance flood risk mitigation strategies, this study presents the methodology underlying a new webtool, FloodSafeHome, that estimates comprehensively the economic benefits and savings of freeboard installation for new construction of residential buildings. Specifically, the proposed evaluation framework has been designed to calculate monthly savings for individual buildings by assessing freeboard cost, insurance savings per year, and expected annual flood loss. This new evaluation method is built into a web-based, decision-making tool for use by the public and community leaders in three southeastern Louisiana parishes, to identify expected future benefits of building residences with freeboard and enhance their decision-making processes with interactive risk/benefit analysis features. For example, results indicate the levels of freeboard that optimize the costbenefit ratio for flood-insured homes in the study area. This approach is expected to improve long-term flood resilience and provide cost-efficient flood mitigation strategies particularly in disaster vulnerable regions.

The geometry of the Antarctic-Phoenix Plate system, with the Antarctic Plate forming both the overriding plate and the conjugate to the subducting oceanic plate, allows quantification of slab age and convergence rate back to the Paleocene and direct comparison with the associated magmatic arc. New Ar-Ar data from Cape Melville (South Shetland Islands, SSI) and collated geochronology shows Antarctic arc magmatism ceased at ~19 Ma. Since the Cretaceous, the arc front remained ~100 km from the trench whilst its rear migrated trenchward at 6 km/Myr. South of the SSI, arc magmatism ceased ~8–5 Myr prior to each ridge-trench collision, whilst on the SSI (where no collision occurred) the end of arc magmatism predates the end of subduction by ~16 Myr. Despite the narrowing and successive cessation of the arc, geochemical and dyke orientation data shows the arc remained in a consistently transitional state of compressional continental arc and extensional backarc tectonics. Numerically relating slab age, convergence rate, and slab dip to the Antarctic-Phoenix Plate system, we conclude that the narrowing of the arc and the cessation of magmatism south of the South Shetland Islands was primarily in response to the subduction of progressively younger oceanic crust, and secondarily to the decreasing convergence rate. Increased slab dip beneath the SSI migrated the final magmatism offshore. Comparable changes in the geometry and composition are observed on the Andean arc, suggesting slab age and convergence rate may affect magmatic arc geometry and composition in settings currently attributed to slab dip variation.

One of the most prominent plate tectonic processes is seafloor spreading. But its formation processes are poorly understood. In this study, we thoroughly address how the brittle-ductile weakening process affects the formation and development of tectonic patterns at spreading centers using 3D magmatic-thermomechanical numerical models. Grain size evolution and brittle/plastic strain weakening are fully coupled into the model. A spectrum of tectonic patterns, from asymmetric long-lived detachment faults in rolling-hinge mode, short-lived detachment faults in flip-flop mode, to symmetric conjugate faults in flip-flop mode are documented in our models. Systematic numerical results indicate that fault strength reduction and axial brittle layer thickness are two pivotal factors in controlling the faulting patterns and spreading modes. Strain weakening induced by localized hydrothermal alteration can lead to the variation of the fault strength reduction. Strong strain weakening with large fault strength reduction results in very asymmetric detachment faults developing in rolling-hinge mode, while weak strain weakening leads to small fault strength reduction, forming conjugate faults. Moreover, the thermal structure beneath the ridge is influenced by spreading rates, hydrothermal circulation, and mantle potential temperature, which in turn controls the thickness of the axial brittle layer and results in variation in tectonic patterns. Further, in order to test a damage mechanism with a physical basis, we investigate grain size reduction at the root of detachment faults. We found that its effect in the formation of detachment faults appears to play a subordinate role compared to brittle/plastic strain weakening of faults.

Studying bedrock rivers during their transient states helps understand the response of a fluvial system to changed boundary conditions. Although studies show how river form adjusts to changes in incision or rock uplift rates, field constraints on the timescale of this adjustment are limited. We present a method that uses knickpoint travel time to estimate the adjustment times of channel width and angle of valley-side slopes to accelerated incision. The travel time of knickpoints between their current positions and the points where changes in width or hillslope angle have just finished represents the time required for morphological adjustment after knickpoint passage. We documented channel slopes, channel widths, and hillslope angles along six rivers that cross an active normal fault in Iwaki, Japan, and identified river sections in a transient state. Channel slopes and basin-averaged erosion rates determined from 10Be concentrations are distinct between rivers near and distant from the fault, suggesting that past increases in fault throw rates triggered the knickpoint formation and the observed transient response. Adjustment time depends on the slope exponent in the detachment-limited model and is 2–5 times greater for channel width than hillslope angle, indicating that catchment adjustment times can be much longer than times predicted only by knickpoint travel time. The fact that channel slope, channel width, and hillslope angle have distinct adjustment times underlines the importance of correctly identifying river sections that are fully adjusted to the new boundary conditions when inferring erosion or relative uplift rates for bedrock rivers.

Tethyan evolution is characterized by cyclical continent-transfer from Gondwana to the continents in the Northern Hemisphere, similar to a “one-way” train. Subduction has been viewed as the primary driver of transference. Therefore, it is crucial to understand the tectonic evolution of all past subduction zones that occurred along Eurasia’s southern margin. We studied the earliest known eclogite located at the Neo-Tethyan suture in the Iranian segment. A prograde-E-MORB-like eclogite reached a peak metamorphic condition of 2.2 GPa and 560°C, at 190 ± 11 Ma (1 rutile U-Pb ages), which constrains the youngest age for subduction initiation of the Neo-Tethyan slab. Combined with regional magmatic and structural data, the oldest age for Neo-Tethys subduction initiation is 210–192 Ma, which is younger than the Paleo-Tethyan closure time of 228–209 Ma. These data, used with previous numerical modeling, supports collision-induced subduction initiation. The collision-induced force, together with the Paleo-Tethyan subduction driven-mantle flow, is likely to have exploited weak inherited structures from earlier Neo-Tethyan rifting, resulting in a northward directed subduction zone along the southern margin of Central Iran Block.

The recently selected NASA VERITAS and DAVINCI missions, the ESA EnVision, the Roscosmos Venera-D will open a new era in the exploration of Venus. One of the key targets of the future orbiting and in-situ investigations of Venus is the identification of volcanically active areas on the planet. The study of the areas characterized by recent or ongoing volcano-tectonic activity can inform us on how volcanism and tectonism are currently evolving on Venus. Following this key target, the manuscript by Brossier et al. (2022) (https://doi.org/10.1029/2022GL099765) extends the successful approach and methodology used by previous works to Ganis Chasma in Atla Regio. We comment here on the main results of the manuscript published by Brossier et al. (2022) (https://doi.org/10.1029/2022GL099765) and discuss the important implications of their work for the future orbiting and in-situ investigation of Venus. Their results add further lines of evidence indicating possibly recent volcanism on Venus.

Arctic-Boreal lakes emit methane (CH₄), a powerful greenhouse gas. Recent studies suggest ebullition may be a dominant methane emission pathway in lakes but its drivers are poorly understood. Various predictors of lake methane ebullition have been proposed, but are challenging to evaluate owing to different geographical characteristics, field locations, and sample densities. Here we compare large geospatial datasets of lake area, lake perimeter, permafrost, landcover, temperature, soil organic carbon content, depth, and greenness with remotely sensed methane ebullition estimates for 5,143 Alaskan lakes. We find that lake wetland fraction (LWF), a measure of lake wetland and littoral zone area, is a leading predictor of methane ebullition (adj. R² = 0.211), followed by lake surface area (adj. R² = 0.201). LWF is inversely correlated with lake area, thus higher wetland fraction in smaller lakes may explain a commonly cited inverse relationship between lake area and methane ebullition. Lake perimeter (adj. R² = 0.176) and temperature (adj. R² = 0.157) are moderate predictors of lake ebullition, and soil organic carbon content, permafrost, lake depth, and greenness are weak predictors. The low adjusted R² values are typical and informative for methane attribution studies. A multiple regression model combining LWF, area, and temperature performs best (adj. R² = 0.325). Our results suggest landscape-scale geospatial analyses can complement smaller field studies, for attributing Arctic-Boreal lake methane emissions to readily available environmental variables.

The Canadian Beaufort Sea continental margin of northwestern Canada is a Cenozoic convergent margin, potentially representing a rare case of incipient subduction. Here, we produce P- and S-wave seismic velocity models of the crust and the uppermost mantle using recordings from regional earthquakes. Our models reveal a northwest-dipping very low-velocity anomaly within the crust (δV up to -15%) beneath the Romanzof Uplift. We interpret this low-velocity feature to correspond to a weaker and thicker crust due to shortening and stacking of igneous and sedimentary rocks. The co-location of the thickened crust and lack of present-day seismicity indicates that north-south compression is accommodated by slow, aseismic deformation in the narrow margin beneath the Romanzof Uplift or more broadly offshore. Neither interpretation requires a subduction initiation process.

Key to most subsurface processes is to determine how structural and topological features at small length scales, i.e., the microstructure, control the effective and macroscopic properties of earth materials. Recent progress in imaging technology has enabled us to visualise and characterise microstructures at different length scales and dimensions. An approach to characterisation is the sampling of n-point correlation functions - known as statistical microstructural descriptors (SMDs) - from images. SMDs can then be used to generate statistically equivalent structures having larger sizes and additional dimensions – this process is known as $reconstruction$. We show that a deep-convolutional generative adversarial network trained with Wasserstein-loss and gradient penalty (WGAN-GP) results in a stable training and high-quality reconstructions of two-dimensional electron microscopy images of complex rock samples. To evaluate reconstruction performance, n-point polytope functions are calculated in both reconstructed and original microstructures and mean square error between them is used as a quality metric. These n-point polytope functions provide statistical information about symmetric, user-oriented higher-order geometrical patterns in microstructures. Our results show that GANs can naturally capture these higher-order statistics at short and long ranges. Furthermore, we compare our model with a benchmark stochastic reconstruction method based solely on two-point correlation. Our findings indicate that although yielding the same two-point statistics, two microstructures can be morphologically and structurally different, emphasising the need for coupling higher-order correlation functions with reconstruction methods. This is a critical step for future schemes that aim to reconstruct complex heterogeneous systems and couple microstructures to macroscopic phenomena.

Nowcasting is a term originating from economics, finance and meteorology. It refers to the process of determining the uncertain state of the economy, markets or the weather at the current time by indirect means. In this paper we describe a simple 2-parameter data analysis that reveals hidden order in otherwise seemingly chaotic earthquake seismicity. One of these parameters relates to a mechanism of seismic quiescence arising from the physics of strain-hardening of the crust prior to major events. We observe an earthquake cycle associated with major earthquakes in California, similar to what has long been postulated. An estimate of the earthquake hazard revealed by this state variable timeseries can be can be optimized by the use of machine learning in the form of the Receiver Operating Characteristic skill score. The ROC skill is used here as a loss function in a supervised learning mode. Our analysis is conducted in the region of 5o x 5o in latitude-longitude centered on Los Angeles, a region which we used in previous papers to build similar timeseries using more involved methods (Rundle and Donnellan, 2020; Rundle et al., 2021). Here we show that not only does the state variable timeseries have forecast skill, the associated spatial probability densities have skill as well. In addition, use of the standard ROC and Precision (PPV) metrics allow probabilities of current earthquake hazard to be defined in a simple, straightforward and rigorous way.

The lithosphere of the Moon has been deformed by tectonic processes for at least 4 billion years, resulting in a variety of tectonic surface features. Extensional large lunar graben formed during an early phase of net thermal expansion before 3.6 Ga. With the emplacement of mare basalts at ~3.9 – 4.0 Ga, faulting and folding of the mare basalts initiated, and wrinkle ridges formed. Lunar wrinkle ridges exclusively occur within the lunar maria and are thought to be the result of superisostatic loading by dense mare basalts. Since 3.6 Ga, the Moon is in a thermal state of net contraction, which led to the global formation of small lobate thrust faults called lobate scarps. Hence, lunar tectonism recorded changes in the global and regional stress fields and is, therefore, an important archive for the thermal evolution of the Moon. Here, we mapped tectonic features in the non-mascon basin Mare Tranquillitatis and classified these features according to their respective erosional states. This classification aims to give new insights into the timing of lunar tectonism and the associated stress fields. We found a wide time range of tectonic activity, ranging from ancient to recent (3.8 Ga to < 50 Ma). Early wrinkle ridge formation seems to be closely related to subsidence and flexure. For the recent and ongoing growth of wrinkle ridges and lobate scarps, global contraction with a combination of recession stresses, diurnal tidal stresses, as well as with a combination of SPA ejecta loading and true polar wander are likely.

The Gravity Recovery and Climate Experiment (GRACE) data help to determine the total water storage anomalies (TWS) across the global scale. The various other important components such as Groundwater storage (GWS) and evapotranspiration for the region of South –East Asia have been determined. With the study of the gravity variation across the globe the long-term changes in the hydrological cycle can be determined which can be related to climate science or the influence of anthropogenic activities. The variation between the Groundwater storage (GWS) and the Total water storage (TWS) of the study area has been calculated for the pre and post-monsoon season of the study area. The variation between groundwater storage and total water storage can be visualized through geospatial analysis. Therefore, the regions with a substantial decrease in water storage can be related to various climate and anthropogenic factors hence implying a sustainable use of groundwater as a resource. Keywords: Machine Learning, Remote Sensing, Groundwater Recharge, Climate science.

Through machine learning and remote sensing, a high-end model with a finer resolution for groundwater recharge has been developed for the region of South-East Asia. The groundwater recharge coefficient can be found by the application of Random Forest regression followed by the implication of the water budget method to calculate the Groundwater Recharge values. Climatic factors such as precipitation and actual evapotranspiration to map Groundwater Recharge has been framed with a sophisticated machine learning method to be considered as a scale predicting model. A comprehensive visualization of the dataset has been done; the accuracy of the model is noted through random forest regression. Thus, the model can be used for various regions of the dataset specifically for the area where there is a lack of reach for data. It can be successfully used to form a sophisticated end-to-end ML model. Keywords: Machine Learning, Remote Sensing, Groundwater Recharge, Climate science.

Machine Learning and Remote sensing method to determine the relationship between Climate and Groundwater Recharge. Adya Aiswarya Dash1, Abhijit Mukherjee1,2,3. 1Department of Geology and Geophysics, Indian Institute of Technology Kharagpur, West Bengal 721302, India 2School of Environmental Science and Engineering, Indian Institute of Technology Kharagpur, West Bengal 721302, India 3Applied Policy Advisory for Hydrogeoscience (APAH) Group, Indian Institute of Technology Kharagpur, West Bengal 721302, India Abstract Through machine learning and remote sensing, a high-end model with a finer resolution for groundwater recharge has been developed for the region of South-East Asia. The groundwater recharge coefficient can be found by the application of Random Forest regression followed by the implication of the water budget method to calculate the Groundwater Recharge values. Climatic factors such as precipitation and actual evapotranspiration to map Groundwater Recharge has been framed with a sophisticated machine learning method to be considered as a scale predicting model. A comprehensive visualization of the dataset has been done; the accuracy of the model is noted through random forest regression. Thus, the model can be used for various regions of the dataset specifically for the area where there is a lack of reach for data. It can be successfully used to form a sophisticated end-to-end ML model. Keywords: Machine Learning, Remote Sensing, Groundwater Recharge, Climate science.

In a new study, Wu et al. (this issue) present a comprehensive study of the North Margin Orogen of the North China Craton, showing that older accreted rocks in this belt preserve a record of active margin magmatism from 2.2-2.0 Ga, followed by collisional tectonics, marked by mélange and mylonitic shear zones, then granulite facies metamorphism at 1.9-1.8 Ga, marking the final collision of the North China Craton with the Columbia Supercontinent. The multidisciplinary studies present in this work support earlier suggestions that the North China amalgamated during accretionary orogenesis in the Neoarchean to earlier Paleoproterozoic, and that the late widespread 1.85 Ga high-grade metamorphism is craton-wide in scale, and not confined to a narrow orogen in the center of the craton. This new understanding creates new possibilities for refining reconstructions of one of Earth’s earliest, best documented supercontinents, showing a globally-linked plate network at 1.85 Ga, and suggests drastic new correlations and models for mineral resource exploration.

Surface melt forces summertime ice-flow accelerations on glaciers and ice sheets. Here, we show that large meltwater-forced accelerations also occur in winter in Greenland. We document supraglacial lakes (SGLs) draining in cascades at unusually high elevation, causing an expansive flow acceleration over a ~5200 km2 region during winter. The 3-component interferometric surface velocity field and decomposition modeling reveals the underlying flood propagation with unprecedented detail as it traveled over 160 km from the drainage site to the margin, providing novel constraints on subglacial water pathways, drainage morphology, and links with basal sliding. The triggering SGLs continuously grew over 40 years and suddenly released decades of stored meltwater into regions of the bed never previously forced, demonstrating surface melt can impact dynamics well beyond its production. We show these events are common and thus their cumulative impact on dynamics should be further evaluated.

A document by Sean James Trim. Click on the document to view its contents.

High-quality digital rock images are essential for subsequent high-precision numerical simulations. But limited by the imaging capability of computed tomography (CT), high resolution digital rock images with wide imaging field of view (FOV) cannot be acquired simultaneously. To cope with this constraint, we propose a novel Multi Attention Super-Resolution Neural Network (MASR) that enhances the resolution of images with wide FOV. Considering that textures and edges are more crucial in digital rocks, MASR introduces the component attention mechanism of Component Divide-and-Conquer Super-Resolution (CDCSR) model. By redesigning the hourglass network with spatial and channel attention mechanisms, proposing a spatial attention-based mask module, and optimizing the component attention mask calculation process, MASR delivers higher information utilization with fewer parameters and faster training than CDCSR. And we optimize the depth of MASR to trade off speed and super-resolution quality. Furthermore, we retrained several state-of-the-art models. Through quantitative evaluations and qualitative visualizations, it is verified that MASR can recover sharper edges while removing noise, and obtain digital rock images with superior quality and reliability. The pixelwise relative errors of MASR reconstructions are reduced by 15% to 26% over bicubic interpolation method. Our codes are publicly available at https://github.com/MHDXing/MASR-for-Digital-Rock-Images.

During hurricane season, the U.S. Geological Survey (USGS) forecasts the probability of coastal change prior to named storm landfall. Forecasts both quantify potential storm effects on the sandy coastlines and test our understanding of the drivers of coastal change. The forecasts can also be used to aid emergency response and management decisions in real-time. This study analyzed the skill of three USGS forecasts of coastal change, defined as the probability of collision, overwash, and inundation (PCOI) along the approximately 250 km of Louisiana coast from Hurricanes Laura, Delta, and Zeta in 2020. To test forecast skill, forecasts were compared with coastal changes identified in post-storm emergency response aerial imagery. Forecasts accurately identified areas where overwash and inundation were likely (true positive forecast ratios >0.75). Forecasts also produced an overly conservative estimation of overwash and inundation (false positive forecast ratios 0.56). High false positive forecast ratios for overwash and inundation may be the result of an overestimate in forecast extreme water levels.

Pulsing seepages of native hydrogen (H2) have been observed at the surface on several emitting structures. It is still unclear whether this H2 pulsed flux is controlled by deep migration processes, atmosphere/near-surface interactions or by bacterial fermentation. Here, we investigate mechanisms that may trigger pulsating fluid migration at depth and the resulting periodicity. We set up a numerical model to simulate the migration of a deep constant fluid flow. To verify the model’s formulation to solve complex fluid flows, we first simulate the morphology and amplitude of 2D thermal anomalies induced by buoyancy-driven water flow within a fault zone. Then, we simulate the H2 gas flow along a 1-km draining fault, crosscut by a lower permeable rock layer to investigate the conditions for which a pulsing system is generated from a deep control. For a constant incoming flow of H2 at depth, persistent bursts at the surface only appear in the model if: (I) a permeability with an effective-stress dependency is used, (II) a strong contrast of permeability exists between the different zones, (III) a sufficiently high value of the initial effective stress state at the base of the low permeable layer exists, and (IV) the incoming and continuous fluid flow of H2 at depth remains low enough so that the overpressure does not “open” instantly the low permeability layer. The typical periodicity expected for this type of valve-fault control of H2 pulses at the surface is at a time scale of the order of 100 to 300 days.

The Christiana-Santorini-Kolumbo volcanic field in the southern Aegean Sea is one of the most hazardous volcanic regions in the world. Forming the northeastern part of this volcanic field, the Kolumbo Volcanic Chain (KVC) comprises more than 20 submarine volcanic cones. However, due to their inaccessibility, little is known about the spatio-temporal evolution and tectonic control of these submarine volcanoes and their link to the volcanic plumbing system of Santorini. In this study, we use multichannel reflection seismic imaging to study the internal architecture of the KVC and its link to Santorini. We show that the KVC evolved during two episodes, which initiated at ~1 Ma with the formation of mainly effusive volcanic edifices along a NE-SW trending zone. The cones of the second episode were formed mainly by submarine explosive eruptions between 0.7 and 0.3 Ma and partly developed on top of volcanic edifices from the first episode. We identify two prominent normal faults that underlie and continue the two main trends of the KVC, indicating a direct link between tectonics and volcanism. In addition, we reveal several buried volcanic centers and a distinct volcanic ridge connecting the KVC with Santorini, suggesting a connection between the two volcanic centers in the past. This connection was interrupted by a major tectonic event and, as a result, the two volcanic systems now have separate, largely independent plumbing systems despite their proximity.

The petrophysical properties of rocks are a strong and an effective indicator of the extent of the susceptibility of the rocks themselves to building and construction operations above and above them. As these tests are conclusive evidence that such rocks will not have a landslide or semi-collapse, and from here we focus in this scientific proposal paper on them practically in a manner of step-by-step, to make it easier for the specialist to understand the well. These properties are an assistant to the geologist and civil engineer in the field of work, as they work to provide actual numbers of the rocks, or in other words, the process of converting rocks into mere numbers that speak for themselves effectively and feasibly, such properties are sufficient.