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SUMMARYOne of the main constraints on the use of satellite radar data for monitoring natural hazards is the existence of atmospheric signals. In particular, volcanic deformation can be difficult to identify because atmospheric phase delays can mask or even mimic ground deformation signals. Eliminating atmospheric signals is particularly crucial for high-relief volcanoes such as Ağrı, Tendürek, Acigöl, Göllüdağ and Hasandağ in the Eastern and Central Anatolia. To overcome the atmospheric effects, we use high-resolution ECMWF weather models coupled with an empirical phase-elevation approach for correcting Sentinel-1 interferograms. We apply these methods to two areas of Turkey, the first of which covers three volcanoes in Central Anatolia (Acigöl, Göllüdağ, Hasandağ) between January 2016 and December 2018 and the second covers two volcanoes in Eastern Anatolia (Ağrı, Tendürek) between September 2016 and December 2018. The reduction in standard deviation (quality factor) is calculated for both ascending and descending tracks and the atmospheric corrections are found to perform better on descending interferograms in both cases. Then, we use a least-squares approach to produce a time-series. For Central Anatolia, we used 416 ascending and 415 descending interferograms to create 144 and 145 cumulative displacement maps, respectively, and for Eastern Anatolia, we used 390 ascending and 380 descending interferograms to produce 137 and 130 cumulative displacement maps, respectively. We find that the temporal standard deviation before atmospheric corrections ranges between 0.9 and 3.7 cm for the five volcanoes in the region and is consistently higher on ascending track data, which is acquired at the end of the day when solar heating is greatest. Atmospheric correction reduces the standard deviation to 0.5–2.5 cm. Residual signals might be due to the ice-cap at Ağrı and agriculture near Acigöl. We conclude that these volcanoes did not experience significant magmatic deformation during this time period, despite the apparent signals visible in individual uncorrected interferograms. We demonstrate that atmospheric corrections are vital when using InSAR for monitoring the deformation of high-relief volcanoes in arid continental climates such as Turkey.

Satellite-based earth observation sensors are increasingly able to monitor geophysical signals related to natural hazards, and many groups are working on rapid data acquisition, processing, and dissemination to data users with a wide range of expertise and goals. A particular challenge in the meaningful dissemination of Interferometric Synthetic Aperture Radar (InSAR) data to non-expert users is its unique differential data structure and sometimes low signal to noise ratio. In this study, we evaluate the online dissemination of ground deformation measurements from InSAR through Twitter, alongside the provision of open access InSAR data from the Centre for Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET) Looking Into Continents from Space with Synthetic Aperture Radar (LiCSAR) processing system. Our aim is to evaluate (1) who interacts with disseminated InSAR data, (2) how the data are used and (3) to discuss strategies for meaningful communication and dissemination of open InSAR data. We found that InSAR Twitter activity was primarily associated with natural hazard response, specifically following earthquakes and volcanic activity, where InSAR measurements of ground deformation were disseminated, often using wrapped and unwrapped interferograms. For earthquake events, Sentinel-1 data were acquired, processed, and tweeted within 4.7±2.8 days (shortest was one day). Open access Sentinel-1 data dominated the InSAR tweets and were applied to volcanic and earthquake events in the most engaged with (retweeted) content. Open access InSAR data provided by LiCSAR was widely accessed, including automatically processed and tweeted interferograms and interactive event pages revealing ground deformation following earthquake events. The further work required to integrate dissemination of InSAR data into longer-term disaster risk reduction strategies is highly specific, both to hazard-type, international community of practice, and local political setting and civil protection mandates. Notably, communication of uncertainties and processing methodologies are still lacking. We conclude by outlining the future direction of COMET LiCSAR products to maximise their useability.

Active fault data are commonly used in seismic hazard assessments, but there are challenges in deriving the slip rate, geometry, and frequency of earthquakes along active faults. Herein, we present the open-access geospatial Malawi Seismogenic Source Model (MSSM; https://doi.org/10.5281/zenodo.5599616), which describes the seismogenic properties of faults that formed during ongoing east African rifting in Malawi. We first use empirically derived constraints to geometrically classify active faults into section, fault, and multifault seismogenic sources. For sources in the North Basin of Lake Malawi, slip rates can be derived from the vertical offset of a seismic reflector that dated lake cores indicate is 75 ka. Elsewhere, slip rates are constrained from advancing a systems-based approach that partitions geodetically derived rift extension rates in Malawi between seismogenic sources using a priori constraints on a regional strain distribution and a hanging wall flexural extension in magma-poor continental rifts. Slip rates are then combined with source geometry and empirical scaling relationships to estimate earthquake magnitudes and recurrence intervals, and their uncertainty is described from the variability in logic tree outcomes used in these calculations. Sources in the MSSM are 5–269 km long, which implies that large-magnitude (Mw 7–8) earthquakes may occur in Malawi. However, low slip rates (0.05–2 mm yr−1) mean that the frequency of such events will be low (recurrence intervals of ∼103–104 years). We also find that, for 9 out of 11 faults in Lake Malawi's North Basin, differences in the slip rates, when estimated independently from the geodetic data and the offset seismic reflector, are not statistically significant. The MSSM represents an important resource for investigating Malawi's increasing seismic risk and provides a framework for incorporating active fault data into seismic hazard assessment elsewhere in the East African Rift and other tectonically active regions.

Radar (SAR) satellites systematically acquire imagery that can be used for volcano monitoring, characterising magmatic systems and potentially forecasting eruptions on a global scale. However, exploiting the large dataset is limited by the need for manual inspection, meaning timely dissemination of information is challenging. Here we automatically process ~ 600,000 images of 1000 volcanoes acquired by the Sentinel-1 satellite in a 5-year period (2015-2020) and use the dataset to demonstrate the applicability and limitations of machine learning for detecting deformation signals. Of the 16 volcanoes flagged most often, 5 experienced eruptions, 6 showed slow deformation, 2 had non-volcanic deformation and 3 had atmospheric artefacts. The detection threshold for the whole dataset is 5.9 cm, equivalent to a rate of 1.2 cm/year over the 5-year study period. We then use the large testing dataset to explore the effects of atmospheric conditions, land cover and signal characteristics on detectability and find that the performance of the machine learning algorithm is primarily limited by the quality of the available data, with poor coherence and slow signals being particularly challenging. The expanding dataset of systematically acquired, processed and flagged images will enable the quantitative analysis of volcanic monitoring signals on an unprecedented scale, but tailored processing will be needed for routine monitoring applications.The online version contains supplementary material available at 10.1007/s00445-022-01608-x.

The TanDEM-X satellite mission has revolutionized DEM generation from spaceborne synthetic aperture radar. In addition to the primary objective of generating a consistent digital elevation model with global coverage and unprecedented accuracy, the mission has acquired time series of topographic data over several volcanoes, providing an excellent opportunity to test the use of this innovative dataset for volcano monitoring and research. In this article, we review the utilization of the single-pass TanDEM-X data for studying various kinds of volcanic activity, such as basaltic lava flows, the formation and destruction of lava domes and related pyroclastic density currents, and subsurface magma withdrawal and intrusion. We then consider the uses of these data for hazard assessment and forecasting. Our goal is to highlight the importance of timely and repeated topographic information in volcanology, and to suggest the development of future spaceborne bistatic synthetic aperture radar satellite missions, such as ESA's Earth Explorer 10 candidate mission, “Harmony.”

Tectonic and paleo-environmental reconstructions of rift evolution typically rely on the interpretation of sedimentary sequences, but this is rarely possible in early-stage rifts where sediment volumes are low. To overcome this challenge, we use geomorphology to investigate landscape evolution and the role of different forcing mechanisms during basin development. Here, we focus on the humid Middle Shire River basin, located within the zone of progressive interaction and linkage between the southern Malawi Rift and Shire Rift Zone, East Africa. We used a digital elevation model to map knickpoints and knickpoint morphologies in the Middle Shire River basin and examined the relationships with pre-rift and syn-rift structures within the rift interaction zone. The main axial stream, Shire River, descends steeply, 372 m over a 50 km distance, across exposed metamorphic basement along the rift floor, exhibiting a strongly disequilibrated longitudinal elevation profile with both ‘mobile’ and ‘fixed’ knickpoints. In particular, we identify two clusters of mobile knickpoints, which we interpret as associated with baselevel fall events at the downstream end of the exposed basement that triggered knickpoint migration through the fluvial network since at least the Mid. Pleistocene. We infer that after the integration of the axial stream across the Middle Shire Basin, the knickpoints migrate upstream in response to fault-related subsidence in the Shire Rift Zone. Conversely, the fixed knickpoints are interpreted to reflect local differential bedrock erodibility at lithologic contacts or basement-hosted fault scarps along the basin floor. The results suggest that Middle Shire basin opening, associated with rift linkage, is likely a recent event (at least Mid. Pleistocene) relative to the Late Oligocene activation of Cenozoic rifting in the East African Rift's Western Branch. These findings support the hypothesis that the Western Branch developed from the gradual propagation, linkage and coalescence of initially nucleated distinct rift basins.

Seismic hazard assessment in slow straining regions is challenging because earthquake catalogues only record events from approximately the last 100 years, whereas earthquake recurrence times on individual faults can exceed 1000 years. Systematic mapping of active faults allows fault sources to be used within probabilistic seismic hazard assessment, which overcomes the problems of short-term earthquake records. We use Shuttle Radar Topography Mission (SRTM) data to analyse surface deformation in the Luangwa Rift in Zambia and develop the Luangwa Rift Active Fault Database (LRAFD). The LRAFD is an open-source geospatial database containing active fault traces and their attributes and is freely available at https://doi.org/10.5281/zenodo.6513691. We identified 18 faults that display evidence for Quaternary activity, and empirical relationships suggest that these faults could cause earthquakes up to Mw 8.1, which would exceed the magnitude of historically recorded events in southern Africa. On the four most prominent faults, the median height of Quaternary fault scarps varies between 12.9 ± 0.4 and 19.2 ± 0.9 m, which suggests they were formed by multiple earthquakes. Deformation is focused on the edges of the Luangwa Rift: the most prominent Quaternary fault scarps occur along the 207 km long Chipola and 142 km long Molaza faults, which are the rift border faults and the longest faults in the region. We associate the scarp on the Molaza Fault with possible surface ruptures from two 20th century earthquakes. Thus, the LRAFD reveals new insights into active faulting in southern Africa and presents a framework for evaluating future seismic hazard.

During earthquakes on low (

In low strain rate regions, extrapolation of incomplete instrumental earthquake records is a limitation for probabilistic seismic hazard analysis (PSHA). This limitation can be addressed by incorporating geologic and geodetic data into fault-based seismogenic sources, although it is not always clear how on-fault magnitude-frequency distributions should be described and, if the seismogenic layer is especially thick, how these sources should be extrapolated down-dip. We explore these issues in the context of a new PSHA for Malawi, where regional extensional rates are 0.5-2 mm/yr, the seismogenic layer is 30-40 km thick, the instrumental catalog is ~60 years long, and fault-based sources were recently collated in the Malawi Seismogenic Source Database. Furthermore, Malawi is one of several countries along the East African Rift where exposure to seismic hazard is growing, but PSHA typically considers instrumental records alone. We use stochastic event catalogs to explore different fault-source down-dip extents and magnitude-frequency distributions. These indicate that hazard levels are highest for a Gutenberg-Richter on-fault magnitude-frequency distribution, even at low probabilities of exceedance (2% in 50 years), whilst seismic hazard levels are also sensitive to how relatively short (

Aseismic afterslip is postseismic fault sliding that may significantly redistribute crustal stresses and drive aftershock sequences. Afterslip is typically modeled through geodetic observations of surface deformation on a case-by-case basis, thus questions of how and why the afterslip moment varies between earthquakes remain largely unaddressed. We compile 148 afterslip studies following 53 Mw6.0–9.1 earthquakes, and formally analyze a subset of 88 well-constrained kinematic models. Afterslip and coseismic moments scale near-linearly, with a median Spearman's rank correlation coefficient (CC) of 0.91 after bootstrapping (95% range: 0.89–0.93). We infer that afterslip area and average slip scale with coseismic moment as urn:x-wiley:21699313:media:jgrb55593:jgrb55593-math-0001 and urn:x-wiley:21699313:media:jgrb55593:jgrb55593-math-0002, respectively. The ratio of afterslip to coseismic moment (Mrel) varies from 300% (interquartile range: 9%–32%). Mrel weakly correlates with Mo (CC: −0.21, attributed to a publication bias), rupture aspect ratio (CC: −0.31), and fault slip rate (CC: 0.26, treated as a proxy for fault maturity), indicating that these factors affect afterslip. Mrel does not correlate with mainshock dip, rake, or depth. Given the power-law decay of afterslip, we expected studies that started earlier and spanned longer timescales to capture more afterslip, but Mrel does not correlate with observation start time or duration. Because Mrel estimates for a single earthquake can vary by an order of magnitude, we propose that modeling uncertainty currently presents a challenge for systematic afterslip analysis. Standardizing modeling practices may improve model comparability, and eventually allow for predictive afterslip models that account for mainshock and fault zone factors to be incorporated into aftershock hazard models.

Active fault data are commonly used in seismic hazard assessments, but there are challenges in deriving the slip rate, geometry, and frequency of earthquakes along active faults. Herein, we present the open-access geospatial Malawi Seismogenic Source Database (MSSD), which describes the seismogenic properties of faults that have formed during East African rifting in Malawi. We first use empirical observations to geometrically classify active faults into section, fault, and multi-fault seismogenic sources. For sources in the North Basin of Lake Malawi, slip rates can be derived from the vertical offset of a seismic reflector that is estimated to be 75 ka based on dated core. Elsewhere, slip rates are constrained from advancing a ‘systems-based’ approach that partitions geodetically-derived rift extension rates in Malawi between seismogenic sources using a priori constraints on regional strain distribution in magma-poor continental rifts. Slip rates are then combined with source geometry and empirical scaling relationships to estimate earthquake magnitudes and recurrence intervals, and their uncertainty is described from the variability of outcomes from a logic tree used in these calculations. We find that for sources in the Lake Malawi’s North Basin, where slip rates can be derived from both the geodetic data and the offset seismic reflector, the slip rate estimates are within error of each other, although those from the offset reflector are higher. Sources in the MSSD are 5–200 km long, which implies that large magnitude (MW 7–8) earthquakes may occur in Malawi. Low slip rates (0.05–2 mm/yr), however, mean that the frequency of such events will be low (recurrence intervals ~103–104 years). The MSSD represents an important resource for investigating Malawi’s increasing seismic risks and provides a framework for incorporating active fault data into seismic hazard assessment in other tectonically active regions.

Over the past two decades, multidisciplinary studies have unearthed a rich history of volcanic activity and unrest in the densely-populated East African Rift System, providing new insights into the influence of rift dynamics on magmatism, the characteristics of the volcanic plumbing systems and the foundation for hazard assessments. The raised awareness of volcanic hazards is driving a shift from crisis response to reducing disaster risks, but a lack of institutional and human capacity in sub-Saharan Africa means baseline data are sparse and mitigating geohazards remains challenging., New observations of volcanic and magmatic activity in Africa are changing our views of continental rifting and raising awareness of the associated hazards. However, despite a shift from crisis response to reducing disaster risks, limited capacity means mitigating geohazards remains challenging.

Southern Africa is typically considered to belong to a single tectonic plate, Nubia, despite active faulting along the southwestern branch of the East African Rift System. We analyze regional Global Navigation Satellite System (GNSS) measurements, and find that the “San” microplate, situated south of the southwestern branch of the East African Rift, is statistically distinct from Nubia, with 0.4–0.7 mm/yr of extension across the boundary. Adding nine new campaign GNSS sites, we show that the extension rate across the southern Malawi Rift is 2.2 ± 0.3 mm/yr, with 75% of the relative velocity occurring over 890 km, despite the surface expression of faulting being

Satellite radar backscatter has the potential to provide useful information about the progression of volcanic eruptions when optical, ground-based, or radar phase-based measurements are limited. However, backscatter changes are complex and challenging to interpret: explosive deposits produce different signals depending on pre-existing ground cover, radar parameters and eruption characteristics. We use high temporal- and spatial-resolution backscatter imagery to examine the emplacement and alteration of pyroclastic density currents (PDCs), lahar and ash deposits from the June 2018 eruption of Volcan de Fuego, Guatemala, using observatory reports and rainfall gauge data to ground truth our observations. We use a temporally dense time series of backscatter data to reduce noise and extract deposit areas. We observe backscatter changes in six drainages, the largest deposit was 11.9-km-long that altered an area of 6.3 urn:x-wiley:21699313:media:jgrb55183:jgrb55183-math-0001 and had a thickness of 10.5 urn:x-wiley:21699313:media:jgrb55183:jgrb55183-math-00022 m in the lower sections as estimated from radar shadows. The 3 June eruption also produced backscatter signal over an area of 40 urn:x-wiley:21699313:media:jgrb55183:jgrb55183-math-0003, consistent with reported ashfall. We use transient patterns in backscatter time series to identify nine periods of high lahar activity in a single drainage system between June and October 2018. We find that the characterisation of subtle backscatter signals associated with explosive eruptions are best observed with (1) radiometric terrain calibration, (2) speckle correction, and (3) consideration of pre-existing scattering properties. Our observations demonstrate that SAR backscatter can capture the emplacement and subsequent alteration of a range of explosive deposits, allowing the progression of an explosive eruption to be monitored.

At the global scale, large tectonic earthquakes and volcanic eruptions are believed to be random and independent events. Here, we compare global time-series of large earthquakes (Mw ≥ 7) and explosive volcanic eruptions (VEI ≥ 2) spanning 1960–2019. Both time-series exhibit decadal timescale trends, over which annual earthquake and eruption rates vary by a factor of ≈2. Moreover, global seismic moment release is positively correlated with global eruption rate, with Monte Carlo permutation tests showing that this correlation is significant with a P-value of 1000 km) by earthquake-induced dynamic stress changes, modulation of global earthquake and eruption rates by variations in Earth's rotational velocity, or natural synchronization of events over repeating cycles, are therefore required to explain the correlation.

A major challenge in using satellite interferometry (InSAR) for volcanic monitoring in the tropics is distinguishing volcano deformation from atmospheric noise. We reanalysed InSAR time series from 2007-2009 from Agung volcano, Indonesia, which had previously been used as evidence for unrest. Using uncorrected data, we find an apparent velocity of 5.0 ± 2.7 cm/yr consistent with previous reports, but we show that this signal is consistent with predictions of atmospheric contributions derived from weather models (ECMWF-HRES). Following the correction, we find a velocity of 1.4 ± 4.2 cm/yr and conclude that there was no significant deformation related to the inflation of a shallow magma source from 2007-2009. We discuss the implications for the inferred magma storage system at Agung and consider which other reported signals might have been wrongly attributed to deformation and should be reanalyzed.

The final stage of continental breakup is often accompanied by abundant magmatism. Erta 'Ale volcano lies on the Nubia‐Arabia extensional boundary in Afar, Ethiopia, an incipient mid‐ocean ridge. A fissure on the south flank of Erta 'Ale began erupting on 21 January 2017 and has remained active until at least July 2019. We use Sentinel‐1 synthetic aperture radar acquisitions to create a time series of ground displacement measurements at Erta 'Ale from October 2014 to June 2019, covering the eruption and its buildup. In the preeruption period, we observe gradual extension centered on the lava lake, consistent with the opening of an axis‐aligned dike. Using synthetic aperture radar intensity shadows, we show that the long‐lived Erta 'Ale lava lake was stable in this period, indicative of a steady pressure state in the shallow plumbing system. During the initial eruption, we observe surface displacements consistent with a shallow dike intrusion below the eruption site and conduit contraction below the lava lake. The pressure change associated with the cointrusive drop in the lava lake level is sufficient to reproduce the deformation pattern suggesting that the lava lake is well connected to the shallow plumbing system. Subsidence and contraction during the long‐lived eruption indicates the presence of an off‐rift vertically extensive source. We suggest that this may represent a system of stacked sources throughout the upper crust, with melt being more distributed. We also propose that high magma flux on the slow‐spreading Erta 'Ale segment may be facilitating the presence of shallow axial magma bodies.

Southern Mozambique is the southernmost expression of the continental East African Rift. Here, extension rates are low and rifting is achieved through normal faulting. Incipient rift environments provide an ideal location to investigate the role of reactivated pre-existing structures, aftershock sequences, and fault interactions in rift development. In 2016 a Mw 5.6 earthquake occurred in the Zinave region of southern Mozambique, ∼10 km south-east of the Mw 7.0 2006 Machaze earthquake. We reanalyse ENVISAT InSAR observations of the Machaze earthquake, together with new Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) observations of the Zinave earthquake, and solve for uniform and distributed slip models for both events. We find the Machaze earthquake occurred on a steeply dipping (∼75◦) fault, in agreement with other studies, but that the Zinave earthquake occurred on a ∼60◦ dipping fault. The occurrence of the Zinave earthquake at the same depth as afterslip following the Machaze earthquake suggests laterally heterogeneous crustal frictional properties. The Machaze earthquake caused a Coulomb stress increase of ∼0.2 MPa on the Zinave fault. The full >10 year record of seismicity following the Machaze event can be fit by the Omori law, showing that the Zinave earthquake is part of a decade-long aftershock sequence, consistent with long-duration aftershock sequences in other slowly straining regions. Aftershocks represent a major hazard that needs to be considered if a large earthquake were to occur in the southern East African Rift system today.

Time series of displacement are now routinely available from satellite InSAR and are used for flagging anomalous ground motion, but not yet forecasting. We test conventional time series forecasting methods such as SARIMA and supervised machine learning approaches such as LSTM compared to simple function extrapolation. We focus initially on forecasting seasonal signals and begin by characterising the time‐series using sinusoid fitting, seasonal decomposition and autocorrelation functions. We find that the three measures are broadly comparable but identify different types of seasonal characteristic. We use this to select a set of 310 points with highly seasonal characteristics and test the three chosen forecasting methods over prediction windows of 1‐9 months. The lowest overall median RMSE values are obtained for SARIMA when considering short term predictions ( 6 months). Machine learning methods (LSTM) perform less well. We then test the prediction methods on 2000 randomly selected points with a range of seasonalities and find that simple extrapolation of a constant function performed better overall than any of the more sophisticated time series prediction methods. Comparisons between seasonality and RMSE show a small improvement in performance with increasing seasonality. This proof‐of‐concept study demonstrates the potential of time‐series prediction for InSAR data but also highlights the limitations of applying these techniques to non‐periodic signals or individual measurement points. We anticipate future developments, especially to shorter timescales, will have a broad range of potential applications, from infrastructure stability to volcanic eruptions.

Volcanoes have dormancy periods that may last decades to centuries meaning that eruptions at volcanoes with no historical records of eruptions are common. Baseline monitoring to detect the early stages of reawakening is therefore important even in regions with little recent volcanic activity. Satellite techniques, such as InSAR, are ideally suited for routinely surveying large and inaccessible regions, but the large datasets typically require expert interpretation. Here we focus on Turkey where there are 10 Holocene volcanic systems, but no eruptions since 1855 and consequently little ground-based monitoring. We analyse data from the first five years of the European Space Agency Sentinel-1 mission which collects data over Turkey every 6 days on both ascending and descending passes. The high relief edifices of Turkey’s volcanoes cause two challenges: 1) snow cover during the winter months causes a loss of coherence and 2) topographically-correlated atmospheric artefacts could be misinterpreted as deformation. We propose mitigation strategies for both. The raw time series at Hasan Dag volcano shows uplift of ~ 10 cm between September 2017 and July 2018, but atmospheric corrections based on global weather models demonstrate that this is an artefact and reduce the scatter in the data to

Seismic hazard is commonly characterised using instrumental seismic records. However, these records are short relative to earthquake repeat times, and extrapolating to estimate seismic hazard can misrepresent the probable location, magnitude, and frequency of future large earthquakes. Although paleoseismology can address this challenge, this approach requires certain geomorphic setting, is resource intensive, and can carry large inherent uncertainties. Here, we outline how fault slip rates and recurrence intervals can be estimated by combining fault geometry, earthquake-scaling relationships, geodetically derived regional strain rates, and geological constraints of regional strain distribution. We apply this approach to southern Malawi, near the southern end of the East African Rift, and where, although no on-fault slip rate measurements exist, there are constraints on strain partitioning between border and intra-basin faults. This has led to the development of the South Malawi Active Fault Database (SMAFD), a geographical database of 23 active fault traces, and the South Malawi Seismogenic Source Database (SMSSD), in which we apply our systems-based approach to estimate earthquake magnitudes and recurrence intervals for the faults compiled in the SMAFD. We estimate earthquake magnitudes of MW 5.4–7.2 for individual fault sections in the SMSSD and MW 5.6–7.8 for whole-fault ruptures. However, low fault slip rates (intermediate estimates ∼ 0.05–0.8 mm/yr) imply long recurrence intervals between events: 102–105 years for border faults and 103–106 years for intra-basin faults. Sensitivity analysis indicates that the large range of these estimates can best be reduced with improved geodetic constraints in southern Malawi. The SMAFD and SMSSD provide a framework for using geological and geodetic information to characterise seismic hazard in regions with few on-fault slip rate measurements, and they could be adapted for use elsewhere in the East African Rift and globally.

Large earthquakes alter the crustal stress field across great distances (hundreds to thousands of kilometers) over geologically short timescales (seconds to years). These stress changes can affect magmatic systems, triggering (or suppressing) volcanic unrest and eruption, along with other deeper processes. We use simple kinematic source models in an isotropic elastic half‐space to assess earthquake‐induced static stress changes (>1 kPa) over the entire thickness of the lithosphere and consider the implications for magma ascent and storage. Modeling subduction zone earthquakes, we calculate static normal stress changes with depth on three mutually perpendicular end‐member magma pathways: vertical arc‐parallel, vertical arc‐perpendicular, and horizontal. From this, we define seven stress change regimes within the adjacent volcanic arc. Three of these regimes may strongly encourage magma ascent in dykes by inducing unclamping (decreased compressive normal stress) of vertical pathways which increases in magnitude toward the surface and clamping of horizontal pathways. Two of the regimes may encourage stalling and storage of magma in sills near the base of the crust by inducing unclamping of horizontal pathways at depth. The spatial distribution of the regimes is largely dependent on earthquake magnitude, but also varies with slip distribution and interface dip. We show how the responses of magmatic systems to earthquakes also depends on the stress change magnitude and the state of the magmatic system, with a greater impact expected for larger stress changes acting on weaker, more thermally mature systems.

Seismic hazard is frequently characterised using instrumental seismic records. However, in regions where the instrumental record is short relative to earthquake repeat times, extrapolating it to estimate seismic hazard can misrepresent the probable location, magnitude, and frequency of future large earthquakes. Although paleoseismology can address this challenge, this approach requires certain geomorphic settings and carries large inherent uncertainties. Here, we outline how fault slip rates and recurrence intervals can be estimated through an approach that combines fault geometry, earthquake-scaling relationships, geodetically derived regional strain rates, and geological constraints of regional strain distribution. We then apply this approach to the southern Malawi Rift where, although no on-fault slip rate measurements exist, there are theoretical and observational constraints on how strain is distributed between border and intrabasinal faults. This has led to the development of the South Malawi Active Fault Database (SMAFD), the first database of its kind in the East African Rift System (EARS) and designed so that the outputs can be easily incorporated into Probabilistic Seismic Hazard Analysis. We estimate earthquake magnitudes of MW 5.4–7.2 for individual fault sections in the SMAFD, and MW 6.0–7.8 for whole fault ruptures. These potentially high magnitudes for continental normal faults reflect southern Malawi's 11–140 km long faults and thick (30–35 km) seismogenic crust. However, low slip rates (intermediate estimates 0.05–0.8 mm/yr) imply long recurrence intervals between events: 102–105 years for border faults and 103–106 years for intrabasinal faults. Sensitivity analysis indicates that the large range of these estimates can be reduced most significantly from an improved understanding of the rate and partitioning of rift-extension in southern Malawi, earthquake scaling relationships, and earthquake rupture scenarios. Hence these are critical areas for future research. The SMAFD provides a framework for using geological and geodetic information to characterize seismic hazard in low strain rate settings with few on-fault slip rate measurements, and could be adapted for use elsewhere in the EARS or globally.

Magmatic intrusions play a vital role not only in accommodating extensional stresses in continental rifts but also in feeding volcanic systems. The location, orientation, and timescale of dike intrusions are dictated by the interaction of regional and local stresses, the effect of pre‐existing weaknesses, and the composition of magma. Observing active intrusions can provide important information regarding the interaction between magmatic processes and the tectonic stress field during continental rifting. We focus on a seismic swarm that occurred in 2015 to the northeast of Fentale volcano, in the Main Ethiopian Rift (MER), and use radar interferometry to study surface deformation associated with the seismic swarm. Interferograms show a pattern of dike‐induced deformation, with a model estimate of volume change of 33×106±0.6×106m3 at a depth range of 5.4 to 8 km. We use a small baseline subset algorithm to calculate line of sight time series and find that the displacements decay exponentially with a decay constant of ∼83 days. Coupled source‐sink models suggest that such slow dike intrusions require a high viscosity rhyolitic magma. The difference in behavior between Fentale and other caldera systems in the MER, which show multi‐year cycles of inflation and deflation, suggests fundamental differences in magma composition and architecture of the plumbing system. This is the first direct observation of a dike intrusion in the MER and provides new constraints on the temporal‐spatial patterns of stress and strain that occur during continental rifting. Whether this activity is transient or a long‐term feature associated with rift evolution is an open question.

Time series of displacement are now routinely available from satellite InSAR and are used for flagging anomalous ground motion, but not yet for forecasting. Here we test the capabilities of conventional time series analysis and forecasting methods such as SARIMA and supervised machine learning approaches such as Long Short Term Memory (LSTM) in comparison to simple function extrapolation methods. For our initial tests, we focus on forecasting periodic signals and begin by characterising the time-series using sinusoid fitting, seasonal decomposition and autocorrelation functions. We find that the three measures are broadly comparable but identify different types of seasonal characteristic. We use this to select a set of 310 points with highly seasonal characteristics and test the three chosen forecasting methods over prediction windows of 1-9 months. The lowest overall RMSE values are obtained for SARIMA when considering short term predictions ($$6 months). Machine learning methods (LSTM) perform less well, as is often the case for non-stationary signals. We then test the prediction methods on 2000 randomly selected points with a range of seasonalities and find that simple extrapolation of a constant function performed better overall than any of the more sophisticated time series prediction methods. Comparisons between seasonality and RMSE show a statistically significant improvement in performance with increasing seasonality. This proof-of-concept study demonstrates the potential of time-series prediction for InSAR data but also highlights the limitations of applying these techniques to non-periodic signals or individual measurements points. We anticipate future developments, especially to shorter timescales, will have a broad range of potential applications, from infrastructure stability to volcanic eruptions.

The large volumes of Sentinel-1 data produced over Europe are being used to develop pan-national ground motion services. However, simple analysis techniques like thresholding cannot detect and classify complex deformation signals reliably making providing usable information to a broad range of nonexpert stakeholders a challenge. Here, we explore the applicability of deep learning approaches by adapting a pretrained convolutional neural network (CNN) to detect deformation in a national-scale velocity field. For our proof-of-concept, we focus on the U.K. where previously identified deformation is associated with coal-mining, ground water withdrawal, landslides, and tunneling. The sparsity of measurement points and the presence of spike noise make this a challenging application for deep learning networks, which involve calculations of the spatial convolution between images. Moreover, insufficient ground truth data exist to construct a balanced training data set, and the deformation signals are slower and more localized than in previous applications. We propose three enhancement methods to tackle these problems: 1) spatial interpolation with modified matrix completion; 2) a synthetic training data set based on the characteristics of the real U.K. velocity map; and 3) enhanced overwrapping techniques. Using velocity maps spanning 2015-2019, our framework detects several areas of coal mining subsidence, uplift due to dewatering, slate quarries, landslides, and tunnel engineering works. The results demonstrate the potential applicability of the proposed framework to the development of automated ground motion analysis systems.The large volumes of Sentinel-1 data produced over Europe are being used to develop pan-national ground motion services. However, simple analysis techniques like thresholding cannot detect and classify complex deformation signals reliably making providing usable information to a broad range of nonexpert stakeholders a challenge. Here, we explore the applicability of deep learning approaches by adapting a pretrained convolutional neural network (CNN) to detect deformation in a national-scale velocity field. For our proof-of-concept, we focus on the U.K. where previously identified deformation is associated with coal-mining, ground water withdrawal, landslides, and tunneling. The sparsity of measurement points and the presence of spike noise make this a challenging application for deep learning networks, which involve calculations of the spatial convolution between images. Moreover, insufficient ground truth data exist to construct a balanced training data set, and the deformation signals are slower and more localized than in previous applications. We propose three enhancement methods to tackle these problems: 1) spatial interpolation with modified matrix completion; 2) a synthetic training data set based on the characteristics of the real U.K. velocity map; and 3) enhanced overwrapping techniques. Using velocity maps spanning 2015-2019, our framework detects several areas of coal mining subsidence, uplift due to dewatering, slate quarries, landslides, and tunnel engineering works. The results demonstrate the potential applicability of the proposed framework to the development of automated ground motion analysis systems.

Large silicic magma reservoirs preferentially form in the upper crust of extensional continental environments. However, our quantitative understanding of the link between mantle magmatism, silicic reservoirs, and surface deformation during rifting is very limited. Here, we focus on Corbetti, a peralkaline caldera in the densely populated Main Ethiopian Rift, which lies above a focused zone of upper mantle partial melt and has been steadily uplifting at a maximum rate of 6.6±1.2 cm yr−1 for more than 10 yr. Numerical modeling shows that a maximum concomitant residual gravity increase of 9±3 μGal yr−1 by the intrusion of mafic magma at ∼7 km depth into a compressible and inelastic crystal mush best explains the observed deformation and gravity changes. The derived magma mass flux of ∼1011 kg yr−1 is anomalously high and at least 1 order of magnitude greater than the mean long‐term mass eruption rate. This study demonstrates that periodic and high‐rate magmatic rejuvenation of upper‐crustal mush is a significant and rapid contributor to mature continental rifting.

The distribution of deformation during the early stages of continental rifting is an important constraint on our understanding of continental breakup. Incipient rifting in East Africa has been considered to be dominated by slip along rift border faults, with a subsequent transition to focussed extension on axial segments in thinned crust and/or with active magmatism. Here, we study high‐resolution satellite data of the Zomba Graben in southern Malawi, an amagmatic rift whose topography is dominated by the west‐dipping Zomba fault. We document evidence for five sub‐parallel fault scarps between 13 and 51 km long spaced ~10‐15 km apart. The scarps consist of up to five segments between 4‐18 km long, separated by minima in scarp height and river knickpoints. The maximum height of each fault scarp ranges from 9.5 ± 4.2 m to 35.3 ± 14.6 m, with the highest scarp measured on the intrabasin Chingale Step fault. We estimate that the scarps were formed by multiple earthquakes of up to Mw7.1, and represent a previously unrecognized seismic hazard. Our calculations show that 55 ± 24 % of extensional strain is accommodated across intrabasin faults within the ~50 km wide rift. This demonstrates that a significant proportion of displacement can occur on intrabasin faults during early stage rifting, even in thick continental lithosphere with no evidence for magmatic fluids.

Geomorphological features such as fault scarps and stream knickpoints are indicators of recent fault activity. Determining whether these features formed during a single earthquake or over multiple earthquakes cycles has important implications for the interpretation of the size and frequency of past events. Here, we focus on the Bilila‐Mtakataka fault, Malawi, where the 20 m high fault scarps exceed the height expected from a single earthquake rupture. We use a high resolution digital elevation model (< 1 m) to identify complexity in the fault scarp and knickpoints in river profiles. Of 39 selected scarp profiles, 20 showed evidence of either multi‐scarps or composite scarps and of the seven selected river and stream profiles, five showed evidence for multiple knickpoints. A near uniform distribution of vertical offsets on the sub‐scarps suggests they were formed by separate earthquakes. These independent methods agree that at least two earthquakes have occurred with an average vertical offset per event of 10 and 12 m. This contrasts earlier studies which proposed that this scarp formed during a single event, and demonstrates the importance of high‐resolution topographic data for understanding tectonic geomorphology. We use a one‐dimensional diffusion model of scarp degradation to demonstrate how fault splays form multi‐scarps and estimate the diffusion age κt of the Bilila‐Mtakataka fault scarp to be 48 ± m25 m2, corresponding to 6400 ± 4000 years since formation. We calculate that a continuous rupture would equate to a MW 7.8 ± 0.3 earthquake, greater than the largest seismic event previously recorded in East Africa.