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Ezgi Karasözen

Publications and source records attributed to Ezgi Karasözen.

4 recordsLinked to original sources

Rapid seismic and infrasound assessment of large landslides: A case study from Denali National Park and Preserve (Alaska)

Large, rapid landslides are a global hazard that can occur in remote, mountainous areas. Eyewitness reports of landslides and satellite imagery can often be limited or delayed, particularly during inclement weather. However, landslide-generated seismic and infrasound (low-frequency atmospheric sound) waves can be remotely detected in near real-time. This information can significantly expedite characterization and possible landslide response activities. Here, we highlight these capabilities using a > 4 million m³ ice–rock avalanche in Denali National Park and Preserve (Alaska). This event was detected via a landslide-specific seismic location and volume estimation algorithm deployed in Alaska, and — notably — by standard earthquake monitoring systems. Following rapid detection of this event, we combined its seismic and infrasound dataset with optical, synthetic aperture radar, and oblique aerial imagery, multitemporal digital elevation models, and a numerical flow model to reconstruct its failure timeline and dynamics. We apply array processing to infrasound signals traveling > 250 km and find that two precursory events occurred minutes prior to the main failure. We use long-period seismic signals to infer the force exerted by the landslide on the Earth and constrain the rheological parameters of our numerical flow simulation with this result and deposit morphology. The main failure produced a steeply-dipping impulsive initial downward force and reached speeds exceeding 60 m/s. This impulsive force generated relatively strong seismic body waves, which contributed to the earthquake system detection. This large, remote Alaska landslide underscores the key value of seismic and infrasound analysis for rapid landslide assessment and motivates efforts to further operationalize these approaches.

Alaska↗

Searching for seismic precursors - The Barry Landslide hazard clean up

The Barry Landslide, located in Barry Arm of Prince William Sound, Alaska, poses a major hazard due to its steep, unstable slopes and the potential for a massive landslide-generated tsunami. With an estimated volume of 500–700 million cubic meters, the Barry Landslide could trigger highly destructive waves. In this study, we focus on seismic signals from the Barry Landslide, which are critical for providing timely tsunami warnings. Since the summer of 2020, the region has been instrumented to monitor the landslide, but the seismic record is complicated by the presence of nearby glaciers and frequent regional earthquakes. Among these signals, we analyze a specific class of short-duration, high-frequency seismic events that exhibit strong seasonal variability, increasing in rate from late summer to mid-winter before ceasing abruptly in late winter or early spring. Our analysis suggests that the source of these signals is likely near or beneath Cascade Glacier, adjacent to the landslide, rather than within the landslide mass itself. We apply detection algorithms to construct a time history for this signal type, which we then compare with environmental factors like precipitation, temperature, and slope displacement data from ground-based radar and remote sensing. Correlations indicate that these seismic events may be driven by seasonal hydrological changes, particularly the freeze-up of subglacial water pathways. While these events are not directly linked to landslide motion, they serve as indirect markers of subsurface hydrological conditions that influence slope stability. Our findings highlight the complex interplay between glaciers, groundwater, and landslide dynamics, emphasizing the need for multi-parameter monitoring to assess evolving geohazards in the region.

Alaska↗

Kinematic evolution of a large paraglacial landslide in the Barry Arm fjord of Alaska

Our warming climate is adversely affecting cryospheric landscapes via glacial retreat, permafrost degradation, and associated slope destabilization. In Prince William Sound, Alaska, the rapid retreat of Barry Glacier has destabilized the slopes flanking the glacier, resulting in numerous landslides. The largest of these landslides (∼500 Mm 3 in volume) is more than 2 km wide and has the potential to generate a tsunami that could affect nearby recreationists, marine traffic, infrastructure, natural and cultural resources, and the community of Whittier, located 60 km from the landslide. Here, we combine landslide structural and kinematic element mapping with data acquired from bi-yearly airborne lidar, multi-week satellite-based synthetic aperture radar (SAR), sub-hourly ground-based SAR, and seismic monitoring from 2020 to 2022 to characterize this landslide and examine its evolution. While some methods serve as a snapshot in time that is a culmination of events, others emphasize the ever-evolving nature of the landslide and associated hazards. Four major kinematic elements define the overall structure of the landslide, which vary in deformation type and rate, from creep (5 mm per day over several months) to episodic movement (2 m in 30 days) and landslide-wide to localized events. In some areas of the landslide, short-term deformation deviates from structures formed by cumulative movement, implying structural and kinematic evolution associated with glacier retreat. These insights are important for assessing landslide hazards and hazard evolution for large, slow-moving bedrock landslides in actively deglaciating environments.

Alaska↗

A global catalog of calibrated earthquake locations

We produced a globally distributed catalog of earthquakes and nuclear explosions with calibrated hypocenters, referred to as the Global Catalog of Calibrated Earthquake Locations (GCCEL). This dataset currently contains 18,782 events in 289 clusters with >3.2 million arrival times observed at 19,258 stations. The term “calibrated” refers to the property that the hypocenters are minimally biased by unknown Earth structure. In addition, we calculate uncertainties using empirically determined variability of the arrival‐time data itself, specific to each calibrated cluster of hypocenters. Outliers in the arrival‐time dataset are removed based on measured variability of the data. In each cluster, we estimate the empirically determined uncertainty for each set of station‐phase arrival times. We use a version of the hypocentroidal decomposition multiple event relocation algorithm specifically adapted for calibrated relocations of clusters of seismic events. Most clusters are calibrated by fitting the subset of direct crustal first arrivals ( Pg and Sg ) with a locally appropriate travel‐time model to estimate the cluster hypocentroid. A few clusters are calibrated by aligning the pattern of relative locations in space and time with one or more events for which a ground‐truth hypocenter is available from an independent source with known uncertainty, such as a nuclear explosion. Epicentral uncertainties in GCCEL typically range from 1 to 5 km with a 90% confidence interval. Most events have depth constraint from one or more sources, usually with an uncertainty of ≤5 km. GCCEL is a significant resource for research at local, regional, and global scales because it provides minimally biased absolute hypocenters, meaningful associated error estimates, and curated arrival times as a reference dataset that can be used as prior constraints in the development of new regional, national, and global earthquake catalogs; validation of new location techniques; and the generation of advanced Earth models.

Seismological Research Letters↗