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Paula Madeline Burgi

Publications and source records attributed to Paula Madeline Burgi.

3 recordsLinked to original sources

USGS2026

High‐resolution surface deformation and slip distribution observations for the 2023 Kahramanmaraş, Türkiye, earthquake sequence help constrain the rupture process

Splay, or branch, faults are a common geometric feature of earthquake surface ruptures and may provide constraints on the rupture behavior of an earthquake. The 2023 M w 7.8 Pazarcık and M w 7.5 Elbistan, Türkiye, earthquakes are examples of ruptures with multiple small splays, and the Pazarcık earthquake nucleated on a splay fault, the Narlı fault, before rupturing bilaterally on the East Anatolian fault (EAF). Here, we present 3‐m‐resolution surface displacement from subpixel correlation of Planet Dove optical images for the entirety of both ruptures with corresponding surface slip distributions. For a 30‐km‐long study region spanning the Narlı‐EAF intersection, we compare surface slip derived from five data sets with different resolutions (on‐the‐ground, WorldView, Planet Dove, Sentinel‐2, and Sentinel‐1) to elucidate complementary information. In addition, we integrate information from the surface expression of faulting with published dynamic rupture simulations and rupture process studies to constrain a rupture evolution for the Pazarcık earthquake that is consistent across data sets. This work highlights the complementary nature of disparate surface slip data sets and the role that high‐resolution surface displacement information, including from fault splays, can play in constraining nonunique rupture models and refining understanding of the earthquake rupture process.

Bulletin of the Seismological Society of America↗

USGS2025

Insights into widespread landsliding in southern Appalachia from Hurricane Helene

Between 23 and 27 September 2024, antecedent rain followed by Hurricane Helene produced one of the most damaging weather events in southern Appalachia history. The back-to-back storm events resulted in a maximum cumulative rainfall of 848 mm and hurricane-force wind gusts over 170 km/h in western North Carolina, eastern Tennessee, and southwestern Virginia. The resulting regional flooding, landslides, and tree blowdown caused over 100 fatalities, damaged or destroyed critical infrastructure and thousands of structures, and severed connectivity across the region. Over the next several weeks, a multi-agency landslide response produced a rapid hazard assessment and mapped 2217 landslides, 55% of which damaged infrastructure or property. Orographic uplift enhanced rainfall, resulting in concentrated landsliding along the ~250 km swath of the Blue Ridge escarpment in western North Carolina. Landslides initiated predominantly on windward-facing (southeast-facing) slopes, and localized clustering of initiation points indicated a strong influence of hillslope-scale meteorological and geomorphic factors. Many shallow landslides mobilized into larger, highly mobile, and damaging debris flows that graded into floods. Here, we put our preliminary observations in the context of historical storm-driven landslide events and open new avenues for investigating the nature and extent of landslides and their effects in southern Appalachia and similar environments.

Georgia, North Carolina, South Carolina, Tennessee↗

USGS2025

Updating regional‐scale geospatial liquefaction models with locally available geotechnical data

We present a method to update the geospatial liquefaction model used by the U.S. Geological Survey’s near‐real‐time ground failure product with subsurface geotechnical data. The geospatial model estimates liquefaction probability from peak ground velocity (via ShakeMap) and geospatial susceptibility proxies. In many regions, additional information relevant to constraining liquefaction likelihood is also available, including surface geology maps and subsurface geotechnical measurements. There is currently no mechanism to use these data in the ground failure product liquefaction model, even though these data could provide more precise constraints on spatial variations in the lithologic character of the soil (surface geology) and direct measurements of the subsurface mechanical properties that affect liquefaction occurrence and severity (geotechnical measurements). In this study, we develop a method to integrate these data with the geospatial model and assess how these data can improve regional‐scale predictions. We develop a Bayesian updating framework and apply it to the 1989 magnitude 6.9 Loma Prieta, California, earthquake, for which mapped observations are available to evaluate performance. We constrain the Bayesian framework with 373 Northern California cone penetration tests and liquefaction susceptibility classes based on the mapped surface geology. This Bayesian model incorporates geotechnical information into the geospatial model and more accurately predicts liquefaction occurrences than the geospatial model, while sacrificing less accuracy in terms of predicting the absence of liquefaction than the geotechnical model. In future applications, this approach could be adapted to update other geospatial models using locally available subsurface data.

California↗