Geology topics

Ben Leshchinsky

Publications and source records attributed to Ben Leshchinsky.

7 recordsLinked to original sources

USGS2026

Impacts of transient critical zone evolution on landslide susceptibility and hazard Across the Utuado batholith, Puerto Rico

Landscapes in humid climates often experience rapid chemical and mechanical weathering that can change groundwater fluxes, drainage pathways, and frictional strength via alterations in subsurface mineral composition and matrix porosity. These changes to hillslope critical zone structure and strength should control landslide susceptibility, size, and failure style. Here we test the impact of differential weathering on landslide failure processes by exploiting a natural experiment along the dioritic Utuado batholith in Puerto Rico's Cordillera Central, where a sharp weathering gradient follows an upstream-propagating knickzone into an uplifted shoreline platform that was affected by Hurricane Maria in 2017. Through a combination of landslide mapping, field geophysical and geotechnical surveys, topographic analysis, calibrated stream profile inversion, 3D back-analysis of hillslope strength, and debris-flow inundation assessments, we show that differential weathering induces changes to critical zone structure and consequently landslide susceptibility and hazard. Our mapping reveals that the hurricane-induced landslides preferentially cluster along less weathered hillslopes despite a marked increase in frictional strength. Jointly inverted seismic refraction and electrical resistivity profiles show that the frictionally weak, heavily weathered hillslopes are highly porous and dry, which we posit acts to stabilize slopes through limiting deeper hydrologic connectivity that can produce shallow water tables with destabilizing lateral seepage forces during storms. Debris-flow inundation mapping and analysis reveals that major contributors to debris-flow growth, channel steepness and landslide coalescence, scale linearly with hillslope friction angle. This leads to higher-mobility debris flows along knickzone reaches, which disproportionately affects communities at the base of the plateau.

Puerto Rico↗

USGS2026

The Cascadia Region Earthquake Science Center (CRESCENT): Advancing understanding of Cascadia's earthquake hazards

The Cascadia Subduction Zone (CSZ) is capable of producing large megathrust earthquakes and tsunamis, posing significant risks to the Pacific Northwest. This paper examines the seismic characteristics of the CSZ, including its offshore coupling, sparse seismicity, and a complex paleoseismic record. While recent advances in geophysical methods and data collection have improved our understanding of subduction zone processes, important uncertainties remain regarding rupture dynamics, ground shaking, and tsunami impacts. The Cascadia Region Earthquake Science Center (CRESCENT) has been established to address these challenges through coordinated research, education, and community engagement. By integrating scientific studies, fostering collaboration, and leveraging new technologies, CRESCENT seeks to improve hazard assessment and resilience in the region. This paper outlines the primary challenges and opportunities in advancing subduction zone science and enhancing societal preparedness for future CSZ events.

California, Oregon, Washington↗

USGS2024

Slope Unit Maker (SUMak): An efficient and parameter-free algorithm for delineating slope units to improve landslide modeling

Slope units are terrain partitions bounded by drainage and divide lines. In landslide modeling, including susceptibility modeling and event-specific modeling of landslide occurrence, slope units provide several advantages over gridded units, such as better capturing terrain geometry, improved incorporation of geospatial landslide-occurrence data in different formats (e.g., point and polygon), and better accommodating the varying data accuracy and precision in landslide inventories. However, the use of slope units in regional ( > 100 km 2 ) landslide studies remains limited due, in part, to the large computational costs and/or poor reproducibility with current delineation methods. We introduce a computationally efficient algorithm for the parameter-free delineation of slope units that leverages tools from within TauDEM and GRASS, using an R interface. The algorithm uses geomorphic laws to define the appropriate scaling of the slope units representative of hillslope processes, avoiding the often ambiguous determination of slope unit size. We then demonstrate how slope units enable more robust regional-scale landslide susceptibility and event-specific landslide occurrence maps.

Natural Hazards and Earth Systems Sciences (NHESS)↗

USGS2023

Mapping landslide susceptibility over large regions with limited data

Landslide susceptibility maps indicate the spatial distribution of landslide likelihood. Modeling susceptibility over large or diverse terrains remains a challenge due to the sparsity of landslide data (mapped extent of known landslides) and the variability in triggering conditions. Several different data sampling strategies of landslide locations used to train a susceptibility model are used to mitigate this challenge. However, to our knowledge, no study has systematically evaluated how different sampling strategies alter a model's predictor effects (i.e., how a predictor value influences the susceptibility output) critical to explaining differences in model outputs. Here, we introduce a statistical framework that examines the variation in predictor effects and the model accuracy (measured using receiver operator characteristics) to highlight why certain sampling strategies are more effective than others. Specifically, we apply our framework to an array of logistic regression models trained on landslide inventories collected at sub-regional scales over four terrains across the United States. Results show significant variations in predictor effects depending on the inventory used to train the models. The inconsistent predictor effects cause low accuracies when testing models on inventories outside the domain of the training data. Grouping test and training sets according to physiographic and ecological characteristics, which are thought to share similar triggering mechanisms, does not improve model accuracy. We also show that using limited landslide data distributed uniformly over the entire modeling domain is better than using dense but spatially isolated data to train a model for applications over large regions.

California, Kentucky, North Carolina, West Virgini↗

USGS2021

Clays are not created equal: How clay mineral type affects soil parameterization

Clay minerals dominate the soil colloidal fraction and its specific surface area. Differences among clay mineral types significantly influence their effects on soil hydrological and mechanical behavior. Presently, the soil clay content is used to parameterize soil hydraulic and mechanical properties (SHMP) for land surface models while disregarding the type of clay mineral. This undifferentiated use of clay leads to inconsistent parameterization, particularly between tropical and temperate soils, as shown herein. We capitalize on recent global maps of clay minerals that exhibit strong climatic and spatial segregation of active and inactive clays to consider spatially resolved clay mineral types in SHMP estimation. Clay mineral-informed pedotransfer functions and machine learning algorithms trained with datasets including different clay types and soil structure formation processes improve SHMP representation regionally with broad implications for hydrological and geomechanical Earth surface processes.

Geophysical Research Letters↗

USGS2021

Using high sample rate lidar to measure debris-flow velocity and surface geometry

Debris flows evolve in both time and space in complex ways, commonly starting as coherent failures but then quickly developing structures such as roll waves and surges. These processes are readily observed but difficult to study or quantify because of the speed at which they evolve. Many methods for studying debris flows consist of point measurements (e.g., flow height or basal stresses), which are inherently limited in spatial coverage and cannot fully characterize the spatiotemporal evolution of a flow. In this study, we use terrestrial lidar to measure debris-flow profiles at high sampling rates to examine debris-flow movement with high temporal and spatial precision and accuracy. We acquired measurements during gate-release experiments at the U.S. Geological Survey debris-flow flume, a unique experimental facility where debris flows can be artificially generated at a large scale. A lidar scanner was used to record repeat topographic profiles of the moving debris flows along the length of the flume with a narrow swath width (∼1 mm) at a rate of 60 Hz. The high-resolution lidar profiles enabled us to quantify flow front velocity of the debris flows and provided an unprecedented record of the development and evolution of the flow structure with a sub-second time resolution. The findings of this study demonstrate how to obtain quantitative measurements of debris-flow movement. In addition, the data help us to quantitatively define the development of a saltating debris-flow front and roll waves behind the debris-flow front. Such measurements may help constrain future modeling efforts.

Environmental and Engineering Geoscience↗

USGS2019

Real-time monitoring of debris-flow velocity and mass deformation from field experiments with high sample rate lidar and video

Debris flows evolve in both time and space in complex ways, commonly starting as coherent failures but then quickly developing structures such as roll waves and surges. This process is readily observed, but difficult to study or quantify because of the speed at which it occurs. Many methods for studying debris flows consist of point measurements (e.g., of flow height or basal stresses), which are inherently limited in spatial coverage and fail to fully capture the spatiotemporal evolution of a flow. In this study, we use a terrestrial lidar to measure debris-flow profiles at high sample rates to examine debris-flow movement with high temporal and spatial precision and accuracy. We acquired measurements during gate-release experiments at the USGS debris flume, a unique experimental facility where debris flows can be simulated at a large scale. In this study, the laser scanner was placed at the bottom of the steep flume and recorded topography of the entire flume bed and debris flow at a rate of 60 Hz along a very narrow profile (~1mm in width), providing a detailed, two-dimensional cross-section of the debris flow through time. The high-resolution profiles enable us to quantify flow front and surge velocities of the debris flow and provide an unprecedented record of the development and evolution of the flow structure over time. The profiles also preserve a record of the highly variable deposition pattern of the debris flow on a downstream fan with a time resolution of hundredths of a second. In addition, video imagery from the experiment was used to track debris flow movement through time. By acquiring high-resolution topographic data and video imagery during a controlled experiment, we have been able to obtain unusually complete quantitative measurements of debris-flow movement. Such measurements may help constrain future modeling efforts.

Conference Paper↗