Geology topics

Matthew A. Thomas

Publications and source records attributed to Matthew A. Thomas.

23 records · Page 2Linked to original sources

USGS2019

Landslides triggered by Hurricane Maria: Assessment of an extreme event in Puerto Rico

Hurricane Maria hit the island of Puerto Rico on 20 September 2017 and triggered more than 40,000 landslides in at least three-fourths of Puerto Rico’s 78 municipalities. The number of landslides that occurred during this event was two orders of magnitude greater than those reported from previous hurricanes. Landslide source areas were commonly limited to surficial soils but also extended into underlying saprolite and bedrock. Slope failures occurred before, during, and after flooding, and many transitioned into long runout debris flows. Steep slopes in hilly and mountainous regions were particularly impacted by landslides due to antecedent soil moisture levels that were 11%–13% higher than average and rainfall totals of at least 250 mm within a 48 h period. High landslide densities were especially widespread across some geologic formations (e.g., granodiorite of the Utuado batholith); however, bedrock geology alone did not determine the location and distribution of landslides caused by Hurricane Maria. While rainfall data collected during Hurricane Maria were inconsistent, satellite-based soil moisture data were correlated with the distribution of landslides. In the future, the use of soil moisture data could enable assessments of regional landslide susceptibility prior to hurricanes or extreme precipitation events.

GSA Today↗

USGS2018

A decade of remotely sensed observations highlight complex processes linked to coastal permafrost bluff erosion in the Arctic

Eroding permafrost coasts are indicators and integrators of changes in the Arctic System as they are susceptible to the combined effects of declining sea ice extent, increases in open water duration, more frequent and impactful storms, sea-level rise, and warming permafrost. However, few observation sites in the Arctic have yet to link decadal-scale erosion rates with changing environmental conditions due to temporal data gaps. This study increases the temporal fidelity of coastal permafrost bluff observations using near-annual high spatial resolution (<1 m) satellite imagery acquired between 2008 and 2017 for a 9-km segment of coastline at Drew Point, Beaufort Sea coast, Alaska. Our results show that mean annual erosion for the 2007 to 2016 decade was 17.2 m yr-1, which is 2.5 times faster than historic rates, indicating that bluff erosion at this site is likely responding to changes in the Arctic System. In spite of a sustained increase in decadal-scale mean annual erosion rates, mean open water season erosion varied from 6.7 m yr-1 in 2010 to more than 22.0 m yr-1 in 2007, 2012, and 2016. This variability provided a range of coastal responses through which we explored the different roles of potential environmental drivers. The lack of significant correlations between mean open water season erosion and the environmental variables compiled in this study indicates that we may not be adequately capturing the environmental forcing factors, that the system is conditioned by long-term transient effects or extreme weather events rather than annual variability, or that other not yet considered factors may be responsible for the increased erosion occurring at Drew Point. Our results highlight an increase in erosion at Drew Point in the 21st century as well as the complexities associated with unraveling the factors responsible for changing coastal permafrost bluffs in the Arctic.

Alaska↗

USGS2018

Identifying physics‐based thresholds for rainfall‐induced landsliding

Most regional landslide warning systems utilize empirically derived rainfall thresholds that are difficult to improve without recalibration to additional landslide events. To address this limitation, we explored the use of synthetic rainfall to generate thousands of possible storm patterns and coupled them with a physics‐based hydrology and slope stability model for various antecedent soil saturation scenarios to analyze pore‐water pressure and factor of safety metrics. We used these metrics to generate two‐tiered alert thresholds that can be employed to assess shallow landslide potential for any given combination of storm and antecedent wetness. When applied to the San Francisco Bay region (California, USA), the results are consistent with events that caused widespread landsliding. Our deterministic modeling approach, which accounts for plausible ranges in soil hydraulic and mechanical properties, can inform the development of the next generation of warning systems for rainfall‐induced landsliding.

Geophysical Research Letters↗

USGS2018

Variability in soil-water retention properties and implications for physics-based simulation of landslide early warning criteria

Rainfall-induced shallow landsliding is a persistent hazard to human life and property. Despite the observed connection between infiltration through the unsaturated zone and shallow landslide initiation, there is considerable uncertainty in how estimates of unsaturated soil-water retention properties affect slope stability assessment. This source of uncertainty is critical to evaluating the utility of physics-based hydrologic modeling as a tool for landslide early warning. We employ a numerical model of variably saturated groundwater flow parameterized with an ensemble of texture-, laboratory-, and field-based estimates of soil-water retention properties for an extensively monitored landslide-prone site in the San Francisco Bay Area, CA, USA. Simulations of soil-water content, pore-water pressure, and the resultant factor of safety show considerable variability across and within these different parameter estimation techniques. In particular, we demonstrate that with the same permeability structure imposed across all simulations, the variability in soil-water retention properties strongly influences predictions of positive pore-water pressure coincident with widespread shallow landsliding. We also find that the ensemble of soil-water retention properties imposes an order-of-magnitude and nearly two-fold variability in seasonal and event-scale landslide susceptibility, respectively. Despite the reduced factor of safety uncertainty during wet conditions, parameters that control the dry end of the soil-water retention function markedly impact the ability of a hydrologic model to capture soil-water content dynamics observed in the field. These results suggest that variability in soil-water retention properties should be considered for objective physics-based simulation of landslide early warning criteria.

Landslides↗

USGS2014

Fluid pressure responses for a Devil's Slide-like system: problem formulation and simulation

This study employs a hydrogeologic simulation approach to investigate subsurface fluid pressures for a landslide-prone section of the central California, USA, coast known as Devil's Slide. Understanding the relative changes in subsurface fluid pressures is important for systems, such as Devil's Slide, where slope creep can be interrupted by episodic slip events. Surface mapping, exploratory core, tunnel excavation records, and dip meter data were leveraged to conceptualize the parameter space for three-dimensional (3D) Devil's Slide-like simulations. Field observations (i.e. seepage meter, water retention, and infiltration experiments; well records; and piezometric data) and groundwater flow simulation (i.e. one-dimensional vertical, transient, and variably saturated) were used to design the boundary conditions for 3D Devil's Slide-like problems. Twenty-four simulations of steady-state saturated subsurface flow were conducted in a concept-development mode. Recharge, heterogeneity, and anisotropy are shown to increase fluid pressures for failure-prone locations by up to 18.1, 4.5, and 1.8% respectively. Previous estimates of slope stability, driven by simple water balances, are significantly improved upon with the fluid pressures reported here. The results, for a Devil's Slide-like system, provide a foundation for future investigations

California↗