Geology topics

Corina Cerovski-Darriau

Publications and source records attributed to Corina Cerovski-Darriau.

14 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

Post-fire soil hydrologic response and recovery in northern California (USA)

Background Wildfires abruptly change landscapes by altering soil properties and vegetation cover. These changes are thought to reduce soil infiltration capacity, making landscapes susceptible to runoff and erosion. However, post-fire soil response is complex and likely varies across locations and time. Aims Here, we aim to understand regional post-fire soil response and recovery by tracking changes across different northern California (USA) lithology and vegetation types. Methods We conducted repeat in situ soil infiltration tests for 3 years post-fire at 31 burned and 10 unburned sites spanning the 2021 Dixie, 2020 LNU Lightning Complex, 2020 Walbridge and 2020 Glass fires. Key results Our two main findings are: (1) burned chaparral soils have increased hydraulic conductivity compared with unburned sites, and (2) infiltration rates return to pre-fire conditions within 3 years across most lithologies and vegetations. Conclusions Recovery might be generalizable by vegetation and lithology but differ regionally, making it important to identify meaningful hydrologic response units (HRUs). Multi-year studies with paired burned and unburned measurements can constrain the recovery timeline and provide information missed by observations solely of burned soils. Implications Understanding where, and for how long, soil remains susceptible to runoff and erosion can help prioritize areas and time periods most in need of mitigation.

California↗

USGS2026

From start to stop: Simple methods for mapping susceptibility to landslide runout and debris-flow inundation

Landslide runout and debris-flow inundation can disrupt areas well beyond their initial sources, causing widespread damage and extensive fatalities. Understanding where they start and how far they might travel is essential in many locations worldwide. However, most landslide susceptibility maps focus on initiation areas and fail to incorporate runout areas. Furthermore, hazards vary greatly with the degree of landslide mobility, and debris flows can grow as they travel beyond their initial source. Here, we use the USGS Grfin Tools software suite to map susceptible areas from start to stop in the Federated States of Micronesia where landslide and debris-flows runout onto gentle ground is a deadly threat. The DEM-based models in Grfin Tools use simple, empirical, and well-documented approaches that require minimal parameters and, thus, can be used in areas that lack detailed physical properties. We illustrate methods to estimate the required parameters using direct landslide observations, and we suggest alternate methods if direct observations are absent. Our simple parameter estimations in the Federated States of Micronesia successfully predict areas that match past landslide runout and debris-flow inundation, as well as zones with no inundation. In addition to creating preliminary regional assessments, Grfin Tools can be used for comparing multiple scenarios and/or identifying areas for further investigations.

Chuuk, Kosrae, Pohnpei↗

USGS2026

Building a national coordination structure to reduce and manage landslide risk in the United States

The National Landslide Hazard Reduction Program is a coordinated Federal effort to reduce landslide risks and losses in the United States. Created in 2021 by the National Landslide Preparedness Act (“the Act”), the Program aims to bolster national capacity to (a) assess landslide hazard and risk, (b) coordinate landslide risk reduction activities, (c) prepare and plan for landslide impacts, and (d) respond to landslide events. The U.S. Geological Survey (USGS) is the lead Federal agency for Program implementation. To support implementation, the Act establishes two new coordination bodies: (1) The Interagency Coordinating Committee on Landslide Hazards (ICCLH), with representation from the USGS, National Weather Service, National Science Foundation, Federal Emergency Management Agency, U.S. Forest Service, Department of Transportation, U.S. Army Corps of Engineers, and other Federal partners; and (2) the Federal Advisory Committee on Landslides (ACL), composed of external advisors from state, Tribal, territorial, and local geological and emergency management organizations, academic institutions, and the private sector. The ICCLH ensures coordination of resources and activities across the many Federal agencies whose missions include landslide hazard and risk. The ACL provides advice and guidance on Program implementation to the USGS and its Federal partners, supporting Program effectiveness, transparency, and accountability. Complementary to these two groups, the new USGS-led National Landslide Hazard and Risk Reduction Work Group brings together local and regional practitioners to share best practices and develop common approaches to landslide hazard and risk management. This presentation will detail USGS efforts over the past 5 years to build a multi-level, multi-sector coordination structure to facilitate landslide loss reduction at a national scale. We will reflect on challenges and opportunities, share examples of successful interagency collaborations, and highlight next steps for the U.S. National Landslide Hazard Reduction Program.

Conference Paper↗

USGS2026

USGS Landslide Disaster Assistance Team (LDAT): Reducing risk through international partnerships

The U.S. Geological Survey (USGS) Landslide Disaster Assistance Team (LDAT) collaborates with international counterparts to reduce landslide risk through technical training and emergency response. LDAT assists foreign partners, upon request, with developing landslide mapping, monitoring and response products and protocols. LDAT draws from USGS scientists and partners with countries globally. LDAT is currently engaging in a range of technical assistance activities in Chile, El Salvador, Fiji, the Federated States of Micronesia (FSM), Guatemala, Peru, and Sri Lanka. In this extended abstract, three examples of recent international landslide collaborations are showcased for FSM and with the Ministerio de Medio Ambiente y Recursos Naturales (MARN) in El Salvador, and the Mineral Resources Department (MRD) in Fiji. These efforts range from USGS- produced landslide initiation and runout maps (FSM) to feedback on independently led efforts to create national susceptibility maps (El Salvador), to trainings focused on building in-country landslide technical programs (Fiji). The LDAT partnerships help foreign partners reduce risk from landslides. The partnerships also help USGS scientists develop important international relationships that foster collaboration and broader understanding of landslides, which help advance the domestic USGS mission of reducing landslide risks.

Chuuk, Kosrae, Pohnpei↗

USGS2025

Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning

Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km 2 (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.

California↗

USGS2025

Smectite-rich horizons in Inceptisols trigger shallow landslides in tropical granitic terranes

Puerto Rico was affected by >70,000 landslides in the wake of 2017 Hurricane Maria, and landslide prevalence was especially high in the Utuado region in the Cordillera Central. Landslide density was highest where soil parent material is granodiorite; landslide slip surfaces tended to be shallow (<60 cm), and often were mobilized rapidly and with long runout distances. This study combines field observations with soil mineralogy (bulk and clay fractions), soil geochemistry (bulk fraction), and soil strength as determined by field cone penetrometer testing (CPT) to test the hypothesis that clay-rich subsoil horizons function as slip planes when water-logged. Soil pits were excavated to depths of ∼200 cm in Ultisols on an undulating plateau and to ∼100 cm in Inceptisols on steep slopes (36-43 o ) that flank the plateau and cone penetrometer tests (CPT) were done within 2 m of the soil pit. Six pits were located adjacent to scarps from previous landslides, enabling analysis of soil profiles downward through extrapolated slip surfaces. Results from X-ray diffraction (XRD), X-ray fluorescence (XRF) and thermogravimetric analysis (TGA) indicate that soils are heterogeneous, often with subsoil horizons enriched in clay minerals and immobile elements (Al, Fe, Ti). Inceptisols on steep slopes often contain smectite-rich horizons at 30–60 cm depth that appear to function as slip surfaces; in other Inceptisols, such horizons are not present and landslide susceptibility is potentially lower. In Ultisols, soil mineralogy is dominated by kaolinite with minor halloysite, and increased kaolinite content at soil depths ≥80 cm at some sites suggests potential slip surfaces enhancing probability of landslides. The origin of clay-rich horizons appears to be (1) fractures in granodiorite that facilitate water flow and leaching, accelerating mineral dissolution during early weathering stages, and (2) smectite-rich buried soils under permeable colluvium likely deposited by a prior mass wasting event. Where clay-rich layers occur beneath more-permeable horizons, rapid infiltration then absorption of water in clay-rich subsoil horizons causes decreased shear strength and increased landslide susceptibility.

Puerto Rico↗

USGS2025

Cascading land surface hazards as a nexus in the Earth system

Earth’s surface is sculpted by numerous processes that move sediment, ranging from gradual and benign to abrupt and catastrophic. Although infrequent, high-magnitude sediment mobilization events can be hazardous to people and infrastructure, leaving topographic imprints on the landscape and remarkable narratives in the historical record. Hazardous events such as fires, storms, and earthquakes accelerate erosion and sediment transport, increasing landscape sensitivity to subsequent perturbations, thus forming a cascading hazard. Although the redistribution of sediment across Earth’s landscape can result in higher risks to vulnerable populations, cascading processes are commonly unaccounted for in hazard assessments. Cascading hazards can occur almost immediately after triggering events, such as coseismic landslides, or over months, years, or even decades after an initial perturbation, such as debris flows after wildfires or flooding in channels alluviated by volcanic debris. Sediment cascades span Earth’s surface, from mountaintops to river valleys, where erosion, deposition, and aggradation can lead to a myriad of hazardous processes, including decreased river conveyance capacity, which increases the likelihood of downstream flooding. An improved understanding of the magnitude, frequency, and persistence of cascading hazards is critical given the rapid changes in the frequency and severity of storms, fires, sea-level change, and cryospheric melting, as well as the expansion of high-population-density urban footprints in regions susceptible to solid Earth hazards. Understanding the full consequences and underlying physics of Earth’s cascading land surface hazards can help minimize future human and economic losses.

California↗

USGS2022

Multi-stage soil-hydraulic recovery and limited ravel accumulations following the 2017 Nuns and Tubbs wildfires in Northern California

Wildfire can impact soil-hydraulic properties by reducing saturated hydraulic conductivity and sorptivity, making recently burned landscapes prone to debris flows and flash floods. The post-fire hazard window can range from years to decades. In Northern California, where wildfire frequency is steadily increasing, the impact and soil-hydraulic recovery from wildfires is unknown. Following the October 2017 Nuns and Tubbs fires in the Northern Bay Area of California, we established 41 monitoring sites for repeat tension-disc infiltrometer measurements of field-saturated hydraulic conductivity ( K fs ) over 3.5 years. Our site arrays, which encompass grasslands, chaparral, and oak and conifer forests across a range in lithology, show a marked decrease in K fs following the wildfires and a swift partial recovery following the initial post-fire rainy season. Our time series reveals a complex path to soil-hydraulic recovery marked by distinct seasonal stages. Analysis of changing K fs , sorptivity, and infiltration model residuals collectively suggests that these stages are related to transitions between soil-hydraulic processes like structural soil sealing from rainsplash, thermal cracking of bare soil, and vegetation regrowth. While soil infiltration rates were strongly impacted by the 2017 fires, dry ravel estimates are an order of magnitude less for similar slopes than the 2009 Station fire in the San Gabriel mountains of Southern California, suggesting that limited ravel flux may insufficiently load channels for debris flows that initiate from within-channel failure. Our analysis suggests that burned landscapes in the Northern Bay Area of California may experience rapid soil-hydraulic recovery and limited pathways toward post-fire debris flow initiation.

California↗

USGS2021

Sediment budget for watersheds of West Maui, Hawaii

Episodic runoff brings suspended sediment to West Maui’s nearshore waters, turning them from blue to brown. This pollution degrades the ecological, cultural, and recreational value of these iconic nearshore waters. We used mapping, monitoring, and modeling to identify and quantify the watershed sources for fine sediment that pollutes the nearshore each year. These results focus strategies to reduce pollution on the outstanding sources for this sediment. Terrestrial runoff causing coastal plumes now occurs when two or more hours of rain falls at rates greater than 10–20 millimeter (mm) per hour in source watersheds. Analysis of recent and historical rainfall indicates that West Maui communities can expect rainfalls to bring coastal plumes at least 3–5 times per year. Former agricultural fields and some unimproved roads are possible sources for the fine sediment of these plumes. We found, however, that these obvious sources do not produce plumes during small annual storms, because they drain water at rates that far exceed most annual rainfalls and because there is no evidence for runoff from rains that caused recent plumes. Streambanks now eroding into historic fill terraces of sands, silts, and clays are a more plausible source. These terraces are found only downstream of historical agricultural fields and are composed of silt and fine sand. Surveys show that the fill terraces occupy ~40 percent of streambank length, making them extensive. During 2015–2016, these deposits eroded at median rates of 5–24 mm per year. Summed over West Maui’s watersheds, these rates imply sediment loads carried to the coast that can be ten times or more than modeled pre-human values. A sediment budget indicates that bank erosion of fill terraces from a few watersheds likely dominates the current annual fine-sediment load to the nearshore, with Kahana Stream watershed producing the largest annual input of 285 metric tons, the equivalent of 29 dump-truck loads every year. Although past large storms have contributed to sediment loading, annual plume generation is now caused by smaller rainfalls eroding these near-stream terrace deposits, a legacy of historic agriculture. Treatments of former agricultural fields, roads, and reserve forests are consequently not likely to measurably effect sediment pollution from smaller, more frequent storms. Increased runoff from residential and commercial development of West Maui has the potential to exacerbate sediment plumes from such storms.

Hawaii↗

USGS2020

Mobility characteristics of landslides triggered by Hurricane Maria in Puerto Rico

Mobility is an important element of landslide hazard and risk assessments yet has been seldom studied for shallow landslides and debris flows in tropical environments. In September 2017, Hurricane Maria triggered > 70,000 landslides across Puerto Rico. Using aerial imagery and a lidar digital elevation model (DEM), we mapped and characterized the mobility of debris slides and flows in four different geologic materials: (1) mudstone, siltstone, and sandstone; (2) submarine basalt and chert; (3) marine volcaniclastics; and (4) granodiorite. We used the ratio of landslide-fall height (H) to travel length (L), H/L, to assess the mobility of landslides in each material. Additionally, we differentiated between landslides with single and multiple source areas and landslides that either did or did not enter drainages. Overall, extreme rainfall contributed to the mobility of landslides during Hurricane Maria, and our results showed that the mobility of debris slides and flows in Puerto Rico increased linearly as a function of the number of source areas that coalesced. Additionally, landslides that entered drainages were more mobile than those that did not. We found that landslides in soils developed on marine volcaniclastics were the most mobile and landslides in soils on submarine basalt and chert were the least mobile. While landslides were generally small (< 100 m 2 ) and displayed a wide range of H/L values (0.1–2), coalescence increased the mobility of landslides that transitioned to debris flows. The high but variable mobility of landslides that occurred during Hurricane Maria and the associated hazards highlight the importance of characterizing and understanding the factors influencing landslide mobility in Puerto Rico and other tropical environments.

Puerto Rico↗

USGS2019

Where’s the rock: Using convolutional neural networks to improve land cover classification

While machine learning techniques have been increasingly applied to land cover classification problems, these techniques have not focused on separating exposed bare rock from soil covered areas. Therefore, we built a convolutional neural network (CNN) to differentiate exposed bare rock ( rock ) from soil cover ( other ). We made a training dataset by mapping exposed rock at eight test sites across the Sierra Nevada Mountains (California, USA) using USDA’s 0.6 m National Aerial Inventory Program (NAIP) orthoimagery. These areas were then used to train and test the CNN. The resulting machine learning approach classifies bare rock in NAIP orthoimagery with a 0.95 F 1 "> F 1 score. Comparatively, the classical OBIA approach gives only a 0.84 F 1 "> F 1 score. This is an improvement over existing land cover maps, which underestimate rock by almost 90%. The resulting CNN approach is likely scalable but dependent on high-quality imagery and high-performance algorithms using representative training sets informed by expert mapping. As image quality and quantity continue to increase globally, machine learning models that incorporate high-quality training data informed by geologic, topographic, or other topical maps may be applied to more effectively identify exposed rock in large image collections.

California↗

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

Dust on a Hawaiian volcano: A regional model using field measurements to estimate transport and deposition

The western slopes of Hawaii's Mauna Kea volcano are mantled by fine-grained soils, the record of volcanic airfall and eolian deposition. Where exposed, strong winds transport this sediment across West Hawaii, affecting tourism and local communities with decreased air and water quality. Operations on US Army's Ke'amuku Maneuver Area (KMA) have the potential to increase dust flux from these deposits. The USGS established 18 ground monitoring sites and sampling locations surrounding KMA. For over 3 years, each station measured vertical and horizontal dust flux, while co-located anemometers measured wind speed and direction. We used these datasets to develop a parsimonious regional model for dust supply and transport to assess whether KMA is a net dust sink or source. We found that dust transport is most highly correlated with threshold wind speeds of 8 m/s. We used this value as the regional average threshold wind speed for dust entrainment. Using a model that partitions measured horizontal dust flux into inward- and outward-directed components, we estimate that KMA is currently a net dust sink. Geochemical analysis of dust samples illustrates that local organics and carbonate make up 64% of dust mass, the remainder being volcanic silt and fine sand. Measured vertical dust deposition rates of 0.006 mm/yr are similar to 0.004 mm/yr of deposition predicted from taking the divergence of dust across KMA's boundary. These rates are low compared with pre-historic rates of ~0.2–0.3 mm/yr, from radiocarbon dating of buried soils. KMA's soils record persistent deposition over millennia, at rates that imply episodic dust storms. Such events created a soil-mantled landscape in the middle of a largely Pleistocene rocky landscape. A substantial portion of fine-grained soils in other leeward Hawaiian Island landscapes may have formed from similar eolian deposition, and not direct weathering of parent rock. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

Hawaii↗