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At least 433 records · Page 24Linked to original sources
USGS2013

Changes in population evacuation potential for tsunami hazards in Seward, Alaska, since the 1964 Good Friday earthquake

Pedestrian evacuation modeling for tsunami hazards typically focuses on current land-cover conditions and population distributions. To examine how post-disaster redevelopment may influence the evacuation potential of at-risk populations to future threats, we modeled pedestrian travel times to safety in Seward, Alaska, based on conditions before the 1964 Good Friday earthquake and tsunami disaster and on modern conditions. Anisotropic, path distance modeling is conducted to estimate travel times to safety during the 1964 event and in modern Seward, and results are merged with various population data, including the location and number of residents, employees, public venues, and dependent care facilities. Results suggest that modeled travel time estimates conform well to the fatality patterns of the 1964 event and that evacuation travel times have increased in modern Seward due to the relocation and expansion of port and harbor facilities after the disaster. The majority of individuals threatened by tsunamis today in Seward are employee, customer, and tourist populations, rather than residents in their homes. Modern evacuation travel times to safety for the majority of the region are less than wave arrival times for future tectonic tsunamis but greater than arrival times for landslide-related tsunamis. Evacuation travel times will likely be higher in the winter time, when the presence of snow may constrain evacuations to roads.

Alaska↗
USGS2025

Topographic controls on landslide mobility: Modeling hurricane-induced landslide runout and debris-flow inundation in Puerto Rico

In 2017, Hurricane Maria triggered more than 70 000 landslides in Puerto Rico. After initiation, these predominantly shallow landslides were mobilized to varying extents – some landslides only traveled partway downslope, whereas others reached drainage channels and were mobilized into long-traveled debris flows that could severely impact roads and infrastructure. Thus, forecasting potential landslide runout and inundation zones is critical for estimating landslide and debris-flow hazards. Here we conduct an in-depth topographic analysis of landslide-affected areas from nine study areas and apply a linked modeling technique to estimate locations susceptible to varying degrees of landslide runout in the Lares, Utuado, and Naranjito municipalities. We find that the longest runout lengths are observed on high-relief escarpments, although highly mobile long-runout debris flows also occurred in lower-relief dissected uplands. These topographic differences indicate that landslides that are initiated under similar conditions and possess equal potential to be mobilized as debris flows may not travel the same distances or affect the same areal extent. Our modeling approach allows the local topography to automatically control the implementation of two runout methods: (1) H/L runout zones are assigned directly downslope of landslide source zones, and (2) debris-flow inundation zones are estimated in the presence of a channel network. Debris-flow volumes are calculated as a function of area-integrated growth factors, estimated as a function of the upstream areas susceptible to shallow landslides. Applying our empirical modeling scheme over an area of 560 km 2 , our results highlight the efficacy of our methods for the assessment of the potential for landslide runout and debris-flow inundation over diverse terrains with varied susceptibility.

Puerto Rico↗
USGS2024

Characteristics of debris-flow-prone watersheds and debris-flow-triggering rainstorms following the Tadpole Fire, New Mexico, USA

Moderate- or high-severity fires promote increases in runoff and erosion, leading to a greater likelihood of extreme geomorphic responses, including debris flows. In the first several years following fire, the majority of debris flows initiate when runoff rapidly entrains sediment on steep slopes. From a hazard perspective, it is important to be able to anticipate when and where watershed responses will be dominated by debris flows rather than flood flows. Rainfall intensity averaged over a 15 min duration, I 15 , in particular, has been identified as a key predictor of debris flow likelihood. Developing effective warning systems and predictive models for post-fire debris flow hazards therefore relies on high-temporal resolution rainfall data at the time debris flows initiate. In this study, we documented the geomorphic response of a series of watersheds following a wildfire in western New Mexico, USA, with an emphasis on constraining debris flow timing within rainstorms to better characterize debris-flow-triggering rainfall intensities. We estimated temporal changes in soil hydraulic properties and ground cover in areas burned at different severities over >2 years to offer explanations for observed differences in spatial and temporal patterns in debris flow activity. We observed 16 debris flows, all of which initiated during the first several months following the fire. The average recurrence interval of the debris-flow-triggering I 15 is 1.3 years, which highlights the susceptibility of recently burned watersheds to runoff-generated debris flows in this region. All but one of the debris flows initiated in watersheds burned primarily at moderate or high soil burn severity. Since soil hydraulic properties appeared to be relatively resilient to burning, we attribute reduced debris flow activity at later times to decreases in the fraction of bare ground. Results provide additional constraints on the rainfall characteristics that promote post-fire debris flow initiation in a region where fire size and severity have been increasing.

New Mexico↗
USGS2012

Community variations in population exposure to near-field tsunami hazards as a function of pedestrian travel time to safety

Efforts to characterize population exposure to near-field tsunami threats typically focus on quantifying the number and type of people in tsunami-hazard zones. To develop and prioritize effective risk-reduction strategies, emergency managers also need information on the potential for successful evacuations and how this evacuation potential varies among communities. To improve efforts to properly characterize and differentiate near-field tsunami threats among multiple communities, we assess community variations in population exposure to tsunamis as a function of pedestrian travel time to safety. We focus our efforts on the multiple coastal communities in Grays Harbor and Pacific Counties (State of Washington, USA), where a substantial resident and visitor population is threatened by near-field tsunamis related to a potential Cascadia subduction zone earthquake. Anisotropic, path-distance modeling is conducted to estimate travel times to safety and results are merged with various population data, including residents, employees, public venues, and dependent-care facilities. Results suggest that there is substantial variability among communities in the number of people that may have insufficient time to evacuate. Successful evacuations may be possible in some communities assuming slow-walking speeds, are plausible in others if travel speeds are increased, and are unlikely in another set of communities given the large distances and short time horizon. Emergency managers can use these results to prioritize the location and determine the most appropriate type of tsunami risk-reduction strategies, such as education and training in areas where evacuations are plausible and vertical-evacuation structures in areas where they are not.

Washington↗
USGS2024

Evaluation of debris-flow building damage forecasts

Reliable forecasts of building damage due to debris flows may provide situational awareness and guide land and emergency management decisions. Application of debris-flow runout models to generate such forecasts requires combining hazard intensity predictions with fragility functions that link hazard intensity with building damage. In this study, we evaluated the performance of building damage forecasts for the 9 January 2018 Montecito postfire debris-flow runout event, in which over 500 buildings were damaged. We constructed forecasts using either peak debris-flow depth or momentum flux as the hazard intensity measure and applied each approach using three debris-flow runout models (RAMMS, FLO-2D, and D-Claw). Generated forecasts were based on averaging multiple simulations that sampled a range of debris-flow volume and mobility, reflecting typical sources and magnitude of pre-event uncertainty. We found that only forecasts made with momentum flux and the D-Claw model could correctly predict the observed number of damaged buildings and the spatial patterns of building damage. However, the best forecast only predicted 50 % of the observed damaged buildings correctly and had coherent spatial patterns of incorrectly predicted building damage (i.e., false positives and false negatives). These results indicate that forecasts made at the building level reliably reflect the spatial pattern of damage but do not support interpretation at the individual building level. We found the event size strongly influences the number of damaged buildings and the spatial pattern of debris-flow depth and velocity. Consequently, future research on the link between precipitation and the volume of sediment mobilized may have the greatest effect on reducing uncertainty in building damage forecasts. Finally, because we found that both depth and velocity are needed to predict building damage, comparing debris-flow models against spatially distributed observations of building damage is a more stringent test for model fidelity than comparison against the extent of debris-flow runout.

Natural Hazards and Earth System Sciences↗
USGS2011

Design and quantification of an extreme winter storm scenario for emergency preparedness and planning exercises in California

The USGS Multihazards Project is working with numerous agencies to evaluate and plan for hazards and damages that could be caused by extreme winter storms impacting California. Atmospheric and hydrological aspects of a hypothetical storm scenario have been quantified as a basis for estimation of human, infrastructure, economic, and environmental impacts for emergency-preparedness and flood-planning exercises. In order to ensure scientific defensibility and necessary levels of detail in the scenario description, selected historical storm episodes were concatentated to describe a rapid arrival of several major storms over the state, yielding precipitation totals and runoff rates beyond those occurring during the individual historical storms. This concatenation allowed the scenario designers to avoid arbitrary scalings and is based on historical occasions from the 19th and 20th Centuries when storms have stalled over the state and when extreme storms have arrived in rapid succession. Dynamically consistent, hourly precipitation, temperatures, barometric pressures (for consideration of storm surges and coastal erosion), and winds over California were developed for the so-called ARkStorm scenario by downscaling the concatenated global records of the historical storm sequences onto 6- and 2-km grids using a regional weather model of January 1969 and February 1986 storm conditions. The weather model outputs were then used to force a hydrologic model to simulate ARkStorm runoff, to better understand resulting flooding risks. Methods used to build this scenario can be applied to other emergency, nonemergency and non-California applications.

California↗
USGS2005

The seismic project of the National Tsunami Hazard Mitigation Program

In 1997, the Federal Emergency Management Agency (FEMA), National Oceanic and Atmospheric Administration (NOAA), U.S. Geological Survey (USGS), and the five western States of Alaska, California, Hawaii, Oregon, and Washington joined in a partnership called the National Tsunami Hazard Mitigation Program (NTHMP) to enhance the quality and quantity of seismic data provided to the NOAA tsunami warning centers in Alaska and Hawaii. The NTHMP funded a seismic project that now provides the warning centers with real-time seismic data over dedicated communication links and the Internet from regional seismic networks monitoring earthquakes in the five western states, the U.S. National Seismic Network in Colorado, and from domestic and global seismic stations operated by other agencies. The goal of the project is to reduce the time needed to issue a tsunami warning by providing the warning centers with high-dynamic range, broadband waveforms in near real time. An additional goal is to reduce the likelihood of issuing false tsunami warnings by rapidly providing to the warning centers parametric information on earthquakes that could indicate their tsunamigenic potential, such as hypocenters, magnitudes, moment tensors, and shake distribution maps. New or upgraded field instrumentation was installed over a 5-year period at 53 seismic stations in the five western states. Data from these instruments has been integrated into the seismic network utilizing Earthworm software. This network has significantly reduced the time needed to respond to teleseismic and regional earthquakes. Notably, the West Coast/Alaska Tsunami Warning Center responded to the 28 February 2001 Mw 6.8 Nisqually earthquake beneath Olympia, Washington within 2 minutes compared to an average response time of over 10 minutes for the previous 18 years. ?? Springer 2005.

Natural Hazards↗
USGS2006

Drainage effects on the transient, near-surface hydrologic response of a steep hillslope to rainfall: Implications for slope stability, Edmonds, Washington, USA

Shallow landslides on steep (>25??) hillsides along Puget Sound have resulted in occasional loss of life and costly damage to property during intense or prolonged rainfall. As part of a larger project to assess landslide hazards in the Seattle area, the U.S. Geological Survey instrumented two coastal bluff sites in 2001 to observe the subsurface hydrologic response to rainfall. The instrumentation at one of these sites, near Edmonds, Washington, consists of two rain gauges, two water-content probes that measure volumetric water content at eight depths between 0.2 and 2.0 m, and two tensiometer nests that measure soil-water suction at six depths ranging from 0.2 to 1.5m. Measurements from these instruments are used to test one- and two-dimensional numerical models of infiltration and groundwater flow. Capillary-rise tests, performed in the laboratory on soil sample from the Edmonds site, are used to define the soil hydraulic properties for the wetting process. The field observations of water content and suction show an apparent effect of porosity variation with depth on the hydraulic response to rainfall. Using a range of physical properties consistent with our laboratory and field measurements, we perform sensitivity analyses to investigate the effects of variation in physical and hydraulic properties of the soil on rainfall infiltration, pore-pressure response, and, hence, slope stability. For a two-layer-system in which the hydraulic conductivity of the upper layer is at least 10 times greater than the conductivity of the lower layer, and the infiltration rate is greater than the conductivity of the lower layer, a perched water table forms above the layer boundary potentially destabilizing the upper layer of soil. Two-dimensional modeling results indicate that the addition of a simple trench drain to the same two-layer slope has differing effects on the hydraulic response depending on the initial pressure head conditions. For slope-parallel flow conditions, pressure head is significantly reduced near the drain; however, for transient, vertical infiltration in a partially saturated soil, conditions consistent with those observed during monitoring at the Edmonds site, the drain decreases the thickness of a perched water table by a small amount.

Natural Hazards and Earth System Sciences↗
USGS2022

Flood resilience in paired US–Mexico border cities: A study of binational risk perceptions

Disastrous floods in the twin cities of Nogales, Arizona, USA, and Nogales, Sonora, Mexico (collectively referred to as Ambos Nogales) occur annually in response to monsoonal summer rains. Flood-related hazards include property damage, impairment to sewage systems, sewage discharge, water contamination, erosion, and loss of life. Flood risk, particularly in Nogales, Sonora, is amplified by informal, “squatter” settlements in the watershed floodplain and associated development and infrastructure. The expected increase in precipitation intensity, resulting from climate change, poses further risk to flooding therein. We explore binational community perceptions of flooding, preferences for watershed management, and potential actions to address flooding and increase socio-ecological resilience in Ambos Nogales using standardized questionnaires and interviews to collect data about people and their preferences. We conducted 25 semi-structured interviews with local subject matter experts and gathered survey responses from community members in Ambos Nogales. Though survey response was limited, expected frequencies were high enough to conduct Chi-squared tests of independence to test for statistically significant relationships between survey variables. Results showed that respondents with previous experience with flooding corresponded with their level of concern about future floods. Additionally, respondents perceived greater flood-related risks from traveling across town and damage to vehicles than from inundation or damages to their homes or neighborhoods. Binationally, women respondents felt less prepared for future floods than men. On both sides of the border, community members and local experts agreed that Ambos Nogales lacks adequate preparation for future floods. To increase preparedness, they recommended flood risk education and awareness campaigns, implementation of green infrastructure, additional stormwater infrastructure (such as drainage systems), enhanced flood early warning systems, and reduction of flood flows through regulations to reduce the expansion of hard surfaces. This study contributes systematic collection of information about flood risk perceptions across an international border, including novel data regarding risks related to climate change and gender-based assessments of flood risk. Our finding of commonalities across both border communities, in perceptions of flood risk and in the types of risk reduction solutions recommended by community members, provides clear directions for flood risk education, outreach, and preparedness, as well as measures to enhance cross-border cooperation.

Arizona, Sonora↗
USGS2023

Triggering conditions, runout, and downstream impacts of debris flows following the 2021 Flag Fire, Arizona, USA

Debris flows pose a serious threat to communities in mountainous areas, particularly in the years following wildfire. These events have been widely studied in regions where post-wildfire debris flows have been historically frequent, such as southern California. However, the threat of post-wildfire debris flows is increasing in many regions where detailed data on debris-flow physical properties, volume, and runout potential are sparse, such as the Southwest United States (US) (Arizona and New Mexico). As the Southwest becomes more vulnerable to these hazards, there is an increasing need to better characterize the properties of post-wildfire debris flows in this region and to identify similarities and differences with nearby areas, particularly southern California, where there is a greater abundance of data. In this paper, we study the characteristics and downstream impacts of two post-wildfire debris flows that initiated following the 2021 Flag Fire in northern Arizona, US. We gathered data regarding soil hydraulic properties, rainfall characteristics, watershed response, and debris-flow initiation, runout, volume, grain size, and downstream impacts during the first two monsoon seasons following the containment of the Flag Fire. We also applied established debris-flow runout and volume models that were developed in southern California to our study watershed and compared the output with observations. In the first monsoon season following the fire, there were two post-wildfire debris flows, one of which resulted in damage to downstream infrastructure, and one major flood event. We found that, while more intense rainfall was observed to generate debris flows at our study site compared to southern California, burned watersheds in northern Arizona are still susceptible to debris flows during storms with low recurrence intervals in the first year following fire. During the second monsoon season, there were no major runoff events, despite more intense storms. This indicates that the temporal window for heightened debris-flow susceptibility at our study area was less than one year, due to the recovery of soil hydraulic properties and vegetation regrowth. We also found that the debris-flow properties at our study site, such as volume, mobility, and grain size distribution, may differ from those in other regions in the western US, including southern California, potentially due to regional differences in rainfall characteristics and sediment supply. Differences in rainfall characteristics and sediment supply may have also influenced the performance of the debris-flow runout and volume models, which overpredicted the observed runout distance by 400 m and predicted a volume more than 17 times greater than what was observed.

Arizona↗
USGS2025

Constraining landslide frequency across the United States to inform county-level risk reduction

Informative landslide hazard estimates are needed to support landslide mitigation strategies to reduce landslide risk across the United States. Whereas existing national-scale landslide susceptibility products assess where landslides are likely to occur, they do not address how often , which is a critical element of landslide hazard and risk assessments. In particular, the U.S. Federal Emergency Management Agency's National Risk Index (NRI) requires landslide frequency estimates to inform expected annual loss estimates. We present county-level landslide frequency (landslides per area per year) estimates for the 50 US states. We applied Bayesian negative binomial regression to estimate both the expected (average) reported landslide frequency and full distribution of annual landslide counts for each county. We compared a suite of models that used combinations of landslide-susceptible area, probability of potentially triggering earthquakes, frequency of potentially triggering precipitation, and ecological region as predictors. We trained our models with landslide inventory data from counties with the most comprehensive records available nationwide and used zero-inflated negative binomial distributions as an incompleteness model to correct for temporal reporting gaps. We selected a preferred frequency model to inform the NRI based on information criteria and physically plausible parameter estimates. The model showed that average annual reported landslide frequencies vary by 5 orders of magnitude across US counties, ranging from 0.002 (0.00015–0.05) landslides 1000 km −2 yr −1 in Kusilvak Census Area, Alaska, to 29 (19–46) landslides 1000 km −2 yr −1 in Lake County, California, reflecting the country's strong variations in landslide susceptibility, earthquake probability, and other factors for which ecological region serves as a proxy. Counties with estimated frequencies in the top 20 % of all counties are predominately along the West Coast of the continental United States, in mountainous regions of the Pacific Northwest and Intermountain West, in locally steep or earthquake-prone regions of the Midwest and Southeast, along the Appalachians, in southern and southeastern Alaska, and on some Hawaiian islands. By examining the number of landslides predicted in 99th percentile years for each county, we identified that 26 % of US counties likely have potential for widespread landsliding with more than 10 landslides 1000 km −2 yr −1 , even when such large events have not been reported in the training data for that county. Overall, our results better represent the range of possible landslide frequencies and spatial variations than previous national-scale estimates reported in the NRI, and our approach can inform other risk-reduction and loss-mitigation efforts across the United States and globally.

Natural Hazards and Earth System Sciences↗
USGS2017

From data to decisions: Processing information, biases, and beliefs for improved management of natural resources and environments

Our different kinds of minds and types of thinking affect the ways we decide, take action, and cooperate (or not). Derived from these types of minds, innate biases, beliefs, heuristics, and values (BBHV) influence behaviors, often beneficially, when individuals or small groups face immediate, local, acute situations that they and their ancestors faced repeatedly in the past. BBHV, though, need to be recognized and possibly countered or used when facing new, complex issues or situations especially if they need to be managed for the benefit of a wider community, for the longer-term and the larger-scale. Taking BBHV into account, we explain and provide a cyclic science-infused adaptive framework for (1) gaining knowledge of complex systems and (2) improving their management. We explore how this process and framework could improve the governance of science and policy for different types of systems and issues, providing examples in the area of natural resources, hazards, and the environment. Lastly, we suggest that an “Open Traceable Accountable Policy” initiative that followed our suggested adaptive framework could beneficially complement recent Open Data/Model science initiatives.

Earth's Future↗
USGS2003

Conceptual model for transferring information between small watersheds

Stream and watershed management and restoration can be greatly facilitated through use of physiographic landform classification to organize and communicate natural resource, hazard, and environmental information at a broad scale (1:250,000) as illustrated by the Piedmont and Coastal Plain Provinces in Maryland, or at a small scale (1:24,000) as illustrated using divisions and zones combined with a conceptual model. The conceptual model brings together geology, surficial processes, landforms and land use change information at the small watershed scale and facilitates transfer of information from one small watershed to another with similar geology and landforms. Stream flow, sediment erosion, and water quality illustrate the use of the model.

Environmental Geology↗
USGS2006

Usoi dam wave overtopping and flood routing in the Bartang and Panj Rivers, Tajikistan

The Usoi dam was created in the winter of 1911 after an enormous seismogenic rock slide completely blocked the valley of the Bartang River in the Pamir Mountains of southeastern Tajikistan. At present the dam impounds 17 million cubic meters of water in Lake Sarez. Flood volume and discharge estimates were made for several landslide generated floods that could overtop the dam. For landslide volumes of 200, 500, and 1,000 million cubic meters, estimated overtopping flood volumes were 2, 22, and 87 million cubic meters of water, respectively. Estimated peak discharge at the dam for these three flood scenarios were 57,000, 490,000, and 1,580,000 m3/s, based on triangular hydrographs of 70-, 90-, and 110-s durations, respectively. Flood-routing simulations were made for the three landslide-induced overtopping floods over a 530-km reach of the Bartang and Panj Rivers below the Usoi dam. A one-dimensional flow model using a Riemann numerical solution technique was selected for the analysis. For the 87 million cubic meter volume overtopping flood scenario, the peak flows were approximately 1, 100, 800, and 550 m3/s at locations 50, 100, and 150 km downstream of the dam respectively. ?? Springer 2006.

Natural Hazards↗
USGS2007

Regularized joint inverse estimation of extreme rainfall amounts in ungauged coastal basins of El Salvador

A regularized joint inverse procedure is presented and used to estimate the magnitude of extreme rainfall events in ungauged coastal river basins of El Salvador: Paz, Jiboa, Grande de San Miguel, and Goascoran. Since streamflow measurements reflect temporal and spatial rainfall information, peak-flow discharge is hypothesized to represent a similarity measure suitable for regionalization. To test this hypothesis, peak-flow discharge values determined from streamflow recurrence information (10-year, 25-year, and 100-year) collected outside the study basins are used to develop regional (country-wide) regression equations. Peak-flow discharge derived from these equations together with preferred spatial parameter relations as soft prior information are used to constrain the simultaneous calibration of 20 tributary basin models. The nonlinear range of uncertainty in estimated parameter values (1 curve number and 3 recurrent rainfall amounts for each model) is determined using an inverse calibration-constrained Monte Carlo approach. Cumulative probability distributions for rainfall amounts indicate differences among basins for a given return period and an increase in magnitude and range among basins with increasing return interval. Comparison of the estimated median rainfall amounts for all return periods were reasonable but larger (3.2-26%) than rainfall estimates computed using the frequency-duration (traditional) approach and individual rain gauge data. The observed 25-year recurrence rainfall amount at La Hachadura in the Paz River basin during Hurricane Mitch (1998) is similar in value to, but outside and slightly less than, the estimated rainfall confidence limits. The similarity in joint inverse and traditionally computed rainfall events, however, suggests that the rainfall observation may likely be due to under-catch and not model bias. ?? Springer Science+Business Media B.V. 2007.

Natural Hazards↗
USGS2009

Community variations in social vulnerability to Cascadia-related tsunamis in the U.S. Pacific Northwest

Tsunamis generated by Cascadia subduction zone earthquakes pose significant threats to coastal communities in the U. S. Pacific Northwest. Impacts of future tsunamis to individuals and communities will likely vary due to pre-event socioeconomic and demographic differences. In order to assess social vulnerability to Cascadia tsunamis, we adjust a social vulnerability index based on principal component analysis first developed by Cutter et al. (2003) to operate at the census-block level of geography and focus on community-level comparisons along the Oregon coast. The number of residents from blocks in tsunami-prone areas considered to have higher social vulnerability varies considerably among 26 Oregon cities and most are concentrated in four cities and two unincorporated areas. Variations in the number of residents from census blocks considered to have higher social vulnerability in each city do not strongly correlate with the number of residents or city assets in tsunami-prone areas. Methods presented here will help emergency managers to identify community sub-groups that are more susceptible to loss and to develop risk-reduction strategies that are tailored to local conditions. ?? z.

Natural Hazards↗
USGS2010

Geomorphic and stratigraphic evidence for an unusual tsunami or storm a few centuries ago at Anegada, British Virgin Islands

Waters from the Atlantic Ocean washed southward across parts of Anegada, east-northeast of Puerto Rico, during a singular event a few centuries ago. The overwash, after crossing a fringing coral reef and 1.5 km of shallow subtidal flats, cut dozens of breaches through sandy beach ridges, deposited a sheet of sand and shell capped with lime mud, and created inland fields of cobbles and boulders. Most of the breaches extend tens to hundreds of meters perpendicular to a 2-km stretch of Anegada’s windward shore. Remnants of the breached ridges stand 3 m above modern sea level, and ridges seaward of the breaches rise 2.2–3.0 m high. The overwash probably exceeded those heights when cutting the breaches by overtopping and incision of the beach ridges. Much of the sand-and-shell sheet contains pink bioclastic sand that resembles, in grain size and composition, the sand of the breached ridges. This sand extends as much as 1.5 km to the south of the breached ridges. It tapers southward from a maximum thickness of 40 cm, decreases in estimated mean grain size from medium sand to very fine sand, and contains mud laminae in the south. The sand-and-shell sheet also contains mollusks—cerithid gastropods and the bivalve Anomalocardia—and angular limestone granules and pebbles. The mollusk shells and the lime-mud cap were probably derived from a marine pond that occupied much of Anegada’s interior at the time of overwash. The boulders and cobbles, nearly all composed of limestone, form fields that extend many tens of meters generally southward from limestone outcrops as much as 0.8 km from the nearest shore. Soon after the inferred overwash, the marine pond was replaced by hypersaline ponds that produce microbial mats and evaporite crusts. This environmental change, which has yet to be reversed, required restriction of a former inlet or inlets, the location of which was probably on the island’s south (lee) side. The inferred overwash may have caused restriction directly by washing sand into former inlets, or indirectly by reducing the tidal prism or supplying sand to post-overwash currents and waves. The overwash happened after A.D. 1650 if coeval with radiocarbon-dated leaves in the mud cap, and it probably happened before human settlement in the last decades of the 1700s. A prior overwash event is implied by an inland set of breaches. Hypothetically, the overwash in 1650–1800 resulted from the Antilles tsunami of 1690, the transatlantic Lisbon tsunami of 1755, a local tsunami not previously documented, or a storm whose effects exceeded those of Hurricane Donna, which was probably at category 3 as its eye passed 15 km to Anegada’s south in 1960.

Natural Hazards↗
USGS2010

Evaluation of TRIGRS (transient rainfall infiltration and grid-based regional slope-stability analysis)'s predictive skill for hurricane-triggered landslides: A case study in Macon County, North Carolina

The key to advancing the predictability of rainfall-triggered landslides is to use physically based slope-stability models that simulate the transient dynamical response of the subsurface moisture to spatiotemporal variability of rainfall in complex terrains. TRIGRS (transient rainfall infiltration and grid-based regional slope-stability analysis) is a USGS landslide prediction model, coded in Fortran, that accounts for the influences of hydrology, topography, and soil physics on slope stability. In this study, we quantitatively evaluate the spatiotemporal predictability of a Matlab version of TRIGRS (MaTRIGRS) in the Blue Ridge Mountains of Macon County, North Carolina where Hurricanes Ivan triggered widespread landslides in the 2004 hurricane season. High resolution digital elevation model (DEM) data (6-m LiDAR), USGS STATSGO soil database, and NOAA/NWS combined radar and gauge precipitation are used as inputs to the model. A local landslide inventory database from North Carolina Geological Survey is used to evaluate the MaTRIGRS’ predictive skill for the landslide locations and timing, identifying predictions within a 120-m radius of observed landslides over the 30-h period of Hurricane Ivan’s passage in September 2004. Results show that within a radius of 24 m from the landslide location about 67% of the landslide, observations could be successfully predicted but with a high false alarm ratio (90%). If the radius of observation is extended to 120 m, 98% of the landslides are detected with an 18% false alarm ratio. This study shows that MaTRIGRS demonstrates acceptable spatiotemporal predictive skill for landslide occurrences within a 120-m radius in space and a hurricane-event-duration (h) in time, offering the potential to serve as a landslide warning system in areas where accurate rainfall forecasts and detailed field data are available. The validation can be further improved with additional landslide information including the exact time of failure for each landslide and the landslide’s extent and run out length.

North Carolina↗