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At least 37 records · Page 2Linked to original sources

Reducing fatigue damage for ships in transit through structured decision making

Research in structural monitoring has focused primarily on drawing inference about the health of a structure from the structure’s response to ambient or applied excitation. Knowledge of the current state can then be used to predict structural integrity at a future time and, in principle, allows one to take action to improve safety, minimize ownership costs, and/or increase the operating envelope. While much time and effort has been devoted toward data collection and system identification, research to-date has largely avoided the question of how to choose an optimal maintenance plan. This work describes a structured decision making (SDM) process for taking available information (loading data, model output, etc.) and producing a plan of action for maintaining the structure. SDM allows the practitioner to specify his/her objectives and then solves for the decision that is optimal in the sense that it maximizes those objectives. To demonstrate, we consider the problem of a Naval vessel transiting a fixed distance in varying sea-state conditions. The physics of this problem are such that minimizing transit time increases the probability of fatigue failure in the structural supports. It is shown how SDM produces the optimal trip plan in the sense that it minimizes both transit time and probability of failure in the manner of our choosing (i.e., through a user-defined cost function). The example illustrates the benefit of SDM over heuristic approaches to maintaining the vessel.

Marine Structures↗

The importance of building construction materials relative to other factors affecting structure survival during wildfire

Structure loss to wildfire is a serious problem in wildland-urban interface areas across the world. Laboratory experiments suggest that fire-resistant building construction and design could be important for reducing structure destruction, but these need to be evaluated under real wildfire conditions, especially relative to other factors. Using empirical data from destroyed and surviving structures from large wildfires in southern California, we evaluated the relative importance of building construction and structure age compared to other local and landscape-scale variables associated with structure survival. The local-scale analysis showed that window preparation was especially important but, in general, creating defensible space adjacent to the home was as important as building construction. At the landscape scale, structure density and structure age were the two most important factors affecting structure survival, but there was a significant interaction between them. That is, young structure age was most important in higher-density areas where structure survival overall was more likely. On the other hand, newer-construction structures were less likely to survive wildfires at lower density. Here, appropriate defensible space near the structure and accessibility to major roads were important factors. In conclusion, community safety is a multivariate problem that will require a comprehensive solution involving land use planning, fire-safe construction, and property maintenance.

International Journal of Disaster Risk Reduction↗

Resilience of Alaska’s boreal forest to climatic change

This paper assesses the resilience of Alaska’s boreal forest system to rapid climatic change. Recent warming is associated with reduced growth of dominant tree species, plant disease and insect outbreaks, warming and thawing of permafrost, drying of lakes, increased wildfire extent, increased postfire recruitment of deciduous trees, and reduced safety of hunters traveling on river ice. These changes have modified key structural features, feedbacks, and interactions in the boreal forest, including reduced effects of upland permafrost on regional hydrology, expansion of boreal forest into tundra, and amplification of climate warming because of reduced albedo (shorter winter season) and carbon release from wildfires. Other temperature-sensitive processes for which no trends have been detected include composition of plant and microbial communities, long-term landscape-scale change in carbon stocks, stream discharge, mammalian population dynamics, and river access and subsistence opportunities for rural indigenous communities. Projections of continued warming suggest that Alaska’s boreal forest will undergo significant functional and structural changes within the next few decades that are unprecedented in the last 6000 years. The impact of these social–ecological changes will depend in part on the extent of landscape reorganization between uplands and lowlands and on policies regulating subsistence opportunities for rural communities.

Alaska↗

Hazard analysis of landslides triggered by Typhoon Chata’an on July 2, 2002, in Chuuk State, Federated States of Micronesia

More than 250 landslides were triggered across the eastern volcanic islands of Chuuk State in the Federated States of Micronesia by torrential rainfall from tropical storm Chata’an on July 2, 2002. Landslides triggered during nearly 20 inches of rainfall in less than 24 hours caused 43 fatalities and the destruction or damage of 231 structures, including homes, schools, community centers, and medical dispensaries. Landslides also buried roads, crops, and water supplies. The landslides ranged in volume from a few cubic meters to more than 1 million cubic meters. Most of the failures began as slumps and transformed into debris flows, some of which traveled several hundred meters across coastal flatlands into populated areas. A landslide-inventory map produced after the storm shows that the island of Tonoas had the largest area affected by landslides, although the islands of Weno, Fefan, Etten, Uman, Siis, Udot, Eot, and Fanapanges also had significant landslides. Based on observations since the storm, we estimate the continuing hazard from landslides triggered by Chata’an to be relatively low. However, tropical storms and typhoons similar to Chata’an frequently develop in Micronesia and are likely to affect the islands of Chuuk in the future. To assess the landslide hazard from future tropical storms, we produced a hazard map that identifies landslide-source areas of high, moderate, and low hazard. This map can be used to identify relatively safe areas for relocating structures or establishing areas where people could gather for shelter in relative safety during future typhoons or tropical storms similar to Chata’an.

Chuuk State↗

Developments in seismic monitoring for risk reduction

This paper presents recent state-of-the-art developments to obtain displacements and drift ratios for seismic monitoring and damage assessment of buildings. In most cases, decisions on safety of buildings following seismic events are based on visual inspections of the structures. Real-time instrumental measurements using GPS or double integration of accelerations, however, offer a viable alternative. Relevant parameters, such as the type of connections and structural characteristics (including storey geometry), can be estimated to compute drifts corresponding to several pre-selected threshold stages of damage. Drift ratios determined from real-time monitoring can then be compared to these thresholds in order to estimate damage conditions drift ratios. This approach is demonstrated in three steel frame buildings in San Francisco, California. Recently recorded data of strong shaking from these buildings indicate that the monitoring system can be a useful tool in rapid assessment of buildings and other structures following an earthquake. Such systems can also be used for risk monitoring, as a method to assess performance-based design and analysis procedures, for long-term assessment of structural characteristics of a building, and as a possible long-term damage detection tool.

Journal of Risk Research↗

Real-time seismic monitoring of structures: Data handling and case studies

Within the last decade, advances in the acquisition, processing and transmission of data from real-time seismic monitoring systems has contributed to the growth in the number structures instrumented with such systems. An equally important factor for such growth can be attributed to the demands by stakeholders to find rapid answers to important questions related to the functionality (or “state of health”) of structures during and immediately following a seismic event. Hence, rapid and accurate assessment of the damage condition or performance of a building or a lifeline structure is of paramount importance to stakeholders, including owners, leasers, permanent and/or temporary occupants, users of infrastructures, city officials and rescue teams that are concerned with safety of those in the building, and those that may be affected in nearby buildings and infrastructures. In earlier papers, we described how observed data from sensors deployed in structures can be configured to establish seismic health monitoring of structures. In these configurations, drift ratios are the main parametric indicator of damage condition of a building. The process described for buildings can be applied directly for bridges as well. For bridges, the term, “drift ratio” is not generally used; however, relative displacements of critical elements of a bridge can be construed as such. While real-time data from structural arrays indicate that these methods are reliable and provide requisite information for owners and other parties to make informed decisions and to choose among pre-defined actions following significant events, there are several issues related to data ownership, transmission and archiving. This paper examines the real-time seismic monitoring systems deployed mainly in the United States, with particular attention to data issues – handling, dissemination, storage, and archiving. In most cases, due to the numerous channels involved, the deployments in each one of the real-time structures can be considered to be an individual array. Two detailed cases are described that demonstrate the variability in data ownership and dissemination.

Book chapter↗

The Pedestrian Evacuation Analyst: geographic information systems software for modeling hazard evacuation potential

Recent disasters such as the 2011 Tohoku, Japan, earthquake and tsunami; the 2013 Colorado floods; and the 2014 Oso, Washington, mudslide have raised awareness of catastrophic, sudden-onset hazards that arrive within minutes of the events that trigger them, such as local earthquakes or landslides. Due to the limited amount of time between generation and arrival of sudden-onset hazards, evacuations are typically self-initiated, on foot, and across the landscape (Wood and Schmidtlein, 2012). Although evacuation to naturally occurring high ground may be feasible in some vulnerable communities, evacuation modeling has demonstrated that other communities may require vertical-evacuation structures within a hazard zone, such as berms or buildings, if at-risk individuals are to survive some types of sudden-onset hazards (Wood and Schmidtlein, 2013). Researchers use both static least-cost-distance (LCD) and dynamic agent-based models to assess the pedestrian evacuation potential of vulnerable communities. Although both types of models help to understand the evacuation landscape, LCD models provide a more general overview that is independent of population distributions, which may be difficult to quantify given the dynamic spatial and temporal nature of populations (Wood and Schmidtlein, 2012). Recent LCD efforts related to local tsunami threats have focused on an anisotropic (directionally dependent) path distance modeling approach that incorporates travel directionality, multiple travel speed assumptions, and cost surfaces that reflect variations in slope and land cover (Wood and Schmidtlein, 2012, 2013). The Pedestrian Evacuation Analyst software implements this anisotropic path-distance approach for pedestrian evacuation from sudden-onset hazards, with a particular focus at this time on local tsunami threats. The model estimates evacuation potential based on elevation, direction of movement, land cover, and travel speed and creates a map showing travel times to safety (a time map) throughout a hazard zone. Model results provide a general, static view of the evacuation landscape at different pedestrian travel speeds and can be used to identify areas outside the reach of naturally occurring high ground. In addition, data on the size and location of different populations within the hazard zone can be integrated with travel-time maps to create tables and graphs of at-risk population counts as a function of travel time to safety. As a decision-support tool, the Pedestrian Evacuation Analyst provides the capability to evaluate the effectiveness of various vertical-evacuation structures within a study area, both through time maps of the modeled travel-time landscape with a potential structure in place and through comparisons of population counts within reach of safety. The Pedestrian Evacuation Analyst is designed for use by researchers examining the pedestrian-evacuation potential of an at-risk community. In communities where modeled evacuation times exceed the event (for example, tsunami wave) arrival time, researchers can use the software with emergency managers to assess the area and population served by potential vertical-evacuation options. By automating and managing the modeling process, the software allows researchers to concentrate efforts on providing crucial and timely information on community vulnerability to sudden-onset hazards.

Techniques and Methods↗

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↗

Seismic reflection characteristics of naturally-induced subsidence affecting transportation

High-resolution seismic reflections have been used effectively to investigate sinkholes formed from the dissolution of a bedded salt unit found throughout most of Central Kansas. Surface subsidence can have devastating effects on transportation structures. Roads, rails, bridges, and pipelines can even be dramatically affected by minor ground instability. Areas susceptible to surface subsidence can put public safety at risk. Subsurface expressions significantly larger than surface depressions are consistently observed on seismic images recorded over sinkholes in Kansas. Until subsidence reaches the ground surface, failure appears to be controlled by compressional forces evidenced by faults with reverse orientation. Once a surface depression forms or dissolution of the salt slows or stops, subsidence structures are consistent with a tensional stress environment with prevalent normal faults. Detecting areas of rapid subsidence potential, prior to surface failure, is the ultimate goal of any geotechnical survey where the ground surface is susceptible to settling. Seismic reflection images have helped correlate active subsidence to dormant paleofeatures, project horizontal growth of active sinkholes based on subsurface structures, and appraise the risk of catastrophic failure. ?? China University of Geosciences (Wuhan) and Springer-Verlag GmbH 2009.

Conference Paper↗

GPS in pioneering dynamic monitoring of long-period structures

Global Positioning System (GPS) technology with 10-20-Hz sampling rates allows scientifically justified dynamic measurements of relative displacements of long-period structures. The displacement response of a simulated tall building in real time and permanent deployment of GPS units at the roof of a building are described. To the authors' best knowledge, this is the first permanent deployment of GPS units (in the world) for continuous dynamic monitoring of a tall building. Data recorded from the building during a windy day is analyzed to determine the structural characteristics. When recorded during extreme motions caused by earthquakes and strong winds, such measurements can be used to compute average drift ratios and changes in dynamic characteristics, and therefore can be used by engineers and building owners or managers to assess the structural integrity and performance by establishing pre-established thresholds. Such information can be used to secure public safety and/or take steps to improve the performance of the building.

Earthquake Spectra↗

UCERF3: A new earthquake forecast for California's complex fault system

With innovations, fresh data, and lessons learned from recent earthquakes, scientists have developed a new earthquake forecast model for California, a region under constant threat from potentially damaging events. The new model, referred to as the third Uniform California Earthquake Rupture Forecast, or "UCERF" ( http://www.WGCEP.org/UCERF3 ), provides authoritative estimates of the magnitude, location, and likelihood of earthquake fault rupture throughout the state. Overall the results confirm previous findings, but with some significant changes because of model improvements. For example, compared to the previous forecast (Uniform California Earthquake Rupture Forecast 2), the likelihood of moderate-sized earthquakes (magnitude 6.5 to 7.5) is lower, whereas that of larger events is higher. This is because of the inclusion of multifault ruptures, where earthquakes are no longer confined to separate, individual faults, but can occasionally rupture multiple faults simultaneously. The public-safety implications of this and other model improvements depend on several factors, including site location and type of structure (for example, family dwelling compared to a long-span bridge). Building codes, earthquake insurance products, emergency plans, and other risk-mitigation efforts will be updated accordingly. This model also serves as a reminder that damaging earthquakes are inevitable for California. Fortunately, there are many simple steps residents can take to protect lives and property.

California↗

Oregon OCS seafloor mapping: Selected lease blocks relevant to renewable energy

In 2014 the U.S. Geological Survey (USGS) and the Bureau of Ocean Energy Management (BOEM) entered into Intra-agency agreement M13PG00037 to map an area of the Oregon Outer Continental Shelf (OCS) off of Coos Bay, Oregon, under consideration for development of a floating wind energy farm. The BOEM requires seafloor mapping and site characterization studies in order to evaluate the impact of seafloor and sub-seafloor conditions on the installation, operation, and structural integrity of proposed renewable energy projects, as well as to assess the potential effects of construction and operations on archaeological resources. The mission of the USGS is to provide geologic, topographic, and hydrologic information that contributes to the wise management of the Nation's natural resources and that promotes the health, safety, and well being of the people. This information consists of maps, databases, and descriptions and analyses of the water, energy, and mineral resources, land surface, underlying geologic structure, and dynamic processes of the earth. For the Oregon OCS study, the USGS acquired multibeam echo sounder and seafloor video data surrounding the proposed development site, which is 95 km2 in area and 15 miles offshore from Coos Bay. The development site had been surveyed by Solmar Hydro Inc. in 2013 under a contract with WindFloat Pacific. The USGS subsequently produced a bathymetry digital elevation model and a backscatter intensity grid that were merged with existing data collected by the contractor. The merged grids were published along with visual observations of benthic geo-habitat from the video data in an associated USGS data release (Cochrane and others, 2015). This report includes the results of analysis of the video data conducted by Oregon State University and the geo-habitat interpretation of the multibeam echo sounder (MBES) data conducted by the USGS. MBES data was published in Cochrane and others (2015). Interpretive data associated with this publication is published in Cochrane (2017). All the data is provided as geographic information system (GIS) files that contain both Esri ArcGIS geotiffs or shapefiles. For those who do not own the full suite of Esri GIS and mapping software, the data can be read using Esri ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed August 29, 2016). Web services, which consist of standard implementations of ArcGIS representational state transfer (REST) Service and Open Geospatial Consortium (OGC) GIS web map service (WMS), also are available for all published GIS data. Web services were created using an ArcGIS service definition file, resulting in data layers that are symbolized as shown on the associated report figures. Both the ArcGIS REST Service and OGC WMS Service include all the individual GIS layers. Data layers are bundled together in a map-area web service; however, each layer can be symbolized and accessed individually after the web service is ingested into a desktop application or web map. Web services enable users to download and view data, as well as to easily add data to their own workflows, using any browser-enabled, standalone or mobile device. Though the surficial substrate is dominated by combinations of mud and sand substrate, a diverse assortment of geomorphologic features are related to geologic processes—one anticlinal ridge where bedrock is exposed, a slump and associated scarps, and pockmarks. Pockmarks are seen in the form of fields of small pockmarks, a lineation of large pockmarks with methanogenic carbonates, and areas of large pockmarks that have merged into larger variously shaped depressions. The slump appears to have originated at the pockmark lineation. Video-supervised numerical analysis of the MBES backscatter intensity data and vector ruggedness derived from the MBES bathymetry data was used to produce a substrate model called a seafloor character raster for the study area. The seafloor character raster consists of three substrate classes: soft-flat areas, hard-flat areas, and hard-rugged areas. A Coastal and Marine Ecological Classification Standard (CMECS) geoform and substrate map was also produced using depth, slope, and benthic position index classes to delineate geoform boundaries. Seven geoforms were identified in this process, including ridges, slump scars, slump deposits, basins, and pockmarks. Statistical analysis of the video data for correlations between substrate, depth, and invertebrate assemblages resulted in the identification of seven biomes: three hard-bottom biomes and four softbottom biomes. A similar analysis of vertebrate observations produces a similar set of biomes. The biome between-group dissimilarity was very high or high. Invertebrates alone represent most of the structure of the whole benthic community into different assemblages. A biotope map was generated using the seafloor character raster and the substrate and depth values of the biomes. Hard substrate biotopes were small in size and were located primarily on the ridge and in pockmarks along the pockmark lineation. The soft-bottom bitopes consisted of large contiguous areas delimited by isobaths.

Open-File Report↗

Time for an updated macroseismic scale

Macroseismology plays a crucial role in earthquake hazard and risk analyses, linking past earthquake occurrences and impacts with those of the present and future. The popularity of internet-based community contributions and the usefulness of intensities for communicating seismic hazards, early warning, and impacts to the public have all bolstered the use of macroseismology beyond its traditional utility in characterizing sources and shaking from historical and modern earthquakes (Wald et al., 2023). Nevertheless, many modern approaches for collecting building damage data and assigning macroseismic intensities suffer limitations. Many countries do not or no longer routinely collect such data, and even after significant and even catastrophic earthquakes, building damage data are often not collected or shared systematically, nor are field-based macroseismic intensities professionally assigned. Additionally, the United States (U.S.), Canada, and other nations still use variations of the Modified Mercalli Intensity (MMI) scale (Wood and Neumann, 1931) for assigning macroseismic intensities. At nearly 100 years old, the MMI scale predates most modern building types. As a result, the scale is silent about and blind to building damage that now matters to most domestic occupants. It says nothing about single- or multi-unit wood-frame buildings, the predominant type of residential structure in the US and Canada, whose damage is a particularly important indicator of shaking intensity, nor about the collapse or safety of modern building types. Importantly, the dependence on the U.S. Geological Survey’s “Did You Feel It?” (DYFI) for domestic intensity data collection limits their accuracy type at higher, damaging intensity levels, where attention to building type is requisite. The MMI and some of its widely used variants are often poorly documented; there is no official version, nor is it even clear which version of the scale was employed in many studies (Musson, 2002). The MMI scale is consistent with—but is more limited than—the 1998 European Macroseismic Scale (EMS-98, Grünthal, 1998). The new International Macroseismic Scale of 2025 (IMS-25; Grünthal et al., 2025) builds on EMS-98—a well-documented, modern scale already widely used in Europe and well beyond. IMS-25 further expands EMS-98 internationally by enhancing the EMS-98 vulnerability table and damage grade collections to include more worldwide building types and their evolving design codes. Because the IMS requires well-defined vulnerability classes and damage grades specific to various structural types, its worldwide adoption will help unify post-event data collection on building damage. Similarly, the IMS requires statistical analyses of damage levels for specific structural types, ensuring that building damage sampling is sufficient for other important engineering analyses, such as the derivation of fragility functions, calibration of loss models, and the assessment of losses and damages after significant events

Seismological Research Letters↗

Map depicting locations susceptible to landslide hazards triggered by prolonged intense rainfall, Utuado Municipio, Puerto Rico

Introduction Landslides commonly occur in Puerto Rico during or soon after rainstorms with prolonged intense rainfall. Rainfall-triggered landslides present significant hazards to the built environment and human safety (for example, Jibson, 1986; Larsen and Torres Sanchez, 1992; Bessette-Kirton and others, 2019a). These hazards were illustrated during September 2017 (Hughes and others, 2019) when Hurricane María triggered more than 70,000 landslides across Puerto Rico (fig. 1), causing loss of life and widespread destruction (figs. 2–4). In Utuado Municipio, about 18,000 landslides were observed after Hurricane María (Hughes and others, 2019). Most intense rainfall-triggered landslides in Puerto Rico occur in soil overlying bedrock and travel downslope from where they initiate (for example, Jibson, 1986; Bessette-Kirton and others, 2019a, 2020). Hazards to human life and infrastructure can differ substantially between where landslides initiate and where they travel. At landslide initiation locations, the ground breaks up (fails) as it moves downslope, removing support for buildings, roadways, and other structures located upon the landslides (fig. 3A, B). This ground failure often causes structures to collapse and suffer severe damage or complete destruction, rendering building occupants at extreme risk. Roadways and other vital infrastructure, such as water, power, and communication lines, are often severed. During intense rainfall events, landslide initiation and movement downslope can occur in seconds to hours. Downslope from where they initiate, landslides in Puerto Rico often move very rapidly (faster than a person can walk or run) and can impact and destroy or fill structures with mud and debris (fig. 4) as well as bury roadways (fig. 3A, C). Moving landslides present extreme hazards to human safety; some fatalities during Hurricane María resulted from mud and debris that flowed through windows and doors of a home and buried occupants. Many landslides in Puerto Rico become fast-moving liquefied masses (debris flows), which are especially common in channels where they can quickly travel kilometers downstream. Multiple debris flows may occur in a channel during a single rainstorm (some channels experienced more than 50 debris flows during Hurricane María; Bessette-Kirton and others [2020] ). This hazard map separately depicts locations and the relative likelihood of where landslides may initiate, where they may move downslope, and where channelized debris flows may travel during or soon after intense rainfall like that during Hurricane María. An estimated average of 399 millimeters of rainfall fell across Utuado during September 19–21, 2017 (Ramos-Scharrón and Arima, 2019). Lower rainfall amounts, durations, and intensities also trigger landsliding in Puerto Rico, although landslides and debris flows become more numerous as rainfall intensities, durations, and cumulative amounts increase. The map does not show potential landslide locations in the karst terrain of northern Utuado (Bawiec, 1999) because Hurricane María-induced landslides were very sparse in this region (Hughes and others, 2019; Baxstrom and others, 2021a), even though rainfall amounts were similar to those in other parts of Utuado. Based on data from Hughes and others (2019), landslides were about 10 times more likely to occur outside of the karst terrane than within it, and our preliminary analyses indicated relatively low susceptibility to rainfall-induced landslide hazards within the karst. Landslide-prone soils appear to be poorly developed on the very steep slopes present in the karst region, where weathering by dissolution appears to dominate.

Puerto Rico, Utuado Municipio↗

Map depicting locations susceptible to landslide hazards triggered by prolonged intense rainfall, Lares Municipio, Puerto Rico

Introduction Landslides commonly occur in Puerto Rico during or soon after rainstorms with prolonged intense rainfall. Rainfall-triggered landslides present significant hazards to the built environment and human safety (for example, Jibson, 1986; Larsen and Torres Sanchez, 1992; Bessette-Kirton and others, 2019a). These hazards were illustrated during September 2017 (Hughes and others, 2019), when Hurricane María triggered more than 70,000 landslides across Puerto Rico (fig. 1), causing loss of life and widespread destruction (figs. 2 and 3). In Lares Municipio, about 3,500 landslides were observed after Hurricane María (Hughes and others, 2019). Most intense-rainfall-triggered landslides in Puerto Rico occur in soil overlying bedrock and travel downslope from where they initiated (for example, Jibson, 1986; Bessette-Kirton and others, 2019a; 2020). Hazards to human life and infrastructure can differ substantially between where landslides initiate and where they travel. At landslide initiation locations, the ground breaks up (fails) as it moves downslope, removing support for buildings, roadways, and other structures located upon the landslides (figs. 2, 3A, B). This ground failure often causes structures to collapse and suffer severe damage or complete destruction, rendering building occupants at extreme risk. Roadways and other vital infrastructure, such as water, power, and communication lines are often severed. During intense rainfall events, landslide initiation and movement downslope can occur in seconds to hours. Downslope from where they initiate, landslides in Puerto Rico often move, or runout, very rapidly (faster than a person can walk or run) and can impact and destroy or fill structures with mud and debris (figs. 3A, C) as well as bury roadways (fig. 3A). Moving landslides present extreme hazards to human safety; some fatalities during Hurricane María resulted from mud and debris that flowed through windows and doors of a home and buried occupants. Many landslides in Puerto Rico become fast-moving debris flows, which are especially common in channels where they can quickly travel kilometers downstream. Multiple debris flows may occur in a channel during a single rainstorm (some channels experienced more than 50 debris flows during Hurricane María; Bessette-Kirton and others, 2020). This map separately depicts locations and the relative likelihood of where landslides may initiate, where they may move downslope, and where channelized debris flows may travel during or soon after intense rainfall like that during Hurricane María. An estimated average of 256 millimeters of rainfall fell across Lares during September 19–21, 2017 (Ramos-Scharrón and Arima, 2019). Lower rainfall amounts, durations, and intensities also trigger landsliding in Puerto Rico, although landslides and debris flows become more numerous as rainfall intensities, durations, and cumulative amounts increase. The map does not show potential landslide locations in the karst terrain of northern Lares (Bawiec, 1999) because Hurricane María-induced landslides were very sparse in this region (Hughes and others, 2019; Baxstrom and others, 2021a), even though rainfall amounts were similar to those in other parts of Lares. Based on data from Hughes and others (2019), landslides were about ten times more likely to occur outside of the karst terrane than within it, and our preliminary analyses indicate relatively low susceptibility to rainfall-induced landslide hazards within the karst. Landslide-prone soils appear to be poorly developed on the very steep slopes present in the karst region, where weathering by dissolution appears to dominate.

Lares Municipio, Puerto Rico↗

Incorporating road crossing data into vehicle collision risk models for moose (Alces americanus) in Massachusetts, USA

Wildlife–vehicle collisions are a human safety issue and may negatively impact wildlife populations. Most wildlife–vehicle collision studies predict high-risk road segments using only collision data. However, these data lack biologically relevant information such as wildlife population densities and successful road-crossing locations. We overcome this shortcoming with a new method that combines successful road crossings with vehicle collision data, to identify road segments that have both high biological relevance and high risk. We used moose ( Alces americanus ) road-crossing locations from 20 moose collared with Global Positioning Systems as well as moose–vehicle collision (MVC) data in the state of Massachusetts, USA, to create multi-scale resource selection functions. We predicted the probability of moose road crossings and MVCs across the road network and combined these surfaces to identify road segments that met the dual criteria of having high biological relevance and high risk for MVCs. These road segments occurred mostly on larger roadways in natural areas and were surrounded by forests, wetlands, and a heterogenous mix of land cover types. We found MVCs resulted in the mortality of 3% of the moose population in Massachusetts annually. Although there have been only three human fatalities related to MVCs in Massachusetts since 2003, the human fatality rate was one of the highest reported in the literature. The rate of MVCs relative to the size of the moose population and the risk to human safety suggest a need for road mitigation measures, such as fencing, animal detection systems, and large mammal-crossing structures on roadways in Massachusetts.

Massachusetts↗

Method for detecting moment connection fracture using high-frequency transients in recorded accelerations

The 1994 Northridge earthquake caused brittle fractures in steel moment frame building connections, despite causing little visible building damage in most cases. Future strong earthquakes are likely to cause similar damage to the many un-retrofitted pre-Northridge buildings in the western US and elsewhere. Without obvious permanent building deformation, costly intrusive inspections are currently the only way to determine if major fracture damage that compromises building safety has occurred. Building instrumentation has the potential to provide engineers and owners with timely information on fracture occurrence. Structural dynamics theory predicts and scale model experiments have demonstrated that sudden, large changes in structure properties caused by moment connection fractures will cause transient dynamic response. A method is proposed for detecting the building-wide level of connection fracture damage, based on observing high-frequency, fracture-induced transient dynamic responses in strong motion accelerograms. High-frequency transients are short (<1 s), sudden-onset waveforms with frequency content above 25 Hz that are visually apparent in recorded accelerations. Strong motion data and damage information from intrusive inspections collected from 24 sparsely instrumented buildings following the 1994 Northridge earthquake are used to evaluate the proposed method. The method’s overall success rate for this data set is 67%, but this rate varies significantly with damage level. The method performs reasonably well in detecting significant fracture damage and in identifying cases with no damage, but fails in cases with few fractures. Combining the method with other damage indicators and removing records with excessive noise improves the ability to detect the level of damage.

Journal of Constructional Steel Research↗

Map depicting locations susceptible to landslide hazards triggered by prolonged intense rainfall, Naranjito Municipio, Puerto Rico

Introduction Landslides commonly occur in Puerto Rico during or soon after rainstorms with prolonged intense rainfall. Rainfall-triggered landslides present significant hazards to the built environment and human safety (for example, Jibson, 1986; Larsen and Torres Sanchez, 1992; Bessette-Kirton and others, 2019a). These hazards were illustrated during September 2017 (Hughes and others, 2019), when Hurricane María triggered more than 70,000 landslides across Puerto Rico (fig. 1), causing loss of life and widespread destruction (figs. 2–4). In Naranjito Municipio, about 2,000 landslides were observed after Hurricane María (Hughes and others, 2019). Most intense-rainfall-triggered landslides in Puerto Rico occur in soil overlying bedrock and travel downslope from where they initiated (for example, Jibson, 1986; Bessette-Kirton and others, 2019a; 2020). Hazards to human life and infrastructure can differ substantially between where landslides initiate and where they travel. At landslide initiation locations, the ground breaks up (fails) as it moves downslope, removing support for buildings, roadways, and other structures located upon the landslides (figs. 3B, 4A, B). This ground failure often causes structures to collapse and suffer severe damage or complete destruction, rendering building occupants at extreme risk. Roadways and other vital infrastructure, such as water, power, and communication lines are often severed. During intense rainfall events, landslide initiation and movement downslope can occur in seconds to hours. Downslope from where they initiate, landslides in Puerto Rico often move, or runout, very rapidly (faster than a person can walk or run) and can impact and destroy or fill structures with mud and debris (figs. 3A, 4A, C) as well as bury roadways (fig. 4A). Moving landslides present extreme hazards to human safety; some fatalities during Hurricane María resulted from mud and debris that flowed through windows and doors of a home and buried occupants. Many landslides in Puerto Rico become fast-moving debris flows, which are especially common in channels where they can quickly travel kilometers downstream. Multiple debris flows may occur in a channel during a single rainstorm (some channels experienced more than 50 debris flows during Hurricane María; Bessette-Kirton and others, 2020). This map separately depicts locations and the relative likelihood of where landslides may initiate, where they may move downslope, and where channelized debris flows may travel during or soon after intense rainfall like that during Hurricane María. An estimated average of 529 millimeters of rainfall fell across Naranjito during September 19–21, 2017 (Ramos-Scharrón and Arima, 2019). Lower rainfall amounts, durations, and intensities also trigger landsliding in Puerto Rico, although landslides and debris flows become more numerous as rainfall intensities, durations, and cumulative amounts increase.

Naranjito Municipio, Puerto Rico↗