Geo-Extreme 2021: Climatic Extremes and Earthquake Modeling

Rainfall hazards from tropical cyclones (TCs) have been emphasized in recent research. A physics-based TC rainfall model (TCR) has been developed and used in TC rainfall hazard assessment. In this study, we develop a joint-probability-method (JPM) for TC rainfall hazard assessment. The JPM method is inspired by the finding that three TC-related parameters—maximum intensity when the storm is near the point of interest (POI), duration of the storm, and the minimal distance between the storm center and POI—are most important to the hazard curve estimated by TCR. It is found that the JPM method can capture the probability feature of rainfall hazard in different locations in the United States relatively well. The necessity of using all three parameters for the probability assignment is explored, and it is shown that the JPM methods using only one or two parameters are inferior to the method using all three important parameters. Finally, the possible application of the JPM method in climate change or climate variability study is discussed.

Guam is a tropical region in the western Pacific that is characterized by mountainous terrain. It is often hit by storm events which bring heavy rainfall in short duration causing slope failures. In this research, soil samples were collected from mountainous slopes of the Piti-Asan watershed in central Guam and saturated as well as unsaturated soil properties including soil water retention curve test and unsaturated hydraulic conductivity functions were experimentally obtained. Transient seepage analysis was conducted on an idealized slope to obtain rainfall-induced changes in pore-water pressure profiles, and the output was coupled with slope stability analyses to study the effect of a recent storm event. Results show that unsaturated soil properties play a key role in estimating the accurate factor of safety of tropical hillslopes. In addition, studies show that there was a minimal effect of applied antecedent rainfall events on the stability of the hillslope.

Effective management of pluvial flooding requires detailed simulation of precipitation events with their corresponding frequencies. In this paper, the authors present a data-driven methodology to simulate precipitation events for flood management based on time series modeling. Combinations of marginal distributions of Burr type III and generalized gamma and autocorrelation structures of Burr type XII, Pareto type II, and Weibull are adopted for time series simulation of precipitations of 10 min intervals. Historical records of precipitation from a gauge station in Harris County, Texas, from 1986 to 2013 are used to calibrate time series models. A minimum interevent time-based definition scheme for event is adopted to derive statistics of observed and simulated precipitation events. Simulated and empirical statistics of precipitation events with intensity measures exceeding severity thresholds are used to evaluate the performance of proposed models.

The Tohoku earthquake which was 9.0 magnitude mega earthquake caused a huge tsunami on March 11, 2011, in the northern part of Japan. This tsunami caused a great damage to the land area with high-salt content. A high content of salt in soil makes it unsuitable for crop production. Traditional method such as leaching with fresh water was expensive for a wide area and the discharge of saline water was another big challenge in the damaged infrastructure. In this study, a series of laboratory test was conducted to investigate the ability of bioremediation to reduce the salinity of soil samples. Saline soil was prepared after soaking the test soil in artificial seawater for three days and dried it to make it as a tsunami affected saline soil. It was then mixed with different microorganisms. Soil samples were collected to measure the electrical conductivity (EC), which is directly related to chloride content, regularly at different specified depths using a portable electrical conductivity meter. It was found that the electrical conductivity reduced with the help of the bacterial activities and the collective microorganism (CM 2) was more effective than the other microbes.

Predictive models using machine learning tools have received increased attention to minimize the negative impact on the environment. Mississippi is considered as one of the wet states in the United States, and the precipitation is considered as the major challenge, and the precipitation pattern is in gradual alteration. The major objective of the current study is to develop an Artificial Neural Network based predictive model of the Yazoo clay soil matric suction to estimate weekly suction variations from field measured instrumentation data. Yazoo clay soil matric suction is one of the influencing factors in the mechanical properties of the soil, which could be an indication of the soil body movement. Six site slopes at different neighborhoods of the Jackson Metroplex area have been instrumented by soil moisture sensor, water potential probe, and precipitation gauge to monitor the change in soil moisture content, soil matric suction, and real precipitation respectively. The installed automated sensors have been located at the 5 ft (1.5 m) depth. The field instrumentation was initiated from mid-August 2018 to the present. The data set has been processed and trained based on generalized autoregression Artificial Neural Network with several backpropagation layers and validated with each target slope. Based on the deep learning analysis results with various performance indices, 98% prediction accuracy was achieved by implementing ANN analysis to the field real measured data.

Under extreme storms, multiple hazards such as landslides, debris flows, and floods may occur simultaneously. This study conducted numerical simulation of rainfall-induced hazard processes, aiming at deciphering the main weaknesses of an urban watershed exposed to slope failures, floods, and debris flows. Under storms of 44%, 65%, and 85% of the 24 h probable maximum precipitation, 0.5%–1.7% of the natural terrain of the study area can lose stability, and 18.2%–21.1% of the urban area may be flooded. The travel distance of debris flows can reach 833 m. The hazards of slope failure, flood, and debris flow could occur in a same site over a relatively short-time interval. Therefore, hazard interactions are very likely to happen, especially in the flow channels where will be affected by all the three hazards.

Large population around the globe live in close proximity to freshwater-influenced coastal regions. These regions are, though, increasingly threatened by coastal extreme hazards. Tropical Cyclones (TCs) are classic examples of compound hazards during which the coincidence/concurrence of two or more hazard drivers intensify the impacts expected from each of those drivers in isolation. Challenges for appropriate modeling of compound coastal floods can be summarized under three main categories: (1) multidimensionality of processes, (2) nonlinearity of interactions between underlying processes, and (3) nonstationarity of processes. Appropriate characterization of risk associated with compound coastal hazards should take all of these features into account otherwise it will fail to provide reliable and actionable information to public and decision makers, and thus yields ineffective communication of risk to threatened coastal communities. In this presentation, the technical challenges we face for appropriate characterization of these compound coastal extremes and also the opportunities to tackle the aforementioned challenges will be discussed.

This study highlights the need for evaluation of levees’ functionality under compounding hazards in a changing climate. For this purpose, this paper presents a methodology to investigate the performance of a levee subjected to the sequence of flood and earthquake loadings. The Elkhorn Levee in Sacramento, CA, is considered as a case study and the effect of flood event superimposed by seismic activities on the levee’s integrity is evaluated. Results from climate models are used to determine the changes in flood levels with different intervals in a changing climate. A ground-motion data of a major earthquake in the area is used to apply seismic loading to the levee structure. The integrity of the levee is then evaluated against slope instability, deformation, and liquefaction using a set of finite element simulations. Results show that flooding increases the probability of soil liquefaction and generation of excess pore-water pressures when the earthquake shakes the levee structure. Excess pore-water pressures and reduction of soil strength due to liquefaction decrease the stability of the levee and cause considerable deformations, which may lead to levee’s failure. Results demonstrate the poor performance of the levee when subjected to flooding followed by a seismic event, which necessitates the evaluation of levees under compound extreme events.

A sequence of hazardous events, or the simultaneous occurrence of events over a region, can cause far greater societal impacts than those arising from individual events alone. Yet the prevalence and severity of the impacts from these connected events are not well understood. The goal of the COEXIST (Connected Extremes In Space and Time) project is to mitigate adverse societal impacts of US floods and droughts through understanding the spatiotemporal connections between extreme meteorological events and how these connections might yield more accurate predictions. The project has thus far identified strong regional and seasonal variability in connection strength among extreme precipitation events in the historical record and is working to link these connections to driving weather phenomena. This paper presents the latest results from this ongoing project. Our purpose in presenting at this multidisciplinary forum is to engage with expertise beyond meteorology and climate science, and to begin to explore the vulnerability of critical infrastructure and its resilience to connected events.

As a result of the M 6.7 1971 San Fernando earthquake the Lower San Fernando Dam (LSFD) suffered significant damage that could have resulted in a breach and uncontrolled release of the reservoir (URR). The damage to the LSFD was a result of liquefaction that led to a massive slide on the upstream slope into the reservoir. The slide lowered the crest of the dam well below the reservoir level. However, a section of the downstream slope remained, with about 5 ft of freeboard. Fortunately, aftershocks did not cause further significant damage and the reservoir was lowered soon after the earthquake, avoiding URR into the heavily populated San Fernando Valley below. Experience suggests that system failures are a result of a combination of events or circumstances (a sequence of events) that collectively conspire to produce the outcome that occurred. This study takes a retrospective look at the events at the LSFD as a result of the 1971 earthquake to assess just how rare (in terms of its annual frequency of occurrence) it was. This retrospective look at the 1971 earthquake provides insights and lessons for conducting prospective seismic risk studies in the future.

The Farmington Siding Landslide Complex is a mapped paleo coseismic landslide in Davis County, Utah, that extends several kilometers beneath heavily developed urban and suburban areas. In design and development of new infrastructure on the complex, there are implications for systems thinking decision approaches for analyzing and mitigating the extreme event hazards versus location or project-specific approaches. Typical landslides or lateral spreads are commonly limited to areas that are a few tens to hundred meters across and systems approaches are not warranted due to the small spatial extents. When dealing with landslides that are several kilometers in width, the implications of compounding effects and unintended consequences of design decisions become pronounced. For example, if a new highway bridge is constructed in the area, how will potential ground improvements to protect individual bridges be designed to resist such large spatial impacts? How will the new highway affect the impacts to pre-existing infrastructure? Are the costs to keep a bridge standing warranted when there will be no undamaged or usable roads to access the bridge? Concepts of performance-based design and resilience enter into these decision-making processes. We use the Farmington Siding Landslide Complex as a canvas on which to discuss these different approaches and the impacts of different decisions both on single site projects and the system as whole.

This paper examines how the level of auxiliary spillway erosion varies depending on the material and structural properties of the spillway. A sensitivity analysis is performed to distinguish the variability in the auxiliary spillway erosion for the Willow Creek Dam, located in Montana, using Windows Dam Analysis Modules (WinDAM) C software. The geologic materials, geometric design parameters, and hydrologic data are considered for the overall sensitivity analysis. The test is performed by changing the input parameters in WinDAM C. It was observed the inflow hydrograph had the largest impact on erosion. The representative diameter, spillway width, and side slope ratio had intermediate levels of impact on erosion.

Extreme rainfall events, such as tropical storms and hurricanes, can produce large amounts of precipitation in a short period of time. In Central Florida where a relatively thick impermeable soil layer (i.e., Hawthorn Clay) is present, a differential water pressure head causes internal soil erosion that can become a catalyst in the creation of sinkholes. To better determine the likelihood of such formations, long-term piezometric data were analyzed to identify abnormal behavior of groundwater where the erosion process is significant. In this study, X-Bar and R control chart, commonly used for quality control in many industries, were employed. The X-Bar chart was used to determine the variation of distinct point averages when compare to an overall system average and R chart looks at the range of individual locations over a given time frame and compares that to the average range of a system. A significant variance in range of a specific point when compared to nearby sensors can help identify ground water flow and possible anomalies. This sensor instrumentation and analysis method was applied to the Wekiva Parkway SR46 connector project in Central Florida. Through analyzing a system of piezometers over a specific time frame in which one or more extreme weather events occur, these management tools could identify abnormal-behavior piezometer locations where the potential of future sinkholes could occur due to active internal soil erosion; thus, preventative monitoring and/or mitigation are necessary.

The Yarlung Tsangpo River Grand Canyon is the most precipitous place in the Yarlung Tsangpo River, has a length of 504.6 km, a slope of 0.155%, and a valley bottom elevation difference of 2,755 m. Evidence shows the Yarlung Tsangpo River as well as its tributaries are frequently blocked by landslides, avalanches, and debris flow. The breaching of some large landslide dams, such as the 2000 Yigong landslide dam and the 2018 Gyalha landslide dam, resulted in huge floods and impacted large downstream areas. This paper reports a method to analyze the breaching flood of landslide dams in different locations on the Yarlung Tsangpo River Grand Canyon. The method can be divided into two steps: first, a physical model is used to predict the breach outflow rate of the landslide dam at the prone points in the basin; second, hydraulic software is used to simulate breach outflow rate and flood routing process downstream of the dam. A digital model is composed of the Yarlung Tsangpo River and two of its tributaries are built for this purpose. The results show that the simulated peak discharge at dam sites and corresponding outflow rate along rivers agree well with field observations. The peak outflow rate is amplified when breaching floods of landslide dams on the mainstream and its tributaries are overlapped. The method proposed in this paper can be effectively applied to breaching flood evolution of landslide dams.

The PANDA variable energy dynamic cone penetrometer (DCP) is a mobile, instrumented DCP that enables rapid site investigation by one user. The PANDA was utilized in this study to measure cone tip resistance and develop site profiles at a blast liquefaction test site in Christchurch, New Zealand. The blast liquefaction testing occurred at two areas within the site. The first blast test was performed in soil that had been improved by resin-injection, whereas the second test was performed in untreated soil. Measurements were performed with the PANDA DCP prior to liquefaction and following liquefaction to evaluate changes in soil resistance as a result of liquefaction. Cone tip resistance profiles were developed for depths to 4.5 m and took approximately 30 min to complete. Results of the testing showed changes in cone tip resistance as a result of liquefaction for the untreated site where a decrease in resistance was observed. In addition, the PANDA DCP results were compared with cone penetration tests that were performed prior to liquefaction at both test areas and showed good agreement. The PANDA DCP was found to be a useful tool for site investigation following blast liquefaction tests as tests could be completed within 30 min of deployment in difficult to access areas.

The anthropogenic emission of industrial pollutants (e.g., nitrogen oxide and carbon dioxide) is the main cause of acidic rain and climate change related problems. In addition, the extreme precipitations caused by climate change can facilitate the migration of contaminant and acidic fluid flow. The interaction between the acidic fluids and the soluble (e.g., carbonate based) rocks induces mineral dissolution/precipitation. The exposure of limestone rock to the acidic rain/contaminant can cause significant levels of calcite dissolution, which in turn can induce land surface depression. In addition, the dissolution of the carbonate rocks in the dam foundation can have detrimental effects such as excessive settlement and compromised structural integrity. The dissolution/precipitation of minerals can significantly change the porosity and permeability of the porous medium, which consequently changes the seepage regime in the dam foundation. In this study, the porosity and permeability evolution of a carbonate-based rock were evaluated by flowing the acidic fluid through the limestone specimen. In addition, the variation of the rock strength upon exposure to the acidic environment was investigated using the Multi-Stage Elastic (MSE) experiments. The X-ray Micro CT was used to perform the porosity analysis before and after injecting the acidic fluid. The results indicated that the mineral dissolution/precipitation increased the permeability of the limestone specimen by more than one order of magnitude (~13.2 times). On the other hand, the average Young’s modulus of the limestone specimen decreased by ~28% during the MSE experiment at confining pressure of 7.5 MPa.

Because of intensive precipitation and the presence of high-plastic Yazoo clay in central Jackson in Mississippi, shallow highway slope failures are a reoccurring phenomenon. Annually, the majority of highway slopes in central Mississippi experience shallow slope failures. The major objective of the current study is to evaluate the performance of two repaired highway slopes in the Jackson Metroplex neighborhood in Mississippi. The highway slope ratios are 3H:1V (Terry Road) and 6H:1V (McRaven Road). Soil boring and CPT testing were conducted as part of site investigations. Vertical slope inclinometers and precipitation gauge were also installed at the site slopes to record and detect displacement along the slope and real precipitation, respectively. One year after monitoring the slops, consecutive shallow slope movements were observed in late 2019. Based on the field monitoring results, the slopes became fully saturated. Impacting factors and potential failure conditions were verified with back analysis using the 3D Finite Element Method in the Plaxis. Based on the 3D coupled flow-deformation analysis results, the progressive precipitation infiltrated in the top soil which significantly impacted the reduction in soil matric suction and creates a perched water zone, which reduced the factor of safety closed to 1.0. Based on the field and numerical observations, the development of the perched water zone as a result of continuous precipitation led to slope surficial layer movements.

Heaving is a common problem experienced with the high-plasticity clays due to water-absorption in pavement structures. Under an excessive amount of precipitation, typically in humid areas, water infiltration and absorption can lead to significant heaving on the surface of the subgrade. If this type of situation is not monitored properly, it can lead to excessive stress at the base of the pavement which in turn can lead to tensile cracks at the surface and can lead to disastrous effects. To overcome these typical problems, the in situ high-plasticity clays in subgrade are often replaced with chemically stabilized soil up to a certain depth. The chemically stabilized soil prevents a significant amount of heaving at the surface by reducing the swelling potential of the high-plasticity clays to a great extent. In this study, a nontraditional stabilizer, namely, lignosulfonate has been chosen and compared for the enhancement of the performance of the subgrade system. Basic tests are carried out to ascertain the effects of chemicals. Swell tests, followed by consolidation and UCS tests have been performed to fix the optimum amount of chemical. Further, to check on the efficacy of the stabilized soil in a pavement utilizing the optimum amount, a brief numerical analysis has been carried out to estimate the heaving in a humid region at different intervals of a year. Lignosulfonate has been found to give good results in terms of a decrease in heaving at an optimum content of 3% of the mass of soil.

The waste containment systems which form an important part of the waste management and environmental protection strategies are highly vulnerable to the impacts of extreme climatic events and are prone to causing colossal and long-term damage to environment upon failure. For example, the extreme precipitation may reduce the infiltration resistance of landfill cover systems causing seepage of toxic leachate into the subsurface and surrounding environment. Similarly, extreme drought events may lead to drying up of the landfill cover giving rise to formation of cracks and ultimately releases of the harmful landfill gas in undesirable amounts. Hence, there is an urgent need to analyze the vulnerability of the waste containment systems and incorporate resilient designs to adapt to extreme climatic events. Toward this goal, this study presents development of a sustainable cover system for municipal solid waste landfills with primary goal to mitigate methane, carbon dioxide, and hydrogen sulfide from fugitive landfill gas that can also adapt to the impacts of changing climate and extreme weather events such as flooding, erosion, drought, saltwater intrusion, and high temperatures. The proposed cover, also called biogeochemical cover, uses sustainable materials such as biochar-amended soil and steel slag. A comprehensive experimental study evaluated the resilience of the biogeochemical cover system under selected extreme climatic conditions. In particular, the methane oxidation potential and microbial community response were evaluated in detail under widely varying moisture (0%–40% w/w), and temperature (5°C–70°C) conditions. The results demonstrated that the extreme environmental conditions such as high temperature (70°C) and wetting (moisture content >30%) impact the performance of the cover components mainly the biologic component. Nevertheless, the proposed cover components showed satisfactory performance under diverse climatic conditions showing greater resiliency to extreme events. However, the same needs to be further researched in detail under field conditions to verify the resiliency of the proposed cover system.

The oil industry has already been exposed to extreme weather events putting its processes, growth, and security at risk. As the majority of its processes and structures have been designed to withstand experienced and known climate change risks, adaptation policies necessitate the development of regional climate-resilient infrastructures by ensuring that assets are located, designed, built, and operated considering the future climate. These, in turn, require the establishment of threshold levels of risks and resilience to the impacts of climate change, over the entire life span of these assets. The work presented in this paper is based on an extensive consideration of how climate change is anticipated to impact the midstream and downstream oil industry in Greece. The analysis carried out indicated shorter return periods for the specific design thresholds of average/maximum temperatures and of the Heat-index indicator as associated with an increase in the number of events above thresholds for both RCP 4.5 and 8.5 W/m² future scenarios. Based on microscale climate characteristics, this study highlights the need for the redesign or enhancement of oil infrastructure based on future projections and risk-informed decisions throughout the facility’s lifetime, including long-term planning and preparedness under deep uncertainties.

This study investigates the behavior of buried concrete pipes and changes in subgrade support capacity due to heavy rainfall-induced flooding at the ground surface and reduction of shear strength of the supporting soil due to the infiltration and leakage from the pipe using the finite element software PLAXIS 2D. A stormwater pipe of diameter 2.8 m and thickness 0.2 m was selected according to the ASTM C 14. The maximum flood head and the infiltration rate were chosen based on the record after Hurricane Florence occurred in September 2018. The effect of the individual occurrence and simultaneous occurrence of flooding, infiltration, and leakage on the behavior of the buried pipe was analyzed. Results indicated that the simultaneous occurrence of the three events induced the highest deflection of 3.80 mm. The bending moment and shear force increased from 15.06 kN m/m to 23.2 kN m/m and 22.65 kN m/m to 36.2 kN m/m, respectively, due to the combined events.

Extreme hydroclimate events are increasing in frequency and intensity with climate change. This, alongside aging infrastructure, increasing population, and land use changes, makes quantifying and reacting to future changes incredibly difficult. This paper highlights two successful interdisciplinary efforts led by the water management community to manage critical infrastructure for climate resilience when current operational paradigms no longer apply. We highlight these efforts to illustrate (1) best practices and lessons learned when prioritizing and designing projects that enhance infrastructure resilience, and (2) key characteristics that make projects focused on increasing infrastructure resilience to changing hydrometeorological extremes successful. These case studies illustrate the importance of relationships built between researchers, decision makers, and stakeholders, and our recommendations stress the value of collaboration throughout, from project design to project assessment. We also identify the need to integrate prognostic weather and climate products when infrastructure functionality is characterized and to uncover ways to enhance resilience when current operations are not adequate to cope with future hydroclimate extremes.

Agriculture has historically been affected by hydrometeorological events. Floods and droughts evidence the vulnerability of farmers and the food production system. We aim to conceptualize a crop risk framework for floods occurring before the onset of the growing season and affecting harvest. We use the NDVI from Sentinel-2 imagery to represent the indirect effects of floods on corn planting. We analyze corn’s spatiotemporal variability and associate its phenological development using NDVI to characterize its attributions to floods before the growing season, and develop a framework for hazards, exposure, and vulnerability to flooding. Floods occurred during the crop’s pregrowing season evidence a three-week delay in the peak of NDVI during the vegetative and silking phenological stages in 2019, compared to an average year. Crop yields were correlated with the NDVI in 2018 and 2019. Risk estimates were higher in counties where rivers and poor drained soils are present (1%–11%).

The City of Boston is advancing climate resilience along the South Boston shoreline through the rehabilitation of Moakley Park. The Moakley Park Vision Plan, released in 2018, presented conceptual design plans for a resilient Moakley Park that included a new flood protection barrier (i.e., levee) measuring approximately 2,600 ft (790 m) in length with a height of up to approximately 10–12 ft (3–3.5 m) to address climate vulnerabilities. The levee is planned to traverse the 62-acre (25-hectare) park and be designed to provide flood protection for the park interior and surrounding South Boston communities. The challenging existing site conditions include shallow groundwater, environmental contamination, several large below ground infrastructure utilities, and a subsurface profile that includes historic urban fill overlying highly compressible organics and soft Boston Blue Clay deposits that is up to approximately 200 ft (61 m) thick. The following case study examines the current and future site challenges, and describes the iterative design process that was required to address the complex goals of mitigating future flooding and improving park amenities for members of the surrounding communities. Climate projection data are presented that informed the basis of design and the adaptable approach, as well as a description of subsurface conditions and an explanation of how the support of the flood protection barrier is being designed to meet the needs of the landscape, including proposed plantings, structures, and below ground utilities.

In this study, a new climate-adaptive design method is developed to investigate the impact of extreme climate events on the safety and serviceability performances of building footing through incorporating the site-specific hydrological loads such as precipitation, evapotranspiration, and water table depth to soil strength and stiffness parameters. The site-specific extreme hydrological cycle was determined based on historical climate records. The Richards equation was used to compute the temporal and spatial variations of the degree of saturation and matric suction considering the hydrological loads as the top and bottom boundary conditions. The proposed method was applied to a semiarid climate site in Austin, TX, as a sample application. The results show that the critical ultimate bearing capacity and settlement obtained from the proposed method are 28% higher and 35% lower, respectively, than those calculated using the conventional deterministic approaches assuming soil is fully saturated.

We present a framework for adaptive infrastructure design that can properly account for variability and uncertainties associated with projected future climatic patterns. Current methods of infrastructure design commonly rely upon the assumption of stationarity, implying that the statistics of the past climate define future risk. Significant changes in climate conditions and event occurrence statistics make this assumption invalid. These variations introduce a new level of uncertainty that should be included in the design, construction, and operation of infrastructure systems. However, current efforts to predict the future climate do not provide sufficient and accurate information for application to infrastructure design. Due to the uncertainty present in the future climate projections, adaptive measures provide the greatest potential for cost effective risk mitigation. In this study, we provide insight into how to revisit the existing design methods with a vision toward embracing climate adaptive methods in engineering practice. The proposed adaptable design prevents the higher costs posed by other adaptation strategies, such as robust infrastructure, reducing overinvestment at the initial stage. A conceptual iterative design example is presented to show how the proposed framework can be employed for adaptive design of a seawall.

To mitigate the effect of expansive clay on roadway foundations, TxDOT conducted a research study by utilizing a combined technique of mechanical and chemical stabilization. The existing subgrade, consisting of expansive clay, was stabilized with cement. The structural pavement section consisted of a 150 mm thick aggregate base course (ABC) with chip seal surfacing. A portion of this pavement section consisted of geogrid stabilized ABC. Field performance was measured by monitoring pavement distresses and the change in elevation of the pavement surface. In situ characterization of the pavement sections was conducted using Automated Plate Load Testing (APLT). The pavement consisting of geogrid showed less longitudinal cracking after experiencing a series of wet and dry season cycles and heavy trafficking. These observations were also supported by the results of APLT which indicated that the pavement with geogrid preserved the stiffness of the aggregate layer over time.

Estimating the extent of sand ejecta effects on building settlements during earthquake, liquefaction is an important research question. Engineers currently need to rely on their judgment and relevant case history data because there is no available methodology that can be used, and details of the mechanism and correlations are unknown. This paper attempts to provide insight on the significance of ejecta by first reviewing literature on liquefaction-induced ejecta including case histories, geotechnical reconnaissance reports, and results from centrifuge tests. Second source of information consists of observations of ejecta occurrences near shallow foundations in a series of nine 1 g shake table experiments conducted at the University of Nevada, Reno, in which a particular attention was paid to the location, distance, and volume of ejecta occurrence in the experiments. Measurements of ejecta dimensions such as height and area were taken, and from those, the volume of ejecta was calculated assuming a conical geometry. The distribution of ejecta based on their volume is compared to measured foundation movements such as overall settlement and tilt. Preliminary conclusions of ejecta correlating with tilt and settlement of foundations are presented in this paper based on the experimental results.

Liquefaction is one of the consequences of earthquakes in which loose saturated soils lose shear strength due to the dynamic loading of the earthquake. Soil liquefaction causes serious damage; therefore, it is important to evaluate the liquefaction potential of areas near seismic zones. The main objective of this research is to develop a Liquefaction Probability Curve (LPC) to generate initial liquefaction hazard maps for Lake County Tennessee, which is within the New Madrid Seismic Zone (NMSZ) and is vulnerable to seismic risk. The geotechnical database utilized for developing the LPC includes information on water table depths, soil classifications, and Standard Penetration Test (SPT) N-values. The liquefaction hazard maps for Lake County are probabilistic (5% and 2% probability of being exceeded in 50 years) and for multiple earthquake scenarios. For this study, the liquefaction hazard maps are presented for the probability of moderate to severe liquefaction. The probabilistic liquefaction hazard maps show 80%–100% (2% in 50 years) and about 75% (5% in 50 years) probability of liquefaction in Lake County which corresponds with the observed prevalence of sand blows and liquefaction features in the county. Liquefaction hazard maps show a high hazard in Lake County for a moment magnitude (M_w) of 6.9 New Madrid scenario and a low hazard for an M_w of 5.8 hypothetical Lake County earthquake.

This paper studies the impacts of sea-level rise on liquefaction triggering and severity around the San Francisco Bay Area, California, for the M 7.0 “HayWired” earthquake scenario along the Hayward fault. This work emerged from stakeholder engagement for the US Geological Survey releases of the HayWired earthquake scenario and the Coastal Storm Modeling System projects, in which local planners and engineers asked where, why, and by how much liquefaction hazards may change due to sea-level rise in the future. We assess the impacts of sea-level rise on liquefaction by computing changes in liquefaction potential index (LPI) for over 400 cone penetration test (CPT) soundings around the San Francisco Bay for groundwater table models developed for current and increased sea levels of up to 5 m. For the M 7.0 HayWired earthquake scenario, we find that while the majority of sites are insensitive to sea-level changes of less than 1 m, some sites are highly sensitive to small changes in water levels. We then repeat these analyses for a uniform shaking scenario to isolate the effects of sea-level rise and we find similar patterns of change. For both earthquake scenarios, modest changes in overall LPI are expected for increases in sea level, but individual sites may see significant increases in liquefaction likelihood and severity.

An accelerogram-based method has been recently developed to quickly assess the liquefaction occurrence using only the ground-motion records. In this method, two frequency-related ground-motion parameters, the richness of the low-frequency components (termed RL), and the temporal variation rate of the mean instantaneous frequency (termed MIFr), are extracted from accelerograms and used as explanatory variables of a logistic regression model that outputs a new probability indicator of liquefaction occurrence (termed LQI). This method achieves an overall accuracy of over 90% when classifying the liquefaction occurrence in both the training dataset and the validation dataset, and the method shows promising potential for applications in real-time disaster mitigation systems and rapid postearthquake loss estimations. However, the success of detecting liquefaction from accelerograms relies on the assumption that the liquefaction effect on the site-specific ground motions is more significant than other effects. In this study, we select eight factors representing the source, path, and site effects of a ground-motion record, and conduct correlation analyses between the eight independent factors and the proposed two frequency-related ground-motion parameters (RL and MIFr). The results reveal that, in general, liquefaction has a more significant effect on the site-specific ground-motion frequency parameters compared to other factors such as earthquake source, path, and site effects, which is the basis of the accelerogram-based liquefaction assessment methods. This study will benefit the advancement of the accelerogram-based methods for rapid liquefaction assessment.

The susceptibility to liquefaction of aged soils is an ongoing concern due to the recurrence of earthquakes in the South Carolina Coastal Plain (SCCP), which includes the Charleston, South Carolina, seismic zone. This paper presents the results from a laboratory study to assess the age-related liquefaction resistance of soils from the Sampit site located within the SCCP where evidence of prehistoric and historic liquefaction has been observed. The potentially liquefiable soil studied herein has a geologic age of about 450,000 years and a possible geotechnical age of about 520 years. Stress-controlled cyclic triaxial tests were performed on high-quality specimens obtained from fixed piston tube samples and specimens reconstituted using water pluviation. The reconstituted specimens maintained a 60% lower cyclic stress ratio than the cyclic stress ratio of the original specimens at initial liquefaction.

Chittagong District is one of the most significant and flourishing coastal regions in the southeastern part of Bangladesh. It lies in the active tectonic framework which has experienced several major earthquakes in the past. Due to its economic, cultural, and military significance, it is of utmost importance that the structures are safe from seismic hazards. Seismicity database of M_w ≥3 from 1900 to 2020 has been used to provide extensive insight into historical earthquakes and also facilitate accurate predictions. The seismic sources have been adopted from the seismotectonic Atlas of India and adjoining regions with a control region of radius 500 km from the political boundary of Chittagong District. The Peak Ground Acceleration (PGA) values were computed at the bedrock level, surface level PGA was calculated using the NEHRP soil amplification relations for Chittagong City, and corresponding response spectrum was plotted. Using these PGA values, hazard contours for the Chittagong City and District have been developed for the ease of seismic design of structures in the future.

Structural risk-based evaluation requires a large number of time-history analyses at different ground-motion (GM) intensity levels, where the scenarios (e.g., magnitude and distance) of the GMs used in the time-history analyses should be consistent with the site’s hazard. The current practice of GM selection typically simplifies the choice of scenario to either an average scenario or the modal scenarios based on the site’s hazard deaggregation results. This paper investigates the impact of hazard deaggregation and scenario selection on estimating structural seismic risk. For a hypothetical site in the eastern US, a Monte Carlo seismic hazard analysis is performed to derive a site-consistent GM suite that captures 1,000,000 years of the site’s seismic activity. The complete GM suite consisting of 99,917 records is then used to perform nonlinear dynamic analyses on a midrise concrete office building to derive a benchmark seismic demand curve. Subsequently, four GM sets are selected based on average and modal scenarios from two different hazard deaggregation formulation, and the resulting demand curves are compared to the benchmark. The results show that the hazard deaggregation method and scenario choice impacts the demand curve estimation. When deaggregation is performed on IM exceedance, GMs that were selected based on both methods agree well with the benchmark up to higher damage states where mode-based records outperform average-based records. On the other hand, when deaggregation is formulated based on IM occurrence, average scenario-based GMs better match the benchmark, except for higher damage states where again modal scenario-based GMs are in better agreement with the benchmark.

The 2011 Mineral, Virginia, Earthquake impacted a large area of the central and eastern United States (CEUS). This paper estimates the ground-motion intensity in northeast Pennsylvania with an epicentral distance of 384 km using existing ground-motion attenuation models. The corrected ground-motion data from the Pacific Earthquake Engineering Research Center (PEER) is used to estimate the ground motion in northeast Pennsylvania for comparison with available attenuation models. The attenuation models were also compared with US Geological Survey (USGS) “Did You Feel It?” intensity reports. The estimated rock site peak horizontal ground acceleration in northeast Pennsylvania is between 0.0075 and 0.030g.

Input (bedrock) ground motions are a critical component of site-specific evaluations of earthquake effects. In this study, we investigate the sensitivities of site-response predictions to input motion selection protocols for different types of site conditions. Analyses are performed for alternative profiles (soft and stiff) in two sedimentary basins, Seattle, Washington, and Boston, Massachusetts, to evaluate the influence of different tectonic, geologic, and geotechnical conditions. Using the results of probabilistic seismic hazard analyses at each site, we develop suites of input motions using alternative target spectrum definitions for various magnitude–distance combinations, perform one-dimensional site response analyses, and evaluate the resulting sensitivities of the site response predictions to the various input motion selection protocols. When the soil behavior is strongly nonlinear at soft sites, we find that the influence of input motion selection protocols on site-response uncertainty decreases significantly, and that nonlinear soil behavior can suppress the variability in surface ground motions. Analyses using alternative profiles indicate that predicted ground motions at stiffer sites are more greatly influenced by input motion selection protocols relative to softer sites where significant nonlinear behavior may occur.

The 2014 New York City Building Code (NYCBC) requires an evaluation of liquefaction for soil at depths shallower than 15 m if standard penetration test (SPT) N₆₀ values plot in the “liquefaction evaluation required” domain. Typically, the liquefaction assessment is performed using the maximum considered geometric mean peak ground acceleration adjusted for site class effect, which is based on SPT N₆₀ values. A project site in New York City area was assigned Seismic Site Class F based on subsurface conditions (i.e., SPT N₆₀ values) encountered in the borings and liquefaction analysis showing extensive potentially liquefiable layers from 2.7 to 15.5 m below ground surface on site. Therefore, in accordance with the NYCBC, a site-specific response analysis is required to determine seismic parameters for the site. To develop design seismic soil profiles, Seismic Cone Penetration Tests (SCPT) were performed to collect shear-wave velocity (V_S) data. The average V_S profile based on SCPT indicated a classification of Seismic Site Class D. In addition to the improvement of the Site Class, a site-specific ground motion analysis was conducted to develop a design acceleration response spectrum in accordance with the applicable provisions of ASCE 7-10 and NYCBC, using dynamic soil properties. Based on the results of the site-specific analysis, the liquefaction hazard was reevaluated. Liquefaction risk and liquefaction-induced settlements were reduced significantly utilizing site-specific analysis results. The case study demonstrates using a site-specific ground-motion analysis to obtain a refined estimate of potential earthquake-induced shaking at a site, which reduced dynamic loads, and thus reduced design and construction costs significantly.

In this study, the site response impacts of accurately characterizing and resolving the Memphis sand layer at the Central United States Seismic Observatory (CUSSO) site are explored. The Memphis sand, also known as the “500 ft sand,” is a major shallow impedance contrast in the Mississippi Embayment, influencing the site response estimates across the embayment. However, the Mississippi Embayment’s available velocity information, including the Central United States Seismic Velocity Model, often does a poor job of properly identifying the depth and impendence contrast associated with the Memphis sand layer. To understand the impacts of the Memphis sand layer on site response estimates, a parametric study using linear viscoelastic transfer function and nonlinear site response analysis is performed on a suite of shear-wave velocity (V_S) profiles with varying depths to the Memphis sand and varying formation velocity of the Memphis sand. The linear and nonlinear site response results indicate that varying the depth and V_S of the Memphis Sand layer within reasonable ranges can significantly impact site response results, with a variation of 10%–30% observed for periods less than 1.0 s. However, the largest variations are observed at periods between 1.0 and 2.0 s with variations of up to 45%. This highlights the need to properly resolve shallow impedance contrast, such as the Memphis Sand in the Mississippi embayment, for site response analyses.

Ensuring the integrity of a country’s life-line infrastructure is necessary to protect surrounding communities in case of disaster, and limiting the extent that unanticipated consequences could have on various aspects of life. Embankment dam systems across the country are an essential component of life-line infrastructure. In this study, numerical models were developed using finite-element modeling to investigate a series of embankment dams in southern California. The models were then verified with real accelerometers data provided by the California Strong Motion Instrumentation Program (CSMIP). The results from this study identified areas of weakness and instability on the dam that posed the greatest risk for its failure. Following this study, the numerical model can now be used to predict the dam’s response to future earthquakes, develop plans for its remediation, and reevaluate the emergency response in case of disaster, and ultimately, having an understanding of the potential outcomes that can occur in case of infrastructure failure.

A pseudo-three-dimensional (pseudo-3D) methodology to back-analyze coseismic landslides was developed and applied to 68 mapped landslides, which occurred over approximately 1 km² area in Egkremnoi, Greece, during the 2015 M_w 6.5 Lefkada earthquake. The methodology is based on a one-dimensional (1D) Newmark-type sliding block model to assess instability and a spatial projection in 3D topography to derive landslide geometry. The strength parameters for modeled landslides that best match the landslide location, area, and volume were derived through an iterative scheme that optimizes the match using predefined matching criteria. The range of different-sized landslides produced shear strength estimates from ~10 to 300 kPa and led to the derivation of a regionally averaged strength envelope characterized by a cohesion of 6 kPa and a friction angle of 53° for the highly fractured limestones that are encountered in this area. Compared to previous full 3D slope stability analyses in this area, the friction angle using this methodology was found to be generally consistent, but the cohesion was lower. The presented methodology can provide a computationally efficient method to estimate the average shear strength of a geologic unit over large areas, especially where extensive field and laboratory tests on the materials are unavailable or difficult to conduct.

The number of earthquakes in Oklahoma in the past decade has seen a multifold increase from its previous average of 25 earthquakes per year. Several studies have suspected a correlation between increased exploration and production activities (e.g., saltwater disposal, hydraulic fracturing) with the increased seismicity in Oklahoma. This study investigates the shift of seismic activities in Oklahoma through data analytics using the Epidemic-Type Aftershock Sequence (ETAS) model and the source parameter approach. It was observed that most earthquakes are induced due to fluid injection. Moreover, the significant earthquakes in Oklahoma with M 5.0+ were induced due to the wastewater injection. Our results suggest shifting of the earthquake hot spots and increased earthquake density from the megashear fault zone toward the Nemaha and central plains fault zones. The proposed modeling approach and findings offer improved understanding and robust tools for anticipation and preparedness against induced earthquakes, leading to earthquake-resilient communities.

The performance of a case history site adjacent to a meandering stream channel in Wufeng, Taiwan, is evaluated using two-dimensional (2D) nonlinear dynamic analyses (NDAs) to examine why past studies using simplified empirical and semiempirical analyses overestimated the observed liquefaction-induced ground displacements (i.e., lateral spreading) during the 1999 Chi-Chi earthquake. In situ data from borings and cone penetration tests (CPTs) delineate thinly interlayered floodplain deposits interrupted by laterally discontinuous channel sand deposits, typical of a fluvial point bar sequence. Most of the encountered soil beds are characterized as “intermediate” (e.g., low-plasticity sandy silts and clays, and silty sands) and may exhibit behavior that is transitional between sand-like and clay-like soils during cyclic loading. The subsurface is simulated using transition probability-based indicator geostatistics, conditioned on available data and geological inferences, for three soil categories based on state of practice soil behavior type index (I_C) boundary values. The NDAs are performed using PM4Sand and PM4Silt constitutive models within the FLAC finite difference program. The results of these NDAs and of simplified analyses performed by others are assessed for their ability to predict the spatial trend of ground displacements observed near the channel face. The NDA and geostatistical models provide insights on how site data interpretations and stratigraphic assumptions for interlayered deposits can affect the degree and extent of predicted liquefaction effects.

In Puerto Rico, the recent exposition to successive natural disasters that cause landslides represents a unique opportunity to collect data that can be used to better model and predict slope failures across the densely populated island. After Hurricane Maria in 2017, a detailed event inventory of over 70,000 mass wasting sites was cataloged and used along with several geospatial datasets to develop a new statistically robust rainfall-induced mass wasting susceptibility map for the territory. Although the susceptibility map was created for excessive rainfall conditions, in a qualitative analysis it performed relatively well in predicting failure sites triggered by the 2020 M 6.4 southwestern Puerto Rico earthquake and associated seismic sequence. More detailed comparison of the susceptibility map using a mass wasting inventory for the seismic sequence will help to evaluate the product’s potential applicability to ground shaking in addition to extreme precipitation. The analysis of the landscape changes provoked by these natural disasters will help with the overarching challenge to better understand landslide occurrence and also their long-term cascading effects like sedimentation and reservoir capacity reduction.

The 2011 Tohoku earthquake (M_w = 9.0) caused widespread damage in the Kanto region of Japan. Along rivers and coastal shorelines (including Tokyo Bay), soil liquefaction, lateral spreading, and seismically induced settlements contributed significantly to the reported damages. In April 2011, the author visited affected areas in the Kanto region and found that much of the observed damage in the Kanto region was associated with human modifications that resulted: in levees constructed over paleochannels, in bridges as well as cities constructed in areas where swamps and old river beds were once present, and in buildings constructed over hydraulic or poorly compacted fill.

Generic predictive models of earthquake-induced slope displacement are developed through classical regression analysis and artificial neural networks (ANNs). The maximum displacement on the slope surface at the end of shaking was computed by finite element simulations of 49 slope models subjected to 1,051 earthquake motions. Predictive models of seismic displacement are developed that characterizes the slope in terms of its yield acceleration (k_y), the natural period of slope (T_slope), and the relative thickness of the slip surface to the height of the slope (H_ratio), and characterizes ground shaking in terms of different ground-motion intensity measures. Across five intensity measures and 10 combinations of intensity measures, peak ground velocity (PGV) is found to be the most efficient and proficient parameter for the displacement prediction, leading to significantly small aleatory variability that is similar to the values derived from the use of multiple intensity measures. The models derived from ANN are similar to those developed from classical regression, although with slightly smaller variability and they did not require development of a complex functional form. These results indicate that ANN may be a viable alternative to classical regression for seismic slope stability models.

The November 2016 M 7.8 Kaikōura earthquake caused major disruption of, and significant damage to, the key transportation corridor on New Zealand’s South Island. The national road, State Highway 1, and rail, Main North Line, were severed by nearly 1M m³ of rock and slope debris from more than 100 landslides and debris flows. Helicopter sluicing was selected as a key mitigation method to remove unstable debris from earthquake-damaged slopes and enable access for construction equipment and staff. The overall sluicing program is described. Lessons learned from sluicing at Kaikōura are being developed together with other New Zealand wide experiences to establish “best practice” principles and processes for future use.