ABSTRACT Persistent seepage from an earthfill dam and associated structures has been observed for decades at Lake Capote, a small, spring-fed, off-stream, man-made lake in southwestern Colorado. Extensive engineering measures in 2006 did not fully remediate seepage. Therefore, we employed electrical resistivity tomography (ERT), induced polarization (IP), and self-potential (SP) methods to determine the location of seepage and its relationships with local geologic conditions. ERT revealed an approximately north–south striking horizontal, high-resistivity feature extending underneath both the northern part of the dam and the adjacent south dike. IP results indicated that this interpretive feature exhibits low chargeability (i.e., a low ability to store electrical charges), and SP results identified localized high positive magnitudes in it. In the context of borehole data and published literature, ERT and IP results suggest that this feature is a rare sandstone bed in the local shale-dominated bedrock (Lewis Shale) and also that it is the location of persistent seepage. Seepage appears to be occurring under the dam along faults in the interpretive sandstone (similar faults are observable in a nearby outcrop) and also within highly fractured shale under the south dike. In contrast, the middle part of the dam shows evidence, in both ERT and IP results, for seepage through its embankment rather than in its foundation. Our results demonstrate the value added to forensic investigations of dams by the integration of different geophysical methods, and they also portend the crucial importance and cost-saving potential of preconstruction geophysical site characterization of damsites.

ABSTRACT Miami-Dade County, FL, has complex hydrological and water management conditions, creating challenges for predicting groundwater levels. Due to the potential impacts of increasing sea level and changes in rain patterns on flooding and saltwater intrusion, it is essential to be able to accurately predict groundwater levels and to understand the drivers of groundwater levels. The method traditionally used to predict groundwater levels in south Florida and elsewhere is through the implementation of a numerical model. This research looks at machine learning techniques as an alternative method to provide improved predictions of groundwater levels. Extreme gradient boosting is one of the machine learning techniques that uses algorithms to train a model by identifying hidden patterns and relationships between groundwater level drivers and groundwater levels. The accuracies of the extreme gradient boosting model and a numerical model were compared by computing the root mean square error as a model performance measure. Comparing these two methods showed that the extreme gradient boosting model had better accuracy in predicting groundwater levels at the majority of groundwater monitoring sites. Furthermore, comparison of these two models helped us to identify problematic areas where both models performed poorly and narrow down the factors that could cause this poor model performance. Finally, the extreme gradient boosting method gave the importance of each feature included among the potential groundwater level drivers, including the ranked importance of a particular factor and its lag time, at each of the considered groundwater level monitoring sites.

ABSTRACT Design of foundation drain holes in bedrock where fractures control the permeability may be optimized based on the discontinuity pattern, specifically the spacing and orientation of the predominant discontinuity sets. When suitable representative outcrops are available, either naturally or by means of excavation, joint spacing and orientation can be measured directly by traditional methods using a measuring tape and compass or pocket transit or newer methods using computer software to measure virtual joint surfaces within a digital terrain model developed from digital photogrammetry or light detection and ranging (LiDAR) surveys. When suitable outcrops are not available, joint spacing and orientation can be measured using oriented core drilling techniques or downhole imaging tools (e.g., optical and acoustic sondes) that provide digital images of the borehole wall. With an understanding of the bedrock jointing pattern obtained from one or more of the above methods, the total apparent spacing (TAS) approach can be used to optimize the orientation of drain holes. The TAS approach employs the vector dot product formula to minimize the total apparent spacing between discontinuities and maximize the number of discontinuities intercepted by the drain hole. The TAS approach was used to optimize the orientation of foundation drain holes during rehabilitation of the Gilboa Dam in Schoharie County, NY. The TAS approach has other applications, e.g., optimizing the orientation of exploratory core holes to collect discontinuity data or the orientation of grout holes for foundation grouting.

ABSTRACT On November 7, 1882, the largest earthquake in Colorado’s recorded history impacted an area estimated to be 470,000 km2 (181,000 mi2). While differing accounts of intensity were recorded by various communities at the time, the distribution of reported damages indicated a likely magnitude between 6 and 7. This study aimed to refine this estimate using landslides within the region that were likely to be co-seismic. Previously proposed methodology was used to calculate surface roughness values for landslides mapped at various scales digitized and compiled by the Colorado Geological Survey. A search radius of 54 km surrounding the epicentral estimate for the earthquake was chosen to evaluate the relative ages of landslides within the defined region. While the proposed methodology requires a calibration using age-dated landslides within the data set, the use of surface roughness as a relative age scale proved to be sufficiently useful to constrain an area within the study that showed anomalously high surface roughness values. Based on this earthquake being one of the only large earthquakes to have occurred in recorded history in Colorado, as well as a lack of wide distribution in the anomalous region expected from a storm event, this anomalous area containing high surface roughness landslides across varying base lithologies was concluded to have a high probability of being co-seismically induced. Utilizing this information, a new initiation ellipse was generated from these data.

ABSTRACT Site investigations that anticipate soil screening within a risk-based corrective action (RBCA) program often require an understanding of naturally occurring or ambient soil conditions. Because most RBCA programs offer very limited, if any, pre-published values for naturally occurring metals (e.g., arsenic and lead), it is imperative that the risk assessment process be informed by defensible screening-level background threshold values (BTVs). In the absence of representative BTVs, conservative screening levels from the RBCA process may incorrectly “screen in” ambient conditions as a release (false positive or Type I error) when none has occurred. False positives add unnecessary cost and confusion to subsequent investigation or remediation decisions. This article demonstrates an effective approach to developing and evaluating soil data sets for BTV development during any stage of the risk-assessment process. Whereas this article focuses on the most common metals associated with Type I errors (e.g., lead and arsenic), the process to estimate BTVs works for any organic or inorganic contaminants when sufficient data is available. The approach outlined in this article is intentionally conservative in nature to both increase regulatory acceptance and simplify the statistical steps needed for BTV estimation at earlier stages of the risk-assessment process.

Abstract A debris slide and subsequent fire on September 18, 2018, destroyed a bank building and damaged property in Warrensville, North Carolina. The slide pushed a propane tank and an electrical generator against the bank. In that collision, an electrical arc caused the propane to explode, which produced a fireball. Employees in the bank narrowly escaped with minor injuries, and slide debris buried part of an unoccupied drive-through lane. North Carolina Geological Survey geologists responded to a request from the Ashe County Emergency Manager and investigated the slide area to assess slope stability for public safety. Aided by uncrewed aerial system imagery, we documented slope and debris slide features and geologic materials and constructed a geologic cross section through the 1,400 m2 debris slide. We concluded that record above-normal precipitation followed by rainfall from the remnants of Hurricane Florence during September 15–18, 2018, induced the slide, and that geologic conditions and hillside modifications over prior decades had predisposed the slope to failure. Colluvial deposits derived from sheared amphibolite bedrock, and curved trees within and adjacent to the 2018 slide indicated pre-existing marginally stable hillslope conditions. The 2018 slide included the area of a 2000 slide that involved a cut slope constructed during earlier site development. Stability analyses showed that the described conditions led to an unstable slope at the time of the 2018 slide. A septic leach field involved in the 2018 slide was damaged; however, it is uncertain if it was a causal factor in the slide.

Abstract Frozen debris lobes (FDLs) are slow-moving landslides in permafrost. FDL-A, the largest monitored FDL in the Brooks Range of Alaska, has steadily progressed downslope toward the Dalton Highway, which is the only road to the oil and gas fields of the North Slope. To avoid this encroaching landslide, the Dalton Highway was realigned farther downslope in 2018. The abandoned portion of the highway was left in place, providing a unique opportunity for a full-scale field experiment to monitor the impact of a landslide on an engineered structure. In 2020, we conducted a subsurface investigation, drilling and sampling the subsurface soils and installing geotechnical instrumentation within the abandoned highway embankment. Here, we present the integration of multiple datasets to provide a detailed description of the landslide–embankment collision. FDL-A is shearing within weathered bedrock ∼7.6 m below the embankment surface. It horizontally displaced a portion of the embankment ∼0.3 m as of November 1, 2023. Using the infinite slope approach and strength properties determined from laboratory testing, we estimate that FDL-A is impacting the highway embankment and underlying soils with at least 77.8 kN/m width shear force. As this force occurs approximately 4 m below the bottom of the embankment, we postulate that the presence of the abandoned Dalton Highway embankment does little to stop FDL-A’s downslope progression.

Abstract Landslides can cause significant infrastructure damage and thousands of deaths around the world. Colorado Springs has experienced numerous damaging landslides that have not been previously geophysically investigated due to its geological and climatic conditions as well as increased urban development into landslide-prone areas. In 2015, heavy rainfall caused the Skyway and Broadmoor Bluffs landslides that destroyed 30 homes. In this study, these two landslides were studied using the electrical resistivity method to evaluate the nature of the landslides. Two-dimensional inverse models constrained by geological and borehole data indicate that both landslides occurred within the weathered portion of the Cretaceous Pierre Shale. The depth to the landslide failure surface ranged between 3 to 6 m and 6 to 8 m for the Skyway and the Broadmoor landslides, respectively. Both landslides have characteristics of a rotational-type landslide, but three models (two for Skyway, one for Broadmoor) do not have smooth failure surfaces. The Pierre Shale is characterized by significantly lower resistivity than the overlying clay. This suggests the landslide failure was promoted by high moisture content within the Pierre Shale. Therefore, the Skyway and Broadmoor areas need to be monitored for future landslides during high-precipitation events. Additional geophysical data are needed to fully determine the nature and extent of the landslides in Colorado Springs. Our results present the first subsurface models of the Skyway and Broadmoor landslides. City planners can use these models as critical data for mitigating future landslides, which can be used for future urban development.

Abstract Large, deep-seated landslides typically occur in hillside settings without any natural buttressing, and many of these landslides remain relatively unstable and prone to reactivation. However, where large, deep-seated landslides have moved into incised valleys that subsequently experienced alluvial aggradation, a natural buttress of alluvium may cover the toes of these landslides, increasing stability. This study presents three examples of large, deep-seated landslides that are buttressed by Quaternary alluvium. The McCracken Hill Landslide in southern California and the Potrero Canyon Landslide Complex in central California are proximal to the Pacific coast. The Knights Valley Landslide Complex in northern California is much farther inland than the other examples. We analyzed the stability of one of the example landslides to demonstrate that a buttress of alluvium increases stability. In most settings, base level primarily controls alluvial aggradation. Base-level rise may result from either climatically driven late Quaternary eustatic sea-level rise or local factors such as damming of streams or downstream tectonic uplift. Late Quaternary eustatic sea-level rise caused alluvial aggradation at the McCracken Hill and Potrero Canyon sites. Downstream tectonic uplift likely caused local base-level rise and alluvial aggradation at Knights Valley.

Abstract An important first step in the geotechnical asset management of Great Smoky Mountains National Park (GRSM) is the creation of an unstable slope inventory along major transportation corridors. Slope-stability problems are frequent in GRSM, often initiated in highly weathered and fractured metasedimentary rocks. In this study, an unstable slope inventory was created using the Unstable Slope Management Program for Federal Land Management Agencies protocols. Hazards and risks were evaluated for 285 unstable slopes along 243.67 km of roadway. Kernel density estimation was used to identify unstable slope hotspots and establish 14 sites for site-specific investigations to evaluate potential impacts of discrete unstable slopes along major roadways. Two-dimensional probabilistic rockfall simulations and acid-base accounting tests were used to predict rockfall pathways and evaluate the acid-producing potential of rocks. Simulations indicated that rock material would likely enter the roadway at all 14 sites. Acid-base accounting test results indicated that slaty rocks of the Anakeesta Formation and graphitic schist of the Wehutty Formation are primary acid-producing rocks in rockfall-prone areas. This research illustrates an approach for prioritizing areas for site-specific investigations towards the goal of improving safety in GRSM, including developing mitigation strategies for rockfall by widening ditches, installing barriers, and encapsulating acidic rockfall material.