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USGS2025

Review and synthesis of the applications of machine learning to coalbed methane recovery

Over the last 30 years, a substantial literature has evolved on the use of machine learning (ML) to assess, predict, and improve the efficiency of coalbed methane (CBM) recovery. In the United States, the production of CBM declined as shale gas production matured, but CBM continues to be an important energy resource in other parts of the world. ML applications that have the potential to improve CBM reservoir management and production forecasts, and to increase exploration and operational efficiency, are still of significant interest. The integration of geostatistical techniques into the CBM ML applications has been largely absent but represents an opportunity for improvement. The literature demonstrates the widespread interest in, and applicability of, ML algorithms applied to CBM problems, and that they continue to result in improvements in predictive performance. However, (1) much of the research is more academic than operational, (2) many results are based on simulations, or small or proprietary datasets, (3) ML performance information can be inconsistent and sometimes entirely omitted, (4) most methodologies are unique to the specific CBM situation and likely not generalizable, (5) no standard data repositories are available to directly compare the performance of competing algorithms, and (6) the spatial component is often omitted. Finally, relatively new ML protocols involving causality analysis and reinforced learning, as well as hybrid workflows combining both supervised and unsupervised learning, are anticipated to dominate the future investigations. Integration of geostatistical and geospatial analysis with ML should enhance performance.

Book chapter↗
USGS2024

Limited preservation of strike-slip surface displacement in the geomorphic record

Offset geomorphic markers are commonly used to interpret slip history of strike-slip faults and have played an important role in forming earthquake recurrence models. These data sets are typically analyzed using cumulative probability methods to interpret average amounts of slip in past earthquakes. However, interpretation of the geomorphic record to infer surface slip history is complicated by slip variability, measurement uncertainty, and modification of offset features in the landscape. To investigate how well geomorphic data record surface slip, we use offset measurements from recent strike-slip surface ruptures ( n = 39), faults with geomorphic evidence of multiple strike-slip earthquakes ( n = 29), and synthetic slip distributions with added noise ( n > 10,000) to examine the constraints of the geomorphic record and the underlying assumptions of the cumulative offset probability distribution analysis method. We find that the geomorphic record is unlikely to resolve more than two paleo-slip distributions, except in specific cases with low slip variability, high slip-per-event, and semiarid climate. In cases where site-specific conditions allow for interpretation of more than two earthquakes, lateral extrapolation along a fault is not straightforward because on-fault displacement and distributed deformation may be spatially variable in each earthquake. We also find that average slip in modern earthquakes is adequately recovered by probability methods, but the reported prevalence of strike-slip faults with characteristic slip history is not supported by geomorphic data. We also propose updated methods to interpret slip history and construct uncertainty bounds for paleo-slip distributions.

Journal of Geophysical Research: Solid Earth↗
USGS2024

RegionGrow3D: A deterministic analysis for characterizing discrete three-dimensional landslide source areas on a regional scale

Regional-scale characterization of shallow landslide hazards is important for reducing their destructive impact on society. These hazards are commonly characterized by (a) their location and likelihood using susceptibility maps, (b) landslide size and frequency using geomorphic scaling laws, and (c) the magnitude of disturbance required to cause landslides using initiation thresholds. Typically, this is accomplished through the use of inventories documenting the locations and triggering conditions of previous landslides. In the absence of comprehensive landslide inventories, physics-based slope stability models can be used to estimate landslide initiation potential and provide plausible distributions of landslide characteristics for a range of environmental and forcing conditions. However, these models are sometimes limited in their ability to capture key mechanisms tied to discrete three-dimensional (3D) landslide mechanics while possessing the computational efficiency required for broad-scale application. In this study, the RegionGrow3D (RG3D) model is developed to broadly simulate the area, volume, and location of landslides on a regional scale (≥1,000 km 2 ) using 3D, limit-equilibrium (LE)-based slope stability modeling. Furthermore, RG3D is incorporated into a susceptibility framework that quantifies landsliding uncertainty using a distribution of soil shear strengths and their associated probabilities, back-calculated from inventoried landslides using 3D LE-based landslide forensics. This framework is used to evaluate the influence of uncertainty tied to shear strength, rainfall scenarios, and antecedent soil moisture on potential landsliding and rainfall thresholds over a large region of the Oregon Coast Range, USA.

Journal of Geophysical Research: Earth Surface↗
USGS2025

What 25+ years of "Did You Feel It" intensities tell us about shaking in California

“When will the Big One happen?” is a question that people often have for earthquake scientists. But while waiting for the “Big One” to occur, people will usually experience frightening or damaging shaking from multiple relatively smaller‐magnitude earthquakes. Given this context, it raises the question: “Where does most of the damage come from?” Could smaller, yet more frequent, earthquakes account for the majority of reported impactful shaking? To explore this question, we consider reports of earthquake damage and felt shaking experiences from a catalog of community‐collected intensity values from the U.S. Geological Survey’s “Did You Feel It?” system. Comparing these intensities to expectations from a ground‐motion model, we find that earthquakes of magnitudes smaller than expected are responsible for most reported intensities of community decimal intensities (CDI) 4.5 and above (moderate and higher shaking intensity levels). (Here “expected value” is meant in its mathematical sense of the mean or equivalently median shaking intensity.) We also present a regional analysis of observed earthquake shaking for specific areas, detailing the maximum intensity experienced within a predetermined area. We identify several instances of M < 4.5 events that generated maximum intensities of CDI > 5 in regions in California surrounding the cities of Eureka, San Francisco, Los Angeles, and San Diego. Our results motivate the need to include smaller‐magnitude earthquakes in communications about earthquake hazard and risk reduction.

California↗
USGS2025

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

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

Natural Hazards and Earth System Sciences↗
USGS2026

Corundum discovered by SuperCam and the Perseverance rover at Jezero crater, Mars

Mars is primarily composed of mafic mineral assemblages and their alteration products, but small, scattered rocks strewn across the landscape offer clues to greater petrological diversity. While traversing the Jezero crater rim, the Perseverance rover encountered several plagioclase-rich light-toned float rocks. SuperCam identified the distinctive signature of corundum (α-Al 2 O 3 ) in these rocks using time-resolved luminescence spectroscopy. Two strong peaks (692.7 and 694.1 nm) with millisecond lifetimes, and additional supporting lines, are consistent with Cr 3+ substitution for Al 3+ in corundum. Corundum forms in Al-rich, Si-depleted environments through magmatic or metamorphic processes. Given the rocks' small size, association with plagioclase, and location on the crater rim, we interpret the most plausible formation scenario to be impact induced metamorphism at the interface of a felsic and a mafic/ultramafic member with the likely action of fluids at some stage, although other possibilities are not excluded.

Geophysical Research Letters↗
USGS2024

Onset of aftershocks: Constraints on the Rate-and-State model

Aftershock rates typically decay with time t after the mainshock according to the Omori–Utsu law, R (t)=K(c+t) −p ⁠ , with parameters K , c , and p . The rate‐and‐state (RS) model, which is currently the most popular physics‐based seismicity model, also predicts an Omori–Utsu decay with p = 1 and a c ‐value that depends on the size of the coseismic stress change. Because the mainshock‐induced stresses strongly vary in space, the c ‐value should vary accordingly. Short‐time aftershock incompleteness (STAI) in earthquake catalogs has prevented a detailed test of this prediction so far, but the newly developed a ‐positive method for reconstructing the true earthquake rate now allows its testing. Using previously published slip models, we calculate the coseismic stress changes for the six largest mainshocks in Southern California in recent decades and estimate the maximum shear as a scalar proxy of the coseismic stress tensor. Aftershock rates reconstructed for events in different stress ranges show that the rates follow a power law with p = 1 independent of stress with no clear sign of a c ‐value. The onset of the power‐law decay is abrupt and more delayed in areas with smaller stress changes. The observations do not necessarily contradict the RS model, as STAI limits the resolution for early aftershocks, and the RS model can reproduce the observations for specific Aσ values. However, the observations lead to strong constraints, namely Aσ <10 kPa and a power‐law decay of the background rate with distance to the fault, with exponent 2.7.

Seismological Research Letters↗
USGS2024

Testing rate‐and‐state predictions of aftershock decay with distance

We analyze aftershocks of the 2019 M 7.1 Ridgecrest mainshock and isolated M 5–6 mainshocks in southern California to test predictions made by the rate‐and‐state friction model of Dieterich (1994) . Rate‐and‐state friction predicts that the seismicity rate after a stress step follows Omori decay, where the Omori c ‐value, which is the saturation in aftershock rate observed at small times, is larger for smaller stress steps. Put in the context of an aftershock sequence, this predicts that the Omori c ‐value will be systematically larger at greater distances from the mainshock. To our knowledge, this predicted effect has not been observed. In part this may be because the Omori c ‐value is difficult to measure because it often reflects short‐term catalog incompleteness rather than a true saturation in aftershock rate. We explore the dependence of the Omori c ‐value on the distance to the mainshock by applying the “ a ‐positive” method ( van der Elst and Page, 2023 ). This method is insensitive to short‐term aftershock incompleteness and allows resolution of the true aftershock rate deep into the mainshock coda. For aftershocks of the Ridgecrest mainshock and stacked M 5–6 mainshocks, we observe systematic differences in early aftershock rates, relative to mainshock distance, consistent with the predictions of rate‐and‐state friction. Furthermore, for the larger Ridgecrest dataset, we observe that aftershocks nearer to the mainshock start earlier, and we resolve a flattening of the Omori curve consistent with a larger Omori c ‐value for the farthest aftershocks, as predicted by Dieterich (1994) .

Seismological Research Letters↗
USGS2026

Moment magnitude for small earthquakes in the Delaware basin of west Texas and southeast New Mexico, USA

The Delaware Basin region of west Texas and southeast New Mexico has become one of the most prolific regions of seismic activity in the continental United States due to widespread hydraulic fracturing and wastewater disposal injection. In response to the increased number of earthquakes in this region, rapid and accurate characterization of earthquake sources is necessary to understand the evolution of seismic activity and level of seismic hazard associated with these earthquakes. This study re-evaluates earthquake magnitudes, estimating moment magnitude (MW) for small earthquakes in the Delaware Basin using 1) moment-rate spectra derived from S-wave coda envelopes, and 2) a relative magnitude method that relies exclusively on the ratio of waveform amplitudes between highly correlated waveform pairs. The coda-envelope method produces accurate M W estimates for small earthquakes ( M 1.5 – 3) that are consistent with independent, waveform modeled moment magnitudes for events with M W > 3 . Using the relative amplitudes method to extend these M W magnitudes to many other events, we successfully provide relative moment magnitude ( M W,rel ) values for 81% of the Texas Seismological Network catalog in the Delaware Basin region, and 45% of the USGS Induced Seismicity Project’s catalog of events in southeast New Mexico. The adoption and integration of the calibrated M W,rel method with current magnitude estimation methods offers valuable insights into the relationships between local and moment magnitude and will contribute to improved characterization of widespread induced seismicity.

New Mexico, Texas↗
USGS2023

Slow slip detectability in seafloor pressure records offshore Alaska

In subduction zones worldwide, seafloor pressure data are used to observe tectonic deformation, particularly from megathrust earthquakes and slow slip events (SSEs). However, such measurements are also sensitive to oceanographic circulation-generated pressures over a range of frequencies that conflate with tectonic signals of interest. Using seafloor pressure and temperature data from the Alaska Amphibious Community Seismic Experiment, and sea surface height data from satellite altimetry, we evaluate the efficacy of various seasonal and oceanographic pressure signal proxy corrections and conduct synthetic tests to determine their impact on the timing and amplitude prediction of ramp-like signals typical of SSEs. We find that subtracting out the first mode of the complex empirical orthogonal functions of the pressure records on either the shelf or slope yields signal root-mean-square error (RMS) reductions up to 73% or 80%, respectively. Additional correction with proxies that exploit the depth-dependent spatial coherence of pressure records provides cumulative variance reductions up to 83% and 93%, respectively. Our detectability tests show that the timing and amplitude of synthetic SSE-like ramps can be well constrained for ramp amplitudes ≥4 cm on the shelf and ≥2 cm on the slope, using a fully automated detector. The principal limits on detectability are residual abrupt changes in pressure that occur as part of the transition to and from summer to winter conditions but are not adequately characterized by our seasonal corrections, as well as the inability to properly account for instrumental drift, which is not readily separated from the seasonal signal.

Alaska↗
USGS2025

Airborne geophysical analysis to decipher salinization for coastal Louisiana

Coastal Louisiana is known for saltwater intrusion that threatens wetlands, aquifers, and rivers. However, the extent of saltwater intrusion is not well understood. This study develops an innovative framework with airborne electromagnetic (AEM) data to map chloride concentration distributions for wetlands in the Mississippi River deltaic plain and Chenier plain as well as for the Mississippi River Valley alluvial aquifer (MRVA) and Chicot aquifer. Moreover, the framework maps chloride concentrations along the Mississippi River and Atchafalaya River. Key components in the framework include the establishment of resistivity-to-chloride concentration transformation, 3D resistivity architecture building through geostatistics, and the employment of a lithologic model. The transformation functions correlate AEM resistivity data with porewater salinity measurements and groundwater and river chloride samples. The results show that AEM data reliably infers soil water chloride concentrations and correlates well with the distribution of various marsh types. AEM data reveals extensive saltwater presence at depth and near the coast, originating from salt domes and the Gulf of Mexico, respectively. The saltwater upconing pattern in the Chicot aquifer is likely due to excessive groundwater withdrawals. The AEM data also confirms a distinct tongue of saltwater intruding into the Atchafalaya Basin from the Gulf. The AEM data helps to identify faults that are obscured or eroded at the surface, which appear as leaky barriers in the subsurface where dramatic changes in chloride concentration are apparent. Finally, this study uses the AEM data to infer the presence of an extensive seawater wedge in the Mississippi River and Atchafalaya River.

Louisiana↗
USGS2025

Uncertainty reduction for subaerial landslide-tsunami hazards

Subaerial rock slopes may generate a tsunami by rapidly moving into the water. Large uncertainty in landslide characteristics propagates into large uncertainty in tsunami hazard, making hazard assessment more difficult for land and emergency managers. Once a potentially tsunamigenic landslide is identified, it may not be clear which landslide characteristics contribute most significantly to uncertainty in the tsunami hazard. Our aim is to document the relative worth of different landslide characteristics (e.g., size, material properties) for reducing uncertainty in landslide-tsunami hazard assessments. Isolating the relative importance of specific landslide characteristics may inform prioritization of data collection and improve efficiency in understanding hazard. To accomplish this, we generated a set of 288 landslide-tsunami simulations in which we systematically varied the size and material properties of possible failure extents at the Barry Arm landslide complex in northwestern Prince William Sound, Alaska, USA. We find that for landslides smaller than the receiving waterbody, the landslide volume has the strongest effect on resulting wave characteristics and thus the highest leverage on reducing uncertainty in tsunami hazard. In contrast, for landslides substantially larger than the waterbody, the duration of rapid movement of the landslide has the highest leverage. Based on our results, we propose a classification scheme for subaerial landslides based on the relative size of the landslide and waterbody. Additionally, our results support the generation of a tsunami height transfer function between existing tide gages and a nearby coastal city. These results have direct implications for the practice of operational early warning.

Alaska↗
USGS2025

Petrogenesis and mineralization potential of spinifex komatiitic basalts in the Bradley Peak greenstone terrane, Wyoming Province

Komatiitic volcanic rocks are important hosts of Ni sulfide mineralization and record early Earth evolution; however, those in the well-studied Archean Wyoming Province have received little attention. Here, we elucidate the timing and petrogenesis of the Bradley Peak komatiitic volcanic rocks using field and textural observations, geochronology, and geochemistry. Detrital and igneous zircon U-Pb ages for two samples from previously undated units support published age determinations, placing the eruption age at 2.72 Ga. Stratigraphy of the volcanic flows was mapped and 36 samples including cumulates, greenschists, and spinifex-textured rocks were collected. Whole-rock geochemistry was used to classify the spinifex-textured samples as Al-undepleted komatiitic basalts (11–17 wt% MgO). Platinum-group element concentrations (n = 25) are like those in global Al-undepleted komatiitic basalts, and PGE/Ti ratios do not indicate the volcanic flows likely host sulfide mineralization. Initial ε Nd values of −0.5 to +4.7 (n = 16), indicate that these lavas were derived from a depleted mantle source and have negligible evolved crust contamination. The primary magma to the komatiitic basalt flows is estimated to have had 19 wt% MgO and be derived from ∼15 to 25 % mantle partial melting at 3–4 GPa. Trace element chemistry and thermodynamic modeling suggest the primary melt assimilated local banded iron formation. Although the Bradley Peak komatiitic basalts do not contain positive evidence of magmatic sulfide deposits, depleted Au in the flows suggests they could be source rocks for nearby orogenic gold deposits.

Wyoming↗
USGS2025

Timescales of surface faulting preservation in low-strain intraplate regions from landscape evolution modeling and the geomorphic and historical record

Large surface-rupturing intraplate earthquakes in stable continental regions (SCRs) are uncommon globally and have recurrence intervals of thousands to hundreds of thousands of years based on the paleoseismic and geomorphic record, challenging accurate active fault identification in these regions. To constrain the timescales of preservation for scarps created by surface ruptures from dip-slip earthquakes, we use a two-dimensional scarp diffusion model for typical intraplate settings and explore which parameters influence fault scarp preservation. These parameters include the coseismic vertical surface offset, the recurrence interval of similar magnitude earthquakes, diffusivity (as a proxy for mean annual precipitation rate), and the erodibility of the surficial material. We constrain parameter ranges from a compilation of historical surface ruptures in intraplate settings in a variety of climates, including the Central and Eastern United States, Australia, Europe, Central Asia (Mongolia, China), India, and West Africa. The timescales of scarp preservation from landscape evolution modeling agree well with observations of scarp preservation in low-strain SCR and intraplate tectonic settings, with some notable exceptions for Australian scarps. We find that the erodibility of the surficial material and earthquake recurrence interval have a stronger effect on the timescales of scarp preservation than diffusivity or coseismic vertical surface offset. Our model results may aid in identifying and characterizing subtle, slow-moving active faults in low-strain SCR and intraplate tectonic settings for different tectonic, geomorphic, and climatic characteristics. Accurate fault locations and characterization from the landscape record has implications for both probabilistic seismic and fault displacement hazard analyses.

Journal of Geophysical Research Solid Earth↗
USGS2023

Prediction of the probability of elevated nitrate concentrations at groundwater depths used for drinking-water supply in the Puget Sound basin, Washington, 2004–19

The Puget Sound basin encompasses the 13,700-square-mile area that drains to the Puget Sound and the adjacent marine waters of Washington State. Well more than 4 million people live within the basin, with numbers continuing to increase, who rely on the basin’s natural resources including groundwater. The Puget Sound Partnership was created by a Washington State statute to implement a science-based recovery of the Puget Sound to help address impacts to these resources. As part of the recovery, the partnership developed the Puget Sound Vital Signs as measures of ecosystem health that guide the assessment of progress toward Puget Sound recovery goals. The Puget Sound Partnership Leadership Council adopted a Drinking Water Vital Sign associated with human health and quality of life, recognizing certain indicators as integral to the sustainability of Puget Sound recovery efforts. One such Vital Sign indicator was the vulnerability of groundwater throughout the aquifers of the Puget Sound basin to elevated nitrate concentrations as defined by the probability of exceeding 2 milligrams/liter (mg/L) at a specific location and well depth. The U.S. Geological Survey (USGS) led the effort to characterize groundwater vulnerability. For this study, groundwater vulnerability refers to a probability with which a contaminant applied at or near the land surface can migrate to the aquifer of interest for a given set of land-use practices. Nitrate concentration data were selected for evaluation because elevated nitrate concentrations are typically caused by anthropogenic activities and have been associated with deleterious impacts on human health. To identify groundwater vulnerability to elevated nitrate concentrations, logistic regression was used to relate anthropogenic (human associated) and natural variables to the occurrence of elevated nitrate concentrations in untreated groundwater from large public water supply system wells found within the Washington State Department of Health Sentry database. Variables that were analyzed included well depth, soil hydraulic conductivity, precipitation, population density, fertilizer application amounts, and land-use types. Statistically significant models that predicted the probabilities of groundwater nitrate concentrations greater than 2 mg/L based on the predictor variables were created for the time periods 2000–04, 2005–09, 2010–14, and 2015–19. For all time periods, well depth and a measure of the abundance of urban and agricultural land over or near the well consistently helped explain the vulnerability of the well to elevated nitrate concentrations defined as a probability of exceeding 2 mg/L of nitrate. Precipitation and (or) soil hydraulic conductivity were also important predictor variables in the models. The models for each time period were used to create maps of groundwater vulnerability at 150- and 300-foot depths throughout the Puget Sound basin. As expected, the most vulnerable locations were associated with shallower well depths and increased agriculture and urban land cover. Across all four time periods, groundwater vulnerability throughout the Puget Sound was low, with probabilities of exceeding 2 mg/L concentrations of nitrate at depths at 150 and 300 feet typically less than 50 percent. Results also found a slight decrease in probabilities of elevated nitrate concentrations throughout the basin over time. More specifically, additional statistical tests found that groundwater with probabilities of less than about 60 percent declined from 2000 to 2019 and represented more than 75 percent of the modeled Puget Sound basin aquifer. Wells with greater than 60 percent probability increased over the same time period but represented only about 25 percent of the aquifer. The maps and statistical analysis presented in the study provide valuable and informative evaluation of the vulnerability of groundwater in the Puget Sound basin to elevated nitrate concentrations. The probability maps do not represent measured nitrate concentrations in groundwater, but rather they present the probability that nitrate concentrations exceed 2 mg/L. The models and predictions from this study are a viable indicator for the Puget Sound Partnership’s Healthy Human Population—Drinking Water Vital Sign. The logistic regression modeling approach presented here benefits water managers by allowing them to assess temporal trends in a range of probabilities, explore vulnerability changes as new regional land cover and anthropogenic data are generated, and distinguish vulnerabilities at different depths within the aquifer.

Washington↗
USGS2024

Constraining mean landslide occurrence rates for non-temporal landslide inventories using high-resolution elevation data

Constraining landslide occurrence rates can help to generate landslide hazard models that predict the spatial and temporal occurrence of landslides. However, most landslide inventories do not include any temporal data due to the difficulties of dating landslide deposits. Here we introduce a method for estimating the mean landslide occurrence rate of deep-seated rotational and translational slides derived solely from high-resolution (≤3 m) elevation data and globally available estimates of the diffusion coefficient for sediment flux. The method applies a linear diffusion model to the roughest landslide deposits until they reach a representative non-landslide roughness distribution. This estimates the time for a landslide deposit to be unrecognizable in high-resolution digital elevation data, which we term the mean lifetime of the landslide. Using the mean lifetime and number of landslides within an area of interest, we can estimate the mean occurrence rate of landslides over that domain. We validate this approach using a comprehensive temporal inventory of landslides in western Oregon created using age-roughness curves that are calibrated with high-resolution elevation data and radiocarbon data. We find good agreement between our diffusion method and the existing age-roughness-derived estimates, producing mean lifetimes of 4500 and 5200 years (4% difference), respectively. Hazard maps produced using the two methodologies generally agree, with the maximum differences in landslide probability reaching 0.1. Due to the relative abundance of high-resolution elevation data compared with age-dated landslides, our method could help constrain landslide occurrence rates in areas previously considered unfeasible.

Oregon↗
USGS2025

Updating regional‐scale geospatial liquefaction models with locally available geotechnical data

We present a method to update the geospatial liquefaction model used by the U.S. Geological Survey’s near‐real‐time ground failure product with subsurface geotechnical data. The geospatial model estimates liquefaction probability from peak ground velocity (via ShakeMap) and geospatial susceptibility proxies. In many regions, additional information relevant to constraining liquefaction likelihood is also available, including surface geology maps and subsurface geotechnical measurements. There is currently no mechanism to use these data in the ground failure product liquefaction model, even though these data could provide more precise constraints on spatial variations in the lithologic character of the soil (surface geology) and direct measurements of the subsurface mechanical properties that affect liquefaction occurrence and severity (geotechnical measurements). In this study, we develop a method to integrate these data with the geospatial model and assess how these data can improve regional‐scale predictions. We develop a Bayesian updating framework and apply it to the 1989 magnitude 6.9 Loma Prieta, California, earthquake, for which mapped observations are available to evaluate performance. We constrain the Bayesian framework with 373 Northern California cone penetration tests and liquefaction susceptibility classes based on the mapped surface geology. This Bayesian model incorporates geotechnical information into the geospatial model and more accurately predicts liquefaction occurrences than the geospatial model, while sacrificing less accuracy in terms of predicting the absence of liquefaction than the geotechnical model. In future applications, this approach could be adapted to update other geospatial models using locally available subsurface data.

California↗
USGS2025

Using hydrogeologic context and water budgets to evaluate the potential for groundwater contributions to contaminants in Lake Superior

This study presents a synthesis of the hydrogeology in the U.S. Lake Superior watershed and the contribution of groundwater to the water budget of the U.S. Lake Superior basin. Much of the shoreline of Lake Superior in Minnesota and Michigan is composed of hydrogeologic units contributing very little direct groundwater discharge to the lake. Groundwater in watersheds adjacent to the lake typically flows in short, local flow systems characterized by thin glacial sediments with active groundwater flow in fractured bedrock within the top 60–90 m below land surface. The complex groundwater system in Wisconsin’s Bayfield Peninsula has the largest groundwater reservoir near the lake, characterized by thick sand and gravel glacial deposits and underlying sandstone aquifer. Although these thick sandy glacial deposits are not in direct contact with the lake at the shoreline, groundwater discharge may still be significant via subsurface exposures beyond the shoreline or flow through the underlying sandstone aquifer. Overall, most groundwater in the watershed is contributed as indirect base flow in streams around the lakeshore and comprises about 60 percent of the upland water budget. Direct groundwater flow to the shoreline contributes 2 to 9 percent of the inflow. Identifying possible contamination sources through direct sampling of groundwater would be an inefficient way to detect problems if sources are unknown, particularly for some chemicals of concern such as PFAS, pesticides, PCBs, chloride, and nutrients. Evaluating the chemical characteristics of contamination is also important to consider in evaluating how groundwater may contribute to pollution in Lake Superior.

Lake Superior↗