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USGS2024

Isotopic evaluation of the National Water Model reveals missing agricultural irrigation contributions to streamflow across the western United States

The National Water Model (NWM) provides critical analyses and projections of streamflow that support water management decisions. However, the NWM performs poorly in lower-elevation rivers of the western United States (US). The accuracy of the NWM depends on the fidelity of the model inputs and the representation and calibration of model processes and water sources. To evaluate the NWM performance in the western US, we compared observations of river water isotope ratios ( 18 O / "> 16 O and 2 H / "> 1 H expressed in δ notation) to NWM-flux-estimated (model) river reach isotope ratios. The modeled estimates were calculated from long-term (2000–2019) mean summer (June, July, and August) NWM hydrologic fluxes and gridded isotope ratios using a mass balance approach. The observational dataset comprised 4503 in-stream water isotope observations in 877 reaches across 5 basins. A simple regression between observed and modeled isotope ratios explained 57.9 % ( δ 18 O) and 67.1 % ( δ 2 H) of variance, although observations were 0.5 ‰ ( δ 18 O) and 4.8 ‰ ( δ 2 H) higher, on average, than mass balance estimates. The unexplained variance suggest that the NWM does not include all relevant water fluxes to rivers. To infer possible missing water fluxes, we evaluated patterns in observation–model differences using δ 18 O diff ( δ 18 O obs − δ 18 O mod ) and d diff ( δ 2 H diff - 8 ⋅ δ 18 O diff "> ). We detected evidence of evaporation in observations but not model estimates (negative d diff and positive δ 18 O diff ) at lower-elevation, higher-stream-order, arid sites. The catchment actual-evaporation-to-precipitation ratio, the fraction of streamflow estimated to be derived from agricultural irrigation, and whether a site was reservoir-affected were all significant predictors of d diff in a linear mixed-effects model, with up to 15.2 % of variance explained by fixed effects. This finding is supported by seasonal patterns, groundwater levels, and isotope ratios, and it suggests the importance of including irrigation return flows to rivers, especially in lower-elevation, higher-stream-order, arid rivers of the western US.

Hydrology and Earth Systems Science↗
USGS2025

Migration of seismicity from the mantle to the upper crust beneath Harrat Lunayyir volcanic field, Saudi Arabia

Harrat Lunayyir is a volcanic field in Saudi Arabia that experienced a Mw~5.4 earthquake driven by an upper-crustal dike intrusion in May 2009. This volcanic field has exhibited numerous forms of volcanic seismicity both prior to and since the 2009 dike intrusion. Significantly, earthquakes within the lithospheric mantle and, rarely, the lower crust are present in the two-decade long seismicity catalog of Harrat Lunayyir. Here we analyze 24 years of volcanic seismicity at Harrat Lunayyir from 1998 to 2022. We find that: 1) precursory seismicity began at least eight years prior to the 2009 event, with a particularly notable seismic episode one year prior; 2) lithospheric mantle seismicity is highly localized in space and in time, largely occurring in discrete sequences lasting on the order of a few hours to a few days; 3) one seismic sequence clearly migrates upward from the lithospheric mantle to the upper crust, including seismicity within the nominally ductile lower crust; 4) crustal seismicity has been slowly declining over time; and 5) lithospheric-mantle seismicity does not show any apparent decline with time. From these observations we infer that the seismicity is driven by magmatic fluids or volatiles, and seismic monitoring of this volcanic field should continue into the future.

Harrat Lunayyir volcanic field↗
USGS2024

Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall

Communities downstream of burned steep lands face increases in debris-flow hazards due to fire effects on soil and vegetation. Rapid postfire hazard assessments have traditionally focused on quantifying spatial variations in debris-flow likelihood and volume in response to design rainstorms. However, a methodology that provides estimates of debris-flow inundation downstream of burned areas based on forecast rainfall would provide decision-makers with information that directly addresses the potential for downstream impacts. We introduce a framework that integrates a 24 h lead-time ensemble precipitation forecast with debris-flow likelihood, volume, and runout models to produce probabilistic maps of debris-flow inundation. We applied this framework to simulate debris-flow inundation associated with the 9 January 2018 debris-flow event in Montecito, California, USA. When the observed debris-flow volumes were used to drive the probabilistic forecast model, analysis of the simulated inundation probabilities demonstrates that the model is both reliable and sharp. In the fully predictive model, however, in which debris-flow likelihood and volume were computed from the atmospheric model ensemble's predictions of peak 15 min rainfall intensity, I 15 , the model generally under-forecasted the inundation area. The observed peak I 15 lies in the upper tail of the atmospheric model ensemble spread; thus a large fraction of ensemble members forecast lower I 15 than observed. Using these I 15 values as input to the inundation model resulted in lower-than-observed flow volumes which translated into under-forecasting of the inundation area. Even so, approximately 94 % of the observed inundated area was forecast to have an inundation probability greater than 1 %, demonstrating that the observed extent of inundation was generally captured within the range of outcomes predicted by the model. Sensitivity analyses indicate that debris-flow volume and two parameters associated with debris-flow mobility exert significant influence on inundation predictions, but reducing uncertainty in postfire debris-flow volume predictions will have the largest impact on reducing inundation outcome uncertainty. This study represents a first step toward a near-real-time hazard assessment product that includes probabilistic estimates of debris-flow inundation and provides guidance for future improvements to this and similar model frameworks by identifying key sources of uncertainty.

California↗
USGS2026

Temporal and spatial changes in seismic attenuation associated with inferred fluid migration in the 2016 central Apennines earthquake sequence

Prior work suggests that high‐frequency seismic attenuation acts as a highly sensitive proxy for crustal permeability and fluid mobility in fractured media. We test the hypothesis that the fault system responsible for the 2016–2017 Amatrice–Visso–Norcia–Capitignano sequence acted as an impermeable seal, compartmentalizing pressurized fluids until dynamic rupture triggered widespread fluid diffusion. By tracking across the sequence the spatiotemporal evolution of the S ‐wave anelastic attenuation parameter, we identify large, positive low‐frequency attenuation anomalies emerging within the hanging wall following the Amatrice mainshock and strictly preceding subsequent large ruptures. Conversely, we observe weaker, negative anomalies in the footwall, anticorrelated in time with those of the hanging wall, revealing a massive asymmetry in fluid redistribution and permeability evolution across the fault system. Furthermore, aftershock migration rates reveal distinct linear alignments in a distance‐reduced time space, allowing us to explicitly track and quantify episodes of lateral and upward fluid migration. These physically consistent patterns suggest that stress‐driven fluid diffusion directly weakens adjacent fault patches, dictating the spatiotemporal migration of seismicity. We conclude that near‐real‐time monitoring of seismic attenuation may help detect fluid redistribution in active fault systems and may provide useful information for time‐dependent seismic hazard assessment.

central Apennines↗
USGS2026

Characterizing changes in postfire debris-flow hazard as burned areas recover

Emergency assessments of postfire debris-flow hazards that are performed by the U.S. Geological Survey (USGS) provide estimates of debris-flow likelihood and rainfall triggering conditions that are used for evaluating and managing runoff-generated debris-flow hazards in recently burned areas throughout the western United States. Although the immediate postfire period, within roughly one year after fire, is typically the most susceptible to runoff-generated debris flows, the hazard evolves in time and space as the burned area recovers. The recovery trajectory a given burned area will take depends on local climate and weather and can be difficult to predict. Some burned areas recover quickly, whereas others experience debris flows for multiple years after fire. As a result, extending our ability to update debris-flow likelihood estimates and rainfall thresholds based on observed recovery of the burned area would be beneficial. We present a method for multi-year runoff-generated debris-flow hazard assessment that leverages the USGS “M1” debris-flow likelihood model and integrates updated, satellite-derived, normalized burn ratio data to estimate vegetation recovery. We predict recovery-aware rainfall thresholds and validate them against a multi-year debris-flow hazard prediction and could be adapted for use with other debris-flow models that incorporate burn severity data.

Arizona, California, Colorado, New Mexico, Washing↗
USGS2022

South Carolina and Landsat

South Carolina, the eighth State admitted to the union, transcends its size with its deep, rich history; striking beauty; vast natural resources; and extensive cultural diversity. Home to part of the Blue Ridge Mountains of the Central Appalachians, the Upstate is graced with more than 100 waterfalls, while the Lowcountry borders the Atlantic Ocean with 187 miles of coastline and 35 barrier islands. Forests cover two-thirds of the State, and forestry and agriculture together, as agribusiness, make up South Carolina’s leading industry. Two historic crops—cotton and tobacco—still rank in the top 10 commodities, though corn and soybeans now rank higher. Poultry, cattle, peanuts, and flowers also make the list. South Carolina’s population totals more than five million. Other residents include a variety of wildlife, bird, reptile, and fish species, including Ursus americanus (black bears), Alligator mississippiensis (American alligators), and Tursiops truncatus (bottlenose dolphins). More than 100 tree species also reside in South Carolina, which pays homage to one with its “The Palmetto State” nickname. South Carolina’s subtropical climate, long coastline, and lower elevations make it highly susceptible to tornado and hurricane activity and coastal flooding. Projected sea-level rise is a growing concern. A view from space can help monitor and manage natural resources on the land and in rivers, marshes, and the coast. Landsat reveals not just what an area looks like now, but also insights from decades ago.

South Carolina↗
USGS2025

Estimation of dynamic geologic CO2 storage resources in the Illinois Basin, including effects of brine extraction, anisotropy, and hydrogeologic heterogeneity

Since the vast majority of carbon dioxide (CO 2 ) storage resources in the United States are in deep saline aquifers, optimizing the use of these saline storage resources could be crucial for efficient development of geologic CO 2 storage (GCS) resources and basin- or larger-scale deployment of GCS in the country. Maximum CO 2 injection rates can be enhanced by extracting brine from the CO 2 storage unit. However, disposal of the extracted brine is both a technological and economic challenge. The lowest-cost option would likely be reinjection of the extracted brine into another formation above or below the CO 2 storage unit. Therefore, it is important to estimate brine injectivity as it will constrain the potential to increase CO 2 injectivity at an injection site that has access to multiple geologic storage units where either CO 2 or brine can be injected. Using a simulation-optimization framework, coupled with a non-isothermal, multiphase CO 2 -water-salt equation-of-state module, we developed a computationally efficient method for evaluating optimization of simultaneous CO 2 injection, brine extraction, and brine (re)injection at hypothetical injection sites deployed across a geologic basin. The Illinois basin is ideal for testing our methodology because it contains multiple geologic storage units with seals in between them to isolate injection of CO 2 in one unit from interfering with the injection of either brine or CO 2 in another unit above or below it. In addition, we investigated the relative effects of variation in key geologic parameters as well as two reservoir structures (hydrogeologic heterogeneity/anisotropy and homogeneity/isotropy) on CO 2 injectivities and enhancement of CO 2 injectivity through extracting brine. Results suggest that permeability, depth, and especially thickness of the storage unit could be the most influential parameters determining CO 2 injectivity. They also suggest that only injecting CO 2 into the storage unit with the greatest injectivity, enhancing that unit’s injectivity by extracting brine, and disposing of the produced brine in other suitable units could maximize total CO 2 injectivity in limited regions of the basin. At the majority of simulated injection sites, however, we found that injecting CO 2 into all of the accessible and suitable storage units was more likely to maximize the CO 2 storage resource.

Illinois, Kentucky, Indiana↗
USGS2026

Microtextural characteristics of adularia in banded quartz veins from the Midas low-sulfidation epithermal deposit, Nevada

High-grade ores at the Miocene Midas low-sulfidation epithermal deposit in northern Nevada are confined to crustiform quartz veins containing abundant adularia. Micro-X-ray fluorescence elemental mapping reveals that adularia is a common gangue mineral occurring in colloform bands, bands showing bladed textures, and bands with dendritic terminations. The adularia aggregates have delicate shapes and are comprised of stacked, submillimeter crystals hosted by fine-grained quartz. The textural evidence suggests that the adularia aggregates originally formed within a gel-like, noncrystalline silica matrix, which subsequently transformed into quartz. This indicates that the adularia did not precipitate in open space along the vein walls. Correlative microscopy, involving scanning electron microscopy-based automated mineralogy and optical petrography, demonstrates that bands containing abundant adularia are not the primary host to ore minerals. The ore minerals occur in different bands within the crustiform veins, implying that adularia and ore mineral precipitation did not always occur simultaneously. It is hypothesized here that fluid flow at Midas involved intermittent short-lived events of fluid flashing, causing rapid solute supersaturation in the liquid. During each flashing event, different amounts of vapor were produced along a given vein. Compositional differences between adjacent bands in the crustiform quartz veins may, therefore, be linked to variations in the amount of vapor formed during each flash event.

Nevada↗
USGS2025

State shifts in the deep Critical Zone drive landscape evolution in volcanic terrains

Understanding the near-surface environment where atmospheric and solid earth processes interact, often termed the “Critical Zone,” is important for assessing resources and building resilient societies. Here, we examine a volcanic landscape in the Oregon Cascade Range, an understudied Critical Zone setting that is host to major regional water resources, pervasive silicate weathering, and significant geohazards. We leverage a bedrock age chronosequence to show that the volcanic Critical Zone undergoes a structural shift, from depth extents of >1 km to meters, over timescales of ~1 My. We map an active groundwater volume comparable to major continental lakes, stored at the Cascade Range crest. This state shift makes volcanic landscape evolution a unique probe of deep coupling between Earth systems.

PNAS↗
USGS2024

Editorial: From cold seeps to hydrothermal vents: Geology, chemistry, microbiology, and ecology in marine and coastal environments

This Research Topic compiles contemporary studies on cold seeps, hydrothermal vents, mud volcanoes, and related seafloor features that are associated with focused fluid emissions and the transfer of carbon, other chemical species, and sometimes heat from the geosphere to the ocean. Because these features sometimes tap fluids and gas originating kilometers below the seafloor, they provide an important window into deep processes that are otherwise inaccessible to scientists. At the shallow portion of their journey, migrating fluids nearing the seafloor contribute to a range of unique biological, physical, and chemical processes within the sediments themselves and at the sediment-water interface. Seafloor fluid emissions play a critical role in global biogeochemical cycles, ocean chemistry, and possibly even climate change. Seafloor leakage points often emit hydrocarbon gases (especially methane and CO 2 ) and are sometimes the loci for deposition of seafloor minerals that have economic value. A burgeoning area of research focuses on natural products generated at these features, seeking compounds with potential pharmaceutical or other applications. Multidisciplinary studies have become routine for characterization of seafloor fluid emission sites, attesting to the inseparability of geologic, physical, chemical, and biological processes in these settings. It is increasingly common for researchers to combine in a single research cruise: subbottom imaging and seafloor mapping; porewater and water column geochemistry and gas sampling; sediment retrieval for lithologic, biostratigraphic, and solid phase analyses; and studies of benthic and subseafloor communities at the microbial to macrofaunal scales. This multidisciplinary approach has the advantage of ensuring the spatial and temporal coincidence of surveys and samples, an important factor at highly dynamic seafloor fluid emission sites. In addition, researchers often use remotely operated vehicles (ROVs), autonomous underwater vehicles (AUVs), or human-occupied vehicles (HOVs) to record video of the seafloor, compile photomosaics, collect targeted samples, and survey with high-resolution geophysical near-seafloor systems, providing a degree of detail about seafloor fluid emission sites that is unprecedented compared to most areas of the deep ocean. While rarer, long-term cabled observatories or shorter-term deployments of portable observatories are also used at some loci for seafloor fluid flux and are particularly helpful for capturing temporal variations at these dynamic features. Here we summarize the Research Topic’s contribution to multidisciplinary seafloor emission studies in the categories of cold seeps, mud volcanoes, and hydrothermal vents. Figure 1 shows the geographic distribution of the studies in this Research Topic and key features referred to in this Introduction.

Frontiers in Earth Science↗
USGS2025

Horizontal transport of Picture Gorge Basalt magma through the Monument Dike Swarm determined by magnetic fabric

Flood basalts of the mid-Miocene Columbia River Basalt Group (CRBG) cover 210,000 km 2 of Washington, Oregon, and Idaho. The source of CRBG melt is debated; widely spaced feeder dike swarms can be projected toward hypothetical sources near the Oregon-Idaho border. In this study, we use anisotropy of magnetic susceptibility (AMS) to track magma flow in the Monument dike swarm (MDS), the feeder dikes of the Picture Gorge Basalt (PGB). This small formation of the main-phase CRBG eruptions allows us to explore in detail the localized dynamics of a large igneous province feeder system, with implications for the larger CRBG picture. We measured the magnetic fabric of 205 oriented paleomagnetic specimens subsampled from 97 samples collected from 15 dikes of the MDS. Thermal demagnetization and hysteresis loops show that the magnetic minerals are a mixture of single domain and multidomain sized titanomagnetites. At three dikes, the paleodepth of sampling was determined to be shallow (<350 m). Magma flowing through dikes has been shown—in most cases— to acquire an anisotropic magnetic fabric with an AMS ellipsoid minimum axis perpendicular to the wall and maximum axis aligned in the direction of flow. Of 15 dikes, 12 show horizontal flow directions in the plane of the dike. Only one dike displayed imbricated fabrics, showing westward flow away from the Oregon-Idaho border. We conclude that magma flow in the MDS was sub-horizontal from a distal source.

Oregon↗
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↗
USGS1976

Non-radiometric borehole geophysical detection of geochemical halos surrounding sedimentary uranium deposits

Roll-type uranium deposits are formed by the concentration of uranium by ground water in geochemical cells. Non-uranium minerals having different solubilities may be deposited ahead of or behind the uranium minerals, forming halos that surround the ore. In addition, oxidizing and reducing environmental conditions may cause zones of mineral alteration to develop beyond the limits of the uranium deposit. Certain physical property anomalies that are commonly associated with halos can be detected by relatively fast and inexpensive borehole geophysical measurements made either in individual holes, or between two adjacent holes. Borehole measurements that have been found to be useful include electrical resistivity, induced polarization, and magnetic susceptibility. Electrical resistivity is increased by the presence of calcite and other cementing minerals that sometimes create permeability barriers in the neighborhood of uranium deposits. Induced polarization (IP) response is increased by sulfide and clay minerals that are commonly found in anomalous concentrations near roll-type deposits. Magnetic susceptibility is usually decreased by the oxidation of magnetite to hematite or limonite in the zone of chemical alteration that is left as a trail behind roll fronts. Borehole measurements of electrical resistivity, induced polarization and magnetic susceptibility were made in the vicinity of a uranium roll-type deposit in south Texas. Results indicate that mineral halos can be detected by borehole measurements made. in wide-spaced drill holes, and that the total amount of drilling needed to find a deposit can be reduced substantially by this exploration approach.

Open-File Report↗
USGS2026

Decadal-scale characteristics of natural and anthropogenic dune morphology along North Carolina Barrier Islands (SE Atlantic Coast)

Dunes offer protection to coastal communities from storms, yet quantitative research characterizing human influences on dune systems across decades and 10–100 km spatial scales constitutes a known data gap. This study analyzed a multidecadal archive of dune crest elevations and positions to map mesoscale spatiotemporal trends in foredune morphology across the barrier island coastline of North Carolina, SE Atlantic coast. Results are summarized within four categories of coastline representing a range of coastal management intensities, integrating beach width and dune lateral accommodation space to assess the comparative influence of differing intensities of anthropogenic intervention on dune morphology. These categories account for the presence of structures, roads, and alongshore connectivity to anthropogenic sediment sources (beach nourishment). These categories show distinct dune and beach system characteristics. Dunes are largest in the areas with the longest legacy of coastal management. As categories decrease in development intensity, dune and beach system characteristics generally depart from the large, static dunes and narrow beaches consistent with hold-the-line management. Where small or transgressive dunes exist on heavily developed coasts, they coincide with relatively strong hydrodynamic forcing or sediment-limiting geology. There is evidence of indirect coastal management influence on undeveloped barrier islands with alongshore connectivity to developed barriers. While this analysis was conducted at the mesoscale, the results provide researchers with the framework to make insights at smaller scales than those demonstrated in this study.

North Carolina↗
USGS2024

On connecting hydro-social parameters to vegetation greenness differences in an evolving groundwater-dependent ecosystem

Understanding groundwater-dependent ecosystems (i.e., areas with a relatively shallow water table that plays a major role in supporting vegetation health) is key to sustaining water resources in the western United States. Groundwater-dependent ecosystems (GDEs) in Colorado have non-pristine temporal and spatial patterns, compared to agro-ecosystems, which make it difficult to quantify how these ecosystems are impacted by changes in water availability. The goal of this study is to examine how key hydrosocial parameters perturb GDE water use in time and in space. The temporal approach tests for the additive impacts of precipitation, surface water discharge, surface water mass balance as a surrogate for surface–groundwater exchange, and groundwater depth on the monthly Landsat normalized difference vegetation index (NDVI). The spatial approach tests for the additive impacts of river confluences, canal augmentation, development, perennial tributary confluences, and farmland modification on temporally integrated NDVI. Model results show a temporal trend (monthly, 1984–2019) is identifiable along segments of the Arkansas River at resolutions finer than 10 km. The temporal impacts of river discharge correlate with riparian water use sooner in time compared to precipitation, but this result is spatially variable and dependent on the covariates tested. Spatially, areal segments of the Arkansas River that have confluences with perennial streams have increased cumulative vegetation density. Quantifying temporal and spatial dependencies between the sources and effects of GDEs could aid in preventing the loss of a vulnerable ecosystem to increased water demand, changing climate, and evolving irrigation methodologies.

Colorado↗
USGS2024

Characteristics of the fault damage zone From high-resolution seismic imaging along the Palos Verdes Fault, California

The distribution and intensity of fault damage zones provides insight into fault activity and its relationship to fluid flow in the crust. Presently, measures of the in-situ distribution of fault damage remain limited and along-strike studies are rare. This study focuses on an offshore section Palos Verdes Fault damage zone that spans 28 km, near Los Angeles, California. To investigate the previously unresolved shallow (∼400 m below the seafloor) fault damage zone we use densely spaced (∼500 m line separation) newly collected sparker multichannel seismic lines and sub-bottom profiles. The combination of high-resolution acquisition methods and specialized seismic processing workflows provide improved imaging of shallow faulting. We apply a multi-trace similarity technique to identify discontinuities in the seismic data that may be attributed to faults and fractures. This fault detection approach reveals diverse fault damage patterns on adjacent seismic profiles. However, a discernible damage zone pattern emerges by stacking multiple damage detection profiles along strike. We find that peak damage identified in this way corresponds to the active main fault strand, confirmed in this study, and thus the technique may be useful for identifying active fault strands elsewhere. Additionally, we observe that the variable width of the damage zone along strike is controlled by fault obliquity. Furthermore, our observations reveal a correlation between fault damage and seafloor fluid seeps visible in the water column, suggesting that damage plays a role in controlling fluid flow around the fault.

California↗
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

A benchmark dataset and workflow for landslide susceptibility zonation

Landslide susceptibility shows the spatial likelihood of landslide occurrence in a specific geographical area and is a relevant tool for mitigating the impact of landslides worldwide. As such, it is the subject of countless scientific studies. Many methods exist for generating a susceptibility map, mostly falling under the definition of statistical or machine learning. These models try to solve a classification problem: given a collection of spatial variables, and their combination associated with landslide presence or absence, a model should be trained, tested to reproduce the target outcome, and eventually applied to unseen data. Contrary to many fields of science that use machine learning for specific tasks, no reference data exist to assess the performance of a given method for landslide susceptibility. Here, we propose a benchmark dataset consisting of 7360 slope units encompassing an area of about 4,100 km 2 "> 4,100 km 2 in Central Italy. Using the dataset, we tried to answer two open questions in landslide research: (1) what effect does the human variability have in creating susceptibility models; (2) how can we develop a reproducible workflow for allowing meaningful model comparisons within the landslide susceptibility research community. With these questions in mind, we released a preliminary version of the dataset, along with a “call for collaboration,” aimed at collecting different calculations using the proposed data, and leaving the freedom of implementation to the respondents. Contributions were different in many respects, including classification methods, use of predictors, implementation of training/validation, and performance assessment. That feedback suggested refining the initial dataset, and constraining the implementation workflow. This resulted in a final benchmark dataset and landslide susceptibility maps obtained with many classification methods. Values of area under the receiver operating characteristic curve obtained with the final benchmark dataset were rather similar, as an effect of constraints on training, cross–validation, and use of data. Brier score results show larger variability, instead, ascribed to different model predictive abilities. Correlation plots show similarities between results of different methods applied by the same group, ascribed to a residual implementation dependence. We stress that the experiment did not intend to select the “best” method but only to establish a first benchmark dataset and workflow, that may be useful as a standard reference for calculations by other scholars. The experiment, to our knowledge, is the first of its kind for landslide susceptibility modeling. The data and workflow presented here comparatively assess the performance of independent methods for landslide susceptibility and we suggest the benchmark approach as a best practice for quantitative research in geosciences.

Earth-Science Reviews↗