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Cascading land surface hazards as a nexus in the Earth system

Earth’s surface is sculpted by numerous processes that move sediment, ranging from gradual and benign to abrupt and catastrophic. Although infrequent, high-magnitude sediment mobilization events can be hazardous to people and infrastructure, leaving topographic imprints on the landscape and remarkable narratives in the historical record. Hazardous events such as fires, storms, and earthquakes accelerate erosion and sediment transport, increasing landscape sensitivity to subsequent perturbations, thus forming a cascading hazard. Although the redistribution of sediment across Earth’s landscape can result in higher risks to vulnerable populations, cascading processes are commonly unaccounted for in hazard assessments. Cascading hazards can occur almost immediately after triggering events, such as coseismic landslides, or over months, years, or even decades after an initial perturbation, such as debris flows after wildfires or flooding in channels alluviated by volcanic debris. Sediment cascades span Earth’s surface, from mountaintops to river valleys, where erosion, deposition, and aggradation can lead to a myriad of hazardous processes, including decreased river conveyance capacity, which increases the likelihood of downstream flooding. An improved understanding of the magnitude, frequency, and persistence of cascading hazards is critical given the rapid changes in the frequency and severity of storms, fires, sea-level change, and cryospheric melting, as well as the expansion of high-population-density urban footprints in regions susceptible to solid Earth hazards. Understanding the full consequences and underlying physics of Earth’s cascading land surface hazards can help minimize future human and economic losses.

California

Geologic input databases for the 2025 Puerto Rico – U.S. Virgin Islands National Seismic Hazard Model update: Crustal faults component

The last National Seismic Hazard Model (NSHM) for Puerto Rico and the U.S. Virgin Islands (PRVI) was published in 2003. In advance of the 2025 PRVI NSHM update, we created three geologic input databases to summarize new onshore and offshore fault source information in the northern Caribbean region between 62°–70° W and 16°–21° N. These databases, of fault sections, fault‐zone polygons, and geologic estimates of fault activity (fault‐slip rate and earthquake recurrence intervals) at specific sites, document updates to fault parameters used in prior seismic hazard models in PRVI. Fault sources were reviewed from published studies since 2003, which document substantial changes to the understanding of fault location, geometry, or activity. New fault section sources were added for features that meet the criteria of (1) length ≥7 km, (2) unequivocal evidence of recurrent tectonic Quaternary activity, and (3) documentation that is publicly available in a peer‐reviewed source. In addition, we revised several broad areal sources, such as the Mona and Anegada extensional zones. The 2003 model included three fault sections and two fault‐zone polygons (areal sources). These databases include 35 fault sections, 6 fault‐zone polygons, and 51 earthquake geology sites. To characterize fault activity rates, slip‐rate bins were assigned based on landscape expression and paleoseismic trench observations for faults without published slip‐rate sites. Additional fault sources were evaluated but not included in these databases due to a lack of published information about fault location, geometry, or recurrent Quaternary activity. The PRVI NSHM 2025 geologic input databases describe crustal faulting; the geometries and coupling of Puerto Rico subduction zone and Muertos Trough models are considered in a separate database. Updates to the fault sections, fault‐zone polygons, and earthquake geology databases can help inform the location and recurrence rate of damaging earthquakes in the PRVI NSHM implementation.

Puerto Rico, U.S. Virgin Islands

Quantifying groundwater response and uncertainty in beaver-influenced mountainous floodplains using machine learning-based model calibration

Beavers ( Castor canadensis ) alter river corridor hydrology by creating ponds and inundating floodplains, and thereby improving surface water storage. However, the impact of inundation on groundwater, particularly in mountainous alluvial floodplains with permeable gravel/cobble layers overlain by a soil layer, remains uncertain. Numerical modeling across various floodplain structures considers topographic and sediment complexity and multidirectional flow, linking inundation to groundwater response. This study develops a model-data integration workflow to address uncertainty in groundwater response to beaver-induced inundations in a mountainous alluvial floodplain in the Upper Colorado River Basin. Uncertain factors include seasonal hydrologic dynamics, hydraulic conductivities, floodplain structures, and meteorological forcings. We employed an ensemble of groundwater models, based on geophysical and hydrologic data, with machine learning-based calibration using a neural density estimator. This allowed us to quantify the vertical flux from the soil layer to the permeable gravel bed, the down-valley underflow within the gravel bed, and their ratios. Results show a significant increase in the vertical flux relative to down-valley underflow, from 2% during dry pond periods to 20% during wet periods, serving as an analogy for conditions without and with beaver ponds. The study highlights the influence of floodplain structure on groundwater storage, water balance, and water quality impacted by beaver ponds. A thick gravel bed layer, with a large down-valley underflow, minimizes the effect of beaver-induced inundation on water quality. We emphasize the need for field-scale measurements of floodplain structure and improved characterization of evapotranspiration changes to reduce uncertainty in groundwater response.

Colorado

Chloride concentrations in groundwater from the western part of the Southern Hills regional aquifer system, Louisiana, 2021–22

Groundwater is heavily used for public supply and industrial uses in the Baton Rouge, Louisiana, area. Lowered water levels resulting from groundwater withdrawals have induced the movement of saltwater towards wells in East Baton Rouge and West Baton Rouge Parishes. Saltwater intrusion has the potential to affect water supply infrastructure, reduce water availability for some uses, and increase treatment costs. To document current conditions, samples were collected from 161 wells screened in 10 aquifers of the Southern Hills regional aquifer system during November 2021 through February 2022. The results were compared with historical data to identify where chloride concentrations are increasing, which could indicate that saltwater intrusion is occurring. Saltwater intrusion, to varying degrees and areal extents, was observed in most of the 10 aquifers. The limited availability of monitoring wells near or within some of the known saltwater plume areas restricts tracking of the movement or delineation of the plumes’ current extents.

Louisiana

From model to action: Identifying the gaps in coastal marsh models for decision making

Coastal salt marsh modeling projects are designed to answer questions about where salt marshes may migrate, how they can migrate, and how they will be impacted by changing water levels. While this information is vital for climate-resilient marsh conservation, translating these findings into actionable results remains a challenge. The authors examined the actionability of marsh modeling efforts in the United States by analyzing data collected from semi-structured interviews of marsh model users ( n = 24) across two ongoing projects along the U.S. East Coast and the Gulf of America (Gulf of Mexico). By qualitatively analyzing the interview data, the authors found that the tasks of practitioners who use coastal marsh model outputs fall into three major themes: (1) marsh restoration, (2) planning with uncertainty, and (3) conserving habitat for marsh-reliant species. For each of these themes, the authors identify unmet needs, including high spatial resolution information for local planning, accessible descriptions of uncertainty to increase user confidence, and the incorporation of human dimensions data (e.g., human alterations to the landscape such as impoundments and culverts) for a comprehensive understanding of the coastal salt marsh. Marsh modeling projects should strategize how to fulfil these unmet user needs so that marsh modeling outputs can better support decisions related to marsh conservation and restoration.

Gulf of America, United States East Coast

Groundwater dominates snowmelt runoff and controls streamflow efficiency in the western United States

Climate change in seasonally snow-covered mountain catchments is reducing water supply and decreasing streamflow predictability. Here, we use tritium age dating to show that contrary to the common assumption that snowmelt quickly contributes to runoff, streamflow during snowmelt in western US catchments is dominated by older groundwater. The average age of streamwater during snowmelt runoff (5.7 ± 4.3 years) was intermediate to the average age of groundwater (10.4 ± 4.5 years) and recent precipitation, indicating that 58% (±34%) of snowmelt runoff was derived from groundwater. Water ages, streamflow, and groundwater storage were mediated by bedrock geology: low-permeability hard rock/shale catchments exhibited younger ages, less storage, and more efficient streamflow generation than high-permeability sandstone/clastic catchments. Our results demonstrate that snowmelt runoff is the result of multiple prior years of climate mediated by groundwater storage. Including these interactions will be crucial for predicting water resources as climate and landscape changes accelerate.

western united States

Groundwater budget for the surficial aquifer surrounding Lake Nokomis, Minneapolis, Minnesota

During prolonged periods of above-average precipitation, rising groundwater levels have the potential to cause damage to and interfere with underground infrastructure and building foundations. To understand the relations between precipitation and groundwater in the vicinity of Lake Nokomis, the U.S. Geological Survey, in collaboration with the University of Minnesota, quantified five components of the groundwater budget: groundwater recharge, change in surficial aquifer storage, surficial aquifer groundwater discharge to Lake Nokomis, groundwater evapotranspiration, and groundwater discharge to underlying bedrock aquifers. Field data, geologic records, and empirical calculation methods were used to quantify groundwater budget components for April 2023 through April 2024. Lake water budget data indicate that Lake Nokomis is a flowthrough system during periods with no outflow through the weir, with groundwater inputs equal to outputs. Roughly 40 percent of precipitation that fell in the study area was added to the surficial aquifer as recharge. Uncertainty in the vertical hydraulic conductivity resulted in wide-ranging estimates (spanning three orders of magnitude) of water discharging from the surficial aquifer to the underlying bedrock aquifer. Drought conditions persisted for the duration of this study and were not representative of the conditions that motivated this study. This study is a start towards understanding relations between precipitation, Lake Nokomis levels, and groundwater levels that could affect local underground infrastructure.

Minnesota

A temporal look at the influence of topographic amplification on earthquake-triggered landslides in 3D seismic simulations

Earthquakes are a primary trigger for landslides, often leading to catastrophic consequences. While numerous studies have explored the spatial distribution of earthquake-triggered landslides, understanding the interaction between seismic waves and topography remains a critical challenge. Topographic irregularities can cause seismic wave amplification, altering ground shaking, and can trigger landslides that are challenging for predictive models to anticipate. This study investigates the spatial and temporal evolution of topographically amplified landslides, focusing on coseismic landslides triggered by the Mw 7.5 mainshock of the 2018 Papua New Guinea earthquake and post-seismic landslides associated with its four aftershocks, each exceeding Mw 6.0. We employ low-frequency, three-dimensional numerical ground shaking simulations and data-driven multivariate analyses to examine how landslides evolved from the coseismic to post-seismic periods. Our findings reveal a spatial shift in landslide distribution, in which the mainshock triggered slope failures predominantly on steep hillslopes, and the aftershocks triggered landslides on gentler slopes, often near geologic boundaries. We attribute this transition partly to the earthquake legacy effect of the mainshock, where the mainshock caused weakening of these hillslopes, making them more prone to failure when aftershocks occur. Additionally, the concentration of failures along geologic contacts in the post-seismic phase suggests that site amplification, stemming from contrasts in subsurface materials, exerts a key influence on landslide occurrence. Although not explicitly captured in our current numerical simulations, this mechanism warrants further investigation for more accurate hazard modeling.

JGR Solid Earth

SlideDetect: Spatio-temporal landslide detection using a three-dimensional convolutional neural network

Landslides pose a serious and ongoing threat to both human lives and infrastructure worldwide; therefore, it is of interest to predict where and when landslides are likely to occur. Advances in machine learning techniques have spurred numerous studies aimed at estimating relative landslide propensity, but are limited to spatial (as opposed to temporal) prediction due to the sparsity of landslide timing data. We address this data gap by training SlideDetect, a 3-dimensional convolutional neural network (3D CNN), to identify landslides based on their spatial and temporal occurrence within multitemporal image stacks. We use an inventory of landsides triggered by the 2018 Hokkaido earthquake and two years of monthly composite optical imagery spanning this event. The model can identify not only landslide location but also landslide date with an area under the precision-recall curve (PR-AUC) of 0.84. We further present a new standard for presenting PR curve results that explicitly compares model performance at different confidence thresholds, allowing for clearer model evaluation and comparison. Our new approach to constraining landslide timing paired with this more consistent and objective method for evaluating model performance shows considerable promise, and with further application and testing, SlideDetect could enhance the data availability and tools needed to advance landslide hazard and risk assessments.

JGR Machine Learning and Computation

Predicted exposure of communities in southeastern United States to climate-related coastal hazards

A rigorous analysis of 21st Century multi-hazard exposure for U.S. Southeast Atlantic coastal communities indicates that up to 70% of residents will be exposed daily to shallow and emerging groundwater by ~2100, 15 times higher than from surficial flooding alone. This threat further exacerbates other coastal stressors, such as flooding, subsidence, and beach erosion, that impact these vulnerable coastal communities and ecosystems under expected future climate change scenarios.

Florida, Georgia, North Carolina, South Carolina,

Completion summary for monitor wells NRF-17 and NRF-18 at the Naval Reactors Facility, Idaho National Laboratory, Idaho

The U.S. Geological Survey (USGS)—in cooperation with the U.S. Department of Energy (DOE) for the Naval Reactors Laboratory Field Office that supports operations for the Naval Reactors Facility (NRF) located at the Idaho National Laboratory (INL)—drilled and constructed well NRF-17 (formerly borehole USGS 151) and well NRF-18 (formerly borehole USGS 152) for stratigraphic framework analyses and water-quality monitoring at the Idaho National Laboratory (INL) near the NRF, in southeastern Idaho. Borehole USGS 151 was continuously cored from about 48 to 1,070 feet (ft) below land surface (BLS); rotary drilled from approximately 1,070 to 1,720 ft BLS; and re-drilled to complete construction as a monitor well NRF-17, completed to 461 ft BLS. Borehole USGS 152 was continuously cored from approximately 19 to 1,259 ft BLS; rotary drilled from approximately 1,259 to 1,630 ft BLS; and re-drilled to complete construction as a monitor well NRF-18, completed to 450 ft BLS. Geophysical data were examined with photographed core material to record lithologic descriptions and to suggest zones where groundwater flow was anticipated. Basalt flows varied from highly fractured to dense, with high-to-low vesiculation. Well NRF-17 generally was constructed in mostly dense basalt (greater than 75 percent), and well NRF-18 was constructed in primarily fractured and (or) vesicular basalt. In well NRF-17, the well capacity is directly affected by the limited amount of fractured basalt, which serves as the primary pathway for groundwater. This effect was observed during the pumping test conducted after the well's final construction. Single-well aquifer tests were done at wells NRF-17 and NRF-18 to provide estimates of transmissivity and hydraulic conductivity after final well construction and initial well development. Estimated values of transmissivity and hydraulic conductivity for well NRF-17 were 8.81 feet squared per day (ft 2 /d) and 1.04×10 -2 feet per day (ft/d), respectively. Estimated values of transmissivity and hydraulic conductivity for well NRF-18 were 4.77×10 3 ft 2 /d and 5.61 ft/d, respectively. The NRF-17 pump test resulted in 19.41 ft of measured drawdown at a sustained average pumping rate of 3.3 gallons per minute (gal/min). The NRF-18 pump test resulted in 0.55 ft of measured drawdown at a sustained average pumping rate of 31.0 gal/min. Water-quality samples collected from the two wells were analyzed for cations, anions, metals, nutrients, volatile organic compounds, stable isotopes, and radionuclides. Water samples for select inorganic constituents showed concentrations consistent with signatures from tributary valley groundwater with influences from ephemeral surface-water recharge from the Big Lost River. Water-quality samples analyzed for stable isotopes of oxygen and hydrogen are consistent with signatures from tributary valley groundwater and surface-water recharge inputs to the aquifer. No measured water-quality results were greater than their respective maximum contaminant levels for public drinking-water supplies. Inorganic and nutrient water-quality results for well NRF-17 and well NRF-18 suggest the groundwater in this area is potentially affected by industrial wastewater disposal.

Idaho

Controls on natural hydrogen generation during serpentinization of mantle rocks

Mantle rocks undergoing serpentinization can generate significant amounts of natural hydrogen, yet the rates and controlling processes remain poorly understood. Here, we constrain the possible hydrogen generation rates in two distinct mantle rock types, the fertile lherzolites of the Western Pyrenees and the depleted harzburgites of Northern California, to relatively low rates of ~0.1 to ~0.5 tonnes H₂ yr⁻¹ km⁻³ of reactive rock. When integrated over the full reactive volumes, this corresponds to total production rates of ~300 to ~600 tonnes H₂ yr⁻¹. By combining three-dimensional geophysical inversion with numerical modelling of fluid-rock processes, we show that hydrogen generation rates are mainly limited by H₂ saturation in the fluid and reaction kinetics. Under these constraints, hydrogen generation in mantle-derived serpentinization systems proceeds slowly, making rapid large-scale replenishment unlikely and suggesting that large, economically relevant accumulations, would require timescales of thousands to tens of thousands of years to develop.

northern California, western Pyrenees

The new self-anchored suspension (SAS) San Francisco Bay Bridge- Its response to a small earthquake

This paper presents a summary of previously published work (Celebi 2023) related to the new Self-Anchored Suspension (SAS) bridge that went into service within the last decade as a replacement for the older truss bridge spanning between Yerba Buena Island and Oakland, California, within the San Francisco Bay Area. During the October 19, 1989 M6.9 Loma Prieta earthquake, which occurred ~100 km south of the Bay Bridge, a section of the upper deck of the truss bridge fell onto the lower deck – thus closing this important lifeline between San Francisco and Oakland. The SAS is unique, self-anchored, and suspended by a single tower that is pivotal in trafficking the cable and hanger system to support the decks. The SAS bridge is extensively instrumented by the California Geological Survey’s Strong Motion Instrumentation Program (CSMIP). There are approximately 85 channels of accelerometers in the seismic monitoring system that recorded the October 14, 2019 Mw4.6 Pleasant Hill earthquake. The data allow a complex but identifiable coupled response of the deck, tower, and cable system. Both acceleration and displacement time-history data are used to extract significant frequencies using system identification methods, including spectral analyses. Results are compared to those from finite-element-model (FEM) analyses carried out during the design and analysis process of the bridge in 2002 (Nader et al. 2002). There are differences between FEM analyses results and those from the low amplitude shaking caused by a seismic event. An apparent frequency (period) of the SAS bridge is assessed (approximately 5.2 seconds). In a plot of deck length versus period, there is an almost linear relationship with periods of other regular suspension bridges, such as the Golden Gate Bridge and the Carquinez Bridge, both in the San Francisco Bay.

California

Extremophile hotspots linked to containerized industrial waste dumping in a deep-sea basin

Decaying barrels on the seafloor linked to DDT contamination have raised concerns about the public health implications of decades old industrial waste dumped off the coast of Los Angeles. To explore their contents, we collected sediment cores perpendicular to five deep-sea barrels. The concentration of DDT and its breakdown products were highly elevated relative to control sites yet did not vary with distance from the barrels, suggesting that they were not associated with the contamination. Sediment cores collected through white halos surrounding three barrels were enriched in calcite and had elevated pH. The associated microbial communities were low diversity and dominated by alkalophilic bacteria with metagenome-assembled genomes adapted to high pH. A solid concretion sampled between a white halo and barrel was composed of brucite, a magnesium hydroxide mineral that forms at high pH. Based on these findings, we postulate that leakage of containerized alkaline waste triggered the formation of mineral concretions that are slowly dissolving and raising the pH of the surrounding sediment pore water. This selects for taxa adapted to extreme alkalinity and drives the precipitation of “anthropogenic” carbonates forming white halos, which serve as a visual identifier of barrels that contained alkaline waste. Remarkably, containerized alkaline waste discarded >50 years ago represents a persistent pollutant creating localized mineral formations and microbial communities that resemble those observed at some hydrothermal systems. These formations were observed at one-third of the visually identified barrels in the San Pedro Basin and have unforeseen, long-term consequences for benthic communities in the region.

California

Parameter ESTimation with the Gauss–Levenberg–Marquardt algorithm: An intuitive guide

In this paper, we review the derivation of the Gauss–Levenberg–Marquardt (GLM) algorithm and its extension to ensemble parameter estimation. We explore the use of graphical methods to provide insights into how the algorithm works in practice and discuss the implications of both algorithm tuning parameters and objective function construction in performance. Some insights include understanding the control of both parameter trajectory and step size for GLM as a function of tuning parameters. Furthermore, for the iterative Ensemble Smoother (iES), we discuss the importance of noise on observations and show how iES can cope with non-unique outcomes based on objective function construction. These insights are valuable for modelers using PEST, PEST++, or similar parameter estimation tools.

Groundwater

Earthquake-triggered ground-failure inventory associated with the M7.1 2018 Southcentral Alaska earthquake

The 30 November 2018, magnitude (Mw) 7.1 earthquake in Southcentral Alaska triggered substantial landslides, liquefaction, and ground cracking throughout the region, resulting in widespread geotechnical damage to buildings and infrastructure. Despite a challenging reconnaissance and remote-sensing environment, we constructed a detailed digital inventory of ground failure associated with the event from several sources. Sources included information derived from remotely sensed data, and data compiled from literature, social media postings, and earthquake damage information compiled by local, state, and federal agencies. Each instance of ground failure within the inventory contains information on the location and type of observed ground failure, and the methods and data used to document the occurrence. Where high-quality data, such as LIDAR or satellite imagery, were available and showed the ground-failure instance clearly, the extent is mapped as a polygon or polyline. All other locations are mapped as points. There are a total of 886 ground-failure instances documented within the inventory (400 landslides, 286 liquefaction features, and 200 features unattributed to specific processes). A semi-quantitative confidence scheme is used to describe mapping certainty associated with each ground-failure feature. This inventory represents a relatively moderate ground-failure-triggering event that occurred in a subarctic environment. This data paper describes the content within the inventory, the inventory data collection procedures, and limitations of the data. Events of this type are not often documented in detail; thus, adding the inventory data to the US Geological Survey Open Repository of Earthquake-Triggered Ground-Failure Inventories further diversifies the datasets available to the scientific community to be used to better understand and model earthquake-triggered ground failure.

Alaska

Site response in the Walnut Creek–Concord region of the San Francisco Bay, California: Ground motion amplification in a fault-bounded basin

Thirty‐seven portable accelerometers were deployed in the eastern San Francisco Bay communities of Walnut Creek and Concord to study site response in a fault‐bounded, urban, sedimentary basin. Local earthquakes were recorded for a period of two years from 2017 to 2019 resulting in 101 well‐recorded events. Site response is estimated by two methods: the reference site spectral ratio method and a source‐site spectral inversion method. The reference site spectral ratio method allows investigation of the variability of site amplification with source azimuth and frequency. The source‐site spectral inversion method yields the best least‐squares fit to site response for a database of ground‐motion records. Both methods show substantial amplification in the Walnut Creek–Concord basin below 2 Hz indicating strong surface‐wave development. Greater amplification is seen for sources aligned along the long axis of the basin. Inversion using close‐in sources at short distances yields lower amplification at longer periods than the entire data set due to reduced surface‐wave generation for steeper angles of incidence. Inversion of site response spectra for shallow shear‐wave velocity using a global search algorithm yields V S30 values consistent with generalized mapping results based on geology and topography but with greater variability due to local site variations. 3D finite‐element modeling shows greater amplification in the Walnut Creek–Concord basin with a basin‐edge effect likely contributing to higher ground motions. Topography is also seen to lead to increased scattering and shadowing effects.

California

Season and antecedent conditions impact concentration-discharge relationships for dissolved organic carbon and alkalinity in southeast Alaskan watershed

Fluvial export of dissolved carbon plays an important role in watershed-scale biogeochemistry. Predicted changes in climate are expected to impact watershed hydrologic regimes, and in turn, the sources and export of dissolved carbon from watersheds. Here, we utilize high resolution measurements of discharge and dissolved carbon concentration to examine how concentration-discharge (CQ) relationships vary seasonally and during high flow events over the main runoff season (May–October) in a temperate forested watershed in Southeast Alaska. Concentration-discharge relationships for dissolved organic carbon (DOC) and alkalinity demonstrated strong seasonal patterns, with more linear relationships in May and June versus other months. Changing power law model slopes ( b values; the exponent in a power law regression between runoff and carbon yields) indicated potentially shifting watershed sources (biogenic vs. geologic) and contrasting dominant flowpaths (shallow vs. deeper groundwater) for DOC and alkalinity over the sampling period. During the largest storm event of the study, DOC and alkalinity b values shifted from an overall pattern of transport (mean b = 1.58 values >1.0 indicate transport limitation) and source limitation (mean b = 0.48, values <1.0 indicate source limitation) to chemostatic (DOC, b = 0.99; alkalinity, b = 1.019). In June through August, patterns in hysteresis index suggest that CQ relationships were altered when storms followed in close succession to each other. Together, these findings indicate that seasonal and antecedent flow conditions play a role in dissolved carbon export from forested watersheds. Understanding these dynamics, particularly during winter months, will become increasingly important as changes to hydroclimate impact riverine carbon export.

Alaska