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USGS2025

Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA

Forecasting water levels in complex ecosystems like wetlands can support effective water resource management, ecological conservation, and understanding surface and groundwater hydrology. Predictive models can be used to simulate the complex interactions among natural processes, hydrometeorological factors, and human activities. The Greater Everglades in the USA is a well-known example of an ecosystem where complexity has motivated adoption of machine learning algorithms in water level prediction studies. This paper aims to contribute to extending existing machine learning algorithms by integrating spatiotemporal data with deep-learning algorithms in the forecasting process. In this study, a deep-learning model is developed to predict water levels on a regional scale, covering a large area of approximately 9,138 square kilometers in the Everglades ecosystem. This model has the architecture of Convolutional Long Short-Term Memory which can deal with spatiotemporal data by capturing both spatial and temporal dependencies in the training data. The forecasting capabilities of this model (referred to as the global model) are assessed by comparing the global model to two Artificial Neural Networks developed at two different gaging stations, referred to here as local models. One local model is developed at a gaging station directly influenced by nearby water control structures, whereas the other is developed at a gaging station located farther away from these structures. By leveraging data from the Everglades Depth Estimation Network spanning from January 2002 to May 2023, the global and local models were trained to forecast water levels with a two-day lead time. Our findings suggest that both the global and local models perform with approximately the same level of accuracy, with Mean Absolute Relative Error values ranging from 0.38% to 1.4% at the selected stations. The developed global model has demonstrated strong potential as a standalone forecasting tool for the entire study area in the Everglades and could eliminate the need for developing multiple local models. This finding also highlights how machine learning can capture complex spatial and temporal relationships to generate accurate water level predictions on a regional scale.

Florida↗

USGS2024

Assessing potential effects of oil and gas development activities on groundwater quality near and overlying the Elk Hills and North Coles Levee Oil Fields, San Joaquin Valley, California

Groundwater resources are utilized near areas of intensive oil and gas development in California’s San Joaquin Valley. In this study, we examined chemical and isotopic data to assess if thermogenic gas or saline water from oil producing formations have mixed with groundwater near the Elk Hills and North Coles Levee Oil Fields in the southwestern San Joaquin Valley. Major ion concentrations and stable isotope compositions were largely consistent with natural processes, including mixing of different recharge sources and water-rock interactions. Trace methane concentrations likely resulted from microbial rather than thermogenic sources. Trace concentrations of benzene and other dissolved hydrocarbons in three wells had uncertain sources that could occur naturally or be derived from oil and gas development activities or other anthropogenic sources. In the mid-1990s, two industrial supply wells had increasing Cl and B concentrations likely explained by mixing with up to 15 percent saline oil-field water injected for disposal in nearby injection disposal wells. Shallow groundwater along the western margin of Buena Vista Lake Bed had elevated Cl, B, and SO 4 concentrations that could be explained by accumulation of salts during natural wetting and drying cycles or, alternatively, legacy surface disposal of saline oil-field water in upgradient ephemeral drainages. This study showed that groundwater had relatively little evidence of thermogenic gas or saline water from oil and gas sources in most parts of the study area. However, the evidence for groundwater mixing with injected disposal water, and possibly legacy surface disposal water, demonstrates produced water management practices as a potential risk factor for groundwater-quality degradation near oil and gas fields. Additional studies in the San Joaquin Valley and elsewhere could improve understanding of such risks by assessing the locations, volumes, and types of produced water disposal practices used during the life of oil fields.

California↗

USGS2026

Variability and consistency in wildfire susceptibility: Insights from a national compilation

Background Wildfire risk in the United States is rising and remains a land management priority. The quantitative wildfire risk assessment (QWRA) framework integrates fuels, topography, weather and values at risk to estimate the potential change in value from wildfire. Within this, response functions (RFs) represent how values respond to fire intensity. These are often based on expert judgment, but variation across assessments is unclear. Aims This study uses data from the US Geological Survey (USGS) Wildfire Hazard and Risk Assessment Clearinghouse to characterize consistency and variation across categories and contexts. Methods We applied descriptive statistics to summarize RFs, using tables, box-and-whisker plots and heat maps stratified by highly valued resource or asset (HVRA) category and spatial scale. Key results RFs and value definitions vary, especially for ecosystem-related resources. Some functions, such as for buildings in the wildland–urban interface (WUI), translate well across contexts, while others require more input. Conclusions Some functions are broadly transferable, while others need customization. This analysis provides references and starting points for improvement to RFs in QWRAs. Interpretations Expanding the clearinghouse and dataset and building more transparency in expert elicitation can build trust among communities, agencies and end-users, and can support efficient use of limited resources to mitigate wildfire risk.

International Journal of Wildland Fire↗

USGS2024

Cross-fade sampling: Extremely efficient Bayesian inversion for a variety of geophysical problems

This paper introduces cross-fade sampling, a computationally efficient Markov Chain Monte Carlo simulation method that uses a semi-analytical approach to quickly solve Bayesian inverse problems that do not themselves have an analytical solution. Cross-fading is efficient in two ways. First, it requires fewer samples to obtain the same quality simulation of the target probability density function (PDF). Secondly, it is much faster to evaluate the posterior probability of each sample than conventional sampling methods for simulating Bayesian posterior PDFs. Conventional methods require evaluating the prior probability (which describes your a priori constraints) and data likelihood (which describes the fit between the observations and the predictions of the model) for each sample model. However, cross-fading does not require evaluating the data likelihood, meaning that ‘big data’ can be fit with zero additional computational cost. Further, the cross-fading approach can be used to calculate the marginal likelihood associated with a model design, facilitating model comparison and Bayesian model averaging. Topics covered in this paper include derivation of the cross-fade approach and how it can be used to simulate Bayesian posterior PDFs and compute the marginal likelihood, discussion of the class of problems to which cross-fading can be applied (with examples from earthquake statistics, earthquake ground motion modelling, volcanic eruption forecasting, and finite fault slip modelling), demonstration of efficiency relative to existing sampling methods and discussion of how cross-fading can be used to account for prediction errors (i.e. epistemic errors) as part of the geophysical inverse problem.

Geophysical Journal International↗

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

Widespread occurrence of former anhydrite phenocrysts in Laramide-age magmas related to porphyry-skarn Cu mineralization at Santa Rita and Hanover-Fierro, New Mexico, USA

Reports of magmatic anhydrite are relatively rare, with only ~30 occurrences documented worldwide so far. However, magmatic anhydrite saturation is difficult to recognize because anhydrite decomposes rapidly in near-surface environments. In most cases, only anhydrite inclusions shielded within other phenocryst phases were able to survive. Alternatively, since anhydrite phenocrysts preserved in fresh volcanic rocks are characteristically intergrown with apatite phenocrysts, the former presence of anhydrite phenocrysts can be recognized based on the occurrence of lath-shaped cavities that show a strong spatial association with apatite phenocrysts. These cavities can be either empty or filled with low-temperature, secondary minerals such as zeolites, carbonates, or microcrystalline silica. A systematic search for the occurrence of such cavities, combined with optical and Raman-spectroscopic identification of anhydrite inclusions preserved within apatite, hornblende and quartz phenocrysts, demonstrates that most of the Laramide-age magmas associated with the Santa Rita and Hanover-Fierro porphyry-skarn Cu (Zn, Mo, Au, Pb) deposits were saturated in magmatic anhydrite. The anhydrite typically coexisted with monosulfide solid solution (MSS), suggesting oxygen fugacities of ~2.0±0.5 log units above the fayalite-magnetite-quartz buffer. The magmas range from andesitic to rhyodacitic in composition, and from shortly pre-mineralization (~61 Ma) to shortly post-mineralization (~57 Ma) in age. In three samples with particularly well-recognizable former anhydrite phenocrysts, their modal abundance could be quantified based on high-resolution scans of polished hand specimens. The observed modal anhydrite abundances of 0.63–1.8 vol% translate into minimum magma sulfur contents of 0.20–0.56 wt% S. The highest sulfur content of 0.56 wt% S is difficult to reconcile with available anhydrite solubility models, but it could be reproduced in an anhydrite solubility experiment performed at 950 °C and 1.15 GPa on a natural latite containing 13.1 wt% dissolved H2O. The sample with the second-highest sulfur content of 0.26 wt% S requires ~10 wt% H2O in the silicate melt, and, consequently, a minimum pressure of ~0.5 GPa. Taken together, the results suggest that the magmas of the Central Mining District were extremely hydrous and thus originated from great depth. Indeed, their major element compositions and reconstructed H2O and S contents agree well with experimentally observed and numerically predicted compositions of residual silicate melts after 50–70 wt% crystallization of ordinary arc basalts at high pressure and high oxygen fugacities.

New Mexico↗

USGS2026

Estimating habitat availability for Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) to inform reintroduction planning in the middle Snake River basin, USA

Anadromous fishes have been blocked from the middle Snake River basin since the construction of flood control, irrigation, and hydroelectric projects during the 19 th and 20 th centuries, culminating with the construction of Hells Canyon Dam (river kilometer [rkm] 398) in 1967. Seven large watersheds in the blocked area of the basin are under consideration for Pacific salmon reintroduction. The primary objective of this study was to identify and characterize potential reintroduction sites with high-quality rearing and spawning habitat for Chinook salmon ( Oncorhynchus tshawytscha ) and steelhead ( O. mykiss ) upstream of the Hells Canyon Complex in Idaho, Oregon, and Nevada, USA. We created and tested habitat models to predict rearing presence/absence, rearing abundance, and spawning presence/absence using channel morphology, hydrology, and stream temperature variables obtained from regional peer-reviewed datasets. Habitat models were trained with salmonid presence and abundance records collected in the lower Snake River basin (downstream of Hells Canyon Dam), where anadromous fish can currently access, from 1993 to 2011. Model performance was tested with set-aside data comprised of randomly selected reaches and independent environmental DNA data. An index model was created in the middle Snake River basin for each species by combining results from the habitat models. Modeling covariates differed by species and life stage and included different combinations of August stream temperature, summer flow, channel slope, and quadratic terms for temperature and slope. The habitat models predicted high versus low Chinook salmon and steelhead probability and abundance with 66% to 85% accuracy depending on species and life stage. The index models predicted a total of 2,887 km of Chinook salmon habitat and 2,434 km of steelhead habitat in the blocked area. The three basins in the blocked area with the greatest amount of predicted habitat were the Powder River, South Fork Payette River, and North Fork Payette River for Chinook salmon, and the Powder River, South Fork Boise River, and South Fork Payette River for steelhead. The modeling approach presented here is complementary to other planning efforts for Chinook salmon and steelhead reintroduction in the blocked area of the Snake River basin, and similar approaches may be useful for reintroduction planning in other systems.

Idaho, Nevada, Oregon, Utah, Washington, Wyoming↗

USGS2025

Four-band image mosaic of the Colorado River Corridor downstream of Glen Canyon Dam in Arizona, derived from the May 2021 airborne image acquisition

In May 2021, the U.S. Geological Survey’s Grand Canyon Monitoring and Research Center acquired airborne multispectral high-resolution data for the Colorado River in the Grand Canyon, Arizona. The image data, which consist of four spectral bands (red, band 1; green, band 2; blue, band 3; and near infrared, band 4) with a ground resolution of 20 centimeters, are available as 16-bit unsigned-integer GeoTIFF files in Sankey and others (2024) (available online at https://doi.org/10.5066/P9BBGN6G ). The image files are projected in the State Plane Coordinate System, using the central Arizona zone (202) with the North American Datum of 1983 National Adjustment of 2011. The assessed spatial accuracy for these data is based on 47 ground-control points that were independent from the ground-control points used by the contractor for aerotriangulation and is reported at the 95-percent confidence level as 0.514 meter (m) and a root mean square error of 0.297 m. The intended uses of this dataset are primarily in support of scientific research and monitoring applications. Examples of these applications include high-resolution spatial and temporal change detection of the river channel, geomorphic landforms, riparian vegetation, and backwater and nearshore habitat, as well as other ecosystem-wide mapping. These imagery data also serve as reference material for field science mission planning, as base data for field data collection including community science activities, and as a highly detailed guide for technical boat operation during science activities such as reconnaissance for nighttime missions and navigating rapids during low flows.

Arizona, Nevada, Utah↗

USGS2025

Applying U-Th disequilbrium for dating siliceous sinters

Continental hydrothermal systems are critical avenues for the crustal transport of heat and mass captured for geothermal energy and mineral exploration. Thus, understanding their temporal evolution and longevity is important for resource characterization. Deposits of microlaminated siliceous sinter, common surface expressions of high temperature reservoirs (> 170 °C), have the potential to trace hydrothermal histories. Geothermal reservoirs are often located within uranium-bearing silicic volcanic rock where subsurface fluid-rock interactions extract U into hydrothermal fluids. U incorporated in the surface sinter deposit has the potential to provide a U— Th disequilibrium dating option. We focus on samples from El Tatio geyser field in the Altiplano of northern Chile, the largest geothermal system in the Andes. Our resulting 230 Th/U ages, along with the water and deposit elemental compositions, suggest concentrations of U and Th vary predictably along the sinter apron. While distal facies containing the highest U concentrations (> 50 μg/g) are least affected by detrital Th corrections, they can display suspected open-system behavior. In contrast, more medial facies, where bacterial mats and other porous textures are co mmonly concentrated, have only trace amounts of U (< 0.1 μg/g), which leads to unreliable or geologically improbable dates. Proximal facies tend to date most consistently. By comparing existing 14 C ages with 230 Th/U results, 230 Th/U ages tend to be younger than the 14 C ages, supporting the presence of a 14 C-dead carbon influence. New data confirm that the onset of geothermal activity at El Tatio goes back to the late Pleistocene.

Altiplano, El Tatio geyser field↗

USGS2026

Assessing natural recharge in Indian Wells Valley, California: A Basin Characterization Model case study

The communities in Indian Wells Valley (IWV), in the northern Mojave Desert in California, rely on groundwater for domestic and agricultural use. Mountain front recharge from the surrounding Sierra Nevada is the main source of natural recharge to the valley. Increased urbanization, agricultural development, and groundwater pumping during recent decades put IWV in a state of critical overdraft. The U.S. Geological Survey Basin Characterization Model, version 8 (BCMv8) was used to evaluate historical and future climate and hydrologic conditions in IWV. The BCMv8 estimated natural recharge in IWV at 10.7 million cubic meters (Mm 3 ) per year for the period from 1981 to 2010. Future patterns of water balance variables using three future climate scenarios, hot-wet, hot-dry, and warm-moderately wet, were calculated for mid-century (2040–69) and end-of-century (2070–99) periods. Results for both wet models projected an increase in recharge in both periods, whereas the hot-dry model projected a decrease in recharge in both periods. All models reported a large increase in seasonal variability in recharge, indicating more future availability and frequent occurrences of drought years. All climate scenarios projected an increase in climatic water deficit in both periods. These increases in irrigation demand and variability of water supply highlight the importance of strategic management planning for the sustainability of water resources in IWV.

California↗

USGS2024

Event classification, seismicity, and eruption forecasting at Great Sitkin Volcano, Alaska: 1999–2023

The frequency content of volcanogenic seismicity is often used to classify events and their spatial and temporal progression is then used to map subsurface volcanic processes. The progression of volcano-seismic events and associated source processes also plays a critical role in eruption forecasting. Here we develop and evaluate a computerized methodology for characterizing volcano-seismic event types using Frequency Index and Average Peak Frequency. We apply and test this technique at Great Sitkin Volcano, Alaska, classifying over 9000 hypocenters between 1999 and 2023. This 24-year time span covers periods of seismic quiescence, earthquake activity on nearby tectonic (bookshelf) faults, precursory unrest from 2016 to 2021, and the explosive onset in May 2021 of the ongoing effusive eruption. We use the spatial and temporal evolution of classified event types to map the active volcanic and tectonic processes, develop a conceptual model of the subsurface magmatic system, and perform a retrospective analysis of eruption forecasts at Great Sitkin Volcano between 2016 and the present. The classification and progression of hypocenters suggests the subsurface Great Sitkin Volcano magmatic system consists of a mid- to lower- crustal source zone between 10 and 40 km depth and an upper crustal magma storage area between −1 and 10 km depth (hypocenter depth is referenced to sea level and negative depths reflect height above sea level). The earliest precursors occurred in July 2016 and consisted of deep long-period and volcano-tectonic earthquakes at mid-crustal depths suggesting the subsequent unrest and eruption were triggered by a deeper intrusion of magma. This mid-crustal seismic activity was immediately followed by the onset upper-crustal long-period events and volcano-tectonic earthquakes VTs suggesting a strong linkage between the shallow and deeper portions of the magmatic system. The upper crustal area was likely capped by the 1974 lava dome until the magmatic explosion on May 26, 2021.

Alaska↗

USGS2025

Ungulate migrations of the Western United States, volume 5

Many ungulates migrate between distinct summer and winter ranges to take advantage of spatially and temporally variable food sources and avoid threats such as predators and deep snow. In 2018, the U.S. Department of the Interior established Secretarial Order 3362, which provided Federal support to expand existing research efforts to study ungulate populations and conserve their migrations by enhancing habitat quality for ungulates across the Western United States. In response to the order, the U.S. Geological Survey (USGS) created the Corridor Mapping Team, which is a collaboration among 11 State agencies, regional and Federal partners, and an expanding number of Tribal wildlife agencies. Together, the Corridor Mapping Team maps ungulate migrations throughout the Western United States and publishes them in the USGS “Ungulate Migrations of the Western United States” report series. This report details migrations and seasonal ranges from 36 additional herds and includes 2 herd updates detailed in previous reports. The Corridor Mapping Team has mapped the migrations and seasonal ranges of 218 unique herds for the report series, including this report. The report series serves as a map-based inventory of the ungulate migrations across the Western United States for biologists, managers, policymakers, and conservation practitioners. Building on the previous report volumes in the series, volume 5 additionally describes some of the local and national initiatives that are incorporating the products, tools, and information from this growing USGS report series.

Navajo Nation↗

USGS2025

The influence of pre-existing structures on geothermal springs: Inferences from potential field mapping in Surprise Valley, CA and other sites In the northwestern Great Basin

Surprise Valley, located in the northwestern Great Basin, is an asymmetric extensional basin that marks a major tectonic transition between the relatively un-extended volcanic Modoc Plateau to the west, and the Basin and Range to the east that has undergone 10-15% extension. In addition, it sits just north of the Walker Lane which accommodates up to 20% of dextral slip associated with Pacific-North American plate interactions. Thermal springs issue from eight areas within Surprise Valley. Most of these occur within the basin and are not situated on the main basin forming range-front faults. As a result, efforts to resolve the structural setting of the valley’s hydrothermal system have relied on geophysics to characterize basin structure and geology. Extensive efforts to map the basin with ground and airborne magnetics have revealed a >35 km-long linear, intra-basin magnetic high, interpreted as a buried dike swarm. Geothermal springs on the eastern side of the valley, including Seifert hot springs, Leonards hot springs, and Surprise Valley hot springs (SVHS), are all situated along the magnetic high and occur at local breaks and bends in the anomaly, suggesting that fracture permeability is enhanced along the feature and particularly at these discontinuities. Recent studies, including drilling over the anomaly near SVHS that likely intersected dike material, as well as subsequent mapping and sampling of dikes outcropping along the anomaly on the playa surface south of SVHS, confirm (as previously inferred) that mafic intrusives are the principal source of the anomaly. Similar interpretations made in two other valleys (in southern Oregon and northwestern Nevada), where inferred intra-basin dikes appear to be spatially correlated with hot springs or prospective geothermal resource areas, suggest that the impact of pre-existing basement structure on hydrothermal activity may pertain more generally to other hydrothermal settings throughout the Great Basin. If so, efforts to map basement may enhance understanding structural controls on some geothermal systems. Furthermore, similarities across these disparate sites suggest that magmatism may play a much larger role in accommodating extension and influencing basin evolution across the western Great Basin than previously recognized.

Conference Paper↗

USGS1976

Solute transport and modeling of water quality in a small stream

An injection of chloride, sodium, and stable strontium was made at a constant rate for 3 hours into Uvas Creek, Santa Clara County, Calif., to determine the mass transport processes in a small stream. Five observation points were selected within a 610-metre reach of the stream below the injection site. Water samples were collected at the observation points during and immediately after the injection. A mathematical model of the stream was obtained by solving analytically and optimally the one-dimensional mass transport equation of the solutes in the stream. Comparison of field results with a simplified mathematical model indicates the dominance of convection in the behavior of sodium and chloride. The concentration of chloride and sodium can be closely simulated by the model. However, strontium cannot be well represented by the simplified model, which contains a first-order decay-type sink.

California↗

USGS2024

Near-real-time earthquake-induced fatality estimation using crowdsourced data and few-shot large-language models

When a damaging earthquake occurs, immediate information about casualties (e.g., fatalities and injuries) is critical for time-sensitive decision-making by emergency response and aid agencies in the first hours and days. Systems such as the Prompt Assessment of Global Earthquakes for Response (PAGER) by the U.S. Geological Survey (USGS) were developed to provide a forecast of such impacts within about 30 min of any significant earthquake globally. However, existing disaster-induced human loss estimation systems often rely on early casualty reports manually retrieved from global traditional media, which are labor-intensive, time-consuming, and have significant time latencies. Recent approaches use keyword matching and topic modeling to identify human casualty-relevant information from social media but tend to be error-prone when dealing with complex semantics in multi-lingual text data and parsing dynamically changing and conflicting human death and injury numbers shared by various unvetted sources in social media platforms. In this work, we introduce an end-to-end framework to significantly improve the timeliness and accuracy of global earthquake-induced human loss forecasting using multi-lingual, crowdsourced social media. Our framework integrates (i) a hierarchical casualty extraction model built upon large language models, prompt design, and few-shot learning to retrieve quantitative human loss claims from social media, (ii) a physical constraint-aware, dynamic-truth discovery model that discovers the truthful human loss from massive noisy and potentially conflicting human loss claims, and (iii) a Bayesian updating loss projection model that dynamically updates the final loss estimation using discovered truths. We test the framework in real-time on a series of global earthquake events in 2021 and 2022 and show that our framework effectively automates the retrieval of casualty information faster but with comparable accuracy to those now retrieved manually by the USGS. The code associated with this work is made available at: https://github.com/SusuXu-s-Lab/Hierarchical-Earthquake-Casualty-Information-Retrieval

International Journal of Disaster Risk Reduction↗

USGS2026

Site-specific amplifications in Northwestern Turkiye: A generic approach

In this study, we derive generic site amplification functions applicable to Northwestern Türkiye and follow guidance on site classifications established by the United States National Earthquake Hazards Reduction Program (NEHRP). We employ the one-dimensional (1-D) equivalent linear ground response analysis method and focus on recordings from a select suite of free-field strong motion (SM) stations. These particular SM stations are associated with a comprehensive geotechnical site conditions dataset comprising 76 shear-wave velocity profiles. Despite their varying resolutions and depths, this diversity allows for a more representative analysis across different site conditions, enhancing the robustness of our findings. For analyses, we utilize a robust set of global ground motion records, selected from both within and outside of Türkiye, to serve as strong and weak input bedrock motions. Site amplification is determined by propagating these bedrock records through 76 site-specific Afet ve Acil Durum Yönetimi Başkanlığı (AFAD) station profiles and calculating the spectral acceleration ratio between the ground surface and the input motion. Our analyses reveal substantial disparities between the amplification functions derived from 1-D site response analyses using strong and weak input motions. These disparities are central to our analysis and inform the subsequent comparison with site amplification functions reported in the literature. We compare the generic site amplification functions derived in this study with those reported in the literature for regions with similar geological and seismic conditions to Northwestern Türkiye. For example, site amplification functions for NEHRP Site Classes C and D have been documented for Greece and the United States utilizing frequency-dependent methods such as the quarter-wavelength approximation. Our findings reveal that the generic site amplification functions derived in this study exhibit differences in peak amplitudes and predominant frequencies compared to those in the literature, reflecting regional variations in geotechnical and seismic properties. This study represents an initial effort to formulate generic site amplification functions for Türkiye, with a particular emphasis on the Northwestern region. A thorough literature review indicated no prior studies have proposed such functions specifically for this area.

Northwestern Turkiye↗

USGS2025

Relating systematic molecular and textural properties of graptolite pyrolyzed via gold tube hydrous pyrolysis: Implications for thermal proxies in lower Paleozoic marine shales

A series of gold tube pyrolysis experiments (72 h, 300–550 °C, 50 MPa) conducted on a graptolite-rich lower Paleozoic marine shale generated pyrolysis residues for a comprehensive evaluation of the molecular and structural variability of three types of graptolite periderm. Organic petrology, Raman spectroscopy, and field emission scanning electron microscopy (FE-SEM) with energy dispersive spectroscopy (EDS) were combined to evaluate the thermal evolution process. The three types of graptolite periderm, namely granular, non-granular, and nodular graptolite, were analyzed by Raman spectroscopy wherein point measurements were obtained after the maceral was identified and the location verified by organic petrology. Distinct thermal evolution pathways among non-granular, granular, and nodular graptolite periderms were recorded. The evolution patterns of the Raman parameters, particularly D1 and G bands, highlight the differences in geochemical composition of the graptolite periderm types and the alteration of molecular structure with increasing thermal maturity. Raman parameters D1 (position of the D1 peak), G-FWHM (full width at half maximum of the G peak), and ratios D1-FWHM/G-FWHM (full width at half maximum of the D1 peak ratioed to G-FWHM) and A D1 /A G (ratio of D1 and G peak intensities) showed effectiveness in assessing thermal maturity. Bireflectance with increasing gold tube pyrolysis temperature followed a hierarchy: non-granular > granular > nodular, reflecting different molecular alignment intensities. Qualitative FE-SEM evaluation showed that fine-grained mineral inclusions (primarily Fe-sulfide as determined via EDS) were associated with the graptolite populations, with granular graptolite containing greater amounts of coarser-grained (e.g., ∼300–1400 nm) mineral inclusions relative to non-granular and nodular graptolite, which contain finer-grained (e.g., ∼100–200 nm) inclusions difficult to resolve with optical microscopy. These findings are investigated to highlight the mechanisms that drive organic matter evolution within graptolite during thermal maturation, as well as to explore some of the limitations of using spectroscopic parameters as thermal maturity proxies.

International Journal of Coal Geology↗

USGS2024

Diel temperature signals track seasonal shifts in localized groundwater contributions to headwater streamflow generation at network scale

Groundwater contributions to streamflow sustain aquatic ecosystem resilience; streams without significant groundwater inputs often have well-coupled air and water temperatures that degrade cold-water habitat during warm low flow periods. Widespread uncertainty in stream-groundwater connectivity across space and time has created disparate predictions of energy and nutrient fluxes across headwater networks, hindering predictions of cold-water habitat resilience under climate change scenarios. Recently, annual paired air and water temperature signals have been harnessed to indicate stream water thermal sensitivity and the dominance of deep versus shallow groundwater influence, although the utility of diel air–water temperature signal metrics for hydrologic inference has remained unexplored. Here we analyzed two consecutive years of locally paired, air–water temperature data from 47 headwater stream sites in the Catskill Mountains, New York, USA, and discovered characteristic seasonal patterns in diel temperature signal sinusoid metrics (amplitude ratio, phase lag, and mean ratio) driven by shifts in streamflow generation mechanisms and stream network position. Hydrologic interpretations of observed patterns were supported by stream heat budget model scenarios and additional analysis of paired air–water temperature data from two streams in Shenandoah National Park, Virginia, USA, with well characterized stream-groundwater connectivity. We found that within smaller tributaries, streamflow generation transitions from runoff to groundwater dominance were driven by hillslope drying during seasonal periods of lower precipitation. This was evidenced by significant correlations (p < 0.01) between daily water:air temperature signal amplitudes (non-linear decreases of ∼ 50 %) and derived base-flow index at 22 of the 28 sites, indicating enhanced local groundwater influence on streamflow promotes decoupling of diel air–water temperature signals. Additionally, ratios between daily water:air temperature signal means were lower in tributaries (∼0.68) when compared to main-stem (∼0.8) sites, increasing linearly throughout the observational period. In conceptual stream heat budget models, groundwater inflow had minimal effects on daily phase lags (∼0.2 hr), but increases in fractional groundwater discharge (0–50 %) depressed daily amplitude (∼20 % to 50 %) and mean ratios (∼15 %), supporting the sensitivity of daily metrics to interpreted changes in seasonal groundwater contributions to streamflow. During observational periods (i.e., April through October 2021 and 2022), significant differences (p < 0.01) between tributary and main-stem air–water metrics occurred when base-flow contributions were highest (∼0.93 vs. ∼ 0.68), as sites lower in the network had daily temperature metrics dominated by stream channel thermal inertia, rather than local groundwater connectivity, showing enhanced air–water diel signal coupling during warmer, drier periods. Divergent air temperature coupling across the network was interpreted as being driven by distance from local groundwater source zones, additional lateral groundwater inflows do not contribute a meaningful fraction to channel discharge lower in the network. Given the growing footprint of stream temperature observations, diel air–water temperature signals can provide distributed metrics sensitive to upstream groundwater discharge. Consequently, these metrics can support ongoing efforts by resource managers and researchers seeking to forecast the resilience of cold-water habitat to climate warming and changing precipitation regimes in mountain headwater streams.

New York, Virginia↗