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Results for “Environmental Monitoring and Assessment”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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1,662 records · Page 32Linked to original sources
USGS2023

Stream sediment geochemistry in mineral exploration: A review of fine-fraction, clay-fraction, bulk leach gold, heavy mineral concentrate and indicator mineral chemistry

Stream sediment surveys support early-stage reconnaissance mineral exploration and regional assessment programmes, enhanced by recent improvements in analytical method detection limits, continuously improving mineral chemistry, and new approaches to the interpretation of geochemical data. Sediment surveys may be used to predict catchment basin lithology, mineralization type based on pathfinder geochemistry, and geological features based on indicator mineral chemistry. Sediment surveys that target a finer-fraction sediment sample led to the discovery of the La Colosa gold deposit, Colombia. The Batu Hijau porphyry Cu–Au deposit in Indonesia was discovered based on an anomalous clay-sized fraction sample 12 km downstream. In an arid region with poorly developed drainages and minor topographic relief, the Ag-base-metal Navidad District in Argentina was discovered with clay-fraction sediment geochemistry. Heavy mineral concentrate (HMC) sediment surveys that include mineral chemistry determinations have led to global diamond discoveries. HMC surveys contributed to discovery of the Ring of Fire Ni–Cu–PGE and chromite district, Ontario, Canada. Discoveries and geochemical mapping can assist advancement of the application of stream sediment geochemistry in those global areas for which lithologies and deposits are exposed. Stream sediment surveys continue to be one of the most cost-effective geochemical methods for covering large areas for mineral exploration.

Geochemistry: Exploration, Environment, Analysis↗
USGS2026

USGS Geochron—A database of geochronological and thermochronological dates and data—Technical documentation

Geochronological and thermochronological data are essential for constraining the timing and rates of geological processes, supporting geologic mapping, natural hazard assessment, and resource exploration. The U.S. Geological Survey (USGS) Geochron Database is a centralized, relational database that integrates USGS and State geological survey data in accordance with the National Geologic Mapping Act of 1992 and its reauthorizations. This report documents the structure and development of the database, including its standardized schema, controlled vocabularies, and protocols for compiling legacy and newly published data. The database is designed to adhere to FAIR (Findable, Accessible, Interoperable, and Reusable) data principles and currently (2026) includes data from a wide range of geochronological and thermochronological methods. Public access is provided through the USGS Geochron Database Explorer, a browser-based geographic information system (GIS) interface, and through versioned data releases available on ScienceBase, which provide sample-level summary data and detailed analytical information. The USGS Geochron Database is structured to be extensible, supporting the inclusion of additional methods and data types as they are compiled. This format ensures long-term utility and aligns with the Mapping Act’s directive to create a national archive of geochronological information that adds interpretive value to geologic map data. Its design reflects a commitment to data transparency, scientific reproducibility, and national geoscience priorities.

Data Report↗
USGS2024

Revision of ModelMuse to support the use of PEST software with MODFLOW and SUTRA models

Executive Summary ModelMuse is a graphical user interface for several groundwater modeling programs. ModelMuse was updated to generate the input files for the parameter estimation software suite PEST. The software is used with MODFLOW or SUTRA models to run PEST-based parameter estimation and display the updated model inputs after parameter estimation. The PEST input files can also be used with the PEST++ version 5 software suite. Parameter estimation typically requires defining the parameters being adjusted during calibration and observations for assessing calibration quality. After a parameter is defined in ModelMuse, it can be applied to all or part of a model dataset. Pilot points—a parameterization device that facilitates higher levels of parameterization—can be used to assign spatially variable distributions of model inputs. Parameters can be applied to temporally varying features, such as boundary conditions, by either applying them to all the values in a series in one step or by applying separate parameters to individual members of a series. ModelMuse allows the definition of many observation types from various model output files. For MODFLOW 6 and SUTRA models, new options were added to ModelMuse to allow it to display the changed input after parameter estimation is complete. For MODFLOW–2005 and MODFLOW–NWT models, ModelMuse can import an entire model for visualization. An example illustrates the use of PEST with a MODFLOW 6 model in ModelMuse.

Techniques and Methods↗
USGS2025

A 700-year rupture sequence of great eastern Aleutian earthquakes from tsunami modeling of stratigraphic records

Great Aleutian underthrusting earthquakes produced destructive tsunamis impacting Hawaiʻi in 1946 and 1957. Prior modeling of the 1957 tsunami deposit and runup records on eastern Aleutian and Hawaiian Islands jointly with tide-gauge observations across the Pacific Ocean constrained a rupture model with shallow slip up to 26 m along 600 km of the plate boundary. Here we implement this modeling approach to older deposits and show alternating deep and shallow megathrust slip up to 26, 32, and 22 m for great earthquakes along the same segment in the 18 th , 15 th , and 14 th centuries. All three modeled prehistoric Aleutian earthquakes produce tsunami inundation in Hawaiʻi with the most severe, 14 th century event having impacts exceeding the 1957 event. The along-dip variability of these four ruptures spanning seven centuries provides insights on earthquake cycles for engineering design and hazard assessment. The 15 th century and 1957 rupture models provide evidence for recurrence of tsunami earthquakes, which can produce disproportionately large tsunamis for a given moment magnitude due to reduced rigidity in the shallow megathrust. The 14 th and 18 th century events likely ruptured deeper regions that did not slip in 1957, suggesting potential for corresponding deeper failure in the next great eastern Aleutian earthquake.

Alaska, Hawaii↗
USGS2024

Projections of multiple climate-related coastal hazards for the US Southeast Atlantic

Faced with accelerating sea level rise and changing ocean storm conditions, coastal communities require comprehensive assessments of climate-driven hazard impacts to inform adaptation measures. Previous studies have focused on flooding but rarely on other climate-related coastal hazards, such as subsidence, beach erosion and groundwater. Here, we project societal exposure to multiple hazards along the Southeast Atlantic coast of the United States. Assuming 1 m of sea level rise, more than 70% of the coastal residents and US \ $ 1 trillion in property are in areas projected to experience shallow and emerging groundwater, 15 times higher than daily flooding. Storms increase flooding exposure by an order of magnitude over daily flooding, which could impact up to ~50% of all coastal residents and US \ $ 770 billion in property value. The loss of up to ~80% of present-day beaches and high subsidence rates that currently affect over 1 million residents will exacerbate flooding and groundwater hazard risks.

Florida, Georgia, North Carolina, South Carolina, ↗
USGS2024

The projected exposure and response of a natural barrier island system to climate-driven coastal hazards

Accelerating sea level rise (SLR) and changing storm patterns will increasingly expose barrier islands to coastal hazards, including flooding, erosion, and rising groundwater tables. We assess the exposure of Cape Lookout National Seashore, a barrier island system in North Carolina (USA), to projected SLR and storm hazards over the twenty-first century. We estimate that with 0.5 m of SLR, 47% of current subaerial barrier island area would be flooded daily, and the 1-year return period storm would flood 74%. For 20-year return period storms, over 85% is projected to be flooded for any SLR. The modelled groundwater table is already shallow (< 2 m deep), and while projected to shoal to the land surface with SLR, marine flooding is projected to overtake areas with emergent groundwater. Projected shoreline retreat reaches an average of 178 m with 1 m of SLR and no interventions, which is over 60% of the current island width at narrower locations. Compounding these hazards is subsidence, with one-third of the study area currently lowering at > 2 mm/yr. Our results demonstrate the difficulty of managing natural barrier systems such as those managed by federal park systems tasked with maintaining natural ecosystems and protecting cultural resources.

North Carolina↗
USGS2026

A methods framework for evaluating measurement consistency across spectrometers for multispectral uncrewed aerial system vegetation mapping applications

The U.S. Geological Survey collects remote sensing data to support national scientific assessments of natural resources, hazards, and landscape change. Spectrometers and spectroradiometers are essential for gathering point-based spectral measurements used in applications such as uncrewed aerial systems (UAS) multispectral image calibration, validation, and analysis. Evaluating how different instruments perform in laboratory and field environments helps determine whether they provide consistent, interoperable measurements. Such verification can expand access to spectral ground data during UAS operations by allowing scientists to use alternative instruments when budgets, logistics, or field conditions limit options. We propose and test a methodological framework for evaluating spectrometers for measurement consistency during UAS multispectral vegetation mapping applications. There are three central evaluation components to the framework: laboratory, field, and relative to UAS multispectral imagery. By evaluating the instruments in both relatively controlled and uncontrolled environments, we thoroughly examine measurement consistency and when/why measurements may differ. We opportunistically selected two instruments for a case study in a coastal marsh setting: a compact laboratory spectrometer we modified for field use and a field-ready spectroradiometer. The instruments produced consistent measurements in both environments. We found differences between the field spectra and UAS spectra that likely reflect the perspectives of ground vs. aerial data and indicate that further radiometric calibration may be needed.

Massachusetts↗
USGS2023

The Saudi Geological Survey-U.S. Geological Survey northern Harrat Rahat project—Styles, rates, causes, and hazards of volcanism near Al Madīnah al Munawwarah, Kingdom of Saudi Arabia

Active volcanic systems pose serious hazards to people and property including inundation and incineration by lava, blanketing by tephra (volcanic ash), exposure to noxious volcanic gases, and damage from shallow earthquakes triggered by ascending molten material (magma). To improve understanding of volcanism and associated seismicity on the western Arabia Plate, the Saudi Geological Survey and the U.S. Geological Survey conducted a multi-year investigation of the northern Harrat Rahat volcanic field adjacent to the city of Al Madīnah al Munawwarah, Kingdom of Saudi Arabia. Project components included creation of a high-resolution digital topographic base; interpretation of eruptive history supported by detailed geologic mapping, paleomagnetism, and abundant high-precision geochronology of volcanic deposits; assessments of eruptive styles and volcanic hazards by physical volcanology; investigation of the origins of magmas in the mantle and of their differentiation in the crust revealed by chemical and isotopic petrology; gravity and magnetotelluric surveys to reveal crustal structures and to search for magma reservoirs; and regional and local seismic tomography and analyses of seismic hazards. Project results are presented in this Professional Paper as chapters written for technical scientific audiences. This initial chapter introduces the project and briefly summarizes results in plain language for readers who have more general backgrounds.

Al Madīnah al Munawwarah↗
USGS2026

Long-term monotonic trends in water budget components in the contiguous United States: Insights from two hydrologic models

Characterizing changes to water availability for domestic, industrial, agricultural, and other uses is essential to support water management. To better quantify these changes, the U.S. Geological Survey and National Science Foundation National Center for Atmospheric Research produced two hydrologic models simulating water budget components from 1980 to 2021 over the contiguous United States (CONUS). Both hydrologic models were driven by a common atmospheric forcing dataset and aggregated to common spatial and temporal scales, which enables a novel evaluation of congruency between the models. We present annual and seasonal trends in six water budget components (precipitation, evapotranspiration, streamflow, groundwater recharge, soil saturation, and snow water equivalent) based on the Mann–Kendall test for monotonic trend and Theil-Sen slope estimate for the water year 1983–2021 period for ~86,000 catchments in CONUS. Additional components and metrics from our analysis pipeline are available in an associated published dataset, which contains more than 46 million trend results. The water budget trends showed broad agreement with prior observational and modeling studies that indicate increasing trends in the northeast and decreasing trends in southwestern CONUS. We found the seasonal variability in water budget trends was greatest in the southern, central, and northwest CONUS. These findings support integrated trend assessments when coupled with trends in water quality and use.

Contiguous United States↗
USGS2026

Spatially referenced watershed models for the binational Red–Assiniboine River Basin: Bayesian vs frequentist comparison

Excess nutrient loading remains a leading cause of declining water quality in lakes, estuaries, and coastal waters worldwide, with global economic costs of US$200 billion – US$2 trillion annually from impacts on fisheries, tourism, freshwater resources, and water treatment. Our study focuses on total phosphorus (TP) in Lake Winnipeg and its binational Red-Assiniboine River Basin, where nutrient inputs have degraded water quality and increased cyanobacterial blooms. These changes pose ecological, public health, and economic risks. We applied a spatially referenced watershed model with a hybrid statistical-mechanistic structure partitioning annual nutrient loads into land-use export, land-to-water delivery, and in-reservoir decay. Bayesian and traditional frequentist model calibrations were compared. In the frequentist model, coefficients for agricultural inputs, forests /wetlands, stream channels, precipitation, and reservoir losses were statistically significant, whereas coefficient for wastewater was not. In contrast, all variables were successfully calibrated using the Bayesian approach. Model results delineate TP-export hotspots across the basin, showing that 54–62% of TP originates from the U.S., with agricultural sources ranging 62–72%—highlighting the importance of agriculture-focused Best Management Practices. Given the global relevance of nutrient-driven water-quality challenges, our results highlight Bayesian calibration for robust risk assessment and adaptive nutrient management.

Red–Assiniboine River Basin↗
USGS2024

Forecasting storm-induced coastal flooding for 21st century sea-level rise scenarios in the Hawaiian, Mariana, and American Samoan Islands

Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding in the populated Hawaiian, Mariana, and American Samoan Islands as a result of climate change and sea-level rise. We followed a hybrid (dynamical and statistical) downscaling approach to map flooding due to waves and storm surge at 10-square meter resolution along all 1,870 kilometers of these islands’ coastlines for annual (1-year), 20-year, and 100-year return-interval storm events and +0.00 meter (m), +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m sea-level rise scenarios. We quantified the coastal flood depths and extents using the latest climate forcing from Intergovernmental Panel for Climate Change’s Sixth Assessment Report Coupled Model Intercomparison Project. The data generated using these methods provide stakeholders and decision makers with a spatially explicit, rigorous valuation of how, where, and when climate change and sea-level rise increase coastal storm-induced flooding to help identify areas where management and (or) restoration could potentially help reduce the risk to, and increase the resiliency of, the coastal communities in the populated Hawaiian, Mariana, and American Samoan Islands.

Hawaii↗
USGS2026

Rewilding the upper Klamath River Basin: Rapid recolonization of Chinook salmon following the world’s largest dam removal

Habitat fragmentation is a global driver of decline in biodiversity, yet evaluations of ecological response following re-connection remain rare. In 2024, four hydroelectric dams on the Klamath River were removed, reconnecting over 640 km of anadromous habitat and marking the largest dam removal project completed to date. We used a stationary high-resolution multi-beam imaging SONAR to quantify adult Chinook salmon ( Oncorhynchus tshawytscha ) passage into newly reopened reaches during the first two migratory seasons following dam removal. An estimated 7,742 (95% CI: 7,702–7,778) Chinook salmon migrated upstream in 2024 and 13,310 (95% CI: 12,876–13,733) in 2025, representing 18–19% of fish returning to the Klamath River Basin. Within this period, Chinook salmon recolonized 88% of their documented historical distribution, expanding into 345 km of reconnected habitats and reaching elevations of up to 1,250 m. Recolonization required fish to swim through dam removal sites, complex hydraulic corridors and engineered fishways, demonstrating the propensity for rapid recolonization at basin scale despite these challenges. These findings provide the first quantitative assessment of salmon response to the world’s largest dam removal and demonstrate how reconnection can catalyze large-scale recolonization in historically fragmented river networks.

California, Oregon↗
USGS2024

Afterslip and creep in the rate-dependent framework: Joint inversion of borehole strain and GNSS displacements for the Mw 7.1 Ridgecrest earthquake

The elusive transition toward afterslip following an earthquake is challenging to capture with typical data resolution limits. A dense geodetic network recorded the Mw 7.1 Ridgecrest earthquake, including 16 Global Navigation Satellite System (GNSS) stations and 3 borehole strainmeters (BSM). The sub-nanostrain precision and sub-second sampling rate of BSMs bridges a gap between conventional seismologic and geodetic methods, exemplified by atypical postseismic shear strain reversals observed at nearfield (<2 km) station B921 that remain unexplained. We jointly invert GNSS displacements and BSM strains for coseismic and postseismic slip spanning hours to months over 7 independent periods. Cosiesmically, our model resolves the largest slip magnitudes of up to 6.6 m on the mainshock rupture plane, with similar patterns to other inferred slip distributions. The foreshock fault appears to slip coincidently with mainshock, revealing potential asperities activated during the preceding Mw 6.4 event. Postseismically, the best-fitting models adhere to mechanical rate-and-state expectations of logarithmically decaying slip adjacent to the coseismic rupture terminus, and where deep rheologic conditions favor creep. Most spatial variation occurs in the early postseismic timeframe (<1–2 weeks), with evidence for regional rheologic control and static stress dependence. Triggered creep on the neighboring Garlock Fault unexpectedly persists for >178 days—further highlighting the importance of fault networks in postseismic stress redistribution, critical to assessing future hazard.

Journal of Geophysics Research↗
USGS2025

Global patterns of coseismic landslide runout mobility differ from aseismic landslide trends

Coseismic landslides significantly contribute to human and economic losses during and immediately following earthquakes, yet very little data on the runout of such landslides exist. While well-established behavior of aseismic (e.g., hydrologically triggered) landslide runout mobility suggests strong correlation between landslide size and mobility, limited studies of coseismic landslide runout find conflicting mobility trends. We present a global dataset of runout lengths produced from a new automated method for estimating landslide runout, developed and validated using 1726 manually mapped landslides from five unique earthquakes. We then apply the automated runout tool to 23 global earthquake-induced landslide inventories, producing a compiled database of 73,665 measured and estimated runout lengths of coseismic landslides to assess mobility trends. We find a significant divergence between well-established aseismic mobility trends and that of coseismic landslides, with far greater scatter and more complex mobility patterns in earthquake-triggered landslides. As a function of landslide size, we observe global coseismic landslide mobility patterns are bilinear, becoming increasingly less mobile with increasing size above some threshold. This discordance between aseismic and coseismic landslide mobility may be a function of landslide type, kinematics, hydrology, and or setting that systematically differ between triggering mechanisms and should be explored in more depth to develop predictive models of these unique runout patterns. These results suggest hazard and risk models for coseismic landslides may significantly under-predict or over-predict impacts, depending on the size of triggered landslides.

Engineering Geology↗
USGS2025

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

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

Book chapter↗
USGS2025

Insights into widespread landsliding in southern Appalachia from Hurricane Helene

Between 23 and 27 September 2024, antecedent rain followed by Hurricane Helene produced one of the most damaging weather events in southern Appalachia history. The back-to-back storm events resulted in a maximum cumulative rainfall of 848 mm and hurricane-force wind gusts over 170 km/h in western North Carolina, eastern Tennessee, and southwestern Virginia. The resulting regional flooding, landslides, and tree blowdown caused over 100 fatalities, damaged or destroyed critical infrastructure and thousands of structures, and severed connectivity across the region. Over the next several weeks, a multi-agency landslide response produced a rapid hazard assessment and mapped 2217 landslides, 55% of which damaged infrastructure or property. Orographic uplift enhanced rainfall, resulting in concentrated landsliding along the ~250 km swath of the Blue Ridge escarpment in western North Carolina. Landslides initiated predominantly on windward-facing (southeast-facing) slopes, and localized clustering of initiation points indicated a strong influence of hillslope-scale meteorological and geomorphic factors. Many shallow landslides mobilized into larger, highly mobile, and damaging debris flows that graded into floods. Here, we put our preliminary observations in the context of historical storm-driven landslide events and open new avenues for investigating the nature and extent of landslides and their effects in southern Appalachia and similar environments.

Georgia, North Carolina, South Carolina, Tennessee↗
USGS2026

Flood-inundation maps for Río Grande De Loíza in and near Caguas, Puerto Rico, 2026

Digital flood-inundation maps for a 2.7-mile reach of Río Grande De Loíza in Caguas, Puerto Rico, were created by the U.S. Geological Survey. Water-surface profiles were computed for the stream reach by using a one-dimensional, steady-state, step-backwater model. The model was calibrated to the current (2025) stage-streamflow relation (rating curve) for the U.S. Geological Survey streamgage 50055000, Río Grande De Loíza, Puerto Rico. The resulting hydraulic model was then used to compute 16 water-surface profiles for water levels (flood stages) ranging from 19.00 to 34.00 feet at the streamgage; these flood stages range from “moderate flood stage” to above “major flood stage” as defined by the National Weather Service. The 34.00-foot stage exceeds the historical maximum peak stage of 33.20 feet, recorded at the streamgage in 1945. The simulated water-surface profiles were used in combination with a digital elevation model derived from light detection and ranging (lidar) data to map the inundated areas associated with each flood profile. The flood-inundation maps and the supporting hydraulic model produced by this study can be used by emergency managers and local officials to assess flood-mitigation strategies and to define flood-hazard areas to help protect life and property, to coordinate flood-response activities such as evacuations and road closures, and to aid post-flood recovery efforts.

Puerto Rico↗
USGS2026

The United States Magnetotelluric Array and the National Impedance Map

The United States Magnetotelluric Array (USMTArray) data set, collected in the years 2006–2024, consists of more than 1,700 long-period magnetotelluric stations covering the entirety of the contiguous United States on a quasi-regular 70 km grid. Funding across multiple federal agencies was critical to sustaining this effort to its completion. Important components of the project included active guidance and participation from the MT community, the open and timely availability of all data, and the application of consistent instrumentation and robust data processing. Together with parallel advancement in the development of publicly available three-dimensional (3D) inversion codes, the USMTArray has revitalized the US magnetotelluric community and increased the visibility of magnetotellurics within the Earth-science community. Taken as a whole, these data are visualized as the National Impedance Map, which, together with a 3D synthesis conductivity model of the nation, reveals the electrical architecture of the contiguous US. USMTArray data are used by researchers worldwide for fundamental and applied studies, including investigations of continental architecture and evolution, estimation of hazards to critical infrastructure due to geomagnetic storms, and assessment of the nation's undiscovered geothermal and mineral resources. We here review the history and development of the project, discuss the challenges and successes in its execution, present the National Impedance Map and synthesis conductivity model, and highlight the breadth of research stemming from this rich data set.

conterminous United States↗