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USGS2024

Remote sensing evapotranspiration in ensemble-based framework to enhance cascade routing and re-infiltration concept in integrated hydrological model applied to support decision making

Integrated hydrological models (IHMs) help characterize the complexity of surface–groundwater interactions. The cascade routing and re-infiltration (CRR) concept, recently applied to a MODFLOW 6 IHM, improved conceptualization and simulation of overland flow processes. The CRR controls the transfer of rejected infiltration and groundwater exfiltration from upslope areas to adjacent downslope areas where that water can be evaporated, re-infiltrated back to subsurface, or discharged to streams as direct runoff. The partitioning between these three components is controlled by uncertain parameters that must be estimated. Thus, by quantifying and reducing those uncertainties, next to uncertainties of the other model parameters (e.g. hydraulic and storage parameters), the reliability of the CRR is improved and the IHM is better suited for decision support modelling, the two key objectives of this work. To this end, the remotely sensed MODIS-ET product was incorporated into the calibration process for complementing traditional hydraulic head and streamflow observations. A total of approximately 150,000 observations guided the calibration of a 13-year MODFLOW 6 IHM simulation of the Sardon catchment (Spain) with daily stress periods. The model input uncertainty was represented by grid-cell-scale parameterization, yielding approximately 500,000 unknown input parameters to be conditioned. The calibration was carried out through an iterative ensemble smoother. Incorporating the MODIS-ET data improved the CRR implementation, and reduced uncertainties associated with other model parameters. Additionally, it significantly reduced the uncertainty associated with net recharge, a critical flux for water management that cannot be directly measured and rather is commonly estimated by IHM simulations.

Sardon catchment↗
USGS2021

Virginia and Landsat

From the shores of Jamestown and spreading north, south, and west, the lands that became the State of Virginia were some of the first in North America top experience rapid landscape change from European settlement. Imagery and data from the USGS Landsat series of satellites offer an unparalleled resource for the study, understanding, and preservation of Virginia’s land and water resources. From monitoring the health of water bodies to managing invasive species to planning for a range of climate change effects, the USGS National Land Imaging Program’s stewardship and public delivery of Landsat data have benefitted Virginians in myriad ways.

Virginia↗
USGS2025

Simulation of groundwater flow in Wake County, North Carolina, 2000 through 2070

In 2019, the U.S. Geological Survey and Wake County Environmental Services began a collaborative study to evaluate groundwater resources and long-term groundwater availability in the county’s fractured-rock groundwater system. Wake County, in central North Carolina, is experiencing rapid population growth, associated land development, and changing water use. Hydrogeologic data including groundwater levels, aquifer testing, borehole fracture flow measurements, water-quality samples, and groundwater age-dating tracers were collected, along with findings from previous investigations, to help inform a conceptual model of the flow system used to develop a modular three-dimensional finite-difference groundwater-flow model (MODFLOW) for simulating historical and future groundwater conditions from 2000 to 2070. Hydraulic conductivity and transmissivity ranges were estimated from 17 slug tests and 21 borehole-flow measurements. Groundwater-quality analytical results from 19 sampling sites indicate that oxidation-reduction (redox) conditions varied within the regolith and bedrock and that minimal evaporation occurred before recharge entered the groundwater system. Age dating revealed mixtures of older and younger water, ranging from the 1940s to the 1990s—indicating variable flow pathways of recharge within permeable bedrock fracture zones. To simplify the complex fractured-rock groundwater system, two layers representing the regolith and the fractured bedrock were used in the MODFLOW model. Model calibration included parameter estimation and provided a reasonable fit to observed groundwater levels and estimated stream base flows. The model forecast scenarios incorporated future climate-model data for two emissions scenarios with land cover change projections to simulate potential impacts to future groundwater levels, recharge, and base flows. Recharge and base flow projections were largely within historical ranges, with no apparent long-term trends, but did indicate a slight downward shift in median values—likely, in part, because of differences in spatial resolution of input climate datasets. Seasonal patterns were consistent with historical data, with projections of possible increases in future winter recharge. Model limitations are discussed, and additional monitoring and model refinement needs are highlighted to support decision making for local groundwater management.

North Carolina↗
USGS2025

Meet the people where they are: Assessing user needs for aftershock forecast products in El Salvador, Mexico and the United States

Aftershock forecasts can help communities reduce their seismic risk by conveying how many aftershocks can be expected following a large earthquake, and how the expected number of aftershocks and their corresponding ground shaking evolves over time and space. Prior work finds that graphical forecast products may communicate such information better than only text or numbers. To identify which visual products can serve multiple user groups, we held workshops with members of several professions, including emergency managers, engineers, critical infrastructure operators, public health specialists, science communicators, and more. We conducted these workshops in El Salvador, Mexico and the United States to understand which forecast products may be effective across different countries. In these workshops, users performed small-group activities to elicit the types of aftershock forecast information that would support decisions in their respective roles and how this information would optimally be displayed. Maps of shaking hazards were frequently requested across all professions and countries, even for dissimilar forecast uses. The design of these maps, and other product needs, were differentiated by profession, country and other factors. Other forecast products, including those showing forecasts about the magnitudes and time periods of future aftershocks, also served a variety of users, but for different types of decisions. We found a greater variation in user needs by profession than by country, and that user needs also vary with time, communication channel and other contextual factors. We discuss practical implications for user-centered visual communication of operational aftershock forecasts.

International Journal for Disaster Risk Reduction↗
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↗
USGS2024

Earthquake relocations delineate discrete a fault network and deformation corridor throughout Southeast Alaska and Southwest Yukon

Deformation in southeastern Alaska and southwest Yukon is governed by the subduction and translation of the Pacific-Yakutat plates relative to the North American plate in the St. Elias region. Despite notable historical seismicity and major regional faults, studies of the region between the Fairweather and Denali faults are complicated by glacial coverage and the remote setting. In the last decade, significant improvements have been made to the density of regional broadband seismometer networks. We relocate more than 5,000 earthquakes between 2010 and 2021 in the region of southeastern Alaska and southwestern Yukon utilizing these improved seismic networks. With reductions in catalog uncertainty, particularly in depth, we quantify the thickness of the seismogenic layer in the crust throughout the region and locate seismicity on a shallow network of upper-crustal faults. Relocated earthquakes, combined with an updated focal-mechanism catalog, permit estimating and classifying motion of active faults. This includes mapping the Totschunda-Fairweather “Connector” fault, which plays an important role in explaining regional deformation, and identifying new faults like the Kathleen Lake fault. We draw similarities between our seismic observations and simplified conceptual models of regional tectonics, which describe a dominant transpressional regime and localized slip partitioning. Our results support a hypothesis where current deformation is taking place on a well-defined and evolved network of shallow faults in the corridor between the Totschunda-Fairweather “Connector” and Denali faults.

Alaska, Yukon↗
USGS2024

Water-quality characteristics of the Red River of the North and tributaries in the Fargo-Moorhead metropolitan area, North Dakota, 2019–22

The Flood Risk Management Project was initiated in 2008 in the Fargo-Moorhead metropolitan area to reduce flood risk, flood damages, and flood protection costs in the Fargo-Moorhead metropolitan area. In cooperation with the U.S. Army Corps of Engineers, the U.S. Geological Survey initiated a water-quality monitoring study to describe the water-quality characteristics of the Red River of the North and its tributaries in the Fargo-Moorhead metropolitan area during the preconstruction period of the Flood Risk Management Project from October 1, 2019, to October 1, 2022. The monitoring study included the collection of discrete and continuous water-quality data and streamflow monitoring at selected sites that integrated and enhanced existing monitoring programs within the study area. Discrete samples collected at 10 sites in the Fargo-Moorhead metropolitan area were analyzed for major ions, trace elements, nutrients, suspended sediment, pesticides, and fecal indicator bacteria. In general, major ion concentrations were higher at sites on the tributaries (Wild Rice, Sheyenne, and Maple Rivers) compared to sites on the Red River of the North. In general, bicarbonate, calcium, magnesium, and sulfate represented most of the dissolved ions measured in samples collected at the 10 sites. Calcium, chloride, fluoride, potassium, silica, and sodium were also measured in samples, but they represented a smaller portion of the total dissolved ions. Sulfate was the most dominant dissolved ion that had the highest concentrations among the major ions measured in samples. A total of 18 trace elements were analyzed in discrete samples. Several of the trace elements had concentrations below the laboratory reporting level in all of the samples, including antimony, beryllium, cadmium, chromium, silver, and thallium. Sites on the Wild Rice River generally had the highest concentrations of arsenic, barium, boron, manganese, and nickel compared to the other sites. Nutrients analyzed in discrete samples included filtered and unfiltered concentrations of ammonia, nitrate plus nitrite, phosphorus, and organic carbon. The median filtered ammonia concentration at most sites was less than the laboratory reporting level of 0.03 milligram per liter as nitrogen except for the Sheyenne River at Harwood, North Dakota (U.S. Geological Survey [USGS] station 05060400), and Red River of the North near Georgetown, Minnesota (USGS station 05062130). The lowest median unfiltered nitrate plus nitrite concentration was measured at sites on the Red River of the North upstream from the Fargo-Moorhead metropolitan area and the highest median was at sites on the Red River of the North downstream from the Fargo-Moorhead metropolitan area compared to all other sites. The increase in nitrate plus nitrite concentrations could reflect the effect of the wastewater-treatment plant discharge that enters the Red River of the North upstream from the site located downstream from the Fargo-Moorhead metropolitan area and from urban runoff. Phosphorus (unfiltered) concentrations were generally higher at sites on the Maple and Sheyenne Rivers compared to the other sites and were higher at sites on the Red River of the North downstream from the Fargo-Moorhead metropolitan area compared to sites upstream on the Red River of the North. Suspended-sediment concentrations were generally highest at sites in the Sheyenne River and lowest in the upstream Red River of the North sites. Suspended-sediment concentration was highly variable in samples collected at the 10 sites, mostly influenced by the occurrence of snowmelt and rainfall-runoff events. The Sheyenne River near Kindred, N. Dak. (USGS station 05059000) had the largest range in sediment concentrations in samples collected at the 10 sites. For all sites other than the Sheyenne River near Kindred, N. Dak., 95 percent or more of the suspended sediment had particle diameter sizes less than 0.0625 millimeter in 50 percent of the samples (median). Of the 102 pesticides and pesticide degradates analyzed, 45 constituents had no detectable concentrations in any of the 17 samples collected at five sites. The remaining 57 pesticides had at least one detection in the samples collected at the five sites. The sites on the Wild Rice River (near Abercrombie, N. Dak., USGS station 05053000, and near St. Benedict, N. Dak., USGS station 05053500) and Sheyenne River near Kindred, N. Dak., had fewer pesticide detections compared to the Maple River below Mapleton, N.Dak. (USGS station 05060100) and the Red River of the North at Fargo, N. Dak (USGS station 05054000) and near Georgetown, Minn. Patterns in annual loads generally followed the same pattern as streamflow at the 10 sites for water years 2020–22. A water year is the 12-month period from October 1 to September 30 and is designated by the calendar year in which it ends. The greatest loads for all constituents were delivered at the two downstream sites on the Red River of the North; sites that also had the highest annual streamflows among the sites and the greatest loads were delivered in water year 2020 when the highest streamflows occurred at the sites. Likewise, the least loads for most constituents were at the Maple River and were least in 2021 compared to the other years because of low-streamflow conditions. Water-quality measurements continuously recorded at the Red River of the North at Hickson, N. Dak. (USGS station 05051522); Red River of the North at Fargo, N. Dak.; and Red River of the North near Georgetown, Minn. included water temperature, specific conductance, dissolved oxygen, pH, and turbidity. Specific conductance values were similar for the Red River of the North near Hickson, N. Dak., and Red River of the North at Fargo, N. Dak., when compared to the Red River of the North near Georgetown, Minn. that had higher values than the other two sites. Dissolved oxygen concentrations and pH were similar among the three sites on the Red River. The patterns in turbidity were mostly related to streamflow conditions and were similar among the three sites on the Red River of the North.

Minnesota, North Dakota↗
USGS2024

Geomorphic map of the Umatilla River corridor, Oregon

This map portrays the distribution of landforms along the Umatilla River in northeastern Oregon and covers a corridor 127 kilometers long from the confluence of the Umatilla River with the Columbia River upstream to Meacham Creek. The map encompasses the valley bottom and extends about 1 kilometer up the adjoining hillslopes. Map data are intended to support water quality and fisheries enhancement efforts pursuant to the First Foods, a resource-management approach that focuses on traditionally gathered foods including water, fish, big game, roots, and berries and calls attention to the reciprocity between people and the foods upon which humans depend. The Umatilla River drains about 6,300 square kilometers on the northwest slope of the Blue Mountains in northeast Oregon. Most of the drainage basin is underlain by Miocene basalt flows of the Columbia River Basalt Group. Younger, weakly lithified, late Miocene and early Pliocene gravel deposits of local origin (for example, McKay Formation) are mapped in a few places. Upland surfaces are mantled with windborne silt (loess) correlative with deposits elsewhere known as the Palouse Formation. Surfaces below an elevation of about 340 meters were inundated repeatedly by large Pleistocene glacial outburst floods, most emanating from glacial Lake Missoula in western Montana. In backflooded areas such as the lower Umatilla River valley, Missoula floods deposited extensive slack-water silt. Areas mapped as open water, active channel and tie channel, flood basin, valley bottom, and modified land constitute the geomorphic floodplain: the area subject to occasional inundation by the Umatilla River. Deposits and landforms within the floodplain are inset into Missoula flood deposits and hence postdate the 20–15-kilo-annum Missoula floods. Some floodplain deposits are no more than a few centuries old, as indicated by substantial erosion and deposition during the Umatilla River flood of February 2020, the largest since systematic measurements began in October 1903. Deposits and landforms of the floodplain are transient features within the longer-term incision of the Umatilla River into mid-Miocene flood basalts and younger gravel of the McKay Formation.

Oregon↗
USGS2024

Following the tug of the audience from complex to simplified hazards maps at Cascade Range volcanoes

Volcano-hazard maps are broadly recognized as important tools for forecasting and managing volcanic crises and for disseminating spatial information to authorities and people at risk. As scientists, we might presume that hazards maps can be developed at the time and with the methods of our discretion, yet the co-production of maps with stakeholder groups, who have programmatic needs of their own, can sway the timing, usability, and acceptance of map products. We examine two volcano hazard map-making efforts by staff at the U.S. Geological Survey. During the 1990s and early 2000s scientists developed a series of hazard assessments and maps with detailed zonations for volcanoes in Washington and Oregon. In 2009, the National Park Service expressed the need for simplified versions of the existing hazard maps for a high-profile visitor center exhibit. This request created an opportunity for scientists to rethink the objectives, scope, content, and map representations of hazards. The primary focus of this article is a discussion of processes used by scientists to distill the most critical information within the official parent maps into a series of simplified maps using criteria specified. We contextualize this project with information about development of the parent maps, public response to the simplified hazard maps, the value of user engagement in mapmaking, and with reference to the abundance of guidance available to the next generation of hazard-mapmakers. We argue that simplified versions of maps should be developed in tandem with any hazard maps that contain technical complexities, not as a replacement, but as a mechanism to broaden awareness of hazards. We found that when scientists endeavor to design vivid and easy-to-understand maps, people in many professions find uses for them within their organization’s information products, resulting in extensive distribution.

Washington↗
USGS2025

Altitude of the potentiometric surface and depth to water in the Mississippi River Valley alluvial aquifer, spring 2022

Potentiometric-surface and depth-to-water maps for spring 2022 were created for the Mississippi River Valley alluvial aquifer (MRVA) using groundwater-altitude data from 1,136 wells completed in the MRVA and from the altitude of the top of the water surface in area rivers from 160 streamgages. The potentiometric-surface and depth-to-water maps for 2022 were created to support investigations to characterize the MRVA as part of the U.S. Geological Survey Water Availability and Use Science Program. Sufficient data were available to map the potentiometric surface and depth to water of the MRVA for spring 2022 for about 83 percent of the aquifer area. The potentiometric contours ranged from 0 to 340 feet (ft) above the North American Vertical Datum of 1988. The regional direction of groundwater gradient was generally to the south-southwest, except in areas of groundwater-altitude depressions, where the groundwater gradient was into the depression, and near rivers, where the groundwater gradient can be from aquifer to the river or from the river into the aquifer. There are large depressions in the potentiometric-surface map in the lower one-half of the Cache region and in much of the Grand Prairie and Delta regions. Depth to water in the MRVA, spring 2022, by well ranged from 5.00 ft above land surface to 145.66 ft below land surface.

Mississippi River Valley alluvial aquifer↗
USGS2024

U.S.-Mexico Borderland & vegetation community map

People on both sides of the United States-Mexico border need a high-resolution, binational vegetation community map that spans the entire United States-Mexico borderlands. Traditionally, mapping efforts in this region were impeded by complex logistics related to the international border, differing national needs and plans, and resource allocations and priorities. To address this need, scientists from the U.S. Geological Survey (USGS) Southwest Biological Science Center partnered with the Sonoran Joint Venture, the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program, data engineers from the Department of Biosystems Engineering at the University of Arizona, and collaborators from the Wildlands Network, the Borderlands Program to produce the first prototype land cover map within the overlapping Mojave Desert, Sonoran Desert, and the North American Bird Conservation Initiative’s Bird Conservation Region 33 (BCR33) using Landsat satellite data . BCR33 is an area of high biodiversity, providing habitat for bird species of concern and other wildlife. The land cover map supports FWS recovery plan efforts related to conservation planning activities for many species, including Yellow-billed Cuckoo ( Coccyzus americanus ), Cactus Ferruginous Pygmy-Owl ( Glaucidium brasilianum cactorum ), Southwestern Willow Flycatcher ( Empidonax traillii extimus ), Yuma Ridgway’s Rail ( Rallus obsoletus yumanensis ), Bendire’s thrasher ( Toxostoma bendirei ), LeConte’s thrasher ( Toxostoma lecontei ), Masked Bobwhite ( Colinus virginianus ridgwayi ), jaguar ( Panthera onca ), and endangered plants such as Bartram’s stonecrop ( Graptopetalum bartramii ) and the Pima pineapple cactus ( Coryphantha robustispina ssp. robustispina ). In 2024, a Phase-II map for the full BCR33 region was completed, increasing the understanding of the binational nature of natural communities. The published map and associated paper can be found here .

Borderland↗
USGS2025

Preliminary field report of landslide hazards following Hurricane Helene

Executive Summary This report reflects our knowledge regarding the widespread landslide activity associated with Hurricane Helene observed during the U.S. Geological Survey’s (USGS) mission assignment to North Carolina in October 2024. The material in this report was originally prepared for the Federal Emergency Management Agency under mission assignment DR-4827-NC. The data and commentary in this report are reflective of a report provided to the Federal Emergency Management Agency (FEMA) on October 18, 2024, as well as information provided in briefings at the Buncombe County Emergency Operations Center. The report has been modified for public dissemination. This assessment was based on systematic visual examination and mapping of landslide locations from aerial and satellite imagery, visual and photographic observations from low-level helicopter overflights and conversations with local landslide experts from the North Carolina Geological Survey and Appalachian Landslide Consultants PLLC, and more than 50 years of combined landslide hazard professional experience of the mission-assigned field team. No systematic field investigations were done by the USGS. While responding to the event, the USGS did not identify any landslides that posed an immediate major threat to recovery personnel in parts of nine counties in North Carolina (Avery, Buncombe, Henderson, McDowell, Mitchell, Polk, Rutherford, Watauga, and Yancey); however, threats from renewed landslide activity may remain heightened in localized areas for months or even years. Known areas of the most abundant landslide occurrence include Bat Cave, Lake Lure, Chimney Rock, Swannanoa, Black Mountain, Fairview, steep areas in Asheville, and the Blue Ridge Parkway. The USGS shared detailed locations of known landslides with the Emergency Operations Centers. The thousands of landslide scars on hillsides and landslide deposits on flatter ground may present some threat to recovery activities. Soil and rocks will continue to erode from newly exposed landslide scars and may pose a threat to people and infrastructure who are immediately nearby. In general, the steeper and taller the landslide scar, the greater the potential threat. This threat is heightened during periods of rainfall and increases with the duration and intensity of rainstorms. Very heavy rainfall, or repeated rainfall events during short periods, could also initiate new landslides on steep slopes. Excavation of landslide deposits, particularly excavation of those deposits directly adjacent to steep slopes, may also pose a threat to nearby people and equipment. An interagency collaborative mapping effort led by the USGS that informed this assessment identified 1,155 landslide locations by the October 2024 briefings, but that number increased to 2,217 in a final reviewed version of the locations published in January 2025. Locations were mapped from satellite imagery, fixed-wing and helicopter surveys, media and social media, and field reports in the 3 weeks following the passage of the remnants of Hurricane Helene. USGS products outlined in this report are publicly available and include geotagged photographs from aerial reconnaissance, hazard models, an interactive view of mapped landslide locations, and landslide safety and education resources.

North Carolina, South Carolina, Tennessee, Virgini↗
USGS2026

End-user needs for remote sensing wetlands of the Prairie Pothole Region of North America

The Prairie Pothole Region (PPR) of North America comprises globally important grassland and wetland ecosystems critical for numerous populations of migratory birds. Due to the importance of this region for migratory birds, and particularly waterfowl, and the threats of habitat loss due to intensifying agriculture, there is a mature and diverse system of conservation organizations, agencies, and partnerships that spends hundreds of millions of dollars annually on habitat conservation to support migratory bird populations. Remote sensing can be a powerful tool for observing and evaluating global change at large scales as well as expanding inferences from field studies to the broader landscape with statistical models. However, development and utilization of these tools has lagged behind their demand for several reasons, including concerns over spatial and temporal resolution and accuracy of products; perception of a misalignment with decision-maker needs; technological barriers such as skill sets of conservation professionals, computing resources, data access, and usability. In this report, we summarize the needs of conservation professionals and scientists who use or want to use remote sensing data products to inform science about wetland change and conservation of wetlands in the PPR. We assembled this information through several methods leading up to, during, and following a January 2026 PPR Wetland Remote Sensing Workshop. The workshop included United States and Canadian scientists, conservation professionals, and policy experts. Our goal was to bring together end-users and remote sensing product developers jointly to explore reducing the lag between product development and utilization of products to inform science and conservation. Specifically, we aimed to identify gaps in wetland remote sensing that limit effective monitoring, management, and conservation in the PPR, and to develop a framework that outlines pathways to address these gaps by fostering collaboration, improving communication networks, encouraging discussion, and building on existing and ongoing efforts. This report summarizes our participants’ descriptions of end-user needs and the outcomes of the workshop.

Prairie Pothole region↗
USGS2025

The Mammoth magnetic anomaly, Pinal County, Arizona

A high-resolution Earth Mapping Resources Initiative airborne geophysical survey was flown in the southwest North American porphyry copper province to improve bedrock geologic maps and to identify areas that have unrecognized critical mineral resource potential. During the review of the aeromagnetic data, a distinctly monopolar-shaped, negative magnetic anomaly was observed at a flight elevation of 200 m above the ground with a maximum amplitude of –9500 nT. We have named this the Mammoth magnetic anomaly (MMA) because it is centered 12 km northeast of the town of Mammoth, Arizona, USA. The total field anomaly (TFA) contour of –500 nT enclosing the MMA defines an elongate shape measuring 2.5 km long by 1 km wide that trends northwest–southeast. Given the striking nature of this negative, monopolar-shaped magnetic anomaly, we conducted a ground campaign in May 2025 to determine its authenticity and potential relationship to critical mineral endowment. The MMA was confirmed on the ground with a TFA approaching –46,000 nT. Total magnetic intensity (TMI) observations routinely fell below the 18,000 nT operating floor of an industry-standard cesium-vapor total field magnetometer, and extremely low TMI measurements were corroborated along coincident traverse lines using two high dynamic range, but lower sensitivity, smartphone vector magnetometers. The lowest TMI values recorded by both smartphone magnetometers were 1000 nT and confirmed with multiple adjacent and crossing lines. Field observations suggest that this magnetic feature is caused by strong remanent magnetization within fine-grained magnetite hosted within locally altered Pinal Schist.

Arizona↗
USGS2026

Nonstationary demographic state-space models using unreplicated counts for species undergoing environmental stressors

A fundamental task in ecological statistics is to estimate abundance and growth rate distributions from wildlife monitoring data to inform conservation management. Modeling time series of wildlife populations presents a number of challenges from both statistical and ecological perspectives, including discreteness; lack of replication; nonstationarity; and observation, demographic, and other phenomenological processes. Nonstationary dynamics are often exhibited by populations undergoing environmental stressors. Models must account for these characteristics to produce reliable estimates of abundance and trends, yet estimation can be challenging with unreplicated data. We propose nonstationary demographic state-space models using unreplicated counts for populations undergoing environmental stressors. A reduced growth rate model matches the complexity of the unreplicated count data, and a fecundity bound on growth rate distributions allows the separation of processes affecting growth rates like environmental stressors from those affecting abundance external to growth rates like migration. NDSSMs allow for the embedding of nonstationary model components, and we explore the use of changepoints, volatility clustering, and migration processes. We apply the proposed nonstationary models in case studies of herons affected by predator/competitor reestablishment and three bat species affected by a fungal pathogen causing white-nose syndrome. Nonstationary models outperform stationary models and generalized linear mixed effects models according to model scoring and visual inspection of predictions, and provide estimates more consistent with published values. Incorporating migration improves model fit universally, even with approximate one-way immigration, most likely because populations are extirpated, recolonized, and increase multiple-fold over the upper bound set by species fecundity. In addition, estimates of the timing and severity of the environmental stressor differed for models with migration. Including nonstationary and demographic components in a fecundity-bounded growth rate model improves inference and benefits interpretability of hyperparameters. In turn, this adjusts uncertainties in predictions of abundance and growth rates over time, providing the ingredients needed for informed conservation analysis and for directing future monitoring of at-risk species.

Journal of Agricultural, Biological and Environmen↗
USGS2024

Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin

Flood-frequency analysis, also called peak-flow frequency or flood-flow frequency analysis, is essential to water resources management applications including critical structure design and floodplain mapping. Federal guidelines for doing flood-frequency analyses are presented in a U.S. Geological Survey Techniques and Methods report known as Bulletin 17C. A basic assumption within Bulletin 17C is that for drainage basins without major hydrologic alterations, statistical properties of the distribution of annual peak streamflows (peak flows) are stationary; that is, the mean, variance, and skew are constant. The stationarity assumption has been widely accepted within the flood-frequency community; however, a better understanding of long-term climatic persistence and concerns about potential climate change and land-use change has caused a reexamination of the stationarity assumption. This work is part of that reexamination. The stationarity assumption is a concern because flood-frequency analyses that do not incorporate observed trends and abrupt changes may result in a poor representation of the true flood risk. Bulletin 17C does not offer guidance for incorporating nonstationarities when estimating floods, and it describes a need for studies that incorporate changing climate or basin characteristics. In response to this need and a history of concern regarding nonstationarity peak flows in the region, this study was done to assess potential nonstationarity in peak flows in the north-central United States. This report summarizes the methods used to detect hydroclimatic changes in peak-flow data in the study region. Four periods were selected for analysis of peak flow, daily streamflow, and climate data. The periods are (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. The starting point for these analyses was the initial data analysis of peak flow described in Bulletin 17C, which includes plotting the peak flow and checking for autocorrelation, monotonic trends, and changes points. Analyses were added to examine additional features in the data. Results are provided in a U.S. Geological Survey data release. The study limitations are documented for users of the results.

Scientific Investigations Report↗
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↗
USGS2022

South Carolina and Landsat

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

South Carolina↗