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Cascading land surface hazards as a nexus in the Earth system

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

California

Scientific opportunities in the National Landscape Conservation System

The National Landscape Conservation System consists of unique and beautiful places across America’s landscapes where identified resources and values are protected and science is highlighted. The mission of the National Landscape Conservation System (NLCS), which is managed by the Bureau of Land Management and is often referred to as the agency’s National Conservation Lands, is to conserve, protect, and restore nationally significant landscapes for their cultural, ecological, and scientific values. This clear inclusion of science in the NLCS mission sets the stage for individual units to serve as places of learning, teaching, discovery, and innovation. Science is an integral part of managing the National Conservation Lands, and science conducted within and across the more than 900 units that make up the NLCS can inform and influence conservation and public land management well beyond its boundaries. Here, we highlight seven core aspects of National Conservation Lands that present valuable science opportunities: (1) the scientific values for which individual units are designated; (2) the many other resources, objects, and values within units; (3) the value of units as “control” sites for understanding the effects of activities such as mineral extraction that commonly occur elsewhere on multiple-use public lands but are often prohibited within National Conservation Lands; (4) the value of units for studying the effects of activities such as recreation that regularly occur and may be intensified on National Conservation Lands; (5) the high visibility of units, which draws strong interest and engagement from scientists, partners, and the public; (6) the functioning of the units as a network managed for a common purpose, which provides an opportunity to explore cross-cutting science questions across widely varying contexts and geographies; and (7) the opportunities units provide to promote and apply Indigenous Knowledge to scientific research to manage natural and cultural resources. Because of all of these characteristics, National Conservation Lands can serve as hubs for basic and applied science that can inform management of all public lands and resources into the future. We highlight these science opportunities through examples from existing units and suggest two actions that could help further science activities and impact on National Conservation Lands.

Parks Stewardship Forum

Evaluating machine learning approaches to identify and predict oil and gas produced water lithium concentrations

Recently, the demand for battery-grade lithium has substantially increased, largely due to electrification of the transportation sector. The search for new lithium sources has turned to produced waters (frequently brines), a large-volume wastewater by-product of oil and gas extraction. Geochemical analysis indicates the presence of varying concentrations of lithium from produced water samples collected across the United States and represented in the U.S. Geological Survey’s National Produced Water Geochemical Database, as well as mixtures of Marcellus Shale produced water included in the Pennsylvania Department of Environmental Protection’s Oil and Gas Well Waste Reports. We first examined whether the geochemical signature of the lithium-bearing produced waters is sufficiently distinct so that machine learning (ML) can be used to correctly classify samples to the formation of origin. The produced water sample data used to assess classification accuracy were from the Marcellus Shale, Utica Shale and Point Pleasant Formation (Utica), and Smackover Formation oil and gas wells. Further, we evaluated the potential for ML to accurately classify Marcellus Shale produced water spatially (i.e., northeast versus southwest Pennsylvania). We then investigated whether ML algorithms applied to a suite of geochemical concentration data (i.e. Ba, Br, Cl, K, Mg, Sr) may be used to predict the lithium concentration of an unknown sample. Finally, we applied an estimated economic lithium grade cutoff of 150 milligrams per liter (mg/l) and assessed the utility of ML to predict whether a produced water sample would fall above or below the grade cutoff based on the suite of geochemical parameters. Four machine learning algorithms—Random Forest (RF), Gradient Boosting Trees (GBT), Extreme Boosting (XGBoost), and Deep Neural Networks (DNN) were assessed. This study successfully demonstrates that all four machine learning methods can precisely and accurately estimate lithium concentrations and geologic formation classification. The products of this study contribute to the growing body of knowledge aimed at expanding the lithium resource base within the United States.

Alabama, Arkansas, Florida, Georgia, Louisiana, Mi

Hyperspectral narrowband imaging spectroscopy: A new paradigm for Earth observation

This editorial introduces the Special Issue entitled “Hyperspectral Narrowband Imaging Spectroscopy: A New Paradigm for Earth Observation” in the August 2026 issue of Photogrammetric Engineering & Remote Sensing (PE&RS), the flagship journal of the American Society for Photogrammetry and Remote Sensing (ASPRS). This volume represents the fourth dedicated hyperspectral special issue published in PE&RS, following earlier contributions by Thenkabail et al. (2025, 2024a, 2024b), and continues ASPRS’s commitment to advancing cutting‑edge imaging spectroscopy research and its applications across Earth system science. Remote sensing is undergoing one of the most profound transformations in its history. The emergence of hyperspectral narrowband (HNB) imaging spectroscopy data, capable of acquiring hundreds of contiguous, narrow spectral bands, has shifted the discipline from observing Earth in a handful of broad spectral windows to capturing continuous spectral signatures of the Planet. This transition marks a decisive break from the multispectral paradigm that has dominated satellite remote sensing for nearly five decades, driven by the advent of new orbital imaging spectrometers such as EnMAP, PRISMA, and NASA’s EMIT, and by the forthcoming Surface Biology and Geology (SBG) mission ((Pires Silva et al., 2026; Bourriz et al., 2025; Thenkabail et al., 2025; Chabrillat et al., 2024; Aneece et al., 2024; Dave et al., 2024; Thenkabail et al., 2024a; Thenkabail et al., 2024b; Thenkabail, 2024a; Thenkabail, 2024b; Thompson et al., 2022; Kokaly et al., 2022; Aneece & Thenkabail, 2022; Cawse Nicholson et al., 2021; Guanter et al., 2021; Vangi et al., 2021; Thenkabail et al., 2021). These missions (e.g., Table 1) deliver unprecedented spectral fidelity, improved signal to noise ratios, and global coverage capabilities, enabling a new era of quantitative, spectroscopy based Earth observation. Where multispectral broadbands (MBBs) provide only a few discrete measurements along the electromagnetic spectrum, HNB systems deliver rich, diagnostic information that enables scientists to characterize Earth’s surface with unprecedented biochemical, biophysical, and structural detail (Figure 1a, 1b). The implications for environmental monitoring, agriculture, water resources, and mineral exploration are profound. Several overarching themes emerge: • Spectral fidelity matters. The ability to preserve subtle absorption features is essential for mineral mapping, vegetation trait retrieval, and biochemical modeling. • AI and deep learning are indispensable. From destriping to classification, modern analytics must be scalable, label‑efficient, and capable of exploiting the full spectral–spatial richness of HNB data. • Physics‑based and data‑driven approaches must converge. Radiative transfer models such as PROSAIL, enhanced with localized soil parameterizations, remain foundational for biophysical retrievals and model‑based inference. • Dimensionality reduction and feature extraction are critical. Techniques such as L1‑ISOMAP demonstrate that intelligent manifold learning can unlock the structure of fused, high‑dimensional datasets. • Next‑generation architectures must be interactive and multimodal. ICTNet exemplifies the future of hyperspectral classification: hybrid, synergistic, and capable of modeling both local textures and global spectral dependencies.

Photogrammetric Engineering and Remote Sensing (PE

Satellite imagery of the north-central Gulf of Mexico, June 1993-May 1997

This CD contains imagery collected by the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA polar-orbiting weather satellites. The AVHRR provides almost daily coverage of a site at a resolution of approximately 1 km. The data types included are sea surface temperature (SST), water reflectance (REF), and a false-color infrared overview (FCI).

Alabama, Florida, Louisiana, Mississippi

VIPER site analysis

We needed to evaluate available orbital data of NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) mission area in order to derive a variety of maps to help the science team identify scientifically interesting places for the rover to visit and to provide scientific context for our mission. Some of these maps also fulfilled engineering and mission design needs to enable safe and efficient landing and roving. We incorporated data from the Lunar Reconnaissance Orbiter Camera, the Lunar Orbital Laser Altimeter, the Mini-RF instrument, the Chandrayaan-2 Orbital High Resolution Camera, the Korean Pathfinder Lunar Orbiter’s Shadowcam, the Kaguya Spectral Profiler and Multiband Imager, and the Chandrayaan-1 Moon Mineralogy Mapper. We used a variety of techniques to build these maps, including stereogrammetry, shape-from-shading, ice stability depth and surface temperature calculations, and the horizon method for solar illumination and direct-to-Earth communications maps. Altogether, these maps allowed us to survey for boulders, evaluate features in permanently shadowed regions that VIPER might explore, provide mineralogic context for what VIPER’s instruments may learn, estimate the ages and radar properties of craters in the VIPER mission area, and evaluate the potential for gravity traverses with the rover. These data and techniques provided a rich set of information from which both the VIPER science team and engineering teams were able to draw in order to plan a safe landing and to plan a VIPER surface mission that will be both scientifically valuable and robust from an operational perspective.

The Planetary Science Journal

Unlocking ecological insights from sub-seasonal visible-to-shortwave infrared imaging spectroscopy: The SHIFT campaign

We stand at the threshold of a transformative era in Earth observation, marked by space-borne visible-to-shortwave infrared (VSWIR) imaging spectrometers that promise consistent global observations of ecosystem function, phenology, and inter- and intra-annual change. However, the full value of repeat spectroscopy, the information embedded within different temporal scales, and the reliability of existing algorithms across diverse ecosystem types and vegetation phenophases have remained elusive due to the absence of suitable sub-seasonal spectroscopy data. In response, the Surface Biology and Geology (SBG) High-Frequency Time Series (SHIFT) campaign was initiated during late February 2022 in Santa Barbara County, California. SHIFT, designed to support NASA's SBG mission, addressed mission scoping, scientific advancement, applications development, and community building. This ambitious endeavor included weekly Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) imagery acquisitions for 13 weeks (spanning February 24 to May 29, 2022), accompanied by coordinated terrestrial vegetation and coastal aquatic data collection. We describe the rich datasets collected and illustrate how the complex sub-seasonal patterns of change can be linked to biological science and applications, surpassing insights from multispectral observations. Leveraging open-source processing methods and cloud-based analysis tools, the SHIFT campaign showcases the readiness of the scientific community to harness ecological insights from remotely sensed hyperspectral time series. We provide an overview of SHIFT's goals, data collections, preliminary results, and the collaborative efforts of early career scientists committed to unlocking the transformative potential of high-frequency time series data from space-borne VSWIR imaging spectrometers.

Ecosphere

Remote compositional analyses of space-weathered lunar maria

Visible-to-shortwave infrared (VSWIR) reflectance spectroscopy has revolutionized our understanding of planetary surface compositions. However, space-weathering processes on airless bodies complicate quantitative compositional analyses. Here, we present a framework to isolate the signatures of space weathering in VSWIR spectra of lunar maria by leveraging radiative transfer modeling under the assumptions that (i) a space-weathered target can be expressed as a mixture of fresh and fully space-weathered components and (ii) remaining signatures can be modeled by including agglutinates as an end-member component. We first validate this approach against laboratory spectra of space-weathered Apollo mare soils of known mineral compositions using a probabilistic Markov Chain Monte Carlo implementation of the Hapke radiative transfer model. Second, we illustrate how this approach can be applied to orbital Moon Mineralogy Mapper data. The proposed space-weathering correction workflow for lunar maria could be expanded to other lunar lithologies and applied to existing and future data sets.

Planetary Science Journal

Prospectivity modeling of the NASA VIPER landing site at Mons Mouton near the Lunar South Pole

We use a high-resolution digital elevation model and a numerical thermal model to produce a variety of inputs for a water-ice prospectivity model for the Volatiles Investigating Polar Exploration Rover (VIPER) landing site. These input data are maps of topography, surface slope, surface aspect, surface curvature, maximum temperature, depth to ice stability, permanently shadowed regions (PSRs), distance to PSRs, and PSR density. This model predicts where water ice is most likely within the top meter of regolith, assuming plausible relationships between ice concentration and the various inputs. The model is designed to be adjusted in near-real time as data are collected during the VIPER mission. As such, it is a tool for both analyzing data from the mission as well as planning operations. Since the current model, at this point, relies only on orbital remote sensing, the final version will also be a tool to extrapolate the VIPER mission results across the lunar poles.

Planetary Science Journal

Making many out of one: Synthetic geologic deformation model distributions for use in USGS NSHM25‐PRVI Puerto Rico-U.S. Virgin Island update

A key use‐case of geologic slip rates is within deformation models used in probabilistic seismic hazard analyses. Field‐derived geologic slip rates have formed the cornerstone of deformation models in such applications for decades. Recent advancements in seismic hazard analyses have expanded the use of faults for which geologic slip rates are not well constrained using categorical slip rate estimates. Because of these advancements, application of a geologic deformation model for use in 2025 U.S. Geological Survey National Seismic Hazard Model Puerto Rico‐U.S. Virgin Islands (NSHM25‐PRVI) proved challenging due to: (1) a lack of field‐based geologic slip rates, and (2) a lack of epistemic uncertainty distributions within a broad range of estimated slip rates. Preliminary versions of the NSHM25‐PRVI model sampled these slip rate bins in a coincident manner along preferred and extreme value branches, which yielded untenable correlations in mean hazard results. To minimize the influence of correlated uncertainties amid these challenges, we develop a synthetic epistemic uncertainty distribution for deformation rate on each crustal fault. Each fault has a weighting schema across four possible distribution shapes: uniform, normal, triangular favoring local minima, and triangular favoring local maxima. The synthetic distributions are then sampled several times for each logic tree branch. The results provide a more realistic distribution of rates across the study region as compared with using correlated extrema sampling. This exploration of our method in a small region like PRVI can pave the way for larger‐scale, more complicated applications (e.g., western United States).

Puerto Rico, US Virgin Islands

Earthquake effects surveyed during the nineteenth century as ecological features of Chinookan tidelands

Lasting effects of a Cascadia earthquake in 1700 were documented during surveys of Chinookan tidelands near the mouth of the Columbia River between 1805 and 1868. The effects resemble estuarine consequences, near Anchorage, of the 1964 Alaska earthquake: fatal drowning of subsided meadows and forests by post-earthquake tides, rebirth of marshes and forests through post-earthquake sedimentation, and uplift. Chinookan remains of killed forests were recorded by James Graham Cooper, John J. Lowell, and Cleveland Rockwell. Cooper, attached to a railroad survey and the Smithsonian Institution, wrote of redcedar stumps and trunks standing dead in tidal marshes of Shoalwater (now Willapa) Bay. Two such snags served as bearing trees for Lowell as he platted a Shoalwater Bay township under contract with the General Land Office. Rockwell, of the US Coast Survey, flecked landward edges of tidal flats west of Astoria with symbols that evoke remains of a bygone spruce forest. The Lewis and Clark Expedition, while in that area in 1805–1806, mapped and puzzled over tideland vegetation that post-1700 succession helps explain.

Alaska, British Columbia, California, Oregon, Wash

Slope Unit Maker (SUMak): An efficient and parameter-free algorithm for delineating slope units to improve landslide modeling

Slope units are terrain partitions bounded by drainage and divide lines. In landslide modeling, including susceptibility modeling and event-specific modeling of landslide occurrence, slope units provide several advantages over gridded units, such as better capturing terrain geometry, improved incorporation of geospatial landslide-occurrence data in different formats (e.g., point and polygon), and better accommodating the varying data accuracy and precision in landslide inventories. However, the use of slope units in regional ( > 100 km 2 ) landslide studies remains limited due, in part, to the large computational costs and/or poor reproducibility with current delineation methods. We introduce a computationally efficient algorithm for the parameter-free delineation of slope units that leverages tools from within TauDEM and GRASS, using an R interface. The algorithm uses geomorphic laws to define the appropriate scaling of the slope units representative of hillslope processes, avoiding the often ambiguous determination of slope unit size. We then demonstrate how slope units enable more robust regional-scale landslide susceptibility and event-specific landslide occurrence maps.

Natural Hazards and Earth Systems Sciences (NHESS)

Triple-oxygen isotopic evidence of prolonged direct bioleaching of pyrite with O2

Sulfate is often touted as containing atmospheric oxygen whose isotopic signature can constrain redox, environmental conditions, and biological activity. Yet, the amount and isotopic fractionation associated with air-O 2 incorporation during sulfate formation is still debated, making its verification difficult. In this study, we identify a distinct, microbially dominated environment with the potential to preserve maximum signals of air-O 2 in sulfate. We report triple-oxygen isotope data for sulfate produced from pyrite oxidation in microbial and abiotic experiments, and from natural dissolved sulfate from the Rio Tinto, Spain, an acid mine drainage site. The oxygen isotope systematics of sulfate in these environments define a unique kinetic isotope effect associated with initial stage pyrite oxidation by Acidithiobacillus ferrooxidans that preserves >80 % oxygen from air-O 2 in sulfate. Unlike experiments, which evolve toward water-oxygen dominated sulfate on short time scales, Rio Tinto, Spain hosts a microbe rich environment with distinct geochemistry that maintains high O 2 -oxygen in sulfate. Therefore, in addition to containing isotopic records from water and air, sulfates can also contain a biosignature that is promising for understanding conditions on Mars and early Earth.

Earth and Planetary Science Letters

Fiber-optic sensing for earthquake hazards research, monitoring and early warning

The use of fiber‐optic sensing systems in seismology has exploded in the past decade. Despite an ever‐growing library of ground‐breaking studies, questions remain about the potential of fiber‐optic sensing technologies as tools for advancing if not revolutionizing earthquake‐hazards‐related research, monitoring, and early warning systems. A working group convened to explore these topics; we comprehensively examined the application of fiber optics in various aspects of earthquake hazards, encompassing earthquake source processes, crustal imaging, data archiving, and technological challenges. There is great potential for fiber‐optic systems to advance earthquake monitoring and understanding, but to fully unlock their capabilities requires continued progress in key areas of research and development, including instrument testing and validation, increased dynamic range for applications focused on larger earthquakes, and continued improvement in subsurface and source imaging methods. A key current stumbling block results from the lack of clear data archiving requirements, and we propose an initial strategy that balances data volume requirements with preserving key data for a broad range of future studies. In addition, we demonstrate the potential for fiber‐optic sensing to impact monitoring efforts by documenting the data completeness in a number of long‐term experiments. Finally, we outline the features of a instrument testing facility that would enable progress toward reliable and standardized distributed acoustic sensing data. Overcoming these current obstacles would facilitate progress in fiber‐optic sensing and unlock its potential application to a broad range of earthquake hazard problems.

California, Oregon, Washington

Estimating paleotemperature using stable isotopes of soil-formed phyllosilicates from paleosols: A review

Fossilized soils, or paleosols, contain soil-formed phyllosilicates whose stable isotopic compositions may be used to calculate paleotemperature and thus reconstruct ancient terrestrial environments. Though paleosols are common in the geologic record, the use of phyllosilicates as paleotemperature proxies is limited in the literature owing to difficulties with selecting optimal paleosols, isolation from non-clay minerals and organic materials, mixtures of phyllosilicates in natural samples, wide variations of chemical compositions for phyllosilicates, and limited to undefined equilibrium fractionation factors between phyllosilicates-water. Here, we address these challenges by examining and comparing methods used for sample selection, mineral isolation, pretreatments, mineral identification, conventional and developing methods for oxygen and hydrogen isotopic analyses, and determination of phyllosilicate-water equilibrium fractionation factors, concluding with recommendations for best approaches for paleotemperature estimation. Additionally, we discuss how to identify and avoid detrital phyllosilicates, the impacts of diagenesis, comparison of stable isotope and non-isotope paleosol paleotemperature proxies, and challenges and opportunities for broadly using paleosols as paleoclimate archives. With ongoing efforts to refine this multi-faceted paleotemperature approach, the stable isotope geochemistry of soil-formed phyllosilicates continues to be an invaluable proxy system, enhancing our understanding of terrestrial paleoenvironments and paleoclimate.

Kansas

Keeping pace: Migrating sea lampreys adjust swim speed in response to shifting water velocity to maintain a constant ground speed

Upstream migrating fish must balance energetic costs with environmental and ecological constraints. Theoretical models predict that fish can conserve energy by adjusting swim speed in response to changing water velocity, but detailed field tests of these predictions remain rare. We used fine-scale acoustic telemetry and hydrodynamic modeling to track adult sea lamprey (Petromyzon marinus) migrating through a river and evaluated how movement speeds varied with environmental conditions and individual traits. Swim speed increased with faster water velocities, while ground speed remained constant, supporting the hypothesis that lampreys regulate swim effort to maintain a fixed migration pace. The average ground speed aligned with a predicted optimum of ∼1 body length per second. Both swim and ground speeds declined slightly in deeper water, suggesting a trade-off between movement efficiency and predator avoidance. These findings provide field-based support for a theoretical model of energy optimization and underscore how migratory fish adaptively adjust behavior to local hydrodynamic conditions. Our results highlight the value of using high-resolution tracking and environmental modeling to reveal behavioral tactics that underlie efficient migration strategies.

Michigan

Microplastics undergo fragmentation during pressurized membrane filtration

Low-micrometer microplastics (<10 μm) have been detected in drinking water, driving growing interest in using pressure-driven membrane filtration to remove these particles and ensure drinking water safety. However, little attention is paid to the fate of microplastics concentrated in the filtration byproduct. In this study, using well-defined polystyrene (PS) and poly(methyl methacrylate) microspheres as model particles, we observed microplastic fragmentation during nanofiltration and the subsequent release of smaller fragments. After operating for 3 h at 20 bar, 67.9 ± 8.0% of the PS spheres in the concentrate, based on particles counted in selected fields of view, were transformed into fractured particles. The characteristic Raman band signals of microplastics were significantly weakened after fragmentation, leading to detection challenges. To address this, a data processing algorithm was developed to identify PS fragments as small as 1 μm. Preliminary statistical analysis reveals that within the tested pressure range, operation time has a stronger influence on fragmentation than pressure magnitude alone and that fragmentation is further governed by the intrinsic mechanical properties of the tested model polymers. This work provides direct evidence that pressure-driven membrane processes induce microplastic fragmentation and highlights the environmental risks associated with the discharge of fragmented microplastics into the concentrate.

Environmental Science & Technology Letters

Tracing mercury from land to river: Global sources, retention, and implications for sustainability

Mercury (Hg) pollution in river systems is a global sustainability challenge. Yet the transport, transformation, and retention of Hg within global rivers remain poorly quantified, particularly in regions with sparse observations such as Southeast Asia and Africa, hindering effective pollution mitigation and reinforcing geographic inequities in scientific knowledge and environmental governance. Here, we present the first global, high-resolution simulation of riverine Hg dynamics using a process-based model that traces Hg from land-based sources through river networks to the ocean. Under a realistic scenario, we estimate that ∼1900 megagrams per year (Mg/yr) of Hg enters global rivers, including 1500 Mg/yr from human-induced sources and 400 Mg/yr from soil erosion. Nearly half of this flux (∼1000 Mg/yr) is retained in reservoirs and dams, which act as major sinks. While such retention limits downstream delivery to the oceans, it also heightens in-reservoir Hg methylation risks. By bridging the gap between Hg releases and observed riverine exports, our framework offers a scalable tool for data-limited regions, promotes data access, and supports global freshwater and pollution-management strategies.

Environmental Science & Technology