USGS Science⌕ Search

SEARCH · USGS Science

Results for “Challenge”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 739 records · Page 41Linked to original sources

Protection of rainbow trout against infectious hematopoietic necrosis virus four days after specific or semi-specific DNA vaccination

A DNA vaccine against a fish rhabdovirus, infectious hematopoietic necrosis virus (IHNV), was shown to provide significant protection as soon as 4 d after intramuscular vaccination in 2 g rainbow trout ( Oncorhynchus mykiss ) held at 15°C. Nearly complete protection was also observed at later time points (7, 14, and 28 d) using a standardized waterborne challenge model. In a test of the specificity of this early protection, immunization of rainbow trout with a DNA vaccine against another fish rhabdovirus, viral hemorrhagic septicemia virus, provided a significant level of cross-protection against IHNV challenge for a transient period of time, whereas a rabies virus DNA vaccine was not protective. This indication of distinct early and late protective mechanisms was not dependent on DNA vaccine doses from 0.1 to 2.5 μg.

Vaccine↗

Approach for quantifying rare Earth elements at low keV

The challenges of analyzing bastnaesite (REECO3F) and hydroxylbastnaesite (REECO3OH) include beam sensitivity, quantification of light elements in a heavy element matrix, the presence of elements that cannot be analyzed with EPMA (H), and the use of x-ray lines whose physical constants are not well known. To overcome some of these challenges, Ca, La, Ce, Pr, Nd, and Sm were analyzed at 15 keV accelerating voltage and the light elements (C, O, F) were analyzed at 7 keV accelerating voltage. This approach is ideal for samples that are homogeneous within the volume analyzed. However, for the bastnaesite of interest, this solution is unsatisfactory as backscattered electron imaging reveals chemical variations at scales of less than 1 m (fig. 1). Monte Carlo simulations and wavescans of the REE M family of x-rays were evaluated to determine the best analytical approach. Monte Carlo simulations using Casino v2.42 were ran on a substrate of CeCO3F with a density of 5.00 g/cm3 at 15 keV and 7 kCV accelerating voltage. Depth distribution curves, φ(ρz), reveal x-ray generation at 15 keV for the Ce L shell x-rays approaches 1.0 m whereas the depth of Ce M shell x-ray generation at 7 keV is less than 0.4 m. Similarly, the K shell x-ray generation depth for C, O, and F at 7 keV is also less than 0.4 m. These simulations demonstrate an accelerating voltage of 7 keV or less and use of the REE M x-rays is necessary to acquire chemical information from the same volume of material for the light and heavy elements. Bastnaesite contains all REE and therefore one must consider the energy of the highest x-ray line of interest, namely the Lu M at 1.83 kV, to achieve an overvoltage (Eo/Ec) of over 2. Bastnaesite is also an insulator and requires a conductive coating, therefore 7 keV was used to avoid contributions of the coating material to the analysis given the above constraints. The USNM REE phosphate standards, Edinburgh REE glasses, CeO2, LaB6, and the metals of Sm, Dy, Gd, Er, and Yb were selected to evaluate the peak overlaps of the M family x-ray lines. The materials were coated with ~ 5nm iridium with a Leica ACE600 prior to analysis. Full spectrometer wavescans were collected at 7 keV accelerating voltage, 50 nA beam current, and 20 um beam diameter on a JEOL 8530F Plus using TAP and TAPL crystals. The step size was 0.109 mm along the length of the spectrometer with a dwell of 3 seconds at each step. M and M lines are broad and not individually resolved for the light REE but become more separated and sharper with increasing atomic number. M and M lines for each REE are also present across the spectrometer range further complicating peak interference corrections. The peak positions and overall shape for the Ce M and M lines vary with the coordination of the element. Significant shifts in position and shape were not observed when comparing the Ce M peaks of CeO2 and CePO4. Similar results were seen when comparing the available REE metal to the phosphate (Sm, Dy, Gd, Er, Yb). These wavescans suggest the use of the M or M lines if matrix matched standards are not available.

Microscopy and Microanalysis↗

Ten new insights in climate science 2025

Interdisciplinary understanding is vital for delivering sound climate policy advice. However, navigating the ever-growing and increasingly diverse scholarly literature on climate change is challenging for any individual researcher. This annual synthesis highlights and explains recent advances across a variety of fields of climate change research. This year, the 10 insights focus on: (1) the record-warmth of 2023/2024 and the elevated Earth energy imbalance; (2) acceleration of ocean warming and intensifying marine heatwaves; (3) northern land carbon sinks under strain; (4) reinforcing feedback between biodiversity loss and climate change; (5) accelerated depletion of groundwater; (6) global dengue incidence; (7) global income losses and labour productivity declines; (8) strategic scaling of CDR; (9) integrity challenges in carbon credit markets and emerging responses; and (10) effective policy mixes for emissions reductions. The insights have been written to be accessible to researchers from different fields, serving as entry-points to specific topics, as well as providing an overview of the evolving landscape of climate change research. In the final section, the insights are used to develop overarching policy-relevant messages. This paper provides the basis for a science-policy report that was shared with all Party delegations ahead of COP30 in Belém, Brazil.

Global Sustainability↗

The US EPA’s National Nutrient Inventory: Critical shifts in US nutrient pollution sources from 1987 to 2017

Efforts to constrain the negative environmental impacts of excess nitrogen (N) and phosphorus (P) are costly and challenging, due in part to inconsistent reporting of nutrient sources at temporal and spatial scales relevant for local decision making. To meet this challenge, the U.S. Environmental Protection Agency’s National Nutrient Inventory provides estimates of major agricultural, urban, atmospheric, and natural nutrient fluxes for the contiguous United States at county and HUC12 scales annually from 1987 (from 1950 for agriculture) to 2017. Since the late 1980s, total N emissions and atmospheric N deposition have declined 22% and 15%, respectively, despite increased agricultural emissions. Over the same period, municipal wastewater N and P loads remained largely stable, despite population increases, through wastewater treatment upgrades and the phaseout of phosphorus-containing detergents. Improved agricultural efficiency allowed for dramatic increases in agricultural production and crop harvest since 1987 (∼25% for N and P), with little change in surplus nutrients left on fields. Overall, a combination of innovative technologies and management has stemmed or even decreased major sources of nutrient pollution to the environment over the last several decades, representing an important shift that, if continued, may contribute to improved air, land, and water quality and human health.

contiguous United States↗

Influence of dissolved organic matter on the environmental fate of metals, nanoparticles, and colloids

We have known for decades that dissolved organic matter (DOM) plays a critical role in the biogeochemical cycling of trace metals and the mobility of colloidal particles in aquatic environments. In recent years, concerns about the ecological and human health effects of metal-based engineered nanoparticles released into natural waters have increased efforts to better define the nature of DOM interactions with metals and surfaces. Nanomaterials exhibit unique properties and enhanced reactivities that are not apparent in larger materials of the same composition 1,2 or dissolved ions of metals that comprise the nanoparticles. These nanoparticle-specific properties generally result from the relatively large proportion of the atoms located at the surface, which leads to very high specific surface areas and a high proportion of crystal lattice imperfections relative to exposed surface area. Nanoscale colloids are ubiquitous in nature,2 and many engineered nanomaterials have analogs in the natural world. The properties of these materials, whether natural or manmade, are poorly understood, and new challenges have been presented in assessing their environmental fate. These challenges are particularly relevant in aquatic environments where interactions with DOM are key, albeit often overlooked, moderators of reactivity at the molecular and nanocolloidal scales.

Environmental Science & Technology↗

Granular avalanches across irregular three-dimensional terrain: 1. Theory and computation

To establish a theoretical basis for predicting and interpreting the behavior of rapid mass movements on Earth's surface, we develop and test a new computational model for gravity-driven motion of granular avalanches across irregular, three-dimensional (3-D) terrain. The principles embodied in the model are simple and few: continuum mass and momentum conservation and intergranular stress generation governed by Coulomb friction. However, significant challenges result from the necessity of satisfying these principles when deforming avalanches interact with steep and highly variable 3-D terrain. We address these challenges in four ways. (1) We formulate depth-averaged governing equations that are referenced to a rectangular Cartesian coordinate system (with z vertical) and that account explicitly for the effect of nonzero vertical accelerations on depth-averaged mass and momentum fluxes and stress states. (2) We compute fluxes of mass and momentum across vertical cell boundaries using a high-resolution finite volume method and Roe-type Riemann solver. Our algorithm incorporates flux difference splitting, an entropy correction for the flux, and eigenvector decomposition to embed the effects of driving and resisting forces in Riemann solutions. (3) We use a finite element method and avalanche displacements predicted by Riemann solutions to compute Coulomb stresses conjugate to the displacements in 3-D stress space. (4) We test the model output against analytical solutions, a sand cone conceptual experiment, and (in a companion paper) data from detailed laboratory experiments. Model results illustrate a complex interplay of basal traction and internal stress, and they successfully predict not only the gross behavior but also many details of avalanche motion from initiation to deposition.

Journal of Geophysical Research Earth Surface↗

Editorial

In our 3 years serving as editors, we have learned to our delight that Water Resources Research is truly the journal of the hydrologic community. Many individuals have expressed to us their sense of ownership of the journal and their passion for the sustained excellence of the journal. This is extremely healthy as it leads to productive discussions in which varying points of view are put forward, all for the purpose of making the journal better. The community decides the future of its journal. For WRR to be strong the community must be engaged, committed, and willing to discuss matters in a way that will enhance the journal. At this time, there are a number of challenges that face Water Resources Research . These are challenges for each member of the hydrologic community to consider.

Water Resources Research↗

Quantifying the spatial details of carbon sequestration potential and performance

Upscaling the spatial and temporal changes of carbon stocks and fluxes from sites to regions is challenging owing to the spatial and temporal variances and covariance of driving variables and the uncertainties in both the model and the input data. Although various modeling approaches have been developed to facilitate the upscaling process, few deal with error transfer from model input to output, and error propagation in time and space. The author has developed the General Ensemble Biogeochemical Modelling System (GEMS) for upscaling carbon stocks and fluxes from sites to regions with measures of uncertainty. This chapter describes the GEMS model, its application to regional- and larger-scale areas, and the new results that demonstrate the challenges of upscaling. GEMS relies on site-scale biogeochemical models to simulate carbon dynamics at the site scale. The spatial deployment of the site-scale model in GEMS is based on the spatial and temporal joint frequency distribution of major driving variables (e.g., land cover and land use change, climate, soils, disturbances, and management). At the site scale, GEMS uses stochastic ensemble simulations to incorporate input uncertainty to quantify uncertainty transfer from input to output, and to identify trends in both input data and simulation results. It permits one to simulate the range of possible permutations of input values and identify the trends and variance in both the input data and results. Using data assimilation techniques, GEMS simulations can be constrained by field and satellite observations, including estimates of net primary production (NPP) from the Moderate Resolution Imaging Spectroradiometer (MODIS), grain yield and cropping practices, and forest inventories. The modeling philosophy embedded in GEMS makes it ideal for assimilating information with various uncertainties to support estimating the spatial details of carbon sequestration potential as well as dynamic monitoring of the performance of carbon sequestration activities over large areas. As a case study, GEMS is applied to simulate the spatial and temporal details of carbon sources, sinks, and uncertainty in the Ridge and Valley ecoregion in the eastern United States

Book chapter↗

Interactions between soil thermal and hydrological dynamics in the response of Alaska ecosystems to fire disturbance

Soil temperature and moisture are important factors that control many ecosystem processes. However, interactions between soil thermal and hydrological processes are not adequately understood in cold regions, where the frozen soil, fire disturbance, and soil drainage play important roles in controlling interactions among these processes. These interactions were investigated with a new ecosystem model framework, the dynamic organic soil version of the Terrestrial Ecosystem Model, that incorporates an efficient and stable numerical scheme for simulating soil thermal and hydrological dynamics within soil profiles that contain a live moss horizon, fibrous and amorphous organic horizons, and mineral soil horizons. The performance of the model was evaluated for a tundra burn site that had both preburn and postburn measurements, two black spruce fire chronosequences (representing space-for-time substitutions in well and intermediately drained conditions), and a poorly drained black spruce site. Although space-for-time substitutions present challenges in model-data comparison, the model demonstrates substantial ability in simulating the dynamics of evapotranspiration, soil temperature, active layer depth, soil moisture, and water table depth in response to both climate variability and fire disturbance. Several differences between model simulations and field measurements identified key challenges for evaluating/improving model performance that include (1) proper representation of discrepancies between air temperature and ground surface temperature; (2) minimization of precipitation biases in the driving data sets; (3) improvement of the measurement accuracy of soil moisture in surface organic horizons; and (4) proper specification of organic horizon depth/properties, and soil thermal conductivity.

Alaska↗

An introduction to global carbon cycle management

Past and current human activities have fundamentally altered the global carbon cycle. Potential future efforts to control atmospheric CO 2 will also involve significant changes in the global carbon cycle. Carbon cycle scientists and engineers now face not only the difficulties of recording and understanding past and present changes but also the challenge of providing information and tools for new management strategies that are responsive to societal needs. The challenge is nothing less than managing the global carbon cycle.

Book chapter↗

Studying geodesy and earthquake hazard in and around the New Madrid Seismic Zone

Workshop on New Madrid Geodesy and the Challenges of Understanding Intraplate Earthquakes; Norwood, Massachusetts, 4 March 2011 Twenty-six researchers gathered for a workshop sponsored by the U.S. Geological Survey (USGS) and FM Global to discuss geodesy in and around the New Madrid seismic zone (NMSZ) and its relation to earthquake hazards. The group addressed the challenge of reconciling current geodetic measurements, which show low present-day surface strain rates, with paleoseismic evidence of recent, relatively frequent, major earthquakes in the region. The workshop presentations and conclusions will be available in a forthcoming USGS open-file report (http://pubs.usgs.gov).

Eos, Transactions, American Geophysical Union↗

Cross-scale phenological data integration to benefit resource management and monitoring

Climate change is presenting new challenges for natural resource managers charged with maintaining sustainable ecosystems and landscapes. Phenology, a branch of science dealing with seasonal natural phenomena (bird migration or plant flowering in response to weather changes, for example), bridges the gap between the biosphere and the climate system. Phenological processes operate across scales that span orders of magnitude—from leaf to globe and from days to seasons—making phenology ideally suited to multiscale, multiplatform data integration and delivery of information at spatial and temporal scales suitable to inform resource management decisions. A workshop report: Workshop held June 2016 to investigate opportunities and challenges facing multi-scale, multi-platform integration of phenological data to support natural resource management decision-making.

Conference Paper↗

Lessons from a post-eruption landscape

From March to May 1980, magma rose high into Mount St. Helens (MSH), swelling and—as it turned out—destabilizing its north flank. Scientists knew the volcano had been highly active at times over the past 40,000 years, but the mountain, located amid the Cascade Range in southwestern Washington, had been mostly quiet since the mid-19th century. The collapse of the north flank on 18 May shattered that quiet, triggering a cascade of events that left resounding impressions not only on those who witnessed and studied them but also on the surrounding landscape [Lipman and Mullineaux, 1981; Waitt, 2015]. The eruption of MSH also provided unparalleled opportunities for advancing several disciplines [e.g., Shore et al., 1986; Newhall, 2000; Franklin and MacMahon, 2000]. Although not as conspicuously as in volcanology, the eruption and its aftermath led to an intensification of research investigating biophysical impacts of eruptions and subsequent responses [e.g., Dale et al., 2005; Pierson and Major, 2014; Crisafulli and Dale, 2018]. Long-term research on the biophysical responses at MSH has provided important new insights, challenged long-standing ideas, and provided many societal benefits. The fortieth anniversary of the eruption this year offers a timely opportunity to reflect on these insights and influences. This long-term vantage is important because sustained, place-based studies following landscape disturbances are rare; because the MSH eruption spurred the greatest depth and breadth of multidisciplinary studies of biophysical responses to landscape disturbance; and because these responses created some of the most significant societal challenges to emerge after the eruption. We summarize key biophysical disturbances and responses, highlight salient insights, and suggest actions that can extend the usefulness of these insights to volcanically vulnerable communities worldwide.

Washington↗

Paleoclimatology and paleoceanography perspectives on integrated, coordinated, open, networked (ICON) science

This article is composed of three independent commentaries about the state of Integrated, Coordinated, Open, Networked (ICON) principles (Goldman et al., 2021, https://doi.org/10.1002/essoar.10508554.1 ) in the AGU section paleoclimatology and paleoceanography (P&P), and a discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: (Section 2) Global collaboration, technology transfer and application, reproducibility, and data sharing and infrastructure; (Section 3) Local knowledge, global gain: improving interactions within the scientific community and with locals, indigenous communities, stakeholders, and the public; (Section 4) Field, experimental, remote sensing, and real-time data research and application. P&P projects can better include ICON principles by directly incorporating them into research proposals. A promising way to overcome the challenges of interdisciplinarity and integration is to foster networking, which will advance our research discipline through the application of ICON.

Earth and Space Science↗

New insights into the relationship between mass eruption rate and volcanic column height based on the IVESPA dataset

Rapid and simple estimation of the mass eruption rate (MER) from column height is essential for real-time volcanic hazard management and reconstruction of past explosive eruptions. Using 134 eruptive events from the new Independent Volcanic Eruption Source Parameter Archive (IVESPA, v1.0), we explore empirical MER-height relationships for four measures of column height: spreading level, sulfur dioxide height, and top height from direct observations and as reconstructed from deposits. These relationships show significant differences and highlight limitations of empirical models currently used in operational and research applications. The roles of atmospheric stratification, wind, and humidity remain challenging to detect across the wide range of eruptive conditions spanned in IVESPA, ultimately resulting in empirical relationships outperforming analytical models that account for atmospheric conditions. This finding highlights challenges in constraining the MER-height relation using heterogeneous observations and empirical models, which reinforces the need for improved eruption source parameter data sets and physics-based models.

Geophysical Research Letters↗

Mapping landslide susceptibility over large regions with limited data

Landslide susceptibility maps indicate the spatial distribution of landslide likelihood. Modeling susceptibility over large or diverse terrains remains a challenge due to the sparsity of landslide data (mapped extent of known landslides) and the variability in triggering conditions. Several different data sampling strategies of landslide locations used to train a susceptibility model are used to mitigate this challenge. However, to our knowledge, no study has systematically evaluated how different sampling strategies alter a model's predictor effects (i.e., how a predictor value influences the susceptibility output) critical to explaining differences in model outputs. Here, we introduce a statistical framework that examines the variation in predictor effects and the model accuracy (measured using receiver operator characteristics) to highlight why certain sampling strategies are more effective than others. Specifically, we apply our framework to an array of logistic regression models trained on landslide inventories collected at sub-regional scales over four terrains across the United States. Results show significant variations in predictor effects depending on the inventory used to train the models. The inconsistent predictor effects cause low accuracies when testing models on inventories outside the domain of the training data. Grouping test and training sets according to physiographic and ecological characteristics, which are thought to share similar triggering mechanisms, does not improve model accuracy. We also show that using limited landslide data distributed uniformly over the entire modeling domain is better than using dense but spatially isolated data to train a model for applications over large regions.

California, Kentucky, North Carolina, West Virgini↗

An integrated sensor network and data driven approach to satellite remote sensing of dissolved organic matter

Traditional remote sensing retrieval models for water quality have historically relied on limited, localized data sets due to the prohibitive costs of extensive field campaigns and logistical challenges of collecting match-up data with satellite overpasses. As a result, these models often lack generalizability across seasons, tides, and sites. Furthermore, small field data sets limit the utility of modern machine learning techniques to advance remote sensing retrieval models. In situ optical sensors deployed in a sensor network to continuously monitor larger water bodies can drastically increase the number of measurements, providing the opportunity to develop new approaches for building robust remote sensing retrieval models by leveraging both remote sensing data and in situ networks as an integrated monitoring system. This study leverages a large “ground-to-space” sensor network that combines an in situ optical sensor network with satellite-based remote sensing to overcome these limitations. Utilizing a large-scale data set from the U.S. Geological Survey's Sacramento—San Joaquin River Delta monitoring network, of dissolved organic matter fluorescence measurements, and remote sensing data from the European Space Agency's Sentinel-2A and -2B satellites, this study implemented a data driven approach for dissolved organic matter models. The data set, consisting of 982 samples collected between 2018 and 2021 was used to train and validate a random forest model ( R 2 = 0.76, RMSE = 6.1 Quinine Sulfate Equivalents), with demonstrated applicability across diverse site conditions, tidal stages, and seasons. This work provides a scalable solution to address critical challenges in water quality monitoring and offers a replicable framework for global water quality management.

Calfornia↗

Did they feel it? Legacy maroseismic data illuminates an engimatic 20th century earthquake

The challenges and the importance of preserving legacy instrumental records of earthquakes are now well-recognized (e.g., Richards & Hellweg, 2020, https://doi.org/10.1785/0220200053 ). Seismologists may not be aware of parallel challenges and opportunities with legacy macroseismic data for earthquakes in the United States. For much of the 20th century, macroseismic data were collected by a series of U.S. government agencies using a standard questionnaire distributed on postcards. Published summaries of postcards provide macroseismic data akin to modern Did You Feel It? questionnaire responses. In this paper we focus on the M 6.5 Fickle Hill, California earthquake, on 21 December 1954 (Hellweg et al., 2025) as a proof-of-concept, illustrating the potential of what we dub Did They Feel It? (DTFI) data to improve our understanding of significant 20th century U.S. earthquakes for which instrumental data are sparse. Legacy macroseismic data interpreted following modern conventions can potentially constrain traditional ShakeMaps at a level of detail and accuracy that in some respects rival maps for modern earthquakes. The updated ShakeMap for the 1954 Fickle Hill earthquake, also drawing from recently published media and first-person accounts, supports the location, depth, and stress drop value estimated from available instrumental data (Hellweg et al., 2025).

California↗