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At least 721 records · Page 40Linked to original sources
USGS2022

A model to assess industry vulnerability to disruptions in mineral commodity supplies

Mineral commodity supply disruptions have the potential to ripple through and impact the economy in many ways. Industrial vulnerability is a crucial component of mineral commodity criticality tools as it provides guidance on the economic importance of these commodities to regional criticality indices. Using an economic model that links mineral commodity end-use data to input-output tables and a linear optimization routine, reductions in economic output of individual industries and of the overall economy may be calculated. Such a model can also help to identify industries, be they direct or indirect consumers of the mineral commodities in question, that are most vulnerable to specific mineral commodity supply disruptions at different disruption magnitudes. In this assessment, 56 commodities’ end-use data for the year 2012 were paired with the United States’ detail-level Benchmark Input-Output accounts to build an industrial vulnerability model. The model does not evaluate the likelihood of specific supply disruptions but can be used to assess potential industry impacts for a range of scenarios. The model findings indicate that when the supplies of mineral commodities such as mica, lithium, and fluorspar were disrupted, large overall economic decline was paired with a large decline in many industries. On the other hand, gold, lead, and rhenium disruptions resulted in low declines and few disrupted industries.

Resources Policy↗
USGS2010

A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska

Shrub cover appears to be increasing across many areas of the Arctic tundra biome, and increasing shrub cover in the Arctic has the potential to significantly impact global carbon budgets and the global climate system. For most of the Arctic, however, there is no existing baseline inventory of shrub canopy cover, as existing maps of Arctic vegetation provide little information about the density of shrub cover at a moderate spatial resolution across the region. Remotely-sensed fractional shrub canopy maps can provide this necessary baseline inventory of shrub cover. In this study, we compare the accuracy of fractional shrub canopy (> 0.5 m tall) maps derived from multi-spectral, multi-angular, and multi-temporal datasets from Landsat imagery at 30 m spatial resolution, Moderate Resolution Imaging SpectroRadiometer (MODIS) imagery at 250 m and 500 m spatial resolution, and MultiAngle Imaging Spectroradiometer (MISR) imagery at 275 m spatial resolution for a 1067 km 2 study area in Arctic Alaska. The study area is centered at 69 °N, ranges in elevation from 130 to 770 m, is composed primarily of rolling topography with gentle slopes less than 10°, and is free of glaciers and perennial snow cover. Shrubs > 0.5 m in height cover 2.9% of the study area and are primarily confined to patches associated with specific landscape features. Reference fractional shrub canopy is determined from in situ shrub canopy measurements and a high spatial resolution IKONOS image swath. Regression tree models are constructed to estimate fractional canopy cover at 250 m using different combinations of input data from Landsat, MODIS, and MISR. Results indicate that multi-spectral data provide substantially more accurate estimates of fractional shrub canopy cover than multi-angular or multi-temporal data. Higher spatial resolution datasets also provide more accurate estimates of fractional shrub canopy cover (aggregated to moderate spatial resolutions) than lower spatial resolution datasets, an expected result for a study area where most shrub cover is concentrated in narrow patches associated with rivers, drainages, and slopes. Including the middle infrared bands available from Landsat and MODIS in the regression tree models (in addition to the four standard visible and near-infrared spectral bands) typically results in a slight boost in accuracy. Including the multi-angular red band data available from MISR in the regression tree models, however, typically boosts accuracy more substantially, resulting in moderate resolution fractional shrub canopy estimates approaching the accuracy of estimates derived from the much higher spatial resolution Landsat sensor. Given the poor availability of snow and cloud-free Landsat scenes in many areas of the Arctic and the promising results demonstrated here by the MISR sensor, MISR may be the best choice for large area fractional shrub canopy mapping in the Alaskan Arctic for the period 2000–2009.

Alaska↗
USGS2018

Detecting geothermal anomalies and evaluating LST geothermal component by combining thermal remote sensing time series and land surface model data

This paper explores for the first time the possibilities to use two land surface temperature (LST) time series of different origins (geostationary Meteosat Second Generation satellite data and Noah land surface modelling, LSM), to detect geothermal anomalies and extract the geothermal component of LST, the LST gt . We hypothesize that in geothermal areas the LSM time series will underestimate the LST as compared to the remote sensing data, since the former does not account for the geothermal component in its model. In order to extract LST gt , two approaches of different nature (physical based and data mining) were developed and tested in an area of about 560 × 560 km 2 centered at the Kenyan Rift. Pre-dawn data in the study area during the first 45 days of 2012 were analyzed. The results show consistent spatial and temporal LST gt patterns between the two approaches, and systematic differences of about 2 K. A geothermal area map from surface studies was used to assess LST gt inside and outside the geothermal boundaries. Spatial means were found to be higher inside the geothermal limits, as well as the relative frequency of occurrence of high LST gt . Results further show that areas with strong topography can result in anomalously high LST gt values (false positives), which suggests the need for a slope and aspect correction in the inputs to achieve realistic results in those areas. The uncertainty analysis indicates that large uncertainties of the input parameters may limit detection of LST gt anomalies. To validate the approaches, higher spatial resolution images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data over the Olkaria geothermal field were used. An established method to estimate radiant geothermal flux was applied providing values between 9 and 24 W/m 2 in the geothermal area, which coincides with the LST gt flux rates obtained with the proposed approaches. The proposed approaches are a first step in estimating LST gt at large spatial coverage from remote sensing and LSM data series, and provide an innovative framework for future improvements.

Remote Sensing of Environment↗
USGS2022

Spectral mixture analysis for surveillance of harmful algal blooms (SMASH): A field-, laboratory-, and satellite-based approach to identifying cyanobacteria genera from remotely sensed data

Algal blooms around the world are increasing in frequency and severity, often with the possibility of adverse effects on human and ecosystem health. The health and economic impacts associated with harmful algal blooms, or HABs, provide compelling rationale for developing new methods for monitoring these events via remote sensing. Although concentrations of chlorophyll- a and key pigments like phycocyanin are routinely estimated from satellite images and used to infer algal or cyanobacterial cell counts, current methods are unable to provide information on the taxonomic composition of a bloom. This study introduced a new approach capable of differentiating among genera based on their reflectance characteristics: Spectral Mixture Analysis for Surveillance of HABs, or SMASH. The foundation of SMASH is a multiple endmember spectral mixture analysis (MESMA) algorithm that takes a library of cyanobacteria endmembers and a hyperspectral image as input and estimates the fractional abundance of each genus, plus water, on a per-pixel basis. Importantly, we assume that the water column consists of only pure water and cyanobacteria, implying that our linear spectral unmixing models do not account for other optically active constituents such as suspended sediment and colored dissolved organic matter (CDOM). We used reflectance spectra for 12 genera measured under a microscope to populate an algal spectral library and applied the SMASH workflow to satellite images from four waterbodies across the United States. Normalized spectral separability scores indicated that the 12 genera were distinct from one another and the MESMA algorithm reproduced known input fractions for simulated mixtures that included all pairwise combinations of genera and water. We used Upper Klamath Lake as an example to illustrate data products generated via SMASH: maps of the normalized difference chlorophyll index and cyanobacterial index, a MESMA-based classification of algal genera, fraction images for each endmember, and a root mean square error (RMSE) image that summarizes uncertainty. For Upper Klamath Lake, these outputs highlighted a complex algal bloom featuring several genera, primarily Aphanizomenon , and intricate spatial patterns associated with gyres. The maximum RMSE constraint imposed on the MESMA algorithm provided a means of avoiding false positive detection of genera not present in a waterbody but must not be set so low as to leave much of an image unclassified in cases where genera included in the library are present. Comparison of endmember fractions with relative biovolumes calculated from field samples indicated that taxonomic information from SMASH was consistent with field observations. For example, the algorithm successfully identified Microcystis in Owasco Lake but avoided misclassifying Asterionella , a genus not yet included in our library, in Detroit Lake. This proof-of-concept investigation demonstrates the potential of SMASH to enhance our understanding of algal blooms, particularly with respect to their spatial and temporal dynamics.

New York, Oregon, Texas↗
USGS2008

Sources of organochlorine contaminants and mercury in seabirds from the Aleutian archipelago of Alaska: Inferences from spatial and trophic variation

Persistent organochlorine compounds and mercury (Hg) have been detected in numerous coastal organisms of the Aleutian archipelago of Alaska, yet sources of these contaminants are unclear. We collected glaucous-winged gulls, northern fulmars, and tufted puffins along a natural longitudinal gradient across the western and central Aleutian Islands (Buldir, Kiska, Amchitka, Adak), and an additional 8 seabird species representing different foraging and migratory guilds from Buldir Island to evaluate: 1) point source input from former military installations, 2) westward increases in contaminant concentrations suggestive of distant source input, and 3) effects of trophic status ( δ 15 N) and carbon source ( δ 13 C) on contaminant accumulation. Concentrations of Σ polychlorinated biphenyls (PCBs) and most chlorinated pesticides in glaucous-winged gulls consistently exhibited a ‘U’-shaped pattern of high levels at Buldir and the east side of Adak and low levels at Kiska and Amchitka. In contrast, concentrations of Σ PCBs and chlorinated pesticides in northern fulmars and tufted puffins did not differ among islands. Hg concentrations increased westward in glaucous-winged gulls and were highest in northern fulmars from Buldir. Among species collected only at Buldir, Hg was notably elevated in pelagic cormorants, and relatively high Σ PCBs were detected in black-legged kittiwakes. Concentrations of Σ PCBs, dichlorodiphenyldichloroethylene ( p , p ′ DDE), and Hg were positively correlated with δ 15 N across all seabird species, indicating biomagnification across trophic levels. The east side of Adak Island (a former military installation) was a likely point source of Σ PCBs and p , p ′ DDE, particularly in glaucous-winged gulls. In contrast, elevated levels of these contaminants and Hg, along with PCB congener and chlorinated pesticide compositional patterns detected at Buldir Island indicated exposure from distant sources influenced by a combination of atmospheric–oceanic processes and the migratory movements of seabirds.

Science of the Total Environment↗
USGS2015

Steep spatial gradients of volcanic and marine sulfur in Hawaiian rainfall and ecosystems

Sulfur, a nutrient required by terrestrial ecosystems, is likely to be regulated by atmospheric processes in well-drained, upland settings because of its low concentration in most bedrock and generally poor retention by inorganic reactions within soils. Environmental controls on sulfur sources in unpolluted ecosystems have seldom been investigated in detail, even though the possibility of sulfur limiting primary production is much greater where atmospheric deposition of anthropogenic sulfur is low. Here we measure sulfur isotopic compositions of soils, vegetation and bulk atmospheric deposition from the Hawaiian Islands for the purpose of tracing sources of ecosystem sulfur. Hawaiian lava has a mantle-derived sulfur isotopic composition (δ 34 S VCDT) of − 0.8‰. Bulk deposition on the island of Maui had a δ 34 S VCDT that varied temporally, spanned a range from + 8.2 to + 19.7‰, and reflected isotopic mixing from three sources: sea-salt (+ 21.1‰), marine biogenic emissions (+ 15.6‰), and volcanic emissions from active vents on Kilauea Volcano (+ 0.8‰). A straightforward, weathering-driven transition in ecosystem sulfur sources could be interpreted in the shift from relatively low (0.0 to + 2.7‰) to relatively high (+ 17.8 to + 19.3‰) soil δ 34 S values along a 0.3 to 4100 ka soil age-gradient, and similar patterns in associated vegetation. However, sub-kilometer scale spatial variation in soil sulfur isotopic composition was found along soil transects assumed by age and mass balance to be dominated by atmospheric sulfur inputs. Soil sulfur isotopic compositions ranged from + 8.1 to + 20.3‰ and generally decreased with increasing elevation (0–2000 m), distance from the coast (0–12 km), and annual rainfall (180–5000 mm). Such trends reflect the spatial variation in marine versus volcanic inputs from atmospheric deposition. Broadly, these results illustrate how the sources and magnitude of atmospheric deposition can exert controls over ecosystem sulfur biogeochemistry across relatively small spatial scales.

Hawaii↗
USGS2015

Characterization of Missouri surface waters near point sources of pollution reveals potential novel atmospheric route of exposure for bisphenol A and wastewater hormonal activity pattern

Surface water contamination by chemical pollutants increasingly threatens water quality around the world. Among the many contaminants found in surface water, there is growing concern regarding endocrine disrupting chemicals, based on their ability to interfere with some aspect of hormone action in exposed organisms, including humans. This study assessed water quality at several sites across Missouri (near wastewater treatment plants and airborne release sites of bisphenol A) based on hormone receptor activation potencies and chemical concentrationspresent in the surface water. We hypothesized that bisphenol A and ethinylestradiol would be greater in water near permitted airborne release sites and wastewater treatment plant inputs, respectively, and that these two compounds would be responsible for the majority of activities in receptor-based assays conducted with water collected near these sites. Concentrations of bisphenol A and ethinylestradiol were compared to observed receptor activities using authentic standards to assess contribution to total activities, and quantitation of a comprehensive set of wastewater compounds was performed to better characterize each site. Bisphenol A concentrations were found to be elevated in surface water near permitted airborne release sites, raising questions that airborne releases of BPA may influence nearby surface water contamination and may represent a previously underestimated source to the environment and potential for human exposure. Estrogen and androgen receptor activities of surface water samples were predictive of wastewater input, although the lower sensitivity of the ethinylestradiol ELISA relative to the very high sensitivity of the bioassay approaches did not allow a direct comparison. Wastewater-influenced sites also had elevated anti-estrogenic and anti-androgenic equivalence, while sites without wastewater discharges exhibited no antagonist activities.

Science of the Total Environment↗
USGS2016

Negative effects of excessive soil phosphorus on floristic quality in Ohio wetlands

Excessive soil nutrients, often from agricultural runoff, have been shown to negatively impact some aspects of wetland plant communities. We measured plant-available phosphorus (Mehlich-3: MeP) in soil samples, and assessed the vascular plant community and habitat degradation at 27 emergent and 13 forested wetlands in Ohio, USA. We tested two hypotheses: (1) that an index of vegetation biological integrity based on floristic quality was lower in wetlands with higher concentrations of MeP in the soil, and (2) that higher concentrations of MeP occurred in wetlands with more habitat degradation (i.e., lower quality), as estimated by a rapid assessment method. Hypothesis (1) was supported for emergent, but not for forested wetlands. Hypothesis (2) was marginally supported ( P = 0.09) for emergent, but not supported for forested wetlands. The results indicate that the effect of concentration of phosphorus in wetland soils and the quality of plant species assemblages in wetlands is more complex than shown in site-specific studies and may depend in part on degree of disturbance in the surrounding watershed and dominant wetland vegetation type. Woody plants in forested wetlands are typically longer lived than herbaceous species in the understory and emergent wetlands, and may persist despite high inputs of phosphorus. Further, the forested wetlands were typically surrounded by a wide band of forest vegetation, which may provide a barrier against sedimentation and the associated phosphorus inputs to the wetland interior. Our results indicate that inferences about soil nutrient conditions made from rapid assessment methods for assessing wetland habitat condition may not be reliable.

Ohio↗
USGS2016

Decadal-scale export of nitrogen, phosphorus, and sediment from the Susquehanna River basin, USA: Analysis and synthesis of temporal and spatial patterns

The export of nitrogen (N), phosphorus (P), and suspended sediment (SS) is a long-standing management concern for the Chesapeake Bay watershed, USA. Here we present a comprehensive evaluation of nutrient and sediment loads over the last three decades at multiple locations in the Susquehanna River basin (SRB), Chesapeake's largest tributary watershed. Sediment and nutrient riverine loadings, including both dissolved and particulate fractions, have generally declined at all sites upstream of Conowingo Dam (non-tidal SRB outlet). Period-of-record declines in riverine yield are generally smaller than those in source input, suggesting the possibility of legacy contributions. Consistent with other watershed studies, these results reinforce the importance of considering lag time between the implementation of management actions and achievement of river quality improvement. Whereas flow-normalized loadings for particulate species have increased recently below Conowingo Reservoir, those for upstream sites have declined, thus substantiating conclusions from prior studies about decreased reservoir trapping efficiency. In regard to streamflow effects, statistically significant log-linear relationships between annual streamflow and annual constituent load suggest the dominance of hydrological control on the inter-annual variability of constituent export. Concentration-discharge relationships revealed general chemostasis and mobilization effects for dissolved and particulate species, respectively, both suggesting transport-limitation conditions. In addition to affecting annual export rates, streamflow has also modulated the relative importance of dissolved and particulate fractions, as reflected by its negative correlations with dissolved P/total P, dissolved N/total N, particulate P/SS, and total N/total P ratios. For land-use effects, period-of-record median annual yields of N, P, and SS all correlate positively with the area fraction of non-forested land but negatively with that of forested land under all hydrological conditions. Overall, this work has informed understanding with respect to four major factors affecting constituent export ( i.e. , source input, reservoir modulation, streamflow, and land use) and demonstrated the value of long-term river monitoring.

Maryland, New York, Pennsylvania↗
USGS2019

Towards globally customizable ecosystem service models

Scientists, stakeholders and decision makers face trade-offs between adopting simple or complex approaches when modeling ecosystem services (ES). Complex approaches may be time- and data-intensive, making them more challenging to implement and difficult to scale, but can produce more accurate and locally specific results. In contrast, simple approaches allow for faster assessments but may sacrifice accuracy and credibility. The ARtificial Intelligence for Ecosystem Services (ARIES) modeling platform has endeavored to provide a spectrum of simple to complex ES models that are readily accessible to a broad range of users. In this paper, we describe a series of five “Tier 1” ES models that users can run anywhere in the world with no user input, while offering the option to easily customize models with context-specific data and parameters. This approach enables rapid ES quantification, as models are automatically adapted to the application context. We provide examples of customized ES assessments at three locations on different continents and demonstrate the use of ARIES' spatial multi-criteria analysis module, which enables spatial prioritization of ES for different beneficiary groups. The models described here use publicly available global- and continental-scale data as defaults. Advanced users can modify data input requirements, model parameters or entire model structures to capitalize on high-resolution data and context-specific model formulations. Data and methods contributed by the research community become part of a growing knowledge base, enabling faster and better ES assessment for users worldwide. By engaging with the ES modeling community to further develop and customize these models based on user needs, spatiotemporal contexts, and scale(s) of analysis, we aim to cover the full arc from simple to complex assessments, minimizing the additional cost to the user when increased complexity and accuracy are needed.

Science of the Total Environment↗
USGS2019

Point sources and agricultural practices control spatial-temporal patterns of orthophosphate in tributaries to Chesapeake Bay

Orthophosphate (PO 4 ) is the most bioavailable form of phosphorus (P). Excess PO 4 may cause harmful algal blooms in aquatic ecosystems. A major restoration effort is underway for Chesapeake Bay (CB) to reduce P, nitrogen, and sediment loading to CB. Although PO 4 cycling and delivery to streams has been characterized in small-scale studies, regional drivers of PO 4 patterns remain poorly understood because most water quality trend assessment focus on total P. Moreover, these trend assessments are usually at an annual timestep. To address this research gap, we analyzed PO 4 patterns over a 9-year period at 53 monitoring stations across the CB watershed to: 1) characterize the role of PO 4 in total P fluxes and trends; 2) describe spatial and temporal patterns of PO 4 concentrations across seasons and streamflow ; and 3) explore factors explaining these patterns. Agricultural watersheds exported the most total P compared with watersheds under different land uses (e.g., urban or forest), with PO 4 comprising up to 50% of those exports. Although PO 4 exports are declining at many sites, some agricultural regions are experiencing increasing trends at a rate sufficient to drive total P trends. Regression modeling results suggest that point source load reductions are likely responsible for decreasing PO 4 concentrations observed at many sites. Watersheds with more Conservation Reserve Program enrollment had lower summer PO 4 concentrations, highlighting the effectiveness of this practice. Manure inputs strongly predicted PO 4 concentrations at high flows across all seasons. Both manure applications and conservation tillage were correlated with changes in PO 4 concentrations at high flow, suggesting these activities could contribute to increasing PO 4 concentrations. This study highlights the effectiveness of point source control for reducing PO 4 exports and underscores the need for management strategies to target sources, practices, and landscape factors determining PO 4 loss from soils where manure inputs remain high.

Delaware, Maryland, New York, Pennsylvania, Virgin↗
USGS2020

Fish growth rates and lake sulphate explain variation in mercury levels in ninespine stickleback (Pungitius pungitius) on the Arctic Coastal Plain of Alaska

Mercury concentrations in freshwater food webs are governed by complex biogeochemical and ecological interactions that spatially vary and are often mediated by climate. The Arctic Coastal Plain of Alaska (ACP) is a heterogeneous, lake-rich landscape where variability in mercury accumulation is poorly understood. Earlier research indicated that the level of catchment influence on lakes varied spatially on the ACP, and affected mercury accumulation in lake sediments. This work sought to determine drivers of spatial variation in mercury accumulation in lake food webs on the ACP. Three lakes that were a priori identified as “high catchment influence” (Reindeer Camp region) and three lakes that were a priori identified as “low catchment influence” (Atqasuk region) were sampled, and variability in water chemistry, food web ecology, and mercury accumulation was investigated. Among-lake differences in ninespine stickleback ( Pungitius pungitius ) length-adjusted methylmercury concentrations were significantly explained by sulphate concentration in lake water, a tracer of catchment runoff input. This effect was mediated by fish growth, which had no pattern between regions. Together, lake water sulphate concentration and fish age-at-size (proxy for growth) accounted for nearly all of the among-lake variability in length-adjusted methylmercury concentrations in stickleback (R 2 adj = 0.94, p < 0.01). The percentage of total mercury as methylmercury (a proxy for net Hg methylation) was higher in sediments of more autochthonous, “low catchment influence” lakes ( p < 0.05), and in the periphyton of more allochthonous, “high catchment influence” lakes (p < 0.05). The results indicate that dominant sources of primary production (littoral macrophyte/biofilm vs. pelagic phytoplankton) and food web structure (detrital vs. grazing) are regulated by catchment characteristics on the ACP, and that this ultimately influences the amount of methylmercury in the aquatic food web. These results have important implications for predicting future mercury concentrations in fish in lakes where fish growth rates and catchment inputs may change in response to a changing climate.

Alaska↗
USGS2022

Nitrogen reductions have decreased hypoxia in the Chesapeake Bay: Evidence from empirical and numerical modeling

Seasonal hypoxia is a characteristic feature of the Chesapeake Bay due to anthropogenic nutrient input from agriculture and urbanization throughout the watershed. Although coordinated management efforts since 1985 have reduced nutrient inputs to the Bay, oxygen concentrations at depth in the summer still frequently fail to meet water quality standards that have been set to protect critical estuarine living resources. To quantify the impact of watershed nitrogen reductions on Bay hypoxia during a recent period including both average discharge and extremely wet years (2016–2019), this study employed both statistical and three-dimensional (3-D) numerical modeling analyses. Numerical model results suggest that if the nitrogen reductions since 1985 had not occurred, annual hypoxic volumes (O 2 < 3 mg L −1 ) would have been ~50–120% greater during the average discharge years of 2016–2017 and ~20–50% greater during the wet years of 2018–2019. The effect was even greater for O 2 < 1 mg L −1 , where annual volumes would have been ~80–280% greater in 2016–2017 and ~30–100% greater in 2018–2019. These results were supported by statistical analysis of empirical data, though the magnitude of improvement due to nitrogen reductions was greater in the numerical modeling results than in the statistical analysis. This discrepancy is largely accounted for by warming in the Bay that has exacerbated hypoxia and offset roughly 6–34% of the improvement from nitrogen reductions. Although these results may reassure policymakers and stakeholders that their efforts to reduce hypoxia have improved ecosystem health in the Bay, they also indicate that greater reductions are needed to counteract the ever-increasing impacts of climate change.

Chesapeake Bay↗
USGS2022

Long-term impacts of impervious surface cover change and roadway deicing agent application on chloride concentrations in exurban and suburban watersheds

Roadway deicing agents, including rock salt and brine containing NaCl, have had a profound impact on the water quality and aquatic health of rivers and streams in urbanized areas with temperate climates. Yet, few studies evaluate impacts to watersheds characterized by relatively low impervious surface cover (ISC; < 15 %). Here, we use long-term (1997-2019), monthly streamwater quality data combined with daily streamflow for six exurban and suburban watersheds in southeastern Pennsylvania to examine the relations among chloride (Cl − ) concentrations and ISC. Both flow-normalized Cl − concentrations and ISC increased over time in each of the six watersheds, consistent with changes in watershed management (e.g., ISC, road salt application, etc.). The watersheds that experienced the greatest changes in percent ISC (e.g., agriculture replaced by residential and commercial development) experienced the greatest changes in flow-normalized Cl − concentrations. We also utilized a comprehensive mass-balance model (2011–2018) that indicated Cl − inputs exceeded the outputs for the study watersheds. Road salt applied to state roads, non-state roads, and other impervious surfaces accounted for the majority of Cl − inputs to the six watersheds. Furthermore, increasing Cl − concentrations during baseflow conditions confirm impacts to shallow groundwater. Although flow-normalized Cl − concentrations are below the U.S. Environmental Protection Agency's chronic threshold value for impacts to aquatic organisms, year-round exceedances may result before the end of this century based on current trends. Though reduced Cl − loading to streams may be achieved by limiting the expansion of impervious surfaces in exurban and suburban watersheds, changes in baseflow concentrations are likely to be gradual because of the accumulated Cl − in groundwater.

Pennsylvania↗
USGS2025

Characterizing pyrethroid and fipronil concentrations in biosolids

Pesticides are prevalent in wastewater, yet few studies have measured pesticides in biosolids and aqueous media from samples collected concurrently. Seventeen California wastewater treatment plants (WWTPs) were sampled in May 2020. Biosolids samples were analyzed for 27 analytes, and paired aqueous samples (influent and effluent) were analyzed for 23 analytes. Analytes included fipronil and its transformation products (fiproles), pyrethroids, novaluron, and several other pesticides with down-the-drain transport potential. Of the 27 compounds analyzed in biosolids samples, 16 were detected in at least one sample, and 10 had a detection frequency (DF) of at least 25 %. Fipronil sulfone, fipronil sulfide, and fipronil were the most frequently detected fiproles (DF = 100 %, 94 %, and 67 %, respectively); permethrin was the most frequently detected pyrethroid (DF = 100 %), followed by bifenthrin (DF = 94 %), cyhalothrin (DF = 89 %), and etofenprox (DF = 78 %). To elucidate fipronil transformation pathways within the treatment system, data from the three sample types were compared; findings were generally consistent with transformation pathways reported previously (e.g., some fiproles were rarely detected in influent or biosolids, but frequently detected in effluent, indicating their formation during the treatment process). No correlations were found between WWTP characteristics and pesticide concentrations in biosolids. The fraction of organic carbon ( f OC ) of each biosolids sample was measured, and a statistically significant negative correlation was observed between f OC and some fiproles, but not fipronil; possible explanations are discussed. Additional analysis for two major agricultural pesticides (bifenthrin and permethrin) indicated that estimated mass loads of these pesticides in biosolids applied to land as a soil amendment are minimal (approximately 2 to 3 orders of magnitude lower) compared to inputs from agricultural applications. This study provides insight on the magnitude of pesticides entering the environment via land-applied biosolids; existing regulations surrounding agricultural pesticide applications are expected to also be protective of the relatively low inputs from biosolids.

Science of the Total Environment↗
USGS2025

A review of post-wildfire adaptations of surface-water-quality models: Synthesis, gaps, and opportunities

As wildfires increasingly affect water-supply watersheds, the demand for models to predict water-quality responses is increasing. This work reviews and synthesizes existing post-wildfire applications of water-quality models in the context of geographic and ecohydrological distribution, hydrologic and water-quality response process representation, model parameterization, model and input data scales, model calibration data availability, as well as calibration and performance evaluation approaches. Emphasis is placed on models that simulate water-quality output, rather than sediment and erosional response as the primary focus. Here, identified gaps and opportunities to advance the post-wildfire application of water-quality models include: 1. applying models in under-represented geographic and ecohydrologic regions, 2. simulating multiple streamflow generation mechanisms, including groundwater, with an emphasis on shifting dominant flow pathways as the landscape recovers following wildfire, 3. adding studies that include the simulation of metals, 4. incorporating more biogeochemical and in-stream processes to model applications, 5. applying finer spatial and temporal resolution of precipitation data input as well as finer spatial resolution hydrologic response units, 6. implementing fully distributed grid or element models or finer resolution response units to capture burn severity heterogeneity, 7. collecting enhanced water-quality data for model calibration and validation, 8. conducting model-intercomparison studies, and 9. developing model parameter value guidance in post-wildfire applications. These identified gaps and opportunities may assist users in deciding on key processes and approaches to consider in modeling post-wildfire water-quality conditions.

Science of the Total Environment↗
USGS2018

Variability in eddy sandbar dynamics during two decades of controlled flooding of the Colorado River in the Grand Canyon

Sandbars are iconic features of the Colorado River in the Grand Canyon, Arizona, U.S.A. Following completion of Glen Canyon Dam in 1963, sediment deficit conditions caused erosion of eddy sandbars throughout much of the 360 km study reach downstream from the dam. Controlled floods in 1996, 2004, and 2008 demonstrated that sand on the channel bed could be redistributed to higher elevations, and that floods timed to follow tributary sediment inputs would increase suspended sand concentrations during floods. Since 2012, a new management protocol has resulted in four controlled floods timed to follow large inputs of sand from a major tributary. Monitoring of 44 downstream eddy sandbars, initiated in 1990, shows that each controlled flood deposited significant amounts of sand and increased the size of subaerial sandbars. However, the magnitude of sandbar deposition varied from eddy to eddy, even over relatively short distances where main-stem suspended sediment concentrations were similar. Here, we characterize spatial and temporal trends in sandbar volume and site-scale (i.e., individual eddy) sediment storage as a function of flow, channel, and vegetation characteristics that reflect the reach-scale (i.e., kilometer-scale) hydraulic environment. We grouped the long-term monitoring sites based on geomorphic setting and used a principal component analysis (PCA) to correlate differences in sandbar behavior to changes in reach-scale geomorphic metrics. Sites in narrow reaches are less-vegetated, stage changes markedly with discharge, sandbars tend to remain dynamic, and sand storage change dominantly occurs in the eddy compared to the main channel. In wider reaches, where stage-change during floods may be half that of narrow sites, sandbars are more likely to be stabilized by vegetation, and floods tend to aggrade the vegetated sandbar surfaces. In these locations, deposition during controlled floods is more akin to floodplain sedimentation, and the elevation of sandbar surfaces increases with successive floods. Because many sandbars are intermediate to the end members described above, high-elevation bar surfaces stabilized by vegetation often have a more dynamic unvegetated sandbar on the channel-ward margin that aggrades and erodes in response to controlled flood cycles. Ultimately, controlled floods have been effective at increasing averaged sandbar volumes, and, while bar deposition during floods decreases through time where vegetation has stabilized sandbars, future controlled floods are likely to continue to result in deposition in a majority of the river corridor.

Colorado River, Grand Canyon↗
USGS2024

A Robot Operating System (ROS) package for mapping flow fields in rivers via Particle Image Velocimetry (PIV)

Non-contact, remote sensing approaches to measuring flow velocities in river channels are widely used, but typical workflows involve acquiring images in the field and then processing data later in the office. To reduce latency between acquisition and output, with the ultimate goal of enabling real-time image velocimetry, we developed a Robot Operating System (ROS) package for Particle Image Velocimetry (PIV) that can be deployed on an embedded computer aboard an uncrewed aircraft system (UAS). The ROSPIV package consists of a series of nodes that can be run in parallel and comprise an end-to-end PIV workflow. Software development involved converting MATLAB code to C++, organizing files within a catkin workspace, and building nodes using catkin_make . The codebase is available via a repository that includes a user’s guide and demo script. This paper describes the nodes in the ROSPIV package as well as functions for preparing inputs, facilitating code generation, and visualizing PIV output. To illustrate the application of the software, we present two examples, one based on a simulated image sequence and the other based on data acquired from a UAS. For the simulated data, the velocity field derived via the ROSPIV package closely matched the known flow field used to generate the image sequence. Using real data as input demonstrated the ability of the ROSPIV package to ingest and pre-process raw images. Our initial results suggest that the ROSPIV package could become a viable approach for mapping river surface velocities in real time.

Software X↗