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At least 487 records · Page 27Linked to original sources
USGS2024

Computational approaches improve evidence synthesis and inform broad fisheries trends

Addressing ecological impacts with effective conservation actions requires information on the links between human pressures and localized responses. Understanding links is a priority for many conservation contexts, including the world's fresh waters, which face intensifying threats to disproportionately high species diversity, including more than half of the world's fish species. Literature synthesis can uncover links and highlight potential research gaps, yet can be very cumbersome and time consuming. Emerging tools like text mining can improve efficiency in extracting relevant information from vast scientific outputs. This study synthesizes evidence of direct anthropogenic threats to major inland fisheries and examines driver-impact-response patterns using coupled automated and manual text classification methods. We screened 9336 abstracts from 45 river basins of high importance to inland fish production; 1152 abstracts contained evidence of direct threats to fish. The most common documented drivers were pollution, dams, and fishing pressure, which were most strongly linked to decreased fitness, altered reproduction, and mortality, respectively. Strong impact-response links to pollution signal potential bias toward documenting acute threats that generate more visible and immediate impacts. The use of machine learning-based text classification performed best in classifying extraneous information. Results can inform the development of inland fisheries indicators and threat-based metrics, highlight possible evidence gaps in linking global drivers to fishery-level responses, and illustrate the application of a coupled synthesis approach for improved efficiency and extraction of information relevant to conservation outcomes. The associated user and interpretation guides address accessibility and technical barriers faced by conservation scientists to improve efficiency in evidence synthesis.

Conservation Science and Practice↗
USGS2024

Editorial: From cold seeps to hydrothermal vents: Geology, chemistry, microbiology, and ecology in marine and coastal environments

This Research Topic compiles contemporary studies on cold seeps, hydrothermal vents, mud volcanoes, and related seafloor features that are associated with focused fluid emissions and the transfer of carbon, other chemical species, and sometimes heat from the geosphere to the ocean. Because these features sometimes tap fluids and gas originating kilometers below the seafloor, they provide an important window into deep processes that are otherwise inaccessible to scientists. At the shallow portion of their journey, migrating fluids nearing the seafloor contribute to a range of unique biological, physical, and chemical processes within the sediments themselves and at the sediment-water interface. Seafloor fluid emissions play a critical role in global biogeochemical cycles, ocean chemistry, and possibly even climate change. Seafloor leakage points often emit hydrocarbon gases (especially methane and CO 2 ) and are sometimes the loci for deposition of seafloor minerals that have economic value. A burgeoning area of research focuses on natural products generated at these features, seeking compounds with potential pharmaceutical or other applications. Multidisciplinary studies have become routine for characterization of seafloor fluid emission sites, attesting to the inseparability of geologic, physical, chemical, and biological processes in these settings. It is increasingly common for researchers to combine in a single research cruise: subbottom imaging and seafloor mapping; porewater and water column geochemistry and gas sampling; sediment retrieval for lithologic, biostratigraphic, and solid phase analyses; and studies of benthic and subseafloor communities at the microbial to macrofaunal scales. This multidisciplinary approach has the advantage of ensuring the spatial and temporal coincidence of surveys and samples, an important factor at highly dynamic seafloor fluid emission sites. In addition, researchers often use remotely operated vehicles (ROVs), autonomous underwater vehicles (AUVs), or human-occupied vehicles (HOVs) to record video of the seafloor, compile photomosaics, collect targeted samples, and survey with high-resolution geophysical near-seafloor systems, providing a degree of detail about seafloor fluid emission sites that is unprecedented compared to most areas of the deep ocean. While rarer, long-term cabled observatories or shorter-term deployments of portable observatories are also used at some loci for seafloor fluid flux and are particularly helpful for capturing temporal variations at these dynamic features. Here we summarize the Research Topic’s contribution to multidisciplinary seafloor emission studies in the categories of cold seeps, mud volcanoes, and hydrothermal vents. Figure 1 shows the geographic distribution of the studies in this Research Topic and key features referred to in this Introduction.

Frontiers in Earth Science↗
USGS2016

Projected wetland densities under climate change: Habitat loss but little geographic shift in conservation strategy

Climate change poses major challenges for conservation and management because it alters the area, quality, and spatial distribution of habitat for natural populations. To assess species’ vulnerability to climate change and target ongoing conservation investments, researchers and managers often consider the effects of projected changes in climate and land use on future habitat availability and quality and the uncertainty associated with these projections. Here, we draw on tools from hydrology and climate science to project the impact of climate change on the density of wetlands in the Prairie Pothole Region of the USA, a critical area for breeding waterfowl and other wetland-dependent species. We evaluate the potential for a trade-off in the value of conservation investments under current and future climatic conditions and consider the joint effects of climate and land use. We use an integrated set of hydrological and climatological projections that provide physically based measures of water balance under historical and projected future climatic conditions. In addition, we use historical projections derived from ten general circulation models (GCMs) as a baseline from which to assess climate change impacts, rather than historical climate data. This method isolates the impact of greenhouse gas emissions and ensures that modeling errors are incorporated into the baseline rather than attributed to climate change. Our work shows that, on average, densities of wetlands (here defined as wetland basins holding water) are projected to decline across the U.S. Prairie Pothole Region, but that GCMs differ in both the magnitude and the direction of projected impacts. However, we found little evidence for a shift in the locations expected to provide the highest wetland densities under current vs. projected climatic conditions. This result was robust to the inclusion of projected changes in land use under climate change. We suggest that targeting conservation towards wetland complexes containing both small and relatively large wetland basins, which is an ongoing conservation strategy, may also act to hedge against uncertainty in the effects of climate change.

Montana, North Dakota, South Dakota↗
USGS2018

Impacts of tidal road-stream crossings on aquatic organism passage

ivers and streams are highly vulnerable to fragmentation from roads due to their prevalence in the landscape. Road-stream crossings are far more numerous than other anthropogenic barriers such as dams; these crossing structures (culverts, bridges, fords, and tide gates) have been demonstrated to impede the passage of aquatic organisms. However, road-stream crossings vary widely in the extent to which they serve as a barrier. It is important to identify barrier severity to facilitate prioritization of restoration activities, since proactively addressing all structures is not feasible. In 2015 the North Atlantic Landscape Conservation Collaborative (LCC) funded a project managed by the North Atlantic Aquatic Connectivity Cooperative (NAACC) to develop a unified protocol for assessing aquatic road-stream crossings focusing on aquatic connectivity. The NAACC relied on rapid field-based assessments, which have been shown to be a useful tool for gathering information necessary for prioritization. However, the rapid assessment protocol developed from the NAACC initiative is not applicable to tidal crossings as it does not address two-directional flow, daily water depth fluctuations, or many of the species likely present in coastal habitats. The goal of this report is to provide the background necessary to create guidelines and rapid assessment tools for assessing risk posed to aquatic organism passage at tidal crossings. To accomplish these goals, this report identifies species present in tidally influenced coastal wetlands, the unique traits they may display that puts them at risk for detrimental impact from impeded passage, and passage threats unique to tidal crossings that are not addressed by protocols designed for non-tidal systems. Species lists were compiled through literature reviews and discussions with regional researchers and managers familiar with coastal ecosystems or fish passage concerns. Life history traits, environmental sensitivities, and movement patterns for each species were compiled to build a database that can be queried to identify species that are highly vulnerable to impeded passage at tidal crossings (Available at: https://umass.box.com/s/w5mhokxjxshyxmr7si2v0gzcypcitu9d ). These risk factors for species, combined with passage threats associated with specific crossing characteristics are discussed in this report. The species list is thorough enough to provide a baseline summary of the types of threats experienced by aquatic organisms at tidal road-stream crossings, but it is not exhaustive. Unique ecosystems, species assemblages, management goals, and prioritization models may require different approaches and solutions. Thus, care must be taken to ensure that assessment tools are appropriate to a project’s target species, habitats, and scale.

Cooperator Science Series↗
USGS1974

Seismic hazards and land-use planning

Basic earth-science data are necessary for a realistic assessment of seismic hazards and as a basis for limiting corrective land-use controls only to those areas of greatest hazard. For example, the location, character, and amount of likely displacement and activity of surface faulting can be predicted if detailed geologic maps and seismic data are available and are augmented by field studies at critical localities. Because few structures can withstand displacement of their foundations, they should be located off active fault traces, the distance varying with the character of faulting, the certainty with which fault traces are known, and the importance of the structure. Recreational activities and other nonoccupancy land uses should be considered for fault zone areas where land is under pressure for development; elsewhere, such areas should remain as open space. Two methods of predicting ground shaking effects have applications to land-use decisions: (1) Relative earthquake effects can be related to firmness of the ground and can be used in a gross way to allocate population density in the absence of more sophisticated analyses; and (2) intensity maps, based on, (a) damage from former earthquakes, or (b) a qualitative analyses of geologic units added to a design earthquake, can be helpful both for general and specific plans. Theoretical models are used with caution to predict ground motion for critical structures to be located at specific sites with unique foundation conditions. Fully adequate methods of assessing possible shaking remain to be developed. Where land-use decisions do not reflect likely ground shaking effects, stringent building codes are needed, particularly for important structures. Ground failure (landsliding, ground cracking and lurching, differential settlement, sand boils, and subsidence) commonly results from liquefaction, loss of soil strength, or compaction. Areas suspected of being most likely to fail should not be developed unless detailed site studies can demonstrate the hazard does not exist or can be overcome. Various methods can be used to reduce the high, long-term public costs that follow development of unstable ground. However, areas subject to tectonic deformation generally cannot be predicted nor can effects of such deformation be minimized. Large water waves, such as produced by tsunamis, seiches, and dam failure or overtopping, can be anticipated in many places. Their effects can be lessened by land-use regulations similar to flood-plain zoning, restrictions on location of critical structures, and appropriate warning systems. Many local, state, and federal government agencies, universities, and private consultants may be able to assist planners by advising them of pertinent data and where those data can be obtained. Interpretation of the data for an evaluation of seismic risk commonly requires a team of planners, geologists, and soil and structural engineers.

Circular↗
USGS2023

Model-based assessment and mapping of total phosphorus enrichment in rivers with sparse reference data

Water nutrient management efforts are frequently coordinated across thousands of water bodies, leading to a need for spatially extensive information to facilitate decision making. Here we explore potential applications of a machine learning model of river low-flow total phosphorus (TP) concentrations to support landscape nutrient management. The model was trained, validated, and then applied for all rivers of Michigan, USA to identify potential drivers of nutrient variation, predict alteration in nutrient concentrations from minimally disturbed conditions, and explore reach specific sensitivity to riparian agricultural change. A boosted regression tree model of low-flow TP concentrations trained on natural and anthropogenic landscape predictors accounted for 53 % of variation in cross-validation data, had good accuracy, little bias, and plausible relationships between predictors and response. Percent riparian agricultural cover accounted for the greatest root mean square error reduction in the modeled response (33.2 %), followed by riparian soil permeability (12.9 %), watershed slope (9.6 %), and percent urban cover (9.6 %). An apparent non-linear relationship between TP concentrations and percent riparian agricultural cover suggested steep positive increases in stream TP concentrations between 10 and 30 % upstream riparian agricultural cover. Predicted minimally disturbed TP concentrations were spatially variable and ranged from 7.0 to 48.5 μg l −1 , with the highest concentrations in watersheds draining low-permeability lake plain soils. Comparison of minimally disturbed predictions to those from the early 2000s suggested that much of northern Michigan existed close to the reference condition, while lower Michigan streams were often substantially enriched. Our predicted values of minimally disturbed condition generally agree with previous studies but offer greater geographic specificity. Expanded application of machine learning modeling with landscape predictor data have great potential to inform large scale strategy development in landscapes with sparse reference data.

Michigan↗
USGS2014

Mycotoxins: diffuse and point source contributions of natural contaminants of emerging concern to streams

To determine the prevalence of mycotoxins in streams, 116 water samples from 32 streams and three wastewater treatment plant effluents were collected in 2010 providing the broadest investigation on the spatial and temporal occurrence of mycotoxins in streams conducted in the United States to date. Out of the 33 target mycotoxins measured, nine were detected at least once during this study. The detections of mycotoxins were nearly ubiquitous during this study even though the basin size spanned four orders of magnitude. At least one mycotoxin was detected in 94% of the 116 samples collected. Deoxynivalenol was the most frequently detected mycotoxin (77%), followed by nivalenol (59%), beauvericin (43%), zearalenone (26%), β-zearalenol (20%), 3-acetyl-deoxynivalenol (16%), α-zearalenol (10%), diacetoxyscirpenol (5%), and verrucarin A (1%). In addition, one or more of the three known estrogenic compounds (i.e. zearalenone, α-zearalenol, and β-zearalenol) were detected in 43% of the samples, with maximum concentrations substantially higher than observed in previous research. While concentrations were generally low (i.e. < 50 ng/L) during this study, concentrations exceeding 1000 ng/L were measured during spring snowmelt conditions in agricultural settings and in wastewater treatment plant effluent. Results of this study suggest that both diffuse (e.g. release from infected plants and manure applications from exposed livestock) and point (e.g. wastewater treatment plants and food processing plants) sources are important environmental pathways for mycotoxin transport to streams. The ecotoxicological impacts from the long-term, low-level exposures to mycotoxins alone or in combination with complex chemical mixtures are unknown

Science of the Total Environment↗
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↗
USGS2016

Evaluating methods to establish habitat suitability criteria: A case study in the upper Delaware River Basin, USA

Defining habitat suitability criteria (HSC) of aquatic biota can be a key component to environmental flow science. HSC can be developed through numerous methods; however, few studies have evaluated the consistency of HSC developed by different methodologies. We directly compared HSC for depth and velocity developed by the Delphi method (expert opinion) and by two primary literature meta-analyses (literature-derived range and interquartile range) to assess whether these independent methods produce analogous criteria for multiple species (rainbow trout, brown trout, American shad, and shallow fast guild) and life stages. We further evaluated how these two independently developed HSC affect calculations of habitat availability under three alternative reservoir management scenarios in the upper Delaware River at a mesohabitat (main channel, stream margins, and flood plain), reach, and basin scale. In general, literature-derived HSC fell within the range of the Delphi HSC, with highest congruence for velocity habitat. Habitat area predicted using the Delphi HSC fell between the habitat area predicted using two literature-derived HSC, both at the basin and the site scale. Predicted habitat increased in shallow regions (stream margins and flood plain) using literature-derived HSC while Delphi-derived HSC predicted increased channel habitat. HSC generally favoured the same reservoir management scenario; however, no favoured reservoir management scenario was the most common outcome when applying the literature range HSC. The differences found in this study lend insight into how different methodologies can shape HSC and their consequences for predicted habitat and water management decisions. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

New York, Pennsylvania↗
USGS2010

Natural chlorate in the environment: Application of a new IC-ESI/MS/MS method with a Cl18O3- internal standard

A new ion chromatography electrospray tandem mass spectrometry (IC-ESI/MS/MS) method has been developed for quantification and confirmation of chlorate (ClO 3 − ) in environmental samples. The method involves the electro-chemical generation of isotopically labeled chlorate internal standard (Cl 18 O 3 − ) using 18 O water (H 2 18 O). The standard was added to all samples prior to analysis thereby minimizing the matrix effects that are associated with common ions without the need for expensive sample pretreatments. The method detection limit (MDL) for ClO 3 − was 2 ng L −1 for a 1 mL volume sample injection. The proposed method was successfully applied to analyze ClO 3 − in difficult environmental samples including soil and plant leachates. The IC-ESI/MS/MS method described here was also compared to established EPA method 317.0 for ClO 3 − analysis. Samples collected from a variety of environments previously shown to contain natural perchlorate (ClO 4 − ) occurrence were analyzed using the proposed method and ClO 3 − was found to co-occur with ClO 4 − at concentrations ranging from <2 ng L −1 in precipitation from Texas and Puerto Rico to >500 mg kg −1 in caliche salt deposits from the Atacama Desert in Chile. Relatively low concentrations of ClO 3 − in some natural groundwater samples (<0.1 μg L −1 ) analyzed in this work may indicate lower stability when compared to ClO 4 − in the subsurface. The high concentrations of ClO 3 − in caliches and soils (3−6 orders of magnitude greater) as compared to precipitation samples indicate that ClO 3 − , like ClO 4 − , may be atmospherically produced and deposited, then concentrated in dry soils, and is possibly a minor component in the biogeochemical cycle of chlorine.

Environmental Science & Technology↗
USGS2023

A residual oil zone (ROZ) assessment methodology with application to the central basin platform (Permian Basin, USA) for enhanced oil recovery (EOR) and long-term geologic CO2 storage

Residual oil zones (ROZ) form due to various geologic conditions and are located below the oil/water contact (OWC) of main pay zones (MPZ). Since ROZs usually contain immobile oil, they have not typically been considered commercially attractive for development by conventional primary recovery methods used in the initial phases of oil production. However, during the last decade some operators of these viable fields that also contain ROZs have extended carbon dioxide enhanced oil recovery (CO 2 -EOR) to below the MPZ to commercially recover oil from the associated ROZ. Increased interest in ROZs is also due to the application of anthropogenic CO 2 for oil recovery, leading to the subsurface sequestration of CO 2 , which can be part of the current net-zero carbon oil and climate change objectives. Several detailed studies of selected formations in the Permian Basin of the United States have shown that ROZs can be as common as traditional conventional oil reservoir traps, suggesting significant resources for potential additional hydrocarbon recovery and subsurface CO 2 sequestration via CO 2 -EOR. However, applications of CO 2 -EOR to ROZs have been limited despite the estimation of significant oil resources considered recoverable through CO 2 -EOR, and the benefit of concurrent geologic CO 2 storage that would help offset carbon emissions from the produced oil. The combination of insufficient economic incentives and technical reasons related to data scarcity, such as lack of penetration of wells and well logs, for locating ROZs has limited development of their resource potential when compared to known fields. This paper presents a probabilistic methodology for identifying and evaluating ROZ resources for CO 2 -EOR and CO 2 sequestration potential with the use of public and proprietary data sources. The methodology was developed during a pilot study that focused on the ROZ in the San Andres Formation of a nine-county area in the Permian Basin in West Texas. The pilot study estimated a mean oil in place of 25 × 10 9 barrels (bbl) of oil and a mean potential incremental oil recovery and CO 2 utilization of 2.6 × 10 9 bbl and 28.2 Tcf (1.46 × 10 9 tons), respectively, with 1 hydrocarbon pore volume (HCPV) of injection using the water alternating gas (WAG) method. The results of this pilot study are consistent with reported volumes in the literature for a similar area in the Permian Basin. The pilot study demonstrated that this methodology could be used to identify and assess the recoverable oil and coincident CO 2 storage volumes of ROZs in other formations and regions.

Texas↗
USGS2021

Physics-guided machine learning for scientific discovery: An application in simulating lake temperature profiles

Physics-based models are often used to study engineering and environmental systems. The ability to model these systems is the key to achieving our future environmental sustainability and improving the quality of human life. This article focuses on simulating lake water temperature, which is critical for understanding the impact of changing climate on aquatic ecosystems and assisting in aquatic resource management decisions. General Lake Model (GLM) is a state-of-the-art physics-based model used for addressing such problems. However, like other physics-based models used for studying scientific and engineering systems, it has several well-known limitations due to simplified representations of the physical processes being modeled or challenges in selecting appropriate parameters. While state-of-the-art machine learning models can sometimes outperform physics-based models given ample amount of training data, they can produce results that are physically inconsistent. This article proposes a physics-guided recurrent neural network model (PGRNN) that combines RNNs and physics-based models to leverage their complementary strengths and improves the modeling of physical processes. Specifically, we show that a PGRNN can improve prediction accuracy over that of physics-based models (by over 20% even with very little training data), while generating outputs consistent with physical laws. An important aspect of our PGRNN approach lies in its ability to incorporate the knowledge encoded in physics-based models. This allows training the PGRNN model using very few true observed data while also ensuring high prediction accuracy. Although we present and evaluate this methodology in the context of modeling the dynamics of temperature in lakes, it is applicable more widely to a range of scientific and engineering disciplines where physics-based (also known as mechanistic) models are used.

ACM/IMS Transactions on Data Science↗
USGS2025

Phytoplankton biomass dynamics in wet (2019) and dry (2023) years in Lake Pontchartrain estuary, Louisiana from Sentinel 2-MSI and PACE-OCI observations

This study provides a comprehensive assessment of phytoplankton biomass dynamics in Lake Pontchartrain, Louisiana, by combining monthly water quality data with multispectral and hyperspectral satellite observations using a machine learning algorithm. A machine learning model based on Variational Autoencoder (VAE), globally applicable, was used to estimate phytoplankton biomass via chlorophyll- a (Chl- a ) from Sentinel 2-MSI and NASA's new hyperspectral mission, PACE-OCI, enabling the first direct comparison between the two sensors. The model performed well in this complex estuarine system, with higher accuracy from PACE-OCI (MAE: 1.48, RMSE: 10.40, slope: 0.87) than Sentinel 2-MSI (MAE: 1.57, RMSE: 11.08, slope: 0.83). This approach enabled continuous high-resolution monitoring of phytoplankton biomass across space and time. Comparative analysis of 2019, a wet year with Bonnet Carré Spillway (BCS) openings, and 2023, a dry year with extremely low riverine inputs, revealed distinct biomass dynamics. In 2019, BCS discharge initially suppressed Chl- a within turbid waters (<5 mg Chl- a m −3 ) but later acted as a nutrient and hydrodynamic driver, transporting nutrients toward the lake outlet and Mississippi coast, promoting high biomass (25–45 mg Chl- a m −3 ) near the entrance. In contrast, dry conditions in 2023 led to more frequent-than-expected high biomass (>35 mg Chl- a m −3 ), persisting in the lake center. Similar spatial patterns were observed again in 2024, revealed for the first time by PACE-OCI. This study demonstrates the value of satellite-derived observations for capturing transient phytoplankton biomass events and highlights the potential of PACE-OCI's hyperspectral capabilities to better distinguish phytoplankton communities and improve understanding of their responses to freshwater inflows and associated processes driving pulses into estuaries.

Louisiana↗
USGS2024

Seasonally varying contributions of contemporaneous and lagged sources of instream total nitrogen and phosphorus load across the Illinois River basin

Quantifying nutrient sources in streams, their temporal and spatial variability, and drivers of that variability can support effective water resources management. Yet a lack of data and modeling capabilities has previously prevented comprehensive quantification across both space and time. Here a dynamic SPARROW (Spatially Referenced Regressions on Watershed attributes) model that accounts for a lagged delivery of nutrients to streams was developed and applied to simulate seasonal and source-specific total nitrogen (TN) and total phosphorus (TP) loads in streams across the Illinois River basin (IRB). Dynamic load predictions from 2000 through 2020 revealed that a third of the TN and a quarter of the TP instream load originated from non-point sources that were lagged in their delivery from land-application to streams by more than a season. This lagged mass was the largest overall TN source—which was estimated as a lagged expression of previous seasonal non-point sources including fertilizer, manure, atmospheric deposition and fixation, and urban land use. Treated wastewater effluent was the largest TP source exported from the basin, contributing 39 % of the TP load and 15 % of the TN load, and dominated the load in the upper Illinois River near Chicago. Loads in the lower river during this period, conversely, were attributed primarily to a mix of agricultural sources and their lagged fractions from headwater tributaries. Instream processes removed 10 % of the TN load while only 4 % of the TP load was removed during instream transport. With appropriate datasets, the models could be extended to other basins or time periods and used to forecast future seasonal nutrient loads.

Illinois↗
USGS2021

Influence of redox gradients on nitrate transport from the landscape to groundwater and streams

Increases in nitrogen applications to the land surface since the 1950s have led to a cascade of negative environmental impacts, including degradation of drinking water supplies, nutrient enrichment of aquatic ecosystems and contributions to global climate change. In this study, groundwater, streambed porewater, and stream sampling were used to establish trends in nitrate concentrations and how redox gradients influence nitrate transport across diverse glacial terranes. Decadal sampling has found that elevated nitrate concentrations in shallow groundwater beneath cropland have been sustained for decades. Redox gradients established in the saturated zone using dissolved O 2 , iron, nitrate and excess N 2 from denitrification suggest that nitrate-bearing zones are thin in glacial terranes dominated by fine materials. These thin nitrate-bearing zones lead to suboxic, low nitrate streambed porewater and limit the contributions of nitrate to streams from slow-flow groundwater. In contrast, thick oxic zones in more coarse-grained glacial terranes allow nitrate to reach deeper groundwater, resulting in streambed porewater with elevated nitrate concentrations and causing a large portion of stream nitrate to be derived from slow-flow groundwater. Groundwater age tracer data indicate that denitrification occurs more quickly in the terrane dominated by fine material than in the more coarse-grained terrane. The quicker depletion of nitrate in the more fine-grained terrane suggests that the thinner oxic zone in this terrane is due, in part, to the greater availability and reactivity of electron donors in this terrane than in the more coarse-grained terrane. Groundwater age tracer data and hydrograph separation analysis suggest that saturated zone lag times between when changes in land use practices occur and when changes in stream water are fully observed may vary widely across hydrogeologic settings.

Illinois, Indiana, Iowa, Michigan, Minnesota, Wisc↗
USGS2020

Snow processes in mountain forests: Interception modeling for coarse-scale applications

Snow interception by the forest canopy controls the spatial heterogeneity of subcanopy snow accumulation leading to significant differences between forested and nonforested areas at a variety of scales. Snow intercepted by the forest canopy can also drastically change the surface albedo. As such, accurately modeling snow interception is of importance for various model applications such as hydrological, weather, and climate predictions. Due to difficulties in the direct measurements of snow interception, previous empirical snow interception models were developed at just the point scale. The lack of spatially extensive data sets has hindered the validation of snow interception models in different snow climates, forest types, and at various spatial scales and has reduced the accurate representation of snow interception in coarse-scale models. We present two novel empirical models for the spatial mean and one for the standard deviation of snow interception derived from an extensive snow interception data set collected in an evergreen coniferous forest in the Swiss Alps. Besides open-site snowfall, subgrid model input parameters include the standard deviation of the DSM (digital surface model) and/or the sky view factor, both of which can be easily precomputed. Validation of both models was performed with snow interception data sets acquired in geographically different locations under disparate weather conditions. Snow interception data sets from the Rocky Mountains, US, and the French Alps compared well to the modeled snow interception with a normalized root mean square error (NRMSE) for the spatial mean of ≤10 % for both models and NRMSE of the standard deviation of ≤13 %. Compared to a previous model for the spatial mean interception of snow water equivalent, the presented models show improved model performances. Our results indicate that the proposed snow interception models can be applied in coarse land surface model grid cells provided that a sufficiently fine-scale DSM is available to derive subgrid forest parameters.

Utah↗
USGS1993

Interaction of rising frazil with suspended particles: Tank experiments with applications to nature

Widespread occurrence of sediment-laden (turbid) sea ice and high concentrations of diatoms and foraminifers in ice have recently been reported from both polar regions. Many possible mechanisms of particle entrainment into ice have been postulated, among which scavenging by rising frazil ice and nucleation or adhesion of ice onto suspended particles appear to be the most likely ones. No reliable experimental data on the mechanisms, however, are available. Because of the importance of turbid ice for sediment transport, tanks for laboratory-scale experiments were constructed, in which frazil crystals produced at the base were monitored rising through water column laden with various types of particulate matter, including plankton. Observations made in salt water are reported here. Over a distance of 1.5 m, frazil < 1 mm in diameter grew to crystals or flocs several cm in diameter, rising at average velocities of 2 to 3 cm/s. Rise velocities were a function of frazil size, but varied greatly due to interactions of ice particles of different size and velocity and the resulting turbulence. Sand-size particles could be either trapped permanently by rising frazil, or were temporarily supported and again released. With live plankton, a several-fold enrichment of ice occurred, suggesting that their irregular shapes or appendages were caught by ice flocs. Diatom- and foram tests were also relatively effectively trapped. The concentration of silt- and clay-size terrigenous detritus in frazil tended to increase relative to the water. We found no preferential sorting by ice in this size range. Various kinds of evidence showed that ice does not nucleate onto foreign particles, and has no adhesive properties. Foreign material resided in the interstices of crystal aggregates, and particles denser than water could be released by agitation, suggesting that scavenging is a mechanical process. With rising frazil, the settling of particulate matter therefore is either retarded or reversed, resulting in a net upward sediment flux and a sediment-laden ice cover from this process of suspension freezing.

Cold Regions Science and Technology↗
USGS2019

Debris-flow monitoring and warning: Review and examples

Debris flows represent one of the most dangerous types of mass movements, because of their high velocities, large impact forces and long runout distances. This review describes the available debris-flow monitoring techniques and proposes recommendations to inform the design of future monitoring and warning/alarm systems. The selection and application of these techniques is highly dependent on site and hazard characterization, which is illustrated through detailed descriptions of nine monitoring sites: five in Europe, three in Asia and one in the USA. Most of these monitored catchments cover less than ∼10 km 2 and are topographically rugged with Melton Indices greater than 0.5. Hourly rainfall intensities between 5 and 15 mm/h are sufficient to trigger debris flows at many of the sites, and observed debris-flow volumes range from a few hundred up to almost one million cubic meters. The sensors found in these monitoring systems can be separated into two classes: a class measuring the initiation mechanisms, and another class measuring the flow dynamics. The first class principally includes rain gauges, but also contains of soil moisture and pore-water pressure sensors. The second class involves a large variety of sensors focusing on flow stage or ground vibrations and commonly includes video cameras to validate and aid in the data interpretation. Given the sporadic nature of debris flows, an essential characteristic of the monitoring systems is the differentiation between a continuous mode that samples at low frequency (“non-event mode”) and another mode that records the measurements at high frequency (“event mode”). The event detection algorithm, used to switch into the “event mode” depends on a threshold that is typically based on rainfall or ground vibration. Identifying the correct definition of these thresholds is a fundamental task not only for monitoring purposes, but also for the implementation of warning and alarm systems.

Earth-Science Reviews↗