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1,668 records · Page 87Linked to original sources
USGS2025

Base-flow sampling to enhance understanding of the groundwater flow component of nitrogen loading in small watersheds draining into Long Island Sound

Excessive nitrogen discharge is a major concern for the Long Island Sound. Programs have been implemented to reduce point sources of nitrogen to the sound, but little is known about the nonpoint sources. This study aims to better understand the current groundwater contributions of nitrogen from nonpoint sources in the Long Island Sound watershed. During the spring and summer of 2022, the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, collected water-quality samples to analyze nutrients (nitrogen and phosphorus), chloride, and bromide at 45 stations in the Long Island Sound watershed in Connecticut, New York, and Rhode Island. The stations were in small drainage watersheds (5 to 30 square kilometers) in the southern part of the Long Island Sound watershed. During two separate synoptic sampling events, water-quality samples and instantaneous streamflow measurements were collected under base-flow conditions (where the streamflow is dominated by groundwater inputs rather than overland flow or runoff flow). One sampling event was in the nongrowing season (April 24–25, 2022), and the other was in the growing season (June 30–July 1, 2022). To calculate instantaneous nitrogen loads and yields, streamflow was measured at the time of sample collection. Nitrogen concentrations, loads, and yields varied among sampling stations and by season. Total filtered nitrogen concentrations were generally lower in the nongrowing season (from less than 0.14 to 1.9 milligrams per liter) than in the growing season (from less than 0.23 to 3.0 milligrams per liter). Nitrate plus nitrite concentrations showed little variation between the nongrowing and growing seasons. Unfiltered ammonia plus organic nitrogen concentrations were generally lower in the nongrowing season (from less than 0.07 to 0.83 milligram per liter) than in the growing season (from 0.11 to 0.98 milligram per liter). In contrast, total filtered and unfiltered nitrogen loads and yields were higher in the nongrowing season than during the growing season, likely because streamflows were higher during the nongrowing season. Total unfiltered nitrogen yields during the nongrowing season ranged from less than 0.15 to 5.0 kilograms per square kilometer per day. Total unfiltered nitrogen yields during the growing season ranged from less than 0.12 to 2.5 kilograms per square kilometer per day. Total filtered nitrogen yields during the nongrowing season ranged from less than 0.13 to 5.2 kilograms per square kilometer per day. Total filtered nitrogen yields during the growing season ranged from less than 0.06 to 2.5 kilograms per square kilometer per day.

Connecticut, New York, Rhode Island↗
USGS2025

Origin of the high Pd/Pt ratio of the J-M Reef, Stillwater Complex Montana USA

The J-M Reef of the Stillwater Complex exhibits a high and consistent Pd/Pt ratio (~3.8). This ratio results from the equilibration of an immiscible sulfide liquid with a relatively high Pd/Pt silicate melt rather than an unusually Pd- and Pt-enriched parental melt. Numerical modeling suggests that the original silicate melt contained typical mantle-derived concentrations of Pd and Pt (~10–20 ppb Pd/Pt ~1). The partitioning of Pt and Pd between sulfide liquid and silicate melt alone cannot explain the consistently high Pd/Pt ratio across variable melt-to-sulfide mass ratios (R factors). Instead Pt-depletion caused by the early fractionation of Pt-alloy from S-undersaturated silicate magma likely established the high Pd/Pt signature. High Pd/Pt ratios can form through batch equilibration of sulfide liquid with silicate melt if partition coefficients are extremely high (>10⁶). Alternatively Pd enrichment may result from sulfide upgrading within the resident footwall mush under smaller partition coefficients (10⁴–10⁶) in this model the instantaneous R factors remain low (R ≈ 100–700). This limits the impact of Pt and Pd partitioning on sulfide composition and helps explain the Pd-enriched character of the J-M Reef.

Montana↗
USGS1983

Use of digital land-cover data from the Landsat satellite in estimating streamflow characteristics in the Cumberland Plateau of Tennessee

Characteristics of Streamflow at ungaged sites in coal-mining areas of the Cumberland Plateau may be estimated with regression equations that relate streamflow characteristics to the physiographic and climatic characteristics of the corresponding drainage basins. An experiment was performed to compare the accuracy of equations using basin characteristics derived from maps and climatological records (control group equations) with the accuracy of equations using basin characteristics derived from digital processing of Landsat spectral data as well as maps and climatological records (experimental group equations). Results of this experiment show that (with the exception of low flows and four of six annual peak logarithms) drainage area can explain more than 90 percent of the variance in all streamflow characteristics in both groups of equations. Seventeen of 39 experimental group equations that have two basin characteristics each are different from the corresponding control group equations. Five of the 17 differing experimental group equations have no counterpart in the control group because of lack of significance in control group basin characteristics, seven are slightly more accurate, and five are not measurably different in accuracy. When the equations in both groups are arranged into six flow categories, there is no substantial difference in accuracy between equations using basin characteristics derived from maps and climatological records (control group) and equations using basin characteristics derived from Landsat tapes as well as maps and climatological records (experimental group) for this particular study area, the Cumberland Plateau of Tennessee.

Tennessee↗
USGS2024

On connecting hydro-social parameters to vegetation greenness differences in an evolving groundwater-dependent ecosystem

Understanding groundwater-dependent ecosystems (i.e., areas with a relatively shallow water table that plays a major role in supporting vegetation health) is key to sustaining water resources in the western United States. Groundwater-dependent ecosystems (GDEs) in Colorado have non-pristine temporal and spatial patterns, compared to agro-ecosystems, which make it difficult to quantify how these ecosystems are impacted by changes in water availability. The goal of this study is to examine how key hydrosocial parameters perturb GDE water use in time and in space. The temporal approach tests for the additive impacts of precipitation, surface water discharge, surface water mass balance as a surrogate for surface–groundwater exchange, and groundwater depth on the monthly Landsat normalized difference vegetation index (NDVI). The spatial approach tests for the additive impacts of river confluences, canal augmentation, development, perennial tributary confluences, and farmland modification on temporally integrated NDVI. Model results show a temporal trend (monthly, 1984–2019) is identifiable along segments of the Arkansas River at resolutions finer than 10 km. The temporal impacts of river discharge correlate with riparian water use sooner in time compared to precipitation, but this result is spatially variable and dependent on the covariates tested. Spatially, areal segments of the Arkansas River that have confluences with perennial streams have increased cumulative vegetation density. Quantifying temporal and spatial dependencies between the sources and effects of GDEs could aid in preventing the loss of a vulnerable ecosystem to increased water demand, changing climate, and evolving irrigation methodologies.

Colorado↗
USGS2024

Characteristics of the fault damage zone From high-resolution seismic imaging along the Palos Verdes Fault, California

The distribution and intensity of fault damage zones provides insight into fault activity and its relationship to fluid flow in the crust. Presently, measures of the in-situ distribution of fault damage remain limited and along-strike studies are rare. This study focuses on an offshore section Palos Verdes Fault damage zone that spans 28 km, near Los Angeles, California. To investigate the previously unresolved shallow (∼400 m below the seafloor) fault damage zone we use densely spaced (∼500 m line separation) newly collected sparker multichannel seismic lines and sub-bottom profiles. The combination of high-resolution acquisition methods and specialized seismic processing workflows provide improved imaging of shallow faulting. We apply a multi-trace similarity technique to identify discontinuities in the seismic data that may be attributed to faults and fractures. This fault detection approach reveals diverse fault damage patterns on adjacent seismic profiles. However, a discernible damage zone pattern emerges by stacking multiple damage detection profiles along strike. We find that peak damage identified in this way corresponds to the active main fault strand, confirmed in this study, and thus the technique may be useful for identifying active fault strands elsewhere. Additionally, we observe that the variable width of the damage zone along strike is controlled by fault obliquity. Furthermore, our observations reveal a correlation between fault damage and seafloor fluid seeps visible in the water column, suggesting that damage plays a role in controlling fluid flow around the fault.

California↗
USGS2025

Total uncertainty quantification in inverse solutions with deep learning surrogate models

We propose an approximate Bayesian method for quantifying the total uncertainty in inverse partial differential equation (PDE) solutions obtained with machine learning surrogate models, including operator learning models. The proposed method accounts for uncertainty in the observations, PDE, and surrogate models. First, we use the surrogate model to formulate a minimization problem in the reduced space for the maximum a posteriori (MAP) inverse solution. Then, we randomize the MAP objective function and obtain samples of the posterior distribution by minimizing different realizations of the objective function. We test the proposed framework by comparing it with the iterative ensemble smoother and deep ensembling methods for a nonlinear diffusion equation with an unknown space-dependent diffusion coefficient. Among other applications, this equation describes the flow of groundwater in an unconfined aquifer. Depending on the training dataset and ensemble sizes, the proposed method provides similar or more descriptive posteriors of the parameters and states than the iterative ensemble smoother method. Deep ensembling underestimates uncertainty and provides less-informative posteriors than the other two methods. Our results show that, despite inherent uncertainty, surrogate models can be used for parameter and state estimation as an alternative to the inverse methods relying on (more accurate) numerical PDE solvers.

Journal of Computational Physics↗
USGS2025

Estimating earthquake source depth using teleseismic broadband waveform modeling at the USGS National Earthquake Information Center

The U.S. Geologic Survey National Earthquake Information Center (NEIC) monitors global seismicity, producing a catalog of earthquake source parameters in near-real-time to provide information that can help mitigate the societal impact of earthquakes. The NEIC commonly relies on teleseismic observations to constrain earthquake source parameters (e.g., location, depth, magnitude, and mechanism) due to a lack of local and regional observations. For these ‘teleseismic’ events, depth phase (i.e., pP , sP ) arrival time observations provide the best estimate on source depth. However, depth phases are often difficult to accurately identify and/or pick. Therefore, NEIC relies on waveform modeling, such as those determined from W-phase ( M ww ), body wave ( M wb ), and regional ( M wr ) moment tensor estimations, to provide constraints on source depth. While depth estimates from these approaches are informative, higher frequency observations provide more precise estimates because depth phases are more prominently observed at higher frequencies. Here, we present NEIC’s relatively high-frequency (~0.04 to 1 Hz) teleseismic waveform modeling approach, termed Synthetic Depth Phase Modeling (SynDepth), for determining source depth. SynDepth was developed to provide NEIC with a tool that enables rapid, accurate, and quantifiable estimates of earthquake source depth in cases where locator depths are not reliable. This relatively simple and fast procedure searches over 1 km-incremented source depths and an expanding triangular source-time function to find the best-fitting solution. We compare automatic SynDepth solutions for a dataset of 1,216 earthquakes (M5.5-M7.6) between 2017 and 2021 to NEIC-derived depth estimates from other methods. Our approach provides a robust depth estimate for earthquakes lacking local arrival time data, and it minimizes the need for analyst review of depth-phase picks ( pP , sP ) or using predefined ‘fixed’ depths.

Seismological Research Letters↗
USGS2025

Disparate groundwater responses to wildfire

Post-wildfire investigations of groundwater response reveal a range of outcomes, varying from substantial increases to notable decreases in recharge and baseflow, with some studies indicating negligible or short-lived effects. This review assesses these varied responses within five critical categories: climate, vegetation, hydrogeology, fire characteristics, and the cryosphere, examining both short-term (within 2 years) and intermediate (2–10 years post-fire) effects. Despite considerable variability, some consistent patterns emerge. For instance, in hydroclimatic settings where water input and evaporative demand cycles are out of sync, post-wildfire groundwater responses tend to be positive (i.e., increased flux or storage), whereas under low fire severity conditions or in vegetation types that quickly recover, groundwater responses tend to be negative (i.e., decreased flux or storage). We synthesize relevant findings into a compendium of testable hypotheses aimed at explaining the spatiotemporal variability in observed post-wildfire groundwater responses. A recurring theme is the critical influence of the pre-wildfire groundwater regime on expected response and recovery. We identify opportunities for specific improvements in post-wildfire monitoring and modeling that would further advance capabilities to predict groundwater response. A key area for further research is understanding how wildfire effects on snow dynamics and other cryospheric processes translate to changes in groundwater.

WIREs Water↗
USGS2024

Turbidite correlation for paleoseismology

Marine turbidite paleoseismology relies on the assumption of synchronous triggering of turbidity currents by earthquake shaking to infer rupture extent and recurrence. Such inference commonly depends on age dating and correlation of the physical stratigraphy of deposits carried by turbidity currents (i.e., turbidites) across great distances. Along the Cascadia subduction zone, which lies offshore the Pacific Northwest, USA, turbidite facies in core photographs, X-ray computed tomography images, and magnetic susceptibility (MS) data exhibit differences in character over relatively short distances, which implies that not all deposits can be correlated with confidence. Thus, subjective correlation based on expected similarity over great distances and weak age constraints does not independently support paleoseismic models. We present a new method for correlating turbidites along the Cascadia margin that can yield a more objective and repeatable stratigraphic framework to underpin earthquake recurrence. We use dynamic time warping to correlate MS logs and measure correlation coefficients of core pairs to evaluate correlation strength. We then compare these measures to a distribution of correlation coefficients of randomly generated turbidite sequences and find that only a small number of core pairs can be correlated more confidently than randomly stacked turbidites. This methodology promises a more robust correlation strategy for future stratigraphic studies.

Oregon, Washington↗
USGS2024

Parsimonious high-resolution landslide susceptibility modeling at continental scales

Landslide susceptibility maps are fundamental tools for risk reduction, but the coarse resolution of current continental-scale models is insufficient for local application. Complex relations between topographic and environmental attributes characterizing landslide susceptibility at local scales are not transferrable across areas without landslide data. Existing maps with multiple susceptibility classifications under-represent landslide potential in moderate and gently sloping terrain. We leverage an extensive landslide database ( N = 613,724), a high-resolution digital elevation model (10-m), and high-performance computing resources, to develop a new nationwide susceptibility map for the contiguous United States, Hawaii, Alaska, and Puerto Rico. We calculate four alternative linear and nonlinear thresholds of topographic slope and relief using an objective split-sample calibration. We down-sample our results to a 90-m grid to account for uncertainty in the digital elevation model and landslide position, and evaluate these thresholds' ability to differentiate areas of greater susceptibility. The less conservative nonlinear model optimally balances our priorities of capturing observed landslides (99%) while minimizing area covered by susceptible terrain (43%). Independent evaluation with four statewide landslide inventories ( N = 172,367) reinforces our model selection but highlights spatially variable performance. Therefore, we propose a novel approach to susceptibility classification using the concentration of landslide-prone terrain within each down-sampled grid. While landslides are possible within any cells containing susceptible terrain, those with the highest concentration capture the majority of observed landslides. Our new map characterizes landside susceptibility more consistently than prior models; our transparent classification approach also provides flexibility for accommodating different tolerances in risk reduction measures.

AGU Advances↗
USGS2024

Parameter ESTimation with the Gauss–Levenberg–Marquardt algorithm: An intuitive guide

In this paper, we review the derivation of the Gauss–Levenberg–Marquardt (GLM) algorithm and its extension to ensemble parameter estimation. We explore the use of graphical methods to provide insights into how the algorithm works in practice and discuss the implications of both algorithm tuning parameters and objective function construction in performance. Some insights include understanding the control of both parameter trajectory and step size for GLM as a function of tuning parameters. Furthermore, for the iterative Ensemble Smoother (iES), we discuss the importance of noise on observations and show how iES can cope with non-unique outcomes based on objective function construction. These insights are valuable for modelers using PEST, PEST++, or similar parameter estimation tools.

Groundwater↗
USGS2025

Updating regional‐scale geospatial liquefaction models with locally available geotechnical data

We present a method to update the geospatial liquefaction model used by the U.S. Geological Survey’s near‐real‐time ground failure product with subsurface geotechnical data. The geospatial model estimates liquefaction probability from peak ground velocity (via ShakeMap) and geospatial susceptibility proxies. In many regions, additional information relevant to constraining liquefaction likelihood is also available, including surface geology maps and subsurface geotechnical measurements. There is currently no mechanism to use these data in the ground failure product liquefaction model, even though these data could provide more precise constraints on spatial variations in the lithologic character of the soil (surface geology) and direct measurements of the subsurface mechanical properties that affect liquefaction occurrence and severity (geotechnical measurements). In this study, we develop a method to integrate these data with the geospatial model and assess how these data can improve regional‐scale predictions. We develop a Bayesian updating framework and apply it to the 1989 magnitude 6.9 Loma Prieta, California, earthquake, for which mapped observations are available to evaluate performance. We constrain the Bayesian framework with 373 Northern California cone penetration tests and liquefaction susceptibility classes based on the mapped surface geology. This Bayesian model incorporates geotechnical information into the geospatial model and more accurately predicts liquefaction occurrences than the geospatial model, while sacrificing less accuracy in terms of predicting the absence of liquefaction than the geotechnical model. In future applications, this approach could be adapted to update other geospatial models using locally available subsurface data.

California↗
USGS2024

Agricultural return flow dynamics on a reach of the East River, Colorado, as assessed by mass balance

The U.S. Geological Survey, in cooperation with the Upper Gunnison River Water Conservancy District, studied historical streamflow in a reach of the East River, Colorado, to gain a preliminary understanding of return flow dynamics. Return flow is agricultural irrigation water that is not consumed by evapotranspiration and instead reaches streams by surface and subsurface flow paths. The study reach had a contributing area of 50 square miles and contained 5.23 square miles of pastures irrigated with water diverted from the East River and its tributaries. By comparing upstream inflows to downstream outflows, the net water balance of the study reach from 1994 to 2023 was assessed. Two general hydrologic conditions for the study reach were identified. One hydrologic condition was characterized by a net loss or consumption of water, termed here as general deficit. This general deficit condition extended about 16 years, from 1997 to 2012. During general deficit years, there was usually a notable net loss of streamflow from April through July, and a small net gain, possibly related to return flows, occurred in August about 75 days after the minimums for losses. The second hydrologic condition was characterized by a net gain of water, termed here as general surplus. This second condition extended about 10 years, from 2014 to 2023. During general surplus years, two separate transitions from net loss to net gain commonly occurred during June through August. Losses during general surplus years were smaller than losses during general deficit years, the respective gains were larger, and times between losses and gains were about 18 and 22 days. Differences between the two hydrologic conditions could reflect interactions among irrigation water, available capacity to store additional shallow groundwater, and streamflow. However, deciphering the causes for the shifts between the two general hydrologic conditions was beyond the scope of this report.

Colorado↗
USGS2021

Factors influencing distribution of Coccidioides immitis in soil, Washington State, 2016

Coccidioides immitis and Coccidioides posadasii are causative agents of Valley fever, a serious fungal disease endemic to regions with hot, arid climate in the United States, Mexico, and Central and South America. The environmental niche of Coccidioide s spp. is not well defined, and it remains unknown whether these fungi are primarily associated with rodents or grow as saprotrophs in soil. To better understand the environmental reservoir of these pathogens, we used a systematic soil sampling approach, quantitative PCR (qPCR), culture, whole-genome sequencing, and soil chemical analysis to identify factors associated with the presence of C. immitis at a known colonization site in Washington State linked to a human case in 2010. We found that the same strain colonized an area of over 46,000 m 2 and persisted in soil for over 6 years. No association with rodent burrows was observed, as C. immitis DNA was as likely to be detected inside rodent holes as it was in the surrounding soil. In addition, the presence of C. immitis DNA in soil was correlated with elevated levels of boron, calcium, magnesium, sodium, and silicon in soil leachates. We also observed differences in the microbial communities between C. immitis -positive and -negative soils. Our artificial soil inoculation experiments demonstrated that C. immitis can use soil as a sole source of nutrients. Taken together, these results suggest that soil parameters need to be considered when modeling the distribution of this fungus in the environment.

Washington↗
USGS2026

Transcriptional changes in wild Yukon River Chinook Salmon associated with Ichthyophonus infections

Objective We compared differentially expressed genes in Chinook Salmon Oncorhynchus tshawytscha with three divergent Ichthyophonus statuses (undetected, subclinical infections, or clinical disease; n = 100) to investigate associated transcriptomic responses. Disease associated with the fish parasite Ichthyophonus sp. was first diagnosed in adult Chinook Salmon from the Yukon River in the late 1980s and has subsequently been implicated in premature host mortality. Methods Chinook Salmon tissue sample collections and Ichthyophonus infection data were leveraged from a multi-agency collaboration during summer 2022 at three locations along the main-stem Yukon River that spanned nearly 2,000 km of freshwater migration (lower, middle, and upper river). We sequenced the transcriptome and compared this to infection status based on routine diagnostic procedures. Results Among the 17,569 genes for which messenger RNA was detected, we identified a transcription signature in the skeletal muscle that was associated with Ichthyophonus infections and included 53 differentially expressed genes. The differentially expressed genes and their pathways included those known for involvement in immune functions, energy synthesis, cellular breakdown, and reproduction—all processes that are known to be influenced by senescence during spawning migrations. Conclusions Results demonstrate a clear transcriptional difference between diseased fish (clinical disease group) and those in which Ichthyophonus was undetected, including identifying candidate markers for infection in this population. These results provide a foundation for development of nonlethal biomarkers to evaluate potential Ichthyophonus infections in Chinook Salmon based on gene transcription, protein products, or gene variants (e.g., polymorphisms).

Journal of Aquatic Animal Health↗
USGS2026

Advancing outreach effectiveness to improve conservation practice adoption

Agricultural conservation practices are central to achieving Chesapeake Bay watershed restoration goals, yet long-term adoption remains challenging even when practices are technically effective and financial assistance is available. Adoption is not a single decision, but a staged and context-dependent process. Awareness and willingness to commitment, implementation, and persistence, are all important. Progress along this pathway is influenced by interacting factors such as knowledge, attitudes, beliefs, social norms, trust, perceived risk, farm characteristics, and practical constraints. Improving adoption requires outreach strategies that respond to the specific factors limiting progress at each stage rather than relying on a one-size-fits-all approach.

Chesapeake Bay watershed↗
USGS2025

Groundwater response to managed aquifer recharge at the Southeast Houghton Artificial Recharge Project in Tucson, Arizona

Managed aquifer recharge is a widespread practice for storing water in the subsurface as groundwater. At a managed aquifer recharge facility in southern Arizona, groundwater-level and repeat microgravity data were collected to monitor aquifer response. These data were used to inform parameter identification for an unsaturated-zone flow model used to simulate the recharge process. The facility, the Southeast Houghton Artificial Recharge Project (SHARP), consists of 3 surface basins (about 27,600 square meters [6.8 acres] total surface area) where recycled water is distributed in recharge cycles lasting several months, with dry periods in between. During the study period, December 2020–December 2022, Tucson Water (the City of Tucson’s water utility) reported 6.56×10 6 cubic meters of water (5,320 acre-feet) recharged. Monitoring included groundwater-level observations at 3 monitoring wells and repeat microgravity measurements at as many as 22 locations (some stations were destroyed between surveys). Six gravity surveys were carried out using absolute- and relative-gravity meters. Large gravity increases, more than 250 microgals, were observed during the first repeat survey, 3.5 months after the start of recharge, but only in the immediate vicinity of the recharge basins. Data show that water moved downward to the water table, and storage changes in the unsaturated zone away from the facility were likely minimal. Gravity decreased at stations more than 1 kilometer from the facility, consistent with regional groundwater-level changes. Groundwater-level increases in wells adjacent to the recharge basins began 2 months after the second repeat gravity survey, and 5.5 months after recharge began. Unsaturated-zone flow modeling was carried out using software that simulates water movement and parameter estimation. Model calibration was carried out by minimizing an objective function calculated from the differences between simulated and observed groundwater levels, and between simulated and observed repeat microgravity data. Including repeat microgravity data in the objective function reduced the uncertainty in estimated parameter values for saturated hydraulic conductivity and saturated water content. Modeling indicated that the unsaturated zone between the recharge basins and the water table does not become saturated even after 685 days of simulated infiltration. This gradual wetting may account for increasing infiltration rates over time, as hydraulic conductivity increases with increasing water content. Unsaturated-zone water content decreased rapidly between recharge cycles. Model-simulated groundwater mounding extended about 1 kilometer from the center of SHARP after the 685-day period following the onset of recharge.

Arizona↗
USGS1976

Results of phytoplankton sampling at National Stream Quality Accounting Network stations in Montana, 1975 water year

Twelve National Stream Quality Accounting Network stations were operated in Montana during the 1975 water year. The network was established for the purpose of acquiring a base of hydrologic data for use by agencies engaged in water-resources planning on a national or regional scale. Among the characteristics analyzed were phytoplankton identification and cell counts. Samples consisted of composites of equal aliquots, collected at the center of each quartile of flow, using modified suspended-sediment samplers and sediment collection techniques. Identification and counting were done using the Sedgwick-Rafter cell method. Cell counts ranged from 21 cells per millilitre at Flathead River at Flathead, British Columbia to 27,000 cells per millilitre at Yellowstone River near Sidney. The class Bacillariophyceae was most abundant in both number and variety at all sampling sites. Anabaena and Aphanizomenon of the phyllum Cyanophyta were found at six stations and two stations respectively. These two genera of blue-green algae often become abundant in enriched waters resulting in nuisance conditions.

Montana↗