Geology topics

Richard L. Kiesling

Publications and source records attributed to Richard L. Kiesling.

At least 19 recordsLinked to original sources

USGS2025

Biological implications for contaminants of emerging concern in the Great Lakes–Upper St Lawrence River drainage: An effect-based ecological hazard assessment in fish

Contaminants of emerging concern (CECs) are released widely and continuously into the Great Lakes Basin–Upper St Lawrence River study area, with many detected in surface water at concentrations known to adversely affect fish. We applied a recent ecological hazard assessment methodology to identify the biological significance of a database of 21,441 surface water CEC concentrations compiled from 7,162 surface water samples collected at 1,021 sampling sites in 387 individual waterbodies throughout the Great Lakes Basin. We assessed hazard to fish in 12 effect categories (e.g., mortality, developmental, reproductive) from aqueous exposure to 16 emerging contaminants. Our hazard assessment used pairs of screening values to generate contaminant- and effect-specific ordinal hazard scores. Using this novel methodology, we generated a database of 93,864 hazard scores. We found the highest level of hazard to fish, indicating probable adverse impacts, was broadly distributed and often associated with municipalities. Mortality, reproductive, and developmental effect categories combined accounted for 17.5% of high hazard observations. Low hazard, indicating possible adverse effects, was prevalent for numerous effect categories and occurred throughout the period 1991–2021. For mortality, reproductive, and developmental effect categories, the incidence of elevated hazard (low or high hazard) among assessed water samples was 20.4%, 39.5%, and 20.3%, respectively. On a local scale, effect-based assessment is an efficient and conceptually simple tool for natural resource managers to obtain effect- and site-specific hazard information concerning CEC effects in fish that can be used in project planning and results interpretation for natural resource monitoring, restoration, and protection.

Great Lakes–Upper St Lawrence River study area↗

USGS2025

A comprehensive assessment of membrane bioreactor contaminant removal efficacy through analytical chemistry, fish exposures, and microbiome characterization

Treated municipal wastewater effluent is an important pathway for Contaminants of Emerging Concern (CEC) to enter aquatic ecosystems. As the aging wastewater infrastructure in many industrialized countries requires upgrades or replacement, assessing new treatment technologies in the context of CEC effects may provide additional support for science-based resource management. Here, we used three lines of evidence, analytical chemistry, fish exposure experiments, and fish and water microbiome analysis, to assess the effectiveness of membrane bioreactor treatment (MBR) to replace traditional activated sludge treatment. To do this, we sampled a municipal wastewater treatment plant with a split wastewater stream, a portion of which was treated with an MBR and another via an oxidation ditch (OXI). The OXI and MBR treatments substantially reduced most measured CECs compared to the primary effluent (PRI). Only pesticides and some pharmaceuticals were recalcitrant to both secondary treatment methods. While ammonia toxicity of PRI prevented its inclusion in fish exposure experiments, exposure of fish with waters from the OXI or MBR treated wastewater produced only subtle biological differences with no adverse apical outcomes. These findings were consistent with low chemically derived exposure: activity ratios for OXI and MBR. Microbiome analysis of fish and wastewater highlighted the significant reduction of microbial abundance and diversity in the MBR treatment compared to all other treatments. The comparable removal efficacy of CECs in MBR makes it an attractive alternative to traditional OXI, especially when MBR may eliminate the need for tertiary treatment for wastewater disinfection.

Environmental Toxicology and Chemistry↗

USGS2025

Comparing contaminants of emerging concern and microbial signatures of wastewater treated by membrane bioreactor and oxidation ditch methods

Membrane bioreactors (MBRs) are an attractive option for upgrades to aging wastewater treatment infrastructure across the United States (U.S.) because they have a relatively small footprint and can handle various wastewater loading conditions. However, little is known regarding the efficiency with which MBRs can reduce contaminants of emerging concern (CECs) and microbial loads, or how they influence the microbiome of wastewater effluent. In 2022, we collected nine paired samples of primary treated effluent (PRI), secondary effluent treated by oxidation ditches (OXI), and secondary effluent treated by MBR from a facility in Minnesota, U.S. Samples were analyzed for CECs including 4 alkylphenol ethoxylates, 6 bisphenol analogues, 20 hormones, 110 pharmaceuticals, and 82 pesticides as well as heterotrophic bacteria counts (HPC) and microbiome communities. Except for pesticides, total sample concentrations of CEC classes in OXI and MBR effluents were similar and lower compared to PRI ( p < 0.01). Pesticide concentrations were similar among all treatments. HPC was lower in MBR, compared to OXI, in 67% of samples. Despite limited differences in CEC signatures, differences in the microbiome between the two secondary treatments were observed. OXI showed more distinct differences in bacterial operational taxonomic unit (OTU) presence from PRI, compared to MBR. Relations between some contaminant groups ( e.g. , pharmaceuticals, bisphenols) and effluent microbiomes were observed, though most correlated with PRI effluent. Results from our study indicate that MBR is as effective as OXI at producing high-quality effluent and offers a viable alternative to conventional secondary treatment methods. This full-scale study provides data that helps fill knowledge gaps related to MBR performance outside of lab or benchtop experiments and direct comparison to OXI treatment.

Environmental Science: Water Research & Technology↗

USGS2024

Role of tributary cyanobacterial and nutrient transport and sediment processes on cyanobacterial bloom initiation in Lake Superior nearshore

Watershed fluxes of suspended sediment (SS), nutrients, in particular phosphorus (P), and cyanobacteria may play a role in driving cyanobacterial blooms along the southwestern shore of oligotrophic Lake Superior. To understand how tributary loads contribute to nearshore blooms, we sampled two southwestern shore tributaries, Bois Brule and Siskiwit Rivers. We collected water-quality samples to compute nutrient and sediment loads and to assess cyanobacteria community composition from the tributaries to the nearshore. We collected suspended and streambed sediment to assess the capacity for sediment to store and transport bioavailable P and to assess cyanobacteria community composition. Storm flows drove export of SS, total P, and total nitrogen, with the majority of total P being particulate P. Equilibrium P concentrations revealed that SS sorbed P as it is moved through the stream network across sites and seasons and was a potential source of P to the nearshore. However, streambed sediment in the Bois Brule and Siskiwit River watersheds were P sinks during summer, which potentially delayed transport of dissolved P to the lake. The cyanobacteria community varied spatially and temporally relating to multiple environmental variables including nutrients (P, N, and C) and specific conductivity. Cyanobacteria capable of producing cyanotoxins were present in tributaries and found across multiple environmental compartments indicating a potential for fluvial flow to the nearshore. This study demonstrated that streamflow is a primary driver of total nutrient and sediment loading in both watersheds, which indicates the potential for algal loading to the nearshore via suspended sediment or water.

Wisconsin↗

USGS2022

A pilot study to assess the influence of infiltrated stormwater on groundwater: Hydrology and trace organic contaminants

Underground infiltration basins (UIBs) mimic the natural hydrologic cycle by allowing stormwater to recharge local groundwater aquifers. However, little is known about the potential transport of organic contaminants to receiving groundwater. We conducted a pilot study in which we collected paired grab samples of stormwater runoff flowing into two UIBs (inflow) and shallow groundwater adjacent to the UIBs. Samples were collected coincident with three rain events and analyzed for volatile organic compounds, semi-volatile organic compounds, pharmaceuticals, and pesticides. Few contaminants were detected in groundwater, compared with inflow, and groundwater concentrations were typically an order of magnitude less. With one exception (trichloroethene), all groundwater concentrations were at least two orders of magnitude below available guidance or screening values. This short communication highlights information gaps in understanding the hydrologic connectivity between UIBs and receiving groundwater and potential consequent contaminant transport to the subsurface from varying climatic conditions.

Minnesota↗

USGS2022

Validation of a vulnerability index of exposure to chemicals of emerging concern in surface water and sediment of Great Lakes tributaries of the United States

Widespread occurrence of emerging contaminants in Great Lakes tributaries led to the development and publication of a vulnerability index (VI) to assess the potential exposure of aquatic communities to chemicals of emerging concern (CEC) in the Great Lakes basin. The robust nature of the VI was tested to evaluate the underlying statistical model and expand the spatial domain of the index. Data collected at 131 new sampling sites (Test 1) and published data from independent studies (Test 2) were used to test the model predictions. Test 1 water and sediment samples were analyzed for the same classes of CEC chemicals and compared to the predictions for the original VI. Concentrations and numbers of unique CECs detected in water and sediment samples were similar between the original data and the two test datasets, although CECs tended to have higher detection frequencies in the original dataset compared to the Test 1 and Test 2 datasets. For example, 69 CECs were detected in ≥30% of water samples in the original dataset compared with 17 CECs in the Test 1 data and 59 in the Test 2 data. Predicted vulnerability for test sites agreed with actual vulnerability 64% of the time for water and 71% of the time for sediment. Agreement percentage results were greater when individual sites were grouped by river, with 82% agreement between predictions and actual vulnerability for water and 78% agreement for sediment. For the entire dataset, the VI ranks correlated with an independent estimate of potential biological impact. Agreement percentage was the greatest for low or high vulnerability index values but highly variable for sites that are classified as having medium vulnerability. Despite the underlying variability, there is a significant correlation (R 2 = 0.26; p < 0.01) between the VI ranking of tributaries and the independent ranking of potential negative biological impact.

Illinois, Indiana, Michigan, Minnesota, New York, ↗

USGS2021

Multiple lines of evidence for identifying potential hazards to fish from contaminants of emerging concern in Great Lakes tributaries

Contaminants of emerging concern (CECs; e.g., pharmaceuticals, flame retardants, pesticides, and industrial chemicals) are omnipresent throughout tributaries to the Great Lakes. Furthermore, CECs are often present at concentrations that are potentially hazardous to aquatic species. Since 2010, we characterized the presence of CECs at 309 sites within 47 Great Lakes tributaries and characterized responses of fathead minnow ( Pimephales promelas ) exposed to river water at a subset of 26 sites within four tributaries. Our work resulted in three independent lines of evidence related to the potential hazards of CEC exposure to fish. First, vulnerability (where vulnerability refers to likelihood) of surface waters to CEC presence was predicted using select watershed characteristics. Second, hazard to fish (where hazard means the potential for adverse biological responses) was predicted using screening values for a subset of CECs. Third, biological responses of fathead minnow exposed to river water in streamside exposures were measured. We assessed the congruence of these three lines of evidence for identifying sites with elevated hazards to CEC exposure. Predicted vulnerability and hazards agreed at 66% of all sites. Where the two indices did not agree, vulnerability often underestimated predicted hazard. When compared with measured biological responses from streamside exposures, predicted hazards agreed for 42% of samples. Furthermore, when predicted hazards for specific effect categories were compared with similar measured biomarkers, 26% and 46% of samples agreed for reproductive and physiological effect categories, respectively. Overall, vulnerability and hazard predictions tended to overestimate the measured biological responses, providing a protective estimate of the potential hazards of CEC exposure to fish. When used together, these three approaches can help resource managers prioritize management activities in minimizing hazards of CEC exposure and can be used by researchers to prioritize studies focused on understanding the hazards of CEC exposure to fish. Integr Environ Assess Manag 2022;18:1246–1259. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Great Lakes↗

USGS2021

Identifying sources of contaminants in urban stormwater and evaluation of their removal efficacy across a continuum of urban best management practices

Precipitation events in urban areas often result in stormwater runoff containing a diverse array of chemical contaminants. Although many traditional contaminants, such as nutrients, heavy metals, and polycyclic aromatic hydrocarbons have been studied extensively, only recently has evidence emerged showing that trace organic compounds (TrOCs), including pharmaceuticals, personal care products and pesticides are frequently found in stormwater runoff. As there is little existing information about the sources of TrOCs in urban stormwater or their removal efficacy across a range of stormwater treatment options, we conducted a study to address these knowledge gaps and to characterize the potential contribution of TrOCs to groundwater resources from stormwater infiltration practices, based on several synoptic measurements. The current study allowed us to enhance an existing effort to assess TrOC presence and toxicity in stormwater runoff and treatment pond outflow by addressing questions related to TrOC sources to stormwater and TrOC transport to groundwaters. Analysis of eDNA confirms multiple sources of TrOCs to stormwater including human sewage, dog waste, and feces from waterfowl. It is likely that the presence of some TrOCs detected in stormwater are the result of direct, untreated sewage inputs to stormwater from either human (i.e., leaking sewer infrastructure) or pet waste (washed from sidewalks into storm drains). The seasonal detection of avian eDNA is noteworthy as it highlights seasonality and patterns of migration patterns as contributing factors to stormwater contamination. In contrast to human and pet waste, which likely enters stormwater ponds via the stormwater conveyance system, avian feces may enter ponds either through stormwater runoff or through direct inputs by waterfowl stopping-over temporarily at stormwater ponds. Stormwater ponds had little effect in reducing TrOCs as determined by comparative inflow and outflow analysis. Our results also indicate that overall few TrOCs were present in receiving groundwater adjacent to underground infiltration basins, compared to inflow. However, some contaminants were present at relatively high concentrations compared to stormwater flowing into the basins. This is particularly true for pesticides and their degradants. Fewer TrOCs were detected in interstitial water collected near stormwater ponds compared to inflow and outflow. The presence and concentrations of TrOCs in outflow from ponds was generally similar to or higher than what was observed in inflow. The data collected as part of this study can be used to guide future research or monitoring in an effort to better understand TrOC fate and transport in the environment via stormwater BMPs. Specifically, more work is needed to track parcels of water as they flow through BMPs to better quantify transport and degradation of TrOCs, monitor flow into and out of ponds for mass balance calculations, and conduct tracer tests to better quantify the amount of water that monitoring wells are intercepting from underground infiltration basins. These results have been shared in multiple presentations and in meetings with high school teachers to develop age-appropriate curriculum to highlight the role of individuals in reducing and preventing stormwater contamination. The ongoing pandemic hindered some of these efforts (cancelled conferences; suspended MN Water Roundtable meetings; pre-occupation with teachers moving materials online), however, as dissemination activities become more common in the near future, we will continue to educate stakeholders and educators about the root causes and effects of urban stormwater contamination.

Minnesota↗

USGS2020

Simulation of discharge, water-surface elevations, and water temperatures for the St. Louis River estuary, Minnesota-Wisconsin, 2016–17

The St. Louis River estuary is a large freshwater estuary, next to Duluth, Minnesota, that encompasses the headwaters of Lake Superior. The St. Louis River estuary is one of the most complex and compromised near-shore systems in the upper Great Lakes with a long history of environmental contamination caused by logging, mining, paper mills, and other heavy industrial activities. Presently (2020), a widely available, science-based assessment tool capable of evaluating ecosystem-level responses to remediation and restoration projects has not existed for the estuary. To address this need, the U.S. Geological Survey (USGS) built a predictive, mechanistic, three-dimensional hydrodynamic model for the estuary using the Environmental Fluid Dynamics Code framework. In the current version, the model can simulate continuous discharge, water-surface elevations, water temperature, and flow velocity, although the modular framework allows for future additions of water-quality modeling. The model was calibrated using data collected from April 2016 through November 2016 and validated with data collected from April 2017 through November 2017. The four types of data used to evaluate model performance were water-surface elevations, discharge, water temperature, and flow velocities. Streamflow and temperature boundary condition data included a mixture of USGS streamgage data, Minnesota Department of Natural Resources gage data, and estimates derived from the gage data. The model was able to simulate the water-surface elevations with generally good agreement between the simulated and measured values for both years at the daily time step. Specifically, the model was able to demonstrate excellent agreement with the measured data with Nash-Sutcliffe efficiency coefficients greater than 0.8 for all three locations; however, the model was unable to produce hourly water-surface elevations with such accuracy for 2016–17. Discharge was more dynamic than the water-surface elevations, both for the measured and simulated data. Generally, most of the discharge ranged from −650 to 1,200 cubic meters per second, but the constantly changing flux exiting the estuary into Lake Superior (positive flows) and entering the estuary from Lake Superior (negative flows) occurred throughout the year. Even upstream at the St. Louis River at Oliver, Wisconsin, gage (USGS station 0402403250), the effect of flows into the estuary from Lake Superior did occur, demonstrating the strong effect of the Lake Superior seiche on flows for the estuary. From a performance standpoint, the model was able to simulate discharge with generally good agreement in both years, although the 2017 validation was better than the 2016 calibration period. For the daily Nash-Sutcliffe efficiency coefficients, the simulated values were 0.98, 0.62, 0.49, and 0.71 for the Oliver gage; the Superior Bay entry channel at Superior, Wisc., (USGS station 464226092005600); the Superior Bay Duluth Ship Canal at Duluth, Minn., (USGS station 464646092052900); and total entries (combination of the Superior entry and Duluth entry), respectively. For the hourly evaluation criteria, the model performed poorly, with Nash-Sutcliffe efficiency coefficients less than 0 for the two entries into Lake Superior; therefore, as a predictor of discharge at the hourly scale, the model performed worse than using the measured data average. Similar to discharge, the model was a good predictor of flow velocity at the daily time scale but had difficulty matching the measured data at the hourly scale. For discharge and flow velocity, matching at subdaily time steps for a system as complicated as the St. Louis River estuary is considered difficult because the match is highly sensitive to coordinating the exact measurement location to the simulated value. The final calibration target was water temperature, calibrated for the Oliver gage and the Duluth entry. For calibration purposes, the Duluth entry was the more important water temperature target because the Oliver gage was more of an internal check on the model. The Nash-Sutcliffe efficiency coefficients for the Duluth entry were high; hourly Nash-Sutcliffe efficiency coefficients at the Duluth entry were either at or greater than 0.7 for both years, and daily values were 0.84 and 0.82 for 2016 and 2017, respectively.

Minnesota, Wisconsin↗

USGS2019

Updates to the Madison Lake (Minnesota) CE–QUAL–W2 water-quality model for assessing algal community dynamics

A previously developed CE–QUAL–W2 model for Madison Lake, Minnesota, simulated the algal community dynamics, water quality, and fish habitat suitability of Madison Lake under recent (2014) meteorological conditions. Additionally, this previously developed model simulated the complex interplay between external nutrient loading, internal nutrient loading from sediment release of phosphorus, and the organic matter decomposition of the algal biomass. However, the partitioning of Cyanophyta within the modeling framework was simplified to one group and did not account for how different Cyanophyta populations are affected by light conditions, use of nitrogen, temperature growth ranges, and differences in settling rates. Properly capturing Cyanophyta dynamics is important given the potential risks posed by potential large algal blooms. For example, when Cyanophyta form large blooms, recreational activities can become restricted in certain areas because of thick algal scums or algal mats, in addition to the possible production of a class of toxins, known as cyanotoxins, capable of threatening human health, domestic animals, and wildlife. Therefore, we updated the model to partition the Cyanophyta into a group that fixed nitrogen and a second, more buoyant Cyanophyta group that did not independently fix nitrogen. The U.S. Geological Survey, in cooperation with the St. Croix Watershed Research Station (Science Museum of Minnesota) with support from the Environmental and Natural Resources Trust Fund of Minnesota (Legislative-Citizen Commission on Minnesota Resources), updated the Madison Lake CE–QUAL–W2 model to address the shortcomings of simulating Cyanophyta in the previously developed model and better characterize Cyanophyta into two groups. In addition to updating the Cyanophyta group differentiation, the part of the model that handles the simulation of algal community dynamics was updated while preserving model predictive capabilities for nutrients, water temperature, and dissolved oxygen. The calibration and validation of the model was done under recent meteorological conditions with large and persistent Cyanophyta blooms (2014 and 2016). Overall, the model simulations predicted the persistently large total phosphorus concentrations in the hypolimnion of Madison Lake and key differences in nutrient concentrations between 2014 and 2016. The Cyanophyta bloom persistence throughout the summer was also simulated by the model in 2014 and 2016, a critical goal of the model update. Finally, monthly total phosphorus budgets were calculated for the updated Madison Lake model for 2014 and 2016.

Minnesota↗

USGS2019

Predicting the occurrence of chemicals of emerging concern in surface water and sediment across the U.S. portion of the Great Lakes Basin

Chemicals of emerging concern (CECs) are introduced into the aquatic environment via various sources, posing a potential risk to aquatic organisms. Previous studies have identified relationships between the presence of CECs in water and broad-scale watershed characteristics. However, relationships between the presence of CECs and source-related watershed characteristics have not been explored across the Great Lakes basin. Boosted regression tree (BRT) analyses were used to develop predictive models of CEC occurrence in water and sediment throughout 24 U.S. tributaries to the Great Lakes. Models were based on the distribution of both broad-scale and source-related watershed characteristics. Twenty-one upstream watershed characteristics, including land cover, number of permitted point sources, and distance to point sources were used to develop models predicting the probability of CEC occurrence in surface water and bottom sediment. Total accuracy of BRT models ranged from 66% to 94% for both matrices. All 21 watershed characteristics were important predictor variables in at least one surface-water model; twenty were important in at least one bottom-sediment model. Among the model variables, developed land use and distance to point sources were important predictors of the presence of CEC classes in both water and sediment. Although limitations exist, BRT models are one tool available for assessing vulnerability of fisheries and aquatic resources to CEC occurrences.

Great Lakes basin↗

USGS2018

Effects of urban stormwater and iron‐enhanced sand filtration on Daphnia magna and Pimephales promelas

Urban stormwater is an important but incompletely characterized contributor to surface‐water toxicity. The present study used 5 bioassays of 2 model organisms ( Daphnia magna and fathead minnow, Pimephales promelas ) to investigate stormwater toxicity and mitigation by full‐scale iron‐enhanced sand filters (IESFs). Stormwater samples were collected from major stormwater conveyances and full‐scale IESFs during 4 seasonal events (winter snowmelt and spring, early summer, and late summer rainfalls) and analyzed for a diverse range of contaminants of emerging concern including pharmaceuticals, personal care products, industrial chemicals, and pesticides. Concurrently, stormwater samples were collected for toxicity testing. Seasonality appeared more influential and consistent than site type for most bioassays. Typically, biological consequences were least in early summer and greatest in late summer and winter. In contrast with the unimproved and occasionally reduced biological outcomes in IESF‐treated and late summer samples, water chemistry indicated that numbers and total concentrations of detected organic chemicals, metals, and nutrients were reduced in late summer and in IESF‐treated stormwater samples. Some potent toxicants showed more specific seasonality (e.g., high concentrations of polycyclic aromatic hydrocarbons and industrial compounds in winter, pesticides in early summer and spring, flame retardants in late summer), which may have influenced outcomes. Potential explanations for insignificant or unexpected stormwater treatment outcomes include confounding effects of complex stormwater matrices, IESF nutrient removal, and, less likely, unmonitored toxicants.

Environmental Toxicology and Chemistry↗

USGS2018

Nitrogen cycling in large temperate floodplain rivers of contrasting nutrient regimes and management

Hydraulic connection between channels and floodplains (“connectivity”) is a fundamental determinant of ecosystem function in large floodplain rivers. Factors controlling material processing in these rivers depend not only on the degree of connectivity but also on the sediment conditions, nutrient loads, and source. Nutrient cycling in the nutrient‐rich upper Mississippi River (MISS) is relatively well studied, whereas that of less eutrophic tributaries is not (e.g., St Croix River; SACN). We examined components of nitrogen cycling in 2 floodplain rivers of contrasting nutrient enrichment and catchment land use to test the hypothesis that N‐cycling rates will be greater in the MISS with elevated nutrient loads and productivity in contrast to the relatively nutrient‐poor SACN. Nitrate (NO 3 − ‐N) concentrations were greatest in flowing habitats in the MISS and often undetectable in isolated backwaters except where groundwater inputs occurred. In the SACN, NO 3 − ‐N concentrations were greatest in the flowing backwater where groundwater inputs were high. Ambient nitrification in the MISS was twice that in the SACN and tended to be lowest in the main channel. Denitrification was 3× greater in the MISS than that in the SACN, N‐limited in both rivers. Community production/respiration was >1 in the MISS and likely provisioned labile C to fuel microbial metabolism and dissimilatory NO 3 − ‐N reduction, whereas the heterotrophic (production/respiration < 1) nature of the SACN likely limited microbial metabolism and NO 3 − ‐N dissimilation. It appears that N‐cycling in the SACN was driven by groundwater, whereas that in the MISS was supported mainly by water column N‐sources.

Minnesota, Wisconsin↗

USGS2018

Environmentally relevant chemical mixtures of concern in waters of United States tributaries to the Great Lakes

The North American Great Lakes are a vital natural resource that provide fish and wildlife habitat, as well as drinking water and waste assimilation services for millions of people. Tributaries to the Great Lakes receive chemical inputs from various point and nonpoint sources, and thus are expected to have complex mixtures of chemicals. However, our understanding of the co‐occurrence of specific chemicals in complex mixtures is limited. To better understand the occurrence of specific chemical mixtures in the US Great Lakes Basin, surface water from 24 US tributaries to the Laurentian Great Lakes was collected and analyzed for diverse suites of organic chemicals, primarily focused on chemicals of concern (e.g., pharmaceuticals, personal care products, fragrances). A total of 181 samples and 21 chemical classes were assessed for mixture compositions. Basin wide, 1664 mixtures occurred in at least 25% of sites. The most complex mixtures identified comprised 9 chemical classes and occurred in 58% of sampled tributaries. Pharmaceuticals typically occurred in complex mixtures, reflecting pharmaceutical‐use patterns and wastewater facility outfall influences. Fewer mixtures were identified at lake or lake‐influenced sites than at riverine sites. As mixture complexity increased, the probability of a specific mixture occurring more often than by chance greatly increased, highlighting the importance of understanding source contributions to the environment. This empirically based analysis of mixture composition and occurrence may be used to focus future sampling efforts or mixture toxicity assessments.

Integrated Environmental Assessment and Management↗

USGS2018

Simulation of hydrodynamics, water quality, and lake sturgeon habitat volumes in Lake St. Croix, Wisconsin and Minnesota, 2013

Lake St. Croix is a naturally impounded, riverine lake that makes up the last 40 kilometers of the St. Croix River. Substantial land-use changes during the past 150 years, including increased agriculture and urban development, have reduced Lake St. Croix water-quality and increased nutrient loads delivered to Lake St. Croix. A recent (2012–13) total maximum daily load phosphorus-reduction plan set the goal to reduce total phosphorus loads to Lake St. Croix by 20 percent by 2020 and reduce Lake St. Croix algal bloom frequencies. The U.S. Geological Survey, in cooperation with the National Park Service, developed a two-dimensional, carbon-based, laterally averaged, hydrodynamic and water-quality model, CE–QUAL–W2, that addresses the interaction between nutrient cycling, primary production, and trophic dynamics to predict responses in the distribution of water temperature, oxygen, and chlorophyll a. Distribution is evaluated in the context of habitat for lake sturgeon, including a combination of temperature and dissolved oxygen conditions termed oxy-thermal habitat. The Lake St. Croix CE–QUAL–W2 model successfully reproduced temperature and dissolved oxygen in the lake longitudinally (from upstream to downstream), vertically, and temporally over the seasons. The simulated water temperature profiles closely matched the measured water temperature profiles throughout the year, including the prediction of thermocline transition depths (often within 1 meter), the absolute temperature of the thermocline transitions (often within 1.0 degree Celsius), and profiles without a strong thermocline transition. Simulated dissolved oxygen profiles matched the trajectories of the measured dissolved oxygen concentrations at multiple depths over time, and the simulated concentrations matched the depth and slope of the measured concentrations. Additionally, trends in the measured water-quality data were captured by the model simulation, gaining some potential insights into the underlying mechanisms of critical Lake St. Croix metabolic processes. The CE–QUAL–W2 model tracked nitrate plus nitrite, total nitrogen, and total phosphorus throughout the year. Inflow nutrient contributions (loads), largely dominated by upstream St. Croix River loads, were the most important controls on Lake St. Croix water quality. Close to 60 percent of total phosphorus to the lake was from phosphorus derived from organic matter, and about 89 percent of phosphorus to Lake St. Croix was delivered by St. Croix River inflows. The Lake St. Croix CE–QUAL–W2 model offered potential mechanisms for the effect of external and internal loadings on the biotic response regarding the modeled algal community types of diatoms, green algae, and blue-green algae. The model also suggested the seasonal dominance of blue-green algae in all four pools of the lake. A sensitivity analysis was completed to test the total maximum daily load phosphorus-reduction scenario responses of total phosphorus and chlorophyll a. The modeling indicates that phosphorus reductions would result in similar Lake St. Croix reduced concentrations, although chlorophyll a concentrations did not decrease in the same proportional amounts as the total phosphorus concentrations had decreased. The smaller than expected reduction in algal growth rates highlighted that although inflow phosphorus loads are important, other constituents also can affect the algal response of the lake, such as changes in light penetration and the breakdown of organic matter releasing nutrients. The available habitat suitable for lake sturgeon was evaluated using the modeling results to determine the total volume of good-growth habitat, optimal growth habitat, and lethal temperature habitat. Overall, with the calibrated model, the fish habitat volume in general contained a large proportion of good-growth habitat and a sustained period of optimal growth habitat in the summer. Only brief periods of lethal oxy-thermal habitat were present in Lake St. Croix during the model simulation.

Minnesota, Wisconsin↗

USGS2018

Contaminants of emerging concern in urban stormwater: Spatiotemporal patterns and removal by iron-enhanced sand filters (IESFs)

Numerous contaminants of emerging concern (CECs) typically occur in urban rivers. Wastewater effluents are a major source of many CECs. Urban runoff (stormwater) is a major urban water budget component and may constitute another major CEC pathway. Yet, stormwater-based CEC field studies are rare. This research investigated 384 CECs in 36 stormwater samples in Minneapolis-St. Paul, Minnesota, USA. Nine sampling sites included three large stormwater conveyances (pipes) and three paired iron-enhanced sand filters (IESFs; untreated inlets and treated outlets). The 123 detected compounds included commercial-consumer compounds, veterinary and human pharmaceuticals, lifestyle and personal care compounds, pesticides, and others. Thirty-one CECs were detected in ≥50% of samples. Individual samples contained a median of 35 targeted CECs (range: 18–54). Overall, median concentrations were ≥10 ng/L for 25 CECs and ≥100 ng/L for 9 CECs. Ranked, hierarchical linear modeling indicated significant seasonal- and site type-based concentration variability for 53 and 30 CECs, respectively, with observed patterns corresponding to CEC type, source, usage, and seasonal hydrology. A primarily warm-weather, diffuse, runoff-based profile included many herbicides . A second profile encompassed winter and/or late summer samples enriched with some recalcitrant, hydrophobic compounds (e.g., PAHs), especially at pipes, suggesting conservative, less runoff-dependent sources (e.g., sediments). A third profile, indicative of mixed conservative/non-runoff, runoff, and/or atmospheric sources and transport that collectively affect a variety of conditions, included various fungicides, lifestyle, non-prescription, and commercial-consumer CECs. Generally, pipe sites had large, diverse land-use catchments, and showed more frequent detections of diverse CECs, but often at lower concentrations; while untreated sites (with smaller, more residential-catchments) demonstrated greater detections of “pseudo-persistent” and other ubiquitous or residentially-associated CECs. Although untreated stormwater transports an array of CECs to receiving waters, IESF treatment significantly removed concentrations of 14 (29%) of the 48 most detected CECs; for these, median removal efficiencies were 26%–100%. Efficient removal of some hydrophobic (e.g., PAHs, bisphenol A) and polar-hydrophilic (e.g., caffeine, nicotine) compounds indicated particulate-bound contaminant filtration and for certain dissolved contaminants, sorption.

Minnesota↗

USGS2017

Water-quality models to assess algal community dynamics, water quality, and fish habitat suitability for two agricultural land-use dominated lakes in Minnesota, 2014

Fish habitat can degrade in many lakes due to summer blue-green algal blooms. Predictive models are needed to better manage and mitigate loss of fish habitat due to these changes. The U.S. Geological Survey (USGS), in cooperation with the Minnesota Department of Natural Resources, developed predictive water-quality models for two agricultural land-use dominated lakes in Minnesota—Madison Lake and Pearl Lake, which are part of Minnesota’s sentinel lakes monitoring program—to assess algal community dynamics, water quality, and fish habitat suitability of these two lakes under recent (2014) meteorological conditions. The interaction of basin processes to these two lakes, through the delivery of nutrient loads, were simulated using CE-QUAL-W2, a carbon-based, laterally averaged, two-dimensional water-quality model that predicts distribution of temperature and oxygen from interactions between nutrient cycling, primary production, and trophic dynamics. The CE-QUAL-W2 models successfully predicted water temperature and dissolved oxygen on the basis of the two metrics of mean absolute error and root mean square error. For Madison Lake, the mean absolute error and root mean square error were 0.53 and 0.68 degree Celsius, respectively, for the vertical temperature profile comparisons; for Pearl Lake, the mean absolute error and root mean square error were 0.71 and 0.95 degree Celsius, respectively, for the vertical temperature profile comparisons. Temperature and dissolved oxygen were key metrics for calibration targets. These calibrated lake models also simulated algal community dynamics and water quality. The model simulations presented potential explanations for persistently large total phosphorus concentrations in Madison Lake, key differences in nutrient concentrations between these lakes, and summer blue-green algal bloom persistence. Fish habitat suitability simulations for cool-water and warm-water fish indicated that, in general, both lakes contained a large proportion of good-growth habitat and a sustained period of optimal growth habitat in the summer, without any periods of lethal oxythermal habitat. For Madison and Pearl Lakes, examples of important cool-water fish, particularly game fish, include northern pike ( Esox lucius ), walleye ( Sander vitreus ), and black crappie ( Pomoxis nigromaculatus ); examples of important warm-water fish include bluegill ( Lepomis macrochirus ), largemouth bass ( Micropterus salmoides ), and smallmouth bass ( Micropterus dolomieu ). Sensitivity analyses were completed to understand lake response effects through the use of controlled departures on certain calibrated model parameters and input nutrient loads. These sensitivity analyses also operated as land-use change scenarios because alterations in agricultural practices, for example, could potentially increase or decrease nutrient loads.

Minnesota↗

USGS2014

Identifying non-point sources of endocrine active compounds and their biological impacts in freshwater lakes

Contaminants of emerging concern, particularly endocrine active compounds (EACs), have been identified as a threat to aquatic wildlife. However, little is known about the impact of EACs on lakes through groundwater from onsite wastewater treatment systems (OWTS). This study aims to identify specific contributions of OWTS to Sullivan Lake, Minnesota, USA. Lake hydrology, water chemistry, caged bluegill sunfish ( Lepomis macrochirus ), and larval fathead minnow ( Pimephales promelas ) exposures were used to assess whether EACs entered the lake through OWTS inflow and the resultant biological impact on fish. Study areas included two OWTS-influenced near-shore sites with native bluegill spawning habitats and two in-lake control sites without nearby EAC sources. Caged bluegill sunfish were analyzed for plasma vitellogenin concentrations, organosomatic indices, and histological pathologies. Surface and porewater was collected from each site and analyzed for EACs. Porewater was also collected for laboratory exposure of larval fathead minnow, before analysis of predator escape performance and gene expression profiles. Chemical analysis showed EACs present at low concentrations at each study site, whereas discrete variations were reported between sites and between summer and fall samplings. Body condition index and liver vacuolization of sunfish were found to differ among study sites as did gene expression in exposed larval fathead minnows. Interestingly, biological exposure data and water chemistry did not match. Therefore, although results highlight the potential impacts of seepage from OWTS, further investigation of mixture effects and life history factor as well as chemical fate is warranted.

Minnesota↗