Great Lakes Environmental Research Laboratory Research Articles

Routine monitoring of western Lake Erie to track water quality changes associated with cyanobacterial harmful algal blooms

Abstract. The western basin of Lake Erie has a history of recurrent cyanobacterial harmful algal blooms (HABs) despite decades of efforts by the United States and Canada to limit phosphorus loading, a major driver of the blooms. In response, the National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) and the Cooperative Institute for Great Lakes Research (CIGLR) created an annual sampling program to detect, monitor, assess, and predict HABs in western Lake Erie (WLE). Here we describe the data collected from this monitoring program from 2012 to 2021. This dataset includes observations on physicochemical properties, major nutrient fractions, phytoplankton pigments, microcystins, and optical properties for western Lake Erie. This dataset is particularly relevant for creating models, verifying and calibrating remote sensing algorithms, and informing experimental research to further understand the water quality dynamics that influence HABs in this internationally significant body of freshwater. The dataset can be freely accessed from NOAA National Centers for Environmental Information (NCEI) at https://doi.org/10.25921/11da-3x54 (Cooperative Institute for Great Lakes Research, University of Michigan and NOAA Great Lakes Environmental Research Laboratory, 2019).

Seasonal variation in light penetration and subsurface chlorophyll-α in southern Lake Michigan observed by a glider

The Cooperative Institute for Great Lakes Research (CIGLR) in collaboration with the Great Lakes Observing System and National Oceanic and Atmospheric Administration, Great Lakes Environmental Research Laboratory (NOAA GLERL) deployed an autonomous underwater glider in southern Lake Michigan several times per year between 2012 and 2019 to collect offshore (>30 m depth) limnological measurements, including temperature, photosynthetically active radiation (beginning during 2015), and chlorophyll-α fluorescence. From these data, we calculated mixed layer depth, several measures of light penetration (diffuse attenuation coefficient, first optical depth, euphotic zone depth), and depth of the subsurface chlorophyll-α maxima. During summer, mean offshore mixed layer depth was typically 10–15 m, Kd for PAR was 0.1–0.17 m−1, first optical depth was 6–9 m, euphotic zone depth was 35–40 m, and depth of subsurface chlorophyll-α maxima was 30–35 m. We also observed substantial spatial and temporal variation in these values across the basin and within and among seasons. Glider-based observations provide a wider horizontal and vertical perspective than other methods (e.g., ship- and satellite-based observations, buoys, and fixed moorings), and are therefore a valuable, complementary tool for Great Lakes limnology. The set of observations reported here provide seasonal and basin-scale information that may help to identify anomalies useful for future glider-assisted investigation into the role of biophysical processes in Great Lakes limnology and ecology.

Seasonal hydrological loading in the Great Lakes region detected by GNSS: a comparison with hydrological models

SUMMARY Crustal deformation caused by hydrological processes has long been detected using space geodetic techniques, yet questions remain about the relative contributions of surface water and groundwater to the geodetic signals in different regions. Here, we investigate forward models of elastic loading deformation caused by a variety of water-storage changes within the Great Lakes region, including fluctuations in lake-water volume, soil moisture and snow load. We use lake-level data from the Great Lakes Environmental Research Laboratory, soil-moisture content from the North American Land Data Assimilation System (NLDAS), snow load from the Snow Data Assimilation System (SNODAS) and background hydrological load at the global scale from Gravity Recovery and Climate Experiment (GRACE). We compare the modelled surface deformation with estimates of hydrological loading deformation inferred from Global Navigation Satellite System (GNSS) measurements. We find that seasonal deformation measured by GNSS is dominated by regional-scale hydrological loading based on strong correlations with the modelled loading displacements. The mean correlation coefficient for the study network is 0.56. The correlation coefficients vary spatially within the study region and exceed 0.9 at some stations near to the Great Lakes. We assess the relative contribution of each individual hydrological component to the total integrated hydrological load. We find that soil moisture consistently explains the largest percentage (27–69 per cent) of the total vertical loading deformation for 87 per cent of GNSS stations in the Great Lakes region. Snow loading and soil moisture contribute relatively equally in the northern reaches of the study area (e.g. Canadian shield, northern Superior basin). Lake loading accounts for about 10–25 per cent of the total loading signal in the immediate vicinity of the lakes. We also investigate the sensitivities of the surface loading displacements to three different Earth models, including two with lateral variations in structure. The structural variations considered here have limited impact (<0.2 mm) on the predicted hydrological loading displacements and could be neglected at the current level of observational precision.

A consistent Great Lakes ice cover digital data set for winters 1973\u20132019

Ice formation and loss in the Laurentian Great Lakes has a strong impact on regional climate, weather, economy and ecology in North America. To record the ice changes during the winter season, Great Lakes ice cover data has been collected and maintained since 1973 by Canadian Ice Service, U.S. National Ice Center, and National Oceanic and Atmospheric Administration’s Great Lakes Environmental Research Laboratory. Throughout this long history, technology has improved and the needs of users have evolved, so Great Lakes ice cover datasets have been upgraded several times in both spatial and temporal resolutions. In order to make those long-term data consistent and accessible, we reprocessed the Great Lakes ice cover database to generate daily gridded data (1.8 km resolution) using a re-project method with Nearest Neighbor Search for spatial interpolation, and linear interpolation with categorization for temporal interpolation. This report elucidates data history, generation procedures, and file structure in order to improve access and usability of Great Lakes ice cover data.

Development and application of a North American Great Lakes hydrometeorological database — Part I: Precipitation, evaporation, runoff, and air temperature

Starting in 1983, the National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) has been developing and maintaining a historical time series of North American Great Lakes basin-scale monthly hydrometeorological data. This collection of data sets, which we hereafter refer to as the NOAA-GLERL monthly hydrometeorological database (GLM-HMD), is, to our knowledge, the first (and perhaps still the only) to assimilate hydrometeorological measurements into model simulations for each of the major components of the water budget across the entirety (i.e., both United States and Canadian portions) of the Great Lakes basin for a period of record dating back to the early and mid 1900s. Here, we describe the development of data sets in the first (GLM-HMD-I) of two subsets of the GLM-HMD including basin-scale estimates of over-lake and over-land precipitation and air temperature, runoff, and over-lake evaporation. Our synthesis of the GLM-HMD-I includes a summary of the monitoring network associated with each variable and an indication of how each monitoring network has changed over time. We conclude with two representative applications of the GLM-HMD aimed at advancing understanding of seasonal and long-term changes in Great Lakes regional meteorology and climatology. These two examples implicitly reflect the historical utility of the GLM-HMD in numerous previous studies, and explicitly demonstrate its potential utility in ongoing and future regional hydrological science and climate change research.

The Operational Implementation of a Great Lakes Wave Forecasting System at NOAA/NCEP*

Abstract The development of a Great Lakes wave forecasting system at NOAA’s National Centers for Environmental Prediction (NCEP) is described. The system is an implementation of the WAVEWATCH III model, forced with atmospheric data from NCEP’s regional Weather Research and Forecasting (WRF) Model [the North American Mesoscale Model (NAM)] and the National Digital Forecast Database (NDFD). Reviews are made of previous Great Lakes wave modeling efforts. The development history of NCEP’s Great Lakes wave forecasting system is presented. A performance assessment is made of model wind speeds, as well as wave heights and periods, relative to National Data Buoy Center (NDBC) measurements. Performance comparisons are made relative to NOAA’s Great Lakes Environmental Research Laboratory (GLERL) wave prediction system. Results show that 1- and 2-day forecasts from NCEP have good skill in predicting wave heights and periods. NCEP’s system provides a better representation of measured wave periods, relative to the GLERL model in most conditions. Wave heights during storms, however, are consistently underestimated by NCEP’s current operational system, whereas the GLERL model provides close agreement with observations. Research efforts to develop new wave-growth parameterizations and overcome this limitation have led to upgrades to the WAVEWATCH III model, scheduled to become operational at NCEP in 2013. Results are presented from numerical experiments made with the new wave-model physics, showing significant improvements to the skill of NCEP’s Great Lakes wave forecasting system in predicting storm wave heights.

The Great Lakes Runoff Intercomparison Project Phase 1: Lake Michigan (GRIP-M)

We assembled and applied five models (one of which included three different configurations) to the Lake Michigan basin to improve our understanding of how differences in model skill at simulating total runoff to Lake Michigan relate to model structure, calibration protocol, model complexity, and assimilation (i.e. replacement of simulated discharge with discharge observations into historical simulations), and evaluate historical changes in runoff to Lake Michigan. We found that the performance among these models when simulating total runoff to the lake varied relatively little, despite variability in model structure, spatial representation, input data, and calibration protocol. Relatively simple empirical, assimilative models, including the National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) area ratio-based model (ARM) and the United States Geological Survey (USGS) Analysis of Flows in Networks of CHannels (AFINCH) model, represent efficient and effective approaches to propagating discharge observations into basin-wide (including gaged and ungaged areas) runoff estimates, and may offer an opportunity to improve predictive models for simulating runoff to the Great Lakes. Additionally, the intercomparison revealed that the median of the simulations from non-assimilative models agrees well with assimilative models, suggesting that using a combination of different methodologies may be an appropriate approach for estimating runoff into the Great Lakes. We then applied one assimilative model (ARM) to the Lake Michigan basin and found that there was persistent reduction in the amount of precipitation that becomes runoff following 1998, corresponding to a period of persistent low Lake Michigan water levels. The study was conducted as a first phase of the Great Lakes Runoff Intercomparison Project, a regional binational collaboration that aims to systematically and rigorously assess a variety of models currently used (or that could readily be adapted) to simulate basin-scale runoff to the North American Laurentian Great Lakes.

Predicting the oscillating bi-directional exchange flow in the Straits of Mackinac

The Straits of Mackinac are a unique feature that connects Lake Michigan and Lake Huron into a single hydraulically linked system. With currents of up to 1m/s and oscillating volumetric transport up to 80,000m3/s, they play an important role in water quality, contaminant transport, navigation, and ecological processes. We present the first three-dimensional hydrodynamic model of the combined Lake Michigan–Huron, including the Straits of Mackinac at high-resolution, that is able to simulate the three dimensional structure of the oscillating flows at the Straits. In comparison with individual lake models for Michigan and Huron (no connection at the Straits), we are able to isolate the effects of the bi-lake oscillation and have found that although the oscillation (Helmholtz mode) is the dominant forcing mechanism, the flow can be modulated when atmospheric systems are in-phase with water level fluctuations. Furthermore, the area of influence of the Straits is found to extend up to 70km into each lake, underscoring the need for realistic predictions within the Straits. For the first time, this combined-lake hydrodynamic model provides the capability to investigate and accurately predict flow at the Straits of Mackinac and its effect on Lake Michigan and Huron. This model forms the basis for the next generation of real-time hydrodynamic models being developed for the Great Lakes Coastal Forecasting System, a suite of models designed by the National Oceanic and Atmospheric Administration Great Lakes Environmental Research Laboratory (NOAA/GLERL) that predict hydrodynamic conditions such as currents, temperatures, and water levels in three dimensions.

An appraisal of the Great Lakes advanced hydrologic prediction system

Great Lakes water level forecasts are used to inform decisions ranging from personal choices of recreational activities to corporate evaluations of alternative cargo transport options. For effective decision-making it is important that these model-based forecasts include an accurate expression of the forecast uncertainty, as well as information regarding the model forecasting skill. We provide an assessment of water level forecasts from 1997 through 2009 that were made using the National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) Advanced Hydrologic Prediction System (AHPS). A visual comparison between observed and forecast water levels suggests that AHPS generally captures seasonal and inter-annual patterns. A more quantitative assessment based on the percentage of observations within 90% prediction intervals, however, indicates that AHPS generally underestimates the observed variability of Great Lakes water levels. This assessment provides a benchmark for forecast performance against which alternative model structures (including future evolutions of AHPS) can be tested, and a basis to identify and prioritize the implementation of those alternatives. Including a calibrated model error term into the AHPS framework, to accommodate the underestimated variability, is a priority for short-term development and research, and represents one step toward more accurately quantifying forecast uncertainty. Our results also underscore the importance of storing historical forecasts and the data from which they were derived to serve as a basis for assessing model performance and prioritizing future model improvements.

Development, implementation, and skill assessment of the NOAA/NOS Great Lakes Operational Forecast System

The NOAA Great Lakes Operational Forecast System (GLOFS) uses near-real-time atmospheric observations and numerical weather prediction forecast guidance to produce three-dimensional forecasts of water temperature and currents, and two-dimensional forecasts of water levels of the Great Lakes. This system, originally called the Great Lakes forecasting system (GLFS), was developed at The Ohio State University and NOAA’s Great Lakes Environmental Research Laboratory (GLERL) in 1989. In 1996, a workstation version of the GLFS was ported to GLERL to generate semi-operational nowcasts and forecasts daily. In 2004, GLFS went through rigorous skill assessment and was transitioned to the National Ocean Service (NOS) Center for Operational Oceanographic Products and Services (CO-OPS) in Silver Spring, MD. GLOFS has been making operational nowcasts and forecasts at CO-OPS since September 30, 2005. Hindcast, nowcast, and forecast evaluations using the NOS-developed skill assessment software tool indicated both surface water levels and temperature predictions passed the NOS specified criteria at a majority of the validation locations with relatively low root mean square error (4–8 cm for water levels and 0.5 to 1°C for surface water temperatures). The difficulty of accurately simulating seiches generated by storms (in particular in shallow lakes like Lake Erie) remains a major source of error in water level prediction and should be addressed in future improvements of the forecast system.

Phytoplankton community composition of Saginaw Bay, Lake Huron, during the zebra mussel ( Dreissena polymorpha) invasion: A multivariate analysis

The colonization of the zebra mussel ( Dreissena polymorpha) in Saginaw Bay dramatically altered the phytoplankton community composition resulting in exclusion of light sensitive species and dominance of species with oligotrophic preferences and light resistance. In 1990, the NOAA Great Lakes Environmental Research Laboratory initiated a 7-year survey program to monitor changes in the lower food web of Saginaw Bay, where zebra mussels became established in the fall of 1991. To investigate shifts in the phytoplankton community composition over the 7-year period from 1990 to 1996 we searched for clusters of similar composition using multivariate principal component analysis (PCA) on proportions of 22 taxonomic groupings of the total phytoplankton density (cells per milliliter). We then used an agglomerative hierarchical clustering analysis of the PCA scores. We identified five characteristic phytoplankton communities in configurations that allowed recognizing four distinct periods in Saginaw Bay linked to the zebra mussel invasion. Significant changes were indicative of increased water clarity and eutrophic conditions being replaced by more oligotrophic conditions as clusters dominated by light sensitive species, such as the cyanobacteria Oscillatoria redekii, became immediately rare and clusters dominated by diatoms such as Cyclotella spp. became common. Microcystis spp., a light tolerant cyanobacteria not grazed by zebra mussel, dominated assemblages after 1994. The shifts in phytoplankton composition confirm that zebra mussels effects on phytoplankton communities are mediated by both direct (filtration) and indirect (nutrient cycling) mechanisms and also suggests that increased light penetration is an important mechanism behind some changes.

The response of Great Lakes water levels to future climate scenarios with an emphasis on Lake Michigan-Huron

Future climate change and its impact on Lake Michigan is an important issue for water supply planning in Illinois. To estimate possible future levels of the Great Lakes due to climate change, the output of 565 model runs from 23 Global Climate Models were applied to a lake-level model developed by the Great Lakes Environmental Research Laboratory (GLERL). In this study, three future emission scenarios were considered: the B1, A1B, and A2 emission scenarios representing relatively low, moderate, and high emissions, respectively. The results showed that the A2 emission scenario yielded the largest changes in lake levels of the three emission scenarios. Of the three periods examined, lake levels in 2080–2094 exhibited the largest changes. The response of Lake Superior was the smallest of the Great Lakes, while lakes Michigan-Huron, Erie, and Ontario were similar in their response over time and between emission scenarios. For Lake Michigan-Huron, the median changes in lake levels at 2080–2094 were − 0.25, − 0.28, and − 0.41 m for the B1, A1B, and A2 emission scenarios, respectively. However, the range in lake levels was considerable. The wide range of results is due to the differences in emission scenarios and the uncertainty in the model simulations. Selecting model simulations based on their historical performance does little to reduce the uncertainty. The wide range of lake-level changes found here make it difficult to envision the level of impacts that change in future lake levels would cause.

Warmer and drier climates that make Lake Huron into a terminal lake

Paleo-hydrologists have adjusted for glacial isostatic uplift and compared the original elevations of paleo-water level indicators and basin outlets for Lake Huron, revealing that Huron lake levels fell tens of meters below its lowest possible outlet (becoming a terminal lake) about 7,900 14C years BP. This corresponds to when the upper Great Lakes stopped receiving glacial melt inflow and became dependent for water supply on precipitation alone, as at present. Since these researchers accounted for differential isostatic effects, they surmised that the upper Great Lakes were impacted by severe dry climate. To understand possible climate changes that led to the closure, the Great Lakes Environmental Research Laboratory applied their Advanced Hydrologic Prediction System to explore deviations from present climates that could force the upper Great Lakes to become terminal. GLERL modeled the steady-state water balance of the present upper Great Lakes with pre-development natural water flow conditions by employing lake outflow-depth rating curves (using estimated sill elevations) reasonable for a natural system and by using dynamic lake areas controlled by observed hypsometric relations for each lake. By using systematic shifts in precipitation and temperature relative to the present base climate, GLERL showed the temperature rises and precipitation drops required for a terminal lake; they may be less extreme if additional effects of past differences in wind speed and insolation are also considered.

Lake Erie hypoxia prompts Canada‐U.S. study

Because of its size and geometry, the central basin of Lake Erie, one of North America's Great Lakes, is subject to periods in the late summer when dissolved oxygen concentrations are low (hypoxia). An apparent increase in the occurrence of these eutrophic conditions and ‘dead zones’ in recent years has led to increased public concern. The International Field Years for Lake Erie (IFYLE) project of the Great Lakes Environmental Research Laboratory (GLERL, a U.S. National Oceanic and Atmospheric Administration (NOAA) laboratory), was established in 2005 in response to this increase.This project is investigating the causes and consequences of hypoxia in the lake. As part of the effort, scientists from the United States and Canada conducted an extensive field study in 2005 to gather more information on the duration and extent of the hypoxic zone and its effects on the biota in the lake. This article gives a brief history and description of the problem and presents initial results from the field study.

Warmer and Drier Climates that Make Terminal Great Lakes

A recent empirical model of glacial-isostatic uplift showed that the Huron and Michigan lake level fell tens of meters below the lowest possible outlet about 7,900 14C years BP when the upper Great Lakes became dependent for water supply on precipitation alone, as at present. The upper Great Lakes thus appear to have been impacted by severe dry climate that may have also affected the lower Great Lakes. While continuing paleoclimate studies are corroborating and quantifying this impacting climate and other evidence of terminal lakes, the Great Lakes Environmental Research Laboratory applied their Advanced Hydrologic Prediction System, modified to use dynamic lake areas, to explore the deviations from present temperatures and precipitation that would force the Great Lakes to become terminal (closed), i.e., for water levels to fall below outlet sills. We modeled the present lakes with pre-development natural outlet and water flow conditions, but considered the upper and lower Great Lakes separately with no river connection, as in the early Holocene basin configuration. By using systematic shifts in precipitation, temperature, and humidity relative to the present base climate, we identified candidate climates that result in terminal lakes. The lakes would close in the order: Erie, Superior, Michigan-Huron, and Ontario for increasingly drier and warmer climates. For a temperature rise of T°C and a precipitation drop of P% relative to the present base climate, conditions for complete lake closure range from 4.7 T + P > 51 for Erie to 3.5T + P > 71 for Ontario.

Watershed Surface and Subsurface Spatial Intraflows Model

We present new developments to the original, spatially lumped large basin runoff model (LBRM) of the National Oceanic and Atmospheric Administration’s Great Lakes Environmental Research Laboratory. In addition to making it a two-dimensional, spatially distributed model, we modify it to allow routing flows between adjacent cells upper soil zones, lower soil zones, and groundwater zones. We modify the LBRM continuity equations for these additional flows and add corresponding corrector terms to the original solution equations. We derive the flow network from elevation and hydrography and the LBRM automatically arranges cell computations. We apply the newly modified LBRM to the Kalamazoo River watershed in Michigan and to the Maumee River watershed in Ohio. The simulations show that the Kalamazoo River has dominant groundwater storage, allowing delayed and sustained hydrologic responses to rainfall whereas the Maumee River lacks any significant groundwater storage, allowing a fast flashy response to rainfall. These results are characteristic of the study watersheds, indicating that the addition of subsurface intraflows in the model has improved watershed representation.

Groundwater Plume Mapping in a Submerged Sinkhole in Lake Huron

A multidisciplinary exploratory project team from the Institute for Exploration, the Great Lakes Environmental Research Laboratory, Grand Valley State University, and the University of Michigan located and explored a submerged sinkhole in Lake Huron during September 2003. A CTD system and an ultra-short baseline (USBL) acoustic navigational tracking system integrated with an open frame remotely operated vehicle (ROV) provided high-resolution depth, temperature, and conductivity maps of the sinkhole and plume. Samples were also peristaltically pumped to the surface from a depth of 92 meters within and outside of the sinkhole plume. A 1-2 m thick cloudy layer with a strong hydrogen sulfide odor characterized the water mass close to the plume. Relative to ambient lake water, water samples collected within this layer were characterized by slightly higher (4-7.5 °C) temperatures, very high levels of chloride and conductivity (10-fold) as well as extremely high concentrations of organic matter (up to 400 mg C/L), sulfate, and phosphorus. Our observations demonstrated the occurrence of unique biogeochemical conditions at this submerged sinkhole environment.

Distributed-Parameter Large Basin Runoff Model. I: Model Development

We present a case study of modifying an existing macroscale rainfall-runoff model, the large basin runoff model (LBRM), developed at NOAA’s Great Lakes Environmental Research Laboratory, to the microscale in a two-dimensional representation. First, we review the LBRM and then describe changes in several process submodels, which were originally designed specifically for large areas. We also change the model structure so that we may use the LBRM on an individual cell at the microscale within a watershed. We then discuss spatial scaling of model parameters to enable an (initial) application to the microscale with parameters available from the macroscale. We then organize watershed cells and flow routing and conclude with notes on computer implementation. In the accompanying companion paper, we present details of the model calibration, application, and experimentation on the Kalamazoo River watershed.

A comparison of observed and modeled surface waves in southern Lake Michigan and the implications for models of sediment resuspension

Subsurface pressure sensors were used to make measurements of surface waves during 18 deployments in southern Lake Michigan between 1998 and 2000. Most of the observations were made during the unstratified period (November–May) in water depths between 10 and 55 m. The observations (as well as those obtained from the National Data Buoy Center (NDBC) buoy 45007, which is located in the middle of the southern basin of the lake) were compared to the results obtained from the Great Lakes Environmental Research Laboratory (GLERL)‐Donelan wave model implemented on a 2‐km grid. The results show that the wave model does a good job of calculating the wave heights, but consistently underestimates the wave periods. In over 80% of the cases the bottom stresses calculated from both the observations and the wave model results agree as to whether or not resuspension occurs, but over 70% of this agreement is for cases when resuspension does not occur; both stresses predict resuspension about 6% of the time. Since the bottom stresses calculated from the model results are usually lower than those calculated from the observations, resuspension estimates based on the wave model parameters are also lower than those calculated from the observed waves.

POTENTIAL EFFECTS OF CLIMATE CHANGE ON GROUND WATER IN LANSING, MICHIGAN1

ABSTRACT: Computer simulations involving general circulation models, a hydrologic modeling system, and a ground water flow model indicate potential impacts of selected climate change projections on ground water levels in the Lansing, Michigan, area. General circulation models developed by the Canadian Climate Centre and the Hadley Centre generated meteorology estimates for 1961 through 1990 (as a reference condition) and for the 20 years centered on 2030 (as a changed climate condition). Using these meteorology estimates, the Great Lakes Environmental Research Laboratory's hydrologic modeling system produced corresponding period streamflow simulations. Ground water recharge was estimated from the streamflow simulations and from variables derived from the general circulation models. The U.S. Geological Survey developed a numerical ground water flow model of the Saginaw and glacial aquifers in the Tri‐County region surrounding Lansing, Michigan. Model simulations, using the ground water recharge estimates, indicate changes in ground water levels. Within the Lansing area, simulated ground water levels in the Saginaw aquifer declined under the Canadian predictions and increased under the Hadley.