A band-ratio algorithm for retrieving open-lake chlorophyll values from satellite observations of the Great Lakes

The U.S. Environmental Protection Agency's Great Lakes National Program Office (GLNPO) has collected water quality data from the five Great Lakes annually since 1993. We used the GLNPO observations made since 2002 along with coincident measurements made by the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) and the Moderate-resolution Imaging Spectroradiometer (MODIS) to develop a new band-ratio algorithm for estimating chlorophyll concentrations in the Great Lakes from satellite observations. The new algorithm is based on a third-order polynomial model using the same maximum band ratios employed in the standard NASA algorithms (OC4 for SeaWiFS and OC3M for MODIS). The sensor-specific coefficients for the new algorithm were obtained by fitting the relationship to several hundred matched field and satellite observations. Although there are some seasonal variations in some lakes, the relationship between the observed chlorophyll values and those modeled using the new coefficients is fairly stable from lake to lake and across years. The accuracy of the satellite chlorophyll estimates derived from the new algorithm was improved substantially relative both to the standard NASA retrievals and to previously published algorithms tuned to individual lakes. Monte-Carlo fits to randomly selected subsets of the observations allowed us to estimate the uncertainty associated with the retrievals purely as a function of the satellite data. Our results provide, for the first time, a single simple band ratio method for retrieving chlorophyll concentrations in the offshore “open” waters of the Great Lakes from satellite observations.     

An algorithm to retrieve chlorophyll,dissolved organic carbon,and suspended minerals from Great Lakes satellite data

An algorithm that utilizes individual lake hydro-optical (HO) models has been developed for the Great Lakes that uses SeaWiFS, MODIS, or MERIS satellite data to estimate concentrations of chlorophyll, dissolved organic carbon, and suspended minerals. The Color Producing Agent Algorithm (CPA-A) uses a specific HO model for each lake. The HO models provide absorption functions for the Color Producing Agents (CPAs) (chlorophyll (chl), colored dissolved organic matter (as dissolved organic carbon, doc), and suspended minerals (sm)) as well as backscatter for the chlorophyll, and suspended mineral parameters. These models were generated using simultaneous optical data collected with in situ measurements of CPAs collected during research cruises in the Great Lakes using regression analysis as well as using specific absorption and backscatter coefficients at specific chl, doc, and sm concentrations. A single average HO model for the Great Lakes was found to generate insufficiently accurate concentrations for Lakes Michigan, Erie, Superior and Huron. These new individual lake retrievals were evaluated with respect to EPA in situ field observations, as well as compared to the widely used OC3 MODIS retrieval. The new algorithm retrievals provided slightly more accurate chl values for Lakes Michigan, Superior, Huron, and Ontario than those obtained using the OC3 approach as well as providing additional concentration information on doc and sm. The CPA-A chl retrieval for Lake Erie is quite robust, producing reliable chl values in the reported EPA concentration ranges. Atmospheric correction approaches were also evaluated in this study.     

A model for determining satellite-derived primary productivity estimates for Lake Michigan

A new MODIS based satellite algorithm to estimate primary production (PP) has been generated and evaluated for Lake Michigan. The Great Lakes Primary Productivity Model (GLPPM) is based on previous models that required extensive in situ data but it can utilize remotely sensed observations as input for some model variables and therefore allows greater spatial resolution for primary productivity estimates. The Color Producing Agent Algorithm (CPA-A) is utilized to obtain robust chlorophyll a values and the NASA KD2M approach is used to obtain the diffuse attenuation coefficient (K_d). Only incident PAR and carbon fixation rates are additionally needed to generate the primary productivity estimate. Comparisons of the satellite derived PP estimates from single monthly images to average monthly field measurements made by NOAA/GLERL found good agreement between estimates. Satellite derived PP estimates were used to estimate a preliminary Lake Michigan annual primary production of 8.5 Tg C/year. The new algorithm can be easily adapted to work on all the Great Lakes and therefore can be used to generate time series dating back to late 1997 (launch of SeaWiFs). These time series can contribute to improved assessment of Great Lakes primary productivity changes as a result of biological events, such as Dreissenid mussel invasions, climatic change and anthropogenic forcing.     

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, K_d 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.     

Effects of Thermocline Displacement Upon Subsurface Chlorophyll Maxima in Lake Michigan

Thermocline displacements from equilibrium were significantly correlated to changes in the depth position of a subsurface chlorophyll maxima at a nearshore station in Lake Michigan. These observations emphasize the large physically induced spatial and temporal variability of this concentrated phytoplankton biomass in the nearshore areas of the Great Lakes.     

A comparison of chlorophyll a values obtained from an autonomous underwater vehicle to satellite-based measures for Lake Michigan

Accurate methods to track changes in lake productivity through time and space are critical to fisheries management. Chlorophyll a is the most widely studied proxy for ecosystem primary production and has been the topic of many studies. The main sources of chlorophyll a measurements are ship-based measures or multi-spectral satellite data. Autonomous underwater vehicles can survey large spatial extents approaching the scale of satellite data, but with the accuracy of ship-based water sampling methods. We use several statistical measures to compare measures of chlorophyll a collected in Lake Michigan with spatiotemporally matched satellite-derived measures of chlorophyll a from the MODIS Aqua multi-spectral sensor using NASA's OC3 and the Great Lakes Fit algorithms. Our findings show a near one to one relationship between AUV data and both satellite-derived data sets when the AUV data are coarsened to the resolution of the satellite data. A comparison of satellite-based chlorophyll a to AUV-derived chlorophyll summarized in discrete water depth bins suggested that, based on decreasing coefficients of determination, satellite estimates of chlorophyll accounted for the most variability in chlorophyll a concentrations in the upper 10 m of the water column, even though satellite sensors may detect past this depth.     

Using satellite observations to assess the spatial representativeness of the GLNPO water quality monitoring program

The U.S. EPA's Great Lakes National Program Office (GLNPO) annual water quality survey (WQS) collects data at a relatively small number of stations in each lake. The survey was designed to measure conditions in the open-water regions of the lakes where an assumption of spatial homogeneity was thought likely to be met and the measured variables could be characterized by simple statistics. Here we use satellite observations to assess how well statistics based on samples collected in the GLNPO sampling network represent the lake-wide values of two variables, surface chlorophyll concentration and Secchi depth. We find strong linear relationships between the mean values calculated from the samples and the corresponding averages based on the subsets of the full satellite images. Although overall the means of the values from the sample locations agree well with means calculated from most of the non-coastal regions of the lakes, in terms of water depth, the GLNPO station averages best represent the regions of Lake Huron deeper than 30?m, of Lakes Michigan and Superior deeper than 90?m, and of Lake Ontario deeper than 60?m. When the lake regions are defined by distance offshore rather than by depth, the GLNPO station chlorophyll means in Lakes Huron, Ontario, and Superior are closest to the means for the area of the lakes >10?km offshore. In Lake Michigan the closest correspondence is with the >20?km offshore region. On a whole-lake basis in Lake Erie the GLNPO station chlorophyll averages are closest to the average calculated from the entire lake.     

Verification and Application of a Bio-optical Algorithm for Lake Michigan Using SeaWiFS: a 7-year Inter-annual Analysis

In this paper we utilize 7 years of SeaWiFS satellite data to obtain seasonal and interannual time histories of the major water color-producing agents (CPAs), phytoplankton chlorophyll (chl), dissolved organic carbon (doc), and suspended minerals (sm) for Lake Michigan. We first present validation of the Great Lakes specific algorithm followed by correlations of the CPAs with coincident environmental observations. Special attention is paid to the satellite observations of the extensive episodic event of sediment resuspension and calcium carbonate precipitation out of the water. We then compare the obtained time history of the CPA's spatial and temporal distributions throughout the lake to environmental observations such as air and water temperature, wind speed and direction, significant wave height, atmospheric precipitation, river runoff, and cloud and lake ice cover. Variability of the onset, duration, and spatial extent of both episodic events and seasonal phenomena are documented from the SeaWiFS time series data, and high correlations with relevant environmental driving factors are established. The relationships between the CPAs retrieved from satellite data and environmental observations are then used to speculate on the future of Lake Michigan under a set of climate change scenarios.     

Spatial and temporal scales of variability of cyanobacteria harmful algal blooms from NOAA GLERL airborne hyperspectral imagery

NOAA GLERL has routinely flown a hyperspectral imager to detect cyanobacteria harmful algal blooms (cyanoHABs) over the Great Lakes since 2015. Three consecutive years of hyperspectral imagery over the Great Lakes warn drinking water intake managers of the presence of cyanoHABs. Western basin imagery of Lake Erie contributes to a weekly report to the Ohio Environmental Protection Agency using the cyanobacteria index (CI) as an indicator of the presence of cyanoHABs. The CI is also used for the weekly NOAA NCCOS cyanoHAB Lake Erie bulletin applied to satellite data. To date, there has not been a sensor comparison to look at the variability between the satellite and hyperspectral imagery on a pixel-by-pixel basis, as well as a time scale comparison between measurements from buoys and shipboard surveys. The spatial scale is a measure of size of a cyanobacteria bloom on a scale of meters to kilometers. The change in the spatial scale or spatial variability has been quantified from satellite and airborne imagery using a decorrelation scale analysis to find the point at which the values are not changing or are not correlated with each other. The decorrelation scales were also applied to the buoy and shipboard survey data to look at temporal scales or changes in time on hourly to daytime scales for blue-green algae, chlorophyll and temperature. These scales are valuable for ecosystem modelers and for those initiating sampling efforts to optimize sampling plans and to infer a potential mechanism in an observational study from a synoptic viewpoint.     

Variations in chromophoric dissolved organic matter and its influence on the use of pigment-specific fluorimeters in the Great Lakes

The variability of colored material (yellow substances, chromophoric dissolved organic matter [CDOM]) in Great Lakes water on the operation of a submersible pigment-based fluorimeter (FluoroProbe) was assessed. The FluoroProbe is designed to account for the influence of ambient CDOM on fluorimetric analysis of natural waters by using background yellow substance content to correct for fluorescence that is not due to phytoplankton. The objective of this study was to assess FluoroProbe performance as well as determine the variability of CDOM that has a bearing on instrument use. This study focused on Lakes Ontario and Huron in spring and summer and employed up to three FluoroProbes for simultaneous comparisons of performance, as assessed by comparing in situ versus extracted concentrations of chlorophyll-a. Conclusions from this study are: FluoroProbes are not equally accurate; yellow substance correction factors obtained by FluoroProbes are instrument specific; there are seasonal differences in yellow substance correction factors between summer and spring and among thermal strata in summer, in Lakes Huron and Ontario.The observed differences among yellow substance correction factors are attributed to chromophoric material that was assessed independently by measuring CDOM using a separate fluorimetric technique and by measuring in situ UV absorption coefficients. These results suggest that the use of FluoroProbes and related instruments for phytoplankton surveillance and monitoring initiatives must account for differences in ambient CDOM.     

Retrieval of ice/water observations from synthetic aperture radar imagery for use in lake ice data assimilation

High-resolution lake ice/water observations retrieved from satellite imagery through efficient, automated methods can provide critical information to lake ice forecasting systems. Synthetic aperture radar (SAR) data is well-suited to this purpose due to its high spatial resolution (approximately 50 m). With recent increases in the volume of SAR data available, the development of automated retrieval methods for these data is a priority for operational centres. However, automated retrieval of ice/water data from SAR imagery is difficult, due to ambiguity in ice and open water signatures, both in terms of image tone and in terms of parameterized texture features extracted from these images. Convolutional neural networks (CNNs) can learn features from imagery in an automated manner, and have been found effective in previous studies on sea ice concentration estimation from SAR. In this study the use of CNNs to retrieve ice/water observations from dual-polarized SAR imagery of two of the Laurentian Great Lakes, Lake Erie and Lake Ontario, is investigated. For data assimilation, it is crucial that the retrieved observations are of high quality. To this end, quality control measures based on the uncertainty of the CNN output to eliminate incorrect retrievals are discussed and demonstrated. The quality control measures are found to be effective in both dual-polarized and single-polarized retrievals. The ability of the CNN to downscale the coarse resolution training labels is demonstrated qualitatively.     

Building a research network to better understand climate governance in the Great Lakes

Climate-driven disturbances threaten the sustainability of coastal communities in the Great Lakes Basin. Because such disturbances are unpredictable, their magnitude, number and intensity are changing, and they occur at varying temporal and spatial scales. Consequently, communities struggle to respond in effective ways. The expected intensification of climate-driven disturbances will require that community capacity and governance structures match the spatial and temporal scales of these disturbances, as the most sustainable social and economic systems will be those that can respond at similar frequencies to key natural system drivers. The Climate Governance Variability in the Great Lakes Research Coordination Network (CGVG-RCN) was recently established to address questions about the relationship between climate-driven disturbances and community response. The objective of this short communication is to introduce the ideas behind the CGVG-RCN, outline its goals, and facilitate engagements and collaboration with social and natural scientists interested in social-ecological systems in the Great Lakes Basin.     

The benthic community of the Laurentian Great Lakes: Analysis of spatial gradients and temporal trends from 1998 to 2014

We used the results of seventeen years of Great Lakes benthic monitoring conducted by the U.S. EPA's Great Lakes National Program Office to describe the spatial and temporal patterns of benthic communities, assess their status, trends, and main drivers, and to infer the potential impact of these community changes on ecosystem functioning. Benthic abundance and diversity were higher at shallow (<70?m in depth) stations with chlorophyll concentrations above 3?μg/L than at deeper sites (<1?μg/L). We infer that lake productivity, measured by chlorophyll was likely the major driver of benthic abundance and diversity across lakes. Consequently, benthic diversity and abundance were the highest in the most productive Lake Erie, followed by lakes Ontario, Michigan, Huron, and Superior. Multivariate analysis distinguished three major communities shared among lakes (littoral, sublittoral, and profundal) that differed in species composition and abundance, functional group diversity, and tolerance to organic pollution. Analysis of temporal trends revealed that the largest changes occurred in profundal communities, apparent in significant shifts in dominant taxa across all lakes except Lake Superior. In lakes Michigan, Huron, and Ontario, the former dominant Diporeia was replaced with Dreissena and Oligochaeta. Profundal species, with the exception of dreissenids, became less abundant, and their depth distribution has shifted. In contrast, density and diversity of native littoral and sublittoral communities increased. The invasion of dreissenids was among the most important drivers of changes in benthic communities. Continued monitoring is critical for tracking unprecedented changes occurring in the Great Lakes ecosystem.     

Great Lakes coastal fish habitat classification and assessment

Basin-scale assessment of fish habitat in Great Lakes coastal ecosystems would increase our ability to prioritize fish habitat management and restoration actions. As a first step in this direction, we identified key habitat factors associated with highest probability of occurrence for several societally and ecologically important coastal fish species as well as community metrics, using data from the Great Lakes Aquatic Habitat Framework (GLAHF), Great Lakes Environmental Indicators (GLEI) and Coastal Wetland Monitoring Program (CWMP). Secondly, we assessed whether species-specific habitat was threatened by watershed-level anthropogenic stressors. In the southern Great Lakes, key habitat factors for determining presence/absence of several species of coastal fish were chlorophyll concentrations, turbidity, and wave height, whereas in the northern ecoprovince temperature was the major habitat driver for most of the species modeled. Habitat factors best explaining fish richness and diversity were bottom slope and chlorophyll a. These models could likely be further improved with addition of high-resolution submerged macrophyte complexity data which are currently unavailable at the basin-wide scale. Proportion of invasive species was correlated primarily with increasing maximum observed inorganic turbidity and chlorophyll a. We also demonstrate that preferred habitat for several coastal species and high-diversity areas overlap with areas of high watershed stress. Great Lakes coastal wetland fish are a large contributor to ecosystem services as well as commercial and recreational fishery harvest, and scalable basin-wide habitat models developed in this study may be useful for informing management actions targeting specific species or overall coastal fish biodiversity.     

Predicted Atrazine Concentrations in the Great Lakes: Implications for Biological Effects

Atrazine is an herbicide used extensively throughout the Midwest corn belt, including the agricultural regions within the Great Lakes basin watershed. Measurements of atrazine concentrations in the Great Lakes are few, however, so knowledge of its current concentrations, persistence, and trends in this ecosystem is limited. A dynamic annual time step model was used to predict atrazine concentrations over time in the Great Lakes based on varied atrazine loading rates to the lakes (“most-likely” and “high” loading conditions). Four degradation scenarios were evaluated: no degradation, and atrazine degradation with half-lives of 2 years, 5 years, and 10 years. Predicted steady-state concentrations for all of the scenarios and all the Great Lakes ranged from 0.0024 to 0.88 μg/L. The number of years until steady-state conditions were achieved ranged from 4 to over 400 years. The most-likely loading rate and two-year half-life scenario had the lowest concentrations (0.0024 to 0.13 μg/L) and the fewest years (4 to 13 years) to achieve steady-state conditions. Available monitored atrazine concentrations in the Great Lakes are very similar to the most-likely loading rate and 2-year half-life scenario predicted values. Monitored and predicted concentrations in the Great Lakes indicate atrazine does not currently pose a toxicological risk to humans or aquatic organisms, and under current and expected lower loading rates should remain well below criteria values.     

Historical changes and current status of crayfish diversity and distribution in the Laurentian Great Lakes

Despite increasing recognition of the importance of invertebrates, and specifically crayfish, to nearshore food webs in the Laurentian Great Lakes, past and present ecological studies in the Great Lakes have predominantly focused on fishes. Using data from many sources, we provide a summary of crayfish diversity and distribution throughout the Great Lakes from 1882 to 2008 for 1456 locations where crayfish have been surveyed. Sampling effort was greatest in Lake Michigan, followed by lakes Huron, Erie, Superior, and Ontario. A total of 13 crayfish species occur in the lakes, with Lake Erie having the greatest diversity (n = 11) and Lake Superior having the least (n = 5). Five crayfish species are non-native to one or more lakes. Because Orconectes rusticus was the most widely distributed non-native species and is associated with known negative impacts, we assessed its spread throughout the Great Lakes. Although O. rusticus has been found for over 100 years in Lake Erie, its spread there has been relatively slow compared to that in lakes Michigan and Huron, where it has spread most rapidly since the 1990s and 2000, respectively. O. rusticus has been found in both lakes Superior and Ontario for 22 and 37 years, respectively, and has expanded little in either lake. Our broad spatial and temporal assessment of crayfish diversity and distribution provides a baseline for future nearshore ecological studies, and for future management efforts to restore native crayfish and limit non-native introductions and their impact on food web interactions.     

Wind Fields over the Great Lakes Measured by the SeaWinds Scatterometer on the QuikSCAT Satellite

This paper demonstrates the utility of satellite scatterometer measurements for wind retrieval over the Great Lakes on a daily basis. We use data acquired by the SeaWinds Scatterometer on the QuikSCAT (QSCAT) satellite launched in June 1999 to derive wind speeds and directions over the lakes at a resolution of 12.5 km, which is two times finer than the QSCAT standard ocean wind product at a resolution of 25 km. To evaluate QSCAT performance for high-resolution measurements of lake wind vectors, we compare QSCAT results with Great Lakes Coastal Forecasting System (GLCFS) nowcast wind fields and with standard QSCAT measurements of ocean wind vectors. Although the satellite results over the Great Lakes are obtained with an ocean model function, QSCAT and GLCFS wind fields compare well together for low to moderate wind conditions (4–32 knots). For wind speed, the analysis shows a correlation coefficient of 0.71, a bias of 2.6 knots in mean wind speed difference (nowcast wind is lower) with a root-mean-square (rms) deviation of 3.8 knots. For wind direction, the correlation coefficient is 0.94 with a very small value of 1.3° in mean wind direction bias and an rms deviation of 38° for all wind conditions. When excluding the low wind range of 4–12 knots, the rms deviation in wind direction reduces to 22°. Considering QSCAT requirements designed for ocean wind measurements and actual evaluations of QSCAT performance over ocean, results for high-resolution lake wind vectors indicate that QSCAT performs well over the Great Lakes. Moreover, we show that wind fields derived from satellite scatterometer data before, during, and after a large storm in October 1999, with winds stronger than 50 knots, can monitor the storm development over large scales. The satellite results for storm monitoring are consistent with GLCFS nowcast winds and lake buoy measurements. A geophysical model function can be developed specifically for the Great Lakes using long-term data from satellite scatterometers, to derive more accurate wind fields for operational applications as well as scientific studies.     

Early observations on an emerging Great Lakes invader Hemimysis anomala in Lake Ontario

Hemimysis anomala, a Ponto-Caspian littoral mysid, is an emerging Great Lakes invader that was discovered in Lakes Michigan and Ontario in 2006. Similar to the native mysid Mysis diluviana, Hemimysis exhibits a diel vertical migration pattern but generally inhabits shallower and warmer waters than M. diluviana. Because basic information on the distribution, habitat use, and biology of Hemimysis in the Great Lakes is scarce, the potential for food web disruption by Hemimysis cannot easily be predicted. Preliminary observations indicate widespread invasion of Hemimysis in Lake Ontario. In this study, we confirm the presence of Hemimysis at sites spanning the northern and southern shores of Lake Ontario and the presence of the individuals during winter months. In one horizontal tow in November 2007, over 26,000 individuals were collected with a length range of 4.4 to 9.0 mm and an average caloric density of 611 cal/g wet weight. The most effective methods for sampling Hemimysis were horizontal tows with either a zooplankton net in the water column or a benthic sled near the lake bottom. Although more quantitative data on the life history and distribution of this species is necessary, our preliminary observations support the prediction that the potential for Hemimysis to impact the nearshore food web in Lake Ontario appears high.     

Underestimation of microzooplankton is a macro problem: One size fits all zooplankton sampling needs alterations

Microzooplankton (rotifers, copepod nauplii, and dreissenid veligers) are an important but overlooked part of zooplankton communities and aquatic food webs, particularly in the Great Lakes. Most studies that do include microzooplankton data are not describing the full picture due to inappropriate sampling methodology. We compared the traditional macrozooplankton sampling method (64-μm mesh plankton net) to a microzooplankton method using a 20-μm mesh screen in various habitats in Lake Michigan. The macrozooplankton method significantly underestimated total rotifer density by an order of magnitude, veliger density by nearly an order of magnitude, and copepod nauplii density by threefold. Combining macrozooplankton method estimates for cladocerans and copepods with estimates of rotifer, nauplii, and veligers from the microzooplankton method samples showed rotifers contributed 51% of total mean zooplankton biomass, refuting the past notion that rotifers contribute little to overall zooplankton biomass. Our study demonstrates that the traditional one-size fits all sampling approach used in the majority of zooplankton monitoring studies in the Great Lakes significantly underestimates microzooplankton abundance and its relative importance. Biassed information on Great Lakes zooplankton community composition has ramifications beyond a basic understanding of Great Lakes food webs. The lack of accurate data on microzooplankton abundance suggests that prey resources available to Asian carp in Lake Michigan have been greatly underestimated along with the likelihood these invasive species could become established. The dual sampling approach must become the norm rather than the exception for zooplankton research in the Great Lakes and other freshwater systems.     

Great Lakes total phosphorus revisited: 1. Loading analysis and update (1994–2008)

Phosphorus load estimates have been updated for all of the Great Lakes with an emphasis on lakes Superior, Michigan, Huron and Ontario for 1994–2008. Lake Erie phosphorus loads have been kept current with previous work and for completeness are reported here. A combination of modeling and data analysis is employed to evaluate whether target loads established by the Great Lakes Water Quality Agreement (GLWQA, 1978, Annex 3) have been and are currently being met. Data from federal, state, and provincial agencies were assembled and processed to yield annual estimates for all lakes and sources. A mass-balance model was used to check the consistency of loads and to estimate interlake transport. The analysis suggests that the GLWQA target loads have been consistently met for the main bodies of lakes Superior, Michigan and Huron. However, exceedances still persist for Saginaw Bay. For lakes Erie and Ontario, loadings are currently estimated to be at or just under the target (with some notable exceptions). Because interannual variability is high, the target loads have not been met consistently for the lower Great Lakes. The analysis also indicates that, because of decreasing TP concentrations in the lakes, interlake transport of TP has declined significantly since the mid-1970s. Thus, it is important that these changes be included in future assessments of compliance with TP load targets. Finally, detailed tables of the yearly (1994–2008) estimates are provided, as well as annual summaries by lake tributary basin (in Supplementary Information).