Spatial and temporal variability of inherent and apparent optical properties in western Lake Erie: Implications for water quality remote sensing

Lake Erie has experienced dramatic changes in water quality over the past several decades requiring extensive monitoring to assess effectiveness of adaptive management strategies. Remote sensing offers a unique potential to provide synoptic monitoring at daily time scales complementing in-situ sampling activities occurring in Lake Erie. Bio-optical remote sensing algorithms require knowledge about the inherent optical properties (IOPs) of the water for parameterization to produce robust water quality products. This study reports new IOP and apparent optical property (AOP) datasets for western Lake Erie that encapsulate the May–October period for 2015 and 2016 at weekly sampling intervals. Previously reported IOP and AOP observations have been temporally limited and have not assessed statistical differences between IOPs over spatial and temporal gradients. The objective of this study is to assess trends in IOPs over variable spatial and temporal scales. Large spatio-temporal variability in IOPs was observed between 2015 and 2016 likely due to the difference in the extent and duration of mid-summer cyanobacteria blooms. Differences in the seasonal trends of the specific phytoplankton absorption coefficient between 2015 and 2016 suggest differing algal assemblages between the years. Other IOP variables, including chromophoric, dissolved organic matter (CDOM) and beam attenuation spectral slopes, suggest variability is influenced by river discharge and sediment re-suspension. The datasets presented in this study show how these IOPs and AOPs change over a season and between years, and are useful in advancing the applicability and robustness of remote sensing methods to retrieve water quality information in western Lake Erie

Satellite monitoring of harmful algal blooms in the Western Basin of Lake Erie: A 20-year time-series

Blooms of harmful cyanobacteria (cyanoHABs) have occurred on an annual basis in western Lake Erie for more than a decade. Previously, we developed and validated an algorithm to map the extent of the submerged and surface scum components of cyanoHABs using MODIS ocean-color satellite data. The algorithm maps submerged cyanoHABs by identifying high chlorophyll concentrations (\u3e18 mg/m3) combined with water temperature \u3e20 °C, while cyanoHABs surface scums are mapped using near-infrared reflectance values. Here, we adapted this algorithm for the SeaWiFS sensor to map the annual areal extents of cyanoHABs in the Western Basin of Lake Erie for the 20-year period from 1998 to 2017. The resulting classified maps were validated by comparison with historical in situ measurements, exhibiting good agreement (81% accuracy). Trends in the annual mean and maximum total submerged and surface scum extents demonstrated significant positive increases from 1998 to 2017. There was also an apparent 76% increase in year-to-year variability of mean annual extent between the 1998–2010 and 2011–2017 periods. The 1998–2017 time-series was also compared with several different river discharge nutrient loading metrics to assess the ability to predict annual cyanoHAB extents. The prediction models displayed significant relationships between spring discharge and cyanoHAB area; however, substantial variance remained unexplained due in part to the presence of very large blooms occurring in 2013 and 2015. This new multi-sensor time-series and associated statistics extend the current understanding of the extent, location, duration, and temporal patterns of cyanoHABs in western Lake Erie

Diverse manganese(II)‐oxidizing bacteria are prevalent in drinking water systems

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136363/1/emi412508_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136363/2/emi412508.pd

Spatial-temporal variability of in situ cyanobacteria vertical structure in Western Lake Erie: Implications for remote sensing observations

Remote sensing has provided expanded temporal and spatial range to the study of harmful algal blooms (cyanoHABs) in western Lake Erie, allowing for a greater understanding of bloom dynamics than is possible through in situ sampling. However, satellites are limited in their ability to specifically target cyanobacteria and can only observe the water within the first optical depth. This limits the ability of remote sensing to make conclusions about full water column cyanoHAB biomass if cyanobacteria are vertically stratified. FluoroProbe data were collected at nine stations across western Lake Erie in 2015 and 2016 and analyzed to characterize spatio-temporal variability in cyanobacteria vertical structure. Cyanobacteria were generally homogenously distributed during the growing season except under certain conditions. As water depth increased and high surface layer concentrations were observed, cyanobacteria were found to be more vertically stratified and the assumption of homogeneity was less supported. Cyanobacteria vertical distribution was related to wind speed and wave height, with increased stratification at low wind speeds (bathymetry and environmental conditions could lead to improved biomass estimates. Additionally, cyanobacteria contributions to total chlorophyll-a were shown to change throughout the season and across depth, suggesting the need for remote sensing algorithms to specifically identify cyanobacteria

Lake Erie hypoxia prompts Canada‐U.S. study

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95631/1/eost15589.pd

Chronicles of hypoxia: Time-series buoy observations reveal annually recurring seasonal basin-wide hypoxia in Muskegon Lake – A Great Lakes estuary

We chronicled the seasonally recurring hypolimnetic hypoxia in Muskegon Lake – a Great Lakes estuary over 3 years, and examined its causes and consequences. Muskegon Lake is a mesotrophic drowned river mouth that drains Michigan\u27s 2nd largest watershed into Lake Michigan. A buoy observatory tracked ecosystem changes in the Muskegon Lake Area of Concern (AOC), gathering vital time-series data on the lake\u27s water quality from early summer through late fall from 2011 to 2013 (www.gvsu.edu/buoy). Observatory-based measurements of dissolved oxygen (DO) tracked the gradual development, intensification and breakdown of hypoxia (mild hypoxia b4 mg DO/L, and severe hypoxia b2 mg DO/L) below the ~6 m thermocline in the lake, occurring in synchrony with changes in temperature and phytoplankton biomass in the water column during July–October. Time-series data suggest that proximal causes of the observed seasonal hypolimnetic DO dynamics are stratified summer water-column, reduced wind-driven mixing, longer summer residence time, episodic intrusions of cold DO-rich nearshore Lake Michigan water, nutrient run off from watershed, and phytoplankton blooms. Additional basin-wide water-column profiling (2011–2012) and ship-based seasonal surveys (2003–2013) confirmed that bottom water hypoxia is an annually recurring lake-wide condition. Volumetric hypolimnetic oxygen demand was high (0.07–0.15 mg DO/Liter/day) and comparable to other temperate eutrophic lakes. Over 3 years of intense monitoring, ~9–24% of Muskegon Lake\u27s volume experienced hypoxia for ~29–85 days/year – with the potential for hypolimnetic habitat degradation and sediment phosphorus release leading to further eutrophication. Thus, time-series observatories can provide penetrating insights into the inner workings of ecosystems and their external drivers

Summer thermal structure and anticyclonic circulation of Lake Erie

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95057/1/grl29007.pd