Document Type
Conference Paper/Presentation
Publication Date
11-2017
Abstract
Long time series of ocean and land color satellite data can be used to measure Laurentian Great Lakes water quality parameters including chlorophyll, suspended minerals, harmful algal blooms (HABs), photic zone and primary productivity on weekly, monthly and annual observational intervals. The observed changes in these water quality parameters over time are a direct result of the introduction of invasive species such as the Dreissena mussels as well as anthropogenic forcing and climate change. Time series of the above mentioned water quality parameters have been generated based on a range of satellite sensors, starting with Landsat in the 1970s and continuing to the present with MODIS and VIIRS. These time series have documented the effect the mussels have had on increased water clarity by decreasing the chlorophyll concentrations. Primary productivity has declined in the lakes due to the decrease in algae. The increased water clarity due to the mussels has also led to an increase in submerged aquatic vegetation. Comparing water quality metrics in Lake Superior to the lower lakes is insightful because Lake Superior is the largest and most northern of the five Great Lakes and to date has not been affected by the invasive mussels and can thus be considered a control. In contrast, Lake Erie, the most southern and shallow of the Laurentian Great Lakes, is heavily influenced by agricultural practices (i.e., nutrient runoff) and climate change, which directly influence the annual extent of HABs in the Western Basin of that lake.
Publication Title
37th International Symposium on Remote Sensing of Environment
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Shuchman, R. A.,
Bosse, K.,
Sayers, M. J.,
Fahnenstiel, G. L.,
&
Leshkevich, G.
(2017).
Satellite observed water quality changes in the Laurentian Great Lakes due to invasive species, anthropogenic forcing, and climate change.
37th International Symposium on Remote Sensing of Environment,
42(3).
http://doi.org/10.5194/isprs-archives-XLII-3-W2-189-2017
Retrieved from: https://digitalcommons.mtu.edu/mtri_p/247
Publisher's Statement
© Authors 2017. Article deposited here in compliance with publisher policies. Publisher's version of record: https://doi.org/10.5194/isprs-archives-XLII-3-W2-189-2017