EOLakeWatch: Remote sensing of algal blooms

Many lakes across Canada have seen an increase in the occurrence of algal blooms. Algal blooms occur when phytoplankton (photosynthetic organisms including single-celled plants and cyanobacteria) grow rapidly because of changes to water conditions. Over-enrichment of lakes with nutrients such as Phosphorus and Nitrogen – a condition known as Eutrophication – can lead to excessive phytoplankton growth, and declining water quality. Additional factors such as water temperature, sunlight, and wind mixing play important roles in the onset, duration and severity of algal blooms.

Algal blooms can become a nuisance or potentially harmful. Some cyanobacteria can produce toxins that pose a risk to human and animal health. Decomposing blooms can lead to hypoxic (oxygen-deficient) conditions. Economic impacts of algal blooms can occur in the form of potential depletion of fishery stocks, losses to tourism/recreation, as well as additional requirements for monitoring and water treatment.

To better monitor algal blooms and further understand the processes driving their occurrence, ECCC scientists have developed satellite remote sensing methods to detect algal blooms from space. Through programs such as the Lake Winnipeg Basin Program, Lake of the Woods Science Plan, and Great Lakes Protection Initiative, these tools have been used to learn more about three particular lakes experiencing annual, often severe, algal blooms; Lake Erie, Lake Winnipeg, and Lake of the Woods.

True colour satellite image
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True colour satellite image from the European Space Agency’s Sentinel-2 Multispectral Instrument (MSI) capturing an intense algal bloom on Lake of the Woods on August 26 2016.

Remote sensing of inland water algal blooms is based on the measurement of water colour using camera-like optical sensors on board satellites. Phytoplankton (as well as other particles and dissolved materials in the water) cause changes in water colour by absorbing and scattering different wavelengths of light. Chlorophyll-a is the main pigment contained in phytoplankton that is used in photosynthesis. It is the concentration of chlorophyll-a that we derived from the remote sensing signal, as an indicator of the total amount of phytoplankton in the water. When present in sufficient quantities, phytoplankton can cause dramatic changes in water colour and form visible scums at the water’s surface. Although blooms can have a wide range of appearances, the pictures below show a typical transition from no-bloom conditions to severe blooms.

A continuum of lake colour
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A continuum of lake colour from no bloom (where the water can appear dark blue to light blue in colour) to severe bloom conditions (where the water appears green in colour).

Remote sensing allows us to capture frequent (several times a week) snapshots of algal bloom conditions across a lake in near-real-time (within a few hours of the satellite passing over), providing observations not possible using ground based sampling alone. Although the satellites provide near daily observations, factors such as cloud cover reduce the frequency of useable data. To reduce data gaps, we use a 14-day rolling average of daily images to obtain complete lake-wide coverage. Image processing algorithms allow us to derive maps of chlorophyll-a and quantitative algal bloom indices (i.e. bloom extent, intensity, duration and severity) to describe bloom conditions for each lake.

Workflow describing the derivation of algal bloom indices from optical satellite data

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Workflow describing the derivation of algal bloom indices from optical satellite data (using the European Space Agency’s MERIS and OLCI satellite sensors). Algorithms are applied to daily aquatic colour satellite data to derive maps of chlorophyll-a concentration. A 14-day average chlorophyll-a map is produced on a daily basis to obtain full-lake coverage to mitigate the effects of data loss from cloud cover and partial images. Algal bloom indices are extracted from the 14-day average imagery to describe bloom extent, intensity, severity, and duration.

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