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Improving understanding of algal blooms using satellite monitoring

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Zia Bukhari
Senior Scientist at American Water

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  • Improving understanding of algal blooms using satellite monitoring

Algal blooms are a common problem in numerous water bodies across the United States, especially during summer months. These blooms cause unsightly scum in water, which can present various challenges for the community (i.e., colour, odours, etc.). For water providers blooms can present many drinking water treatment challenges, including difficulty in the removal of taste and odour compounds. This can lead to increased treatment and infrastructure costs and in some cases possible disruption of water supply.

Additionally, blooms can cause human and animal health concerns. Numerous algal species are known to produce many groups of toxins. Some examples of toxins include: hepatotoxins, neurotoxins, cytotoxins, dermatotoxins, etc. In freshwater cyanobacteria often produce these toxins (known as cyanotoxins). Common cyanotoxins include: microcystin, cylindrospermopsin, anatoxin, guanitoxin (previously anatoxin-a), saxitoxin, nodularin, lyngbyatoxins. Some toxins have many variants (e.g., microcystin has >200 variants), which makes monitoring and understanding the risks posed by harmful algal blooms (HABs) complicated.

Presently algal bloom monitoring is time-consuming, cumbersome and often requires confirmation with laboratory-based methods, which can be slow and require advanced analytical expertise. Typically, laboratory-based methods employ several different platforms (e.g., enzyme linked immunosorbent assays, liquid chromatography/tandem mass spectrometry (LC-MS/MS), quantitative polymerase chain reaction). Unfortunately, these tests have various limitations (i.e., lack specificity, sensitivity, are slow, or require highly equipped laboratories with advanced technical expertise, etc.), which often makes it difficult for utilities to identify algal bloom problems in a timely manner.

New monitoring tools are needed that can reliably and cost-effectively provide spatial-temporal resolution to serve as an Early Warning System

Considering the combination of potential target analytes (i.e., toxins) and the large surface areas of watersheds that often require coverage, most utilities find it difficult, expensive and time-consuming to conduct detailed monitoring. Water providers need rapid yet specific algal detection methods to help improve their responsiveness (i.e., planning, treatment, and risk mitigation) to bloom events. New monitoring tools are needed that can reliably and cost-effectively provide spatial-temporal resolution to serve as an Early Warning System.

Hyperspectral imagery is an attractive advanced imaging option that employs a wide spectrum (i.e., hundreds of relatively narrow spectral bands, including short wave infrared and visible and near infrared) to generate unique image signatures. Differentiation of targets in various applications (i.e., military, archaeology, forensics), including medicine (i.e., cancerous tissues) and the environment (i.e., oil spills in water, plastic refuse on land/oceans, tree disease/mortality rates) has been achieved successfully. In a recently funded Water Research Foundation Tailored Collaboration program (Project WRF 5266), American Water will partner with Element 84, Hazen and Sawyer and Resolve Hydro LLC to examine the use of hyper- and multi-spectral imaging data from satellites in conjunction with advanced data analytics, based on artificial intelligence, for early identification of algal bloom events. The hyperspectral imaging information will be benchmarked against other image acquisition sources (i.e., small aircrafts/drones, microscopy), conventional and advanced chemical/microbial analyses, including whole genome sequencing. Relationships with in situ measurements, algal proxy (or indicator) measurements (e.g., chlorophyll-a, phycocyanin), a suite of taste and odour compounds and specific algal toxins will also be explored. This benchmarking study will be the first of its kind and is expected to provide a road map for proactive monitoring of algal blooms in the future. In addition to providing rapid monitoring tools, the findings of this research will help water providers by providing them with tools to develop holistic algal bloom management strategies.

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