Predicting Harmful Algal Blooms through New Technologies

By Ben Holcomb

Harmful algal blooms have been in the news a lot lately, from the massive scums lining the Florida coast to the blue-green mats that covered Utah Lake and forced its closure. Predicting when these blooms will occur is one of the greatest challenges we face at the Division of Water Quality (DWQ). Currently, we can’t even predict the correct month.

The United States Geological Service (USGS) and DWQ are hoping to change that.

USGS field crews will be on the Great Salt Lake and Utah Lake this week to test-drive a full suite of real-time monitoring equipment. DWQ is in the process of installing a network of high-frequency water quality sensors in Utah Lake and other high-risk waterbodies. Both of these efforts will help improve our ability to track the water quality conditions that lead to cyanobacteria growth and hopefully help us predict and respond more quickly to bloom events.

Cyanobacteria: source of harmful algal blooms

Cyanobacteria are simple, single-celled critters, but their ability to adapt to a variety of water conditions make them overly successful when offered a plentiful, nutrient-rich food supply. They photosynthesize like algae, which is why they are often called blue-green algae. But they are actually bacteria, the only bacteria that use chlorophyll-a to collect sunlight to produce energy. They also contain a pigment called phycocyanin that helps them absorb light more efficiently and gives them their characteristic blue-green color.

Summer and fall are the prime growing season for cyanobacteria. Heat speeds up photosynthesis, and nutrients like nitrogen and phosphorus fuel the growth. Cyanobacteria are particularly well-equipped to float and sink in the water to maximize their ability to convert sunlight into energy. Some species can even “fix” nitrogen by taking it out of the air. So when sunlight and heat levels are high, nutrients are abundant, and waters are calm, cyanobacteria populations can explode into massive blooms that can produce toxins harmful to people, animals, and aquatic life. The presence of cyanobacteria or cyanotoxins in waterbodies can create public-health concerns and economic impacts that can have far-reaching consequences, a lesson we learned during the recent Utah Lake bloom.

Although cyanotoxins represent a clear risk to human health, the apparent absence of toxins in sample results doesn’t guarantee that a bloom won’t have negative health effects. For example, during the recent events in Utah Lake, cyanotoxins were generally low or not detected, and high concentrations were only detected in a couple of samples. Nevertheless, hundreds of people reported symptoms consistent with cyanobacteria or cyanotoxin exposure, such as gastrointestinal distress, headaches, and skin irritation following exposure to the bloom in Utah Lake. It is unclear whether these effects may have resulted from currently unknown toxins, known toxins that went undetected during sampling, or possibly due to exposure to cyanobacteria themselves, but clearly this issue can negatively impact recreational uses.

Current challenges

Traditional, often costly, monitoring methods collect water samples at monthly or weekly intervals, but they don’t always reveal the subtle changes in water chemistry that can precipitate an algal bloom. The rapid changes in water conditions that fuel cyanobacteria growth aren’t always apparent from periodic sampling. In addition, sampling at discrete locations on larger waterbodies may not provide an accurate assessment of overall water conditions. Knowing when, where, and how to collect samples and identifying the relative importance of a host of complicating physical, chemical, and biological factors would help DWQ scientists predict and assess blooms with greater precision and timeliness.

Real-time data-gathering

The USGS pilot project will utilize real-time monitoring strategies that could serve as an early-warning system for water-quality managers. Real-time data would also help scientists develop models and assessment tools to predict blooms and identify areas for more intensive sampling. Advances in the capabilities of in-situ (in-water) sensors to take frequent (e.g., every 15 minutes) measurements of nitrate and dissolved organic matter (DOM) — “food” that stimulates cyanobacteria growth — hold great promise for characterizing the chemical variations in waterbodies like the Great Salt Lake and Utah Lake.

What kinds of monitoring systems will the USGS be using? Well, they will be deploying sondes (water probes) to collect real-time data and creating hyperspectral images and high-resolution spatial maps from the data collected to paint a more accurate picture of the distribution of cyanobacteria and nutrients in the water.

USGS will use fluorometer (light-measuring) sensors to measure the fluorescence produced by certain cyanobacteria indicators:

• Chlorophyll-a: a pigment concentration that is a representative measure of the amount of algae (both green and blue-green) in the water
• Phycocyanin: a pigment concentrations that is a better representation of the amount of cyanobacteria biomass (cell concentration)
• Dissolved organic matter (DOM): composition of DOM can be used to characterize cyanobacteria growth potential in the water and help identify total organic carbon concentrations, another fundamental building block for cyanobacteria growth

These fluorescence measurements help scientists detect, monitor, and evaluate cyanobacteria concentrations in waterbodies.

Sound complicated? It is! But the outcome is a relatively simple snapshot map of water chemistry throughout a waterbody.

Unique lake ecosystems, unique opportunities

Scientists need improved monitoring and data collection methodologies to understand how high nutrient levels in the Great Salt Lake and Utah Lake contribute to harmful algal blooms.

Here are some of the data the USGS plans to collect this week, and methods of analysis they will use to interpret the data:

• Multi-day, continuous records of the temperature, pH, and oxidation-reduction potential (a relative measure of decomposition)
• Multi-day, continuous records of turbidity (murkiness), dissolved organic matter, chlorophyll-a, phycocyanin, and nitrate to estimate nutrient loadings
• Hourly images to evaluate chlorophyll-a and BGA-PC (blue-green algae-phycocyanin) concentrations
• Water samples to compare against the fluorescence measurements
• High-resolution spatial maps of the data to evaluate the spatial extent of the parameters measured
• Concurrent, high-resolution satellite imagery to compare remote observations with onsite spatial nitrate and algal data

Our experiences this summer with algal blooms across the state underscore the need to find and apply new data-collection methods for cyanobacteria. The kind of information collected through the USGS real-time monitoring, combined with DWQ’s deployment of several new, high-frequency sondes at high-risk waterbodies across the state, will not only help us predict algal blooms and be more timely in our response, it will help us develop site-specific standards that address the location, distribution, and load of the nutrient sources that lead to harmful algal blooms.

Want to learn more about harmful algal bloom (HABs)? Check out our HABs webpage. For more information about this summer’s algal blooms, visit our 2016 Algal Blooms webpage.

I am the Division of Water Quality coordinator for the biological assessment and harmful algal bloom programs. I’ve worked at DWQ for seven years and my past work includes salmon, water quality, and tribal sovereignty in the Pacific Northwest.