Blog | Cyanobacteria Monitoring Collaborative

Sensor-based detection of algal blooms for public health advisories and long-term monitoring | Max Rome

Sensor-based detection of algal blooms for public health advisories and long-term monitoring – an online presentation given on March 23, 2021 by Max Rome from Northeastern University.

Presentation as PDF

2021 Mini-Conference Webpage

2021 Mini-Conference Videos

Max Rome on LinkedIn

Read the research paper

Ed Beighley Research Group


Throughout the United States, many eutrophic freshwater bodies experience seasonal blooms of toxic cyanobacteria. These blooms limit recreational uses and pose a threat to both human and ecological health. Traditional bi-weekly chlorophyll-based sampling programs designed to assess overall algal biomass fail to capture important bloom parameters such as bloom timing, duration, and peak intensity. In-situ optical and fluorometric measurements have the potential to fill this gap. However, relating in-situ measurements to relevant water quality measures (e.g. cyanobacterial cell density or chlorophyll concentration) is a challenge that often limits the implementation of probe-based monitoring strategies. This study, of Aphanizomenon dominated blooms in Boston’s Charles River, combines five years of cyanobacterial cell counts with high resolution in-situ sensor measurements to relate turbidity and fluorometric readings to cyanobacterial cell density. Our work compares probe and lab-based estimates of summer-mean chlorophyll concentration and highlights the challenges of working with raw fluorescence in cyanobacteria dominated waterbodies. A strong correlation between turbidity and cyanobacterial cell density (R2 = 0.84) is used to construct a simple cell-density-estimation-model suitable for triggering rapid bloom-response-sampling and classifying bloom events with a true positive rate of 95%. The approach described in this study is potentially applicable to many cyanobacteria dominated freshwater bodies.