Probabilistic forecast of microcystin toxin using satellite remote sensing, in situ observations and numerical modeling. (June 2020)

• Record Type: Journal Article
• Authors: Liu, Qianqian; Rowe, Mark D.; Anderson, Eric J.; Stow, Craig A.; Stumpf, Richard P.; Johengen, Thomas H.
• Is Part Of: Environmental modelling & software. Volume 128(2020)
• Publication Date: 2020-06
• Subjects: Lake Erie -- Cyanobacterial harmful algal bloom -- Microcystin -- Short term forecast -- Probabilistic forecast; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2020.104705
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Lake Erie has experienced a resurgence of cyanobacterial harmful algal blooms (CHABs) since the early 2000's dominated by Microcystis aeruginosa, which produce toxins known as microcystins. We develop an approach to predict the spatially- and temporally-resolved probability of exceeding a public health advisory (PHA) level (6 μg/L) of microcystins in the western basin of Lake Erie that would be suitable for use in a forecast system, consisting of 1) an existing HAB chlorophyll forecast system, 2) a toxin-chlorophyll-a relationship that is updated weekly from observations, and 3) a statistical model relating observed relative frequency of exceeding the PHA to model predictions over a hindcast period. We evaluate the system's performance and the system's useful level of skill. This novel approach to a CHAB toxin forecast system could provide a decision support tool to Lake Erie stakeholders, and the approach may be adapted to other systems. Highlights: We predict toxin concentrations associated with cyanobacterial harmful algal blooms. Our forecast system uses satellite data, in situ observations and numerical models. The system predicts microcystins' spatial distribution in Lake Erie's western basin. Uncertainties in the system are properly conveyed through a probabilistic forecast. This novel approach to toxin forecast has a potentially useful level of skill.