Barataria-Terrebonne National Estuary Program
Developing a harmful algal bloom threat index
Assessing the risk to marine organisms, human health and economic well-being of shellfish and fish industries in Barataria-Terrebonne Estuary
Expected completion January 2024
The Challenge
Harmful algal blooms (HABs) in estuarine waters are those phytoplankton species that can produce a wide range of deleterious impacts to aquatic ecosystems and the humans that rely on them. Many HAB species have been observed throughout Louisiana’s estuaries, including genera that can produce toxins of diatoms (Pseudo-nitzschia), dinoflagellates (Margalefidinium, Dinophysis, Lingulodinium), and cyanobacteria (Microcystis, Dolichospermum, Raphidiopsis), which can impact shellfish through mechanical damage and/or bloom formation that could lead to bottom-water hypoxia, if the water column becomes stratified.
An encouraging method for routinely monitoring algal blooms and for HAB detection in coastal and inland waters is to use both space-based platforms with high spatiotemporal resolution and in-situ sampling. Timely and accurate mapping of HAB distribution in coastal area is decisive in minimizing the damage and evaluating the environmental impacts of annual bloom events. Satellite-estimated Chl a in coastal, estuarine, and inland water environments are frequently inferred from spectral indices based on the red and near infrared (NIR) region of the reflectance spectra. In addition, some spectral indices have been commonly used for species or group level remote detection of HABs (e.g., dinoflagellate and cyanobacteria). However, given the optical complexity estuarine-coastal, and the empirical nature of the algorithm parameterizations, the need for regional tuning should be evaluated in waterbodies where they have not been previously applied, such as Barataria-Terrebonne Estuary in Louisiana. Therefore, there is a pressing need for effective and simple strategies to monitor the spatiotemporal variability of fine-scale algal blooms through remote sensing techniques to assist operational monitoring and emergency plans for aquatic systems.
The Approach
The use of spectral indices poses an advantage regarding implementation simplicity in monitoring strategies. In this BTNEP-funded project, we propose to 1) conduct regional tuning to retrieve Chl a concentration and other water quality parameters from Sentinel 3A/B-OLCI and Sentinel 2A/B-MSI using existing spectral indices based on extensive historical field observations obtained in Barataria-Terrebonne Estuary; 2) apply tuned regional algorithms to detect Chl a levels and calculate the probability of algal bloom based on a binary logistic regression approach; and 3) generate time-series product HAB threat index (1= low, 2= medium 3 = high) to assess the potential threat to marine organisms, human health, and economic well-being of shellfish and fish industries in Barataria-Terrebonne National Estuary.
Expected significance: The proposed HAB Possibility Index can be easily implemented in monitoring efforts and protocols, providing a cost-effective way to significantly increases the frequency and spatial extent of observations, which has great potential as easy-to-implement monitoring tool for policy makers, resource managers and local stakeholders.
KEY TEAM MEMBERS
