Harmful algal blooms and remote sensing
The Challenge
Outbreaks of cyanobacteria blooms (Harmful algal blooms – HABs) in aquatic systems pose a serious threat to public health, economy and biodiversity. They can produce toxins harmful to animals and humans and produce odour problems when decaying. Climate change and increased eutrophication have aggravated the problem showing an increase in occurrence of HABs worldwide. In the River Murray, five mega-blooms have occurred in the last 13 years, compared to four in the preceding 65 years, markedly reducing income for local businesses from tourism. Water treatment plants are also impacted by the occurrence of HABs as they can’t deliver safe drinking or irrigation water under specific conditions.
Algal bloom in a wetland after flooding. PHOTO: Tanya Doody
Our response
The assessment of the risk of HABs depends on our ability to describe their response to changes in their bio-physical environment over large spatial scales with high temporal resolution. Historically, the forecast of harmful algal blooms has been based on single – or multi-site observation of water quality parameters using at best, weekly sampling. Earth observation or remote sensing, allows us to observe large-scale development of such blooms by deriving HAB or other water quality indices from optical data measured by satellite, drones, or local installation of high spectral cameras, the latter of which is even capable of distinguishing between different species of cyanobacteria. Together with Melbourne Water, we have developed a HAB early warning system based on historical data and the installation of a hyperspectral camera on one of their large water treatment lagoons. This provides a warning of the risk of HABs based on the physical environment (temperature and wind) and allows us to monitor bloom development. For Lake Hume, we have implemented hydrodynamical models for the Murray-Darling Basin Authority with support by WaterNSW and Goulburn-Murray Water. These models can forecast water temperature and lake stratification in relation to meteorological conditions and inflow characteristics from river operation, allowing us to assess the risk of HABs. This is accompanied by satellite remote sensing imagery to verify the spatial spread of blooms. A HAB early warning and forecast system, driven by the physical conditions in lakes and reservoirs over a larger region and based on snapshots from remote sensing is in development.
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Our capability
CSIRO Land and Water together with CSIRO Oceans and Atmosphere, combine the necessary knowledge and technology to develop biogeochemical models for water bodies to simulate the spatial and temporal development of water quality parameters in inland freshwater systems, and combines this with water quality parameters derived from satellite imagery and ground observations with bio-optical measurements using our unique sensor technologies.
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Science and Innovation
The project integrates the newest technology in remote sensing of water quality with advanced modelling capabilities. It is an emerging field which is specifically developing algorithms of water quality parameters for complex inland water bodies. The hyperspectral camera we use is a novelty in the field, developed by CSIRO Oceans and Atmosphere and tested here under real conditions. Early warning systems for HABs are still rare (e.g. Great Lakes, specifically Lake Erie, NSW Algal Alert, Oceans and Atmosphere) and are not available for the simultaneous short-term forecast of HABs based on weather forecast.
A broad-scale spatial view of the River Murray floodplain near Mildura and Victoria. PHOTO: Tanya Doody
Results
Early warning from HAB will reduce economic costs related to health issues due to cyanotoxins in drinking and irrigation water. It will allow local tourism operators who depend in clean water, to react in a timely manner, when a bloom is forecast. HAB prediction models, also allow water manager to undertake risk assessments.