Integrating methods for the improved detection and tracking of harmful algal blooms in inland waters
- Overview: The frequency, intensity and geographic spread of harmful algal and cyanobacterial blooms (HABs) are increasing globally in inland waters in response to anthropogenic nutrient inputs and climate change. These blooms not only frequently result in impairment of water quality and ecosystem dysfunction, but because they are often dominated by toxin-producing species they also pose substantial risks to animal and human health (Carvalho et al. 2013; Hunter et al., 2010). There are approximately 117 million lakes and reservoirs on Earth and consequently only a very small proportion of these are routinely monitored for algal or cyanobacterial abundance. This not only limits our understanding of the regional and global distribution of HABs in inland waters and the complexity of their responses to environmental change but it also means that serious risks to animal and human health may go undetected by responsible agencies. Satellite observations can greatly extend our ability to detect HABs in lakes over regional and global scales and provide early warnings of risks to health (Palmer et al. 2015b). However, many lakes and reservoirs, particularly those in the UK, are too small to be reliably observed using ocean colour data at the typical 0.3-1km spatial resolutions provided by platforms such as the European Space Agency’s new Sentinel-3A satellite. Furthermore, in many regions frequent cloud cover can significantly limit the temporal frequency of usable observations from individual satellite missions. The project will address these challenges by making novel use of data from several high spatial resolution satellites now in orbit (e.g. Sentinel-2A, Landsat-8, WorldView-2/3) to complement observations from ocean colour sensors (e.g. MODIS Aqua/Terra, Sentinel-3A OLCI, VIIRS). This ‘virtual constellation’ of high-resolution satellites will permit the observation of many of the smaller water bodies that are not regularly sampled or observable from ocean colour satellites whilst also improving the temporal frequency of data for detection and tracking of HABs. Because blooms can readily form and disperse over a few days, this ‘virtual observatory’ alone will not necessarily provide data at the required temporally frequency to reliably capture short-lived HAB events. Thus the project will explore how we can use satellite observations synergistically in conjunction with data from standard in situ water quality monitoring programmes, instrumented buoys and citizen scientists (e.g. from the new UK Lakes portal) to improve the efficacy of current monitoring approaches. Project aims & objectives: The overarching aim of this project to demonstrate the feasibility of using a ‘virtual constellation’ of satellite sensors in combination with in situ data to improve our ability to detect and track HABs in lakes and reservoirs. Specific project objectives include: To develop algorithms for HABs recognition for satellite sensors with differing imaging capabilities; To rigorously validate phytoplankton abundance metrics derived from satellite observations using high quality in situ data; To cross-validate satellite observations of HAB dynamics in lakes using data from buoys and citizen science observatories.
- Methodology: The project will use of observations from ESA’s state of-the-art Copernicus Sentinel-2A/B MSI and Sentinel-3A/B OLCI sensors (freely available from the Copernicus Data Hub) along with data from other high spatial resolution platforms such as Landsat-8 OLI, WorldView-2/3, Pleiades and SPOT-6/7 (freely available for USGS/ESA) and, where possible, commercial missions such as WorldView-2/3 (available for academic use on application). The satellites that will comprise this virtual constellation provide data at very different spatial, spectral and radiometric resolutions and thus one of the key challenges for this project will be to develop novel approaches for accommodating differences in sensor capability. This will not only necessitate the development and validation of algorithms for the quantitative retrieval of algal and cyanobacteria biomass but also semi-quantitative optical metrics for HABs that can readily generalise across platforms. A detailed time-series analysis of HAB dynamics will be conducted for a number of lakes in the UK and internationally where satellite observations are complemented by the availability of high quality in situ data from existing monitoring programmes, instrumented buoys and/or citizen science observatories. This will be supported by regular field campaigns for the validation of ESA Sentinel-2 MSI and Sentinel-3 OLCI observations on small number of readily accessible UK lakes regularly subject to the occurrence of HABs. This validation work will involve the use of state-of the-art optical field instrumentation for measuring in- and abovewater optical properties in lakes. The data collected will evaluate the efficacy of different algorithms for HAB detection as well as establishing whether the temporal frequency of observations provided by a virtual constellation of satellites is sufficient to permit reliable detection and tracking of HABs in lakes in the UK and globally. More broadly, the results of this project will contribute to wider research on the development and validation of satellite data over inland waters through links with the NERC-funded GloboLakes project (http://www.globolakes.ac.uk) and the EC FP7-funded INFORM project (http://www.copernicus-inform.eu/) as well as our existing involvement as a member of ESA’s Sentinel-3 Validation Team (S3VT). Moreover, the direct involvement of SEPA will ensure the results of this project contribute to future efforts to improve strategies for the monitoring and risk management of cyanobacterial blooms in the UK.
- Carvalho, L. et al. (2013) 'Sustaining recreational quality of European lakes: minimizing the health risks from algal blooms through phosphorus control.' Journal of Applied Ecology, 50: 315-323.
- Palmer, S.C.J., Odermatt, D., Hunter, P.D., et al. (2015a) 'Satellite remote sensing of phytoplankton phenology in Lake Balaton using 10 years of MERIS observations' Remote Sensing of Environment, 158: 441-452.
- Palmer, S.C.J., Hunter, P.D., et al, (2015b) 'Validation of Envisat MERIS algorithms for chlorophyll retrieval in a large, turbid and optically-complex shallow lake,' Remote Sensing of Environment, 157: 158-169.
- Palmer, S.J.C. incl. Hunter, P.D. (2015c) 'Remote sensing of inland waters: challenges, progress and future directions,' Remote Sensing of Environment, 157: 1-8.
- Hunter, P.D., Tyler, A.N., Carvalho, L., et al., (2010) 'Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes,' Remote Sensing of Environment, 114 (11), pp. 2705-2718.