The increased frequency of harmful algal blooms (HABs) is a major environmental concern worldwide, resulting not only in increased treatment costs for drinking water but also in impacts on tourism, commercial fishing and aquaculture and risks to human and animal health. Traditional strategies with ship-based approaches based on field sampling and laboratory analysis have been adopted to assess HABs. However, these methods are labour intensive and costly and do not provide synoptic views of the bloom conditions. Here, we show that the Sentinel-2 twin satellite mission of the Copernicus programme, in combination with in situ data, is a powerful tool that can offer valuable spatiotemporal information about a bloom of the dinoflagellate Lingulodinium polyedra that occurred on the SW Iberian Peninsula. Using the robust ACOLITE atmospheric correction processor combined with the normalized difference chlorophyll index (NDCI), the enhanced mapping of small blooms can be performed at a 10 m spatial resolution, revealing surface patches and a heterogeneous distribution. This research also demonstrates the improved capabilities of Sentinel-2 compared to those of Landsat-8 and Sentinel-3 for continuous monitoring. The Sentinel-3 and Sentinel-2 missions provide ecosystem observations that allow the environmental community and water managers to evaluate changes in water quality and bloom distribution and that facilitate field-based measurements. Therefore, the value added by the Copernicus products in terms of frequency and synoptic observations is of paramount importance for ecological and management purposes at regional and national scales.

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New capabilities of Sentinel-2A/B satellites combined with in situ data for monitoring small harmful algal blooms in complex coastal waters

https://www.srs.fs.usda.gov/pubs/ja/2020/ja_2020_hallema_001.pdf

Wildfire impacts on hydrologic ecosystem services in North American high-latitude forests: A scoping review

Water-quality monitoring for small urban waterbodies by remote sensing gets to be difficult due to the coarse spatial resolution of remote-sensing imagery. The recently launched Sentinel-2 produces...

A machine learning-based strategy for estimating non-optically active water quality parameters using Sentinel-2 imagery

In recent decades, the increasing frequency and severity of cyanobacterial blooms in recreational lakes and water supply reservoirs have become a great concern to public health and a significant threat to the environment. Cyanobacterial bloom monitoring is the basis of early warning and treatment. Previous research efforts have always focused on monitoring blooms in a few specific lakes in China using moderate resolution imaging spectroradiometer (MODIS) images, which are available for the years 2000 onward. However, the lack of overall information on long-term cyanobacterial blooms in the lakes and reservoirs in the middle–lower Yangtze River (MLYR) basin is an obstacle to better understanding the dynamics of cyanobacterial blooms at a watershed scale. In this study, we extracted the yearly coverage area and frequency of cyanobacterial blooms that occurred from 1990 to 2016 in 30 large lakes and 10 reservoirs (inundation area >50 km2) by using time series Landsat satellite images from Google Earth Engine (GEE). Then, we calculated the cyanobacterial bloom area percentage (CAP) and the cyanobacterial bloom frequency index (CFI) and analyzed their inter-annual variation and trends. We also investigated the main driving forces of changes in the CAP and CFI in each lake and reservoir. We found that all reservoirs and more than 60% of lakes exhibited an increasing frequency and coverage area of cyanobacterial blooms under the pressures of climate change and anthropogenic interferences. Reservoirs were more prone to be affected by fertilizer consumption from their regional surroundings than lakes. High temperatures increased blooms of cyanobacteria, while precipitation in the lake and reservoir regions somewhat alleviated blooms. This study completes the data records of cyanobacterial blooms in large lakes and reservoirs located in hotspots of the MLYR basin and provides more baseline information before 2000, which will present references for water resource management and freshwater conservation.

Increasing Outbreak of Cyanobacterial Blooms in Large Lakes and Reservoirs under Pressures from Climate Change and Anthropogenic Interferences in the Middle–Lower Yangtze River Basin

External interaction:The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will include a hyperspectral imaging radiometer to advance ecosystem monitoring beyond heritage retrievals of the concentration of surface chlorophyll and other traditional ocean color variables, offering potential for novel science and applications. PACE is the first NASA ocean color mission to occur under the agency's new and evolving effort to directly engage practical end users prior to satellite launch to increase adoption of this freely available data toward societal challenges. Here we describe early efforts to engage a community of practice around marine food-related resource management, business decisions, and policy analysis. Obviously one satellite cannot meet diverse end user needs at all scales and locations, but understanding downstream needs helps in the assessment of information gaps and planning how to optimize the unique strengths of PACE data in combination with the strengths of other satellite retrievals, in situ measurements, and models. Higher spectral resolution data from PACE can be fused with information from satellites with higher spatial or temporal resolution, plus other information, to enable identification and tracking of new marine biological indicators to guide sustainable management. Accounting for the needs of applied researchers as well as non-traditional users of satellite data early in the PACE mission process will ultimately serve to broaden the base of informed users and facilitate faster adoption of the most advanced science and technology toward the challenge of mitigating food insecurity.

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Developing a community of practice for applied uses of future PACE data to address marine food security challenges

In this study, we demonstrated that the Landsat-8 Operational Land Imager (OLI) sensor is a powerful tool that can provide periodic and system-wide information on the condition of drinking water reservoirs. The OLI is a multispectral radiometer (30 m spatial resolution) that allows ecosystem observations at spatial and temporal scales that allow the environmental community and water managers another means to monitor changes in water quality not feasible with field-based monitoring. Using the provisional Land Surface Reflectance (LSR) product and field-collected chlorophyll-a (chl-a) concentrations from drinking water monitoring programs in North Carolina and Rhode Island, we compared five established approaches for estimating chl-a concentrations using spectral data. We found that using the 3 band reflectance approach with a combination of OLI spectral bands 1, 3, and 5, produced the most promising results for accurately estimating chl-a concentrations in lakes (R2 value of 0.66; RMSE value of 8.9 μg l-1). Using this model, we forecast the spatial and temporal variability of chl-a for Jordan Lake, a recreational and drinking water source in piedmont North Carolina and several small ponds that supply drinking water in southeastern Rhode Island.

/pdf/monitoring-algal-blooms-in-drinking-water-reservoirs-using-2qy4i3im2l.pdf

Jason Green

Papers

Monitoring Algal Blooms in drinking water reservoirs using the Landsat 8 Operational Land Imager.