8 research outputs found
Remote sensing and bio-geo-optical properties of turbid, productive inland waters: a case study of Lake Balaton
Algal blooms plague freshwaters across the globe, as increased nutrient loads lead to eutrophication of inland waters and the presence of potentially harmful cyanobacteria. In this context, remote sensing is a valuable approach to monitor water quality over broad temporal and spatial scales. However, there remain several challenges to the accurate retrieval of water quality parameters, and the research in this thesis investigates these in an optically complex lake (Lake Balaton, Hungary). This study found that bulk and specific inherent optical properties [(S)IOPs] showed significant spatial variability over the trophic gradient in Lake Balaton. The relationships between (S)IOPs and biogeochemical parameters differed from those reported in ocean and coastal waters due to the high proportion of particulate inorganic matter (PIM). Furthermore, wind-driven resuspension of mineral sediments attributed a high proportion of total attenuation to particulate scattering and increased the mean refractive index (n̅p) of the particle assemblage. Phytoplankton pigment concentrations [chlorophyll-a (Chl-a) and phycocyanin (PC)] were also accurately retrieved from a times series of satellite data over Lake Balaton using semi-analytical algorithms. Conincident (S)IOP data allowed for investigation of the errors within these algorithms, indicating overestimation of phytoplankton absorption [aph(665)] and underestimation of the Chl-a specific absorption coefficient [a*ph(665)]. Finally, Chl-a concentrations were accurately retrieved in a multiscale remote sensing study using the Normalized Difference Chlorophyll Index (NDCI), indicating hyperspectral data is not necessary to retrieve accurate pigment concentrations but does capture the subtle heterogeneity of phytoplankton spatial distribution. The results of this thesis provide a positive outlook for the future of inland water remote sensing, particularly in light of contemporary satellite instruments with continued or improved radiometric, spectral, spatial and temporal coverage. Furthermore, the value of coincident (S)IOP data is highlighted and contributes towards the improvement of remote sensing pigment retrieval in optically complex waters
Extraction methods for phycocyanin determination in freshwater filamentous cyanobacteria and their application in a shallow lake
Phycocyanin (PC) is one of the water-soluble accessory pigments of cyanobacteria species, and its concentration in aquatic systems is used to estimate the presence and relative abundance of blue-green algae. PC concentration and the PC/Chl-a ratio of four N2-fixing filamentous cyanobacteria strains (Cylindrospermopsis raciborskii, Anabaena spiroides, Aphanizomenon flos-aquae and Aphanizomenon issatschenkoi) common to Lake Balaton (Hungary) were determined using repeated freezing and thawing. A strong linear correlation was found between the extracted PC and Chl-a concentrations for all strains at high Chl-a concentrations (almost stable PC/Chl-a ratio in the range of 20−100 µg l−1 Chl-a). Extraction of PC and Chl-a from samples with low biomass of cyanobacteria (less than 20 µg l−1 Chl-a) proved to be unreliable using the standard protocol of freeze–thaw cycles (coefficients of variation exceeding 10–15%). In order to find an extraction method that is robust in fresh waters characterized by low algae biomass (e.g. Lake Balaton), the effectiveness of four extraction methods (repeated freeze–thaw method and homogenization with mortar and pestle, Ultrasonic, and Polytron homogenizer) were compared using C. raciborskii. It was found that the efficiency of extraction of phycocyanin was highest when a single freeze–thaw cycle was followed by sonication (25% additional yield compared with using the freeze–thaw method alone). Applying this combined method to surface water samples of Lake Balaton, a strong correlation was found between PC concentration and cyanobacterial biomass (R 2 = 0.9436), whilst the repeated freezing–thawing method found no detectable PC content. Here we show that the combined sonication/freeze–thaw method could be suitable for measuring filamentous cyanobacteria PC content, even at low concentrations; as well as for the estimation of cyanobacterial contribution to total biomass in fresh waters
Optimal Cyanobacterial Pigment Retrieval from Ocean Colour Sensors in a Highly Turbid, Optically Complex Lake
To date, several algorithms for the retrieval of cyanobacterial phycocyanin (PC) from ocean colour sensors have been presented for inland waters, all of which claim to be robust models. To address this, we conducted a comprehensive comparison to identify the optimal algorithm for retrieval of PC concentrations in the highly optically complex waters of Lake Balaton (Hungary). MEdium Resolution Imaging Spectrometer (MERIS) top-of-atmosphere radiances were first atmospherically corrected using the Self-Contained Atmospheric Parameters Estimation for MERIS data v.B2 (SCAPE-M_B2). Overall, the Simis05 semi-analytical algorithm outperformed more complex inversion algorithms, providing accurate estimates of PC up to ±7 days from the time of satellite overpass during summer cyanobacteria blooms (RMSElog 0.66, p < 0.001). In-depth analysis of the Simis05 algorithm using in situ measurements of inherent optical properties (IOPs) revealed that the Simis05 model overestimated the phytoplankton absorption coefficient [aph(λ)] by a factor of ~2. However, these errors were compensated for by underestimation of the mass-specific chlorophyll absorption coefficient [a*chla(λ)]. This study reinforces the need for further validation of algorithms over a range of optical water types in the context of the recently launched Ocean Land Colour Instrument (OLCI) onboard Sentinel-3
Satellite-assisted monitoring of water quality to support the implementation of the Water Framework Directive
The EU Water Framework Directive1 (WFD) is an ambitious legislation framework to achieve good ecological and chemical status for all surface waters and good quantitative and chemical status for groundwater by 2027. A total of 111,062 surface waterbodies are presently reported on under the Directive, 46% of which are actively monitored for ecological status. Of these waterbodies 80% are rivers, 16% are lakes, and 4% are coastal and transitional waters. In the last assessment, 4% (4,442) of waterbodies still had unknown ecological status, while in 23% monitoring did not include in situ water sampling to support ecological status assessment2. For individual (mainly biological) assessment criteria the proportion of waterbodies without observation data is much larger; the full scope of monitoring under the WFD is therefore still far from being realised. At the same time, 60% of surface waters did not achieve ‘good’ status in the second river basin management plan and waterbodies in Europe are considered to be at high risk of having poor water quality based on combined microbial, physical and physicochemical indicators3
Moving towards global satellite based products for monitoring of inland and coastal waters. Regional examples from Europe and South America
Surface waters are a fundamental resource. They fulfil key function in global biogeochemical cycles and are core to our water, food and energy security. The rapidly increasing rate of data collection from different Earth observation (EO) missions suitable for observing water bodies has promoted satellite remote sensing (RS) as a more widely recognised source of information on a number of indicators of water quality and ecosystem condition at local and global scales. In parallel, advances in optical sensors support new and more detailed characterisation of the Earth surface and could lead to innovative EO-based products. Nonetheless, RS of water colour of inland and coastal systems, especially in larger scales and over long-term time series, faces unique challenges. This study provides an overview of the challenges and solutions of developing a global observation platform, including the diverse and complex optical properties of inland waters and guided algorithm selection procedure required to deliver reliable data. The development and validation of a global satellite data processing chain (Calimnos) has been supported by access to an extensive in situ data from more than thirty partners around the world that are now held in the LIMNADES community-owned database. This approach has resulted in a step-change in our ability to produce regional and global water quality products for optically complex waters. Local examples of the data outputs will be explored and the opportunities in how these data can be embedded within local and national monitoring schemes to facilitate better management of water will be discussed
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press