Determining remote sensing spatial resolution requirements for the monitoring of harmful algal blooms in the Great Lakes

Harmful algal blooms (HABs) have become a major health and environmental concern in the Great Lakes. In 2014, severe HABs prompted the State of Ohio to request NASA Glenn Research Center (GRC) to assist with monitoring algal blooms in Lake Erie. The most notable species of HAB is Microcystis aeruginosa, a hepatotoxin producing cyanobacteria that is responsible for liver complications for humans and other fauna that come in contact with these blooms. NASA GRC conducts semiweekly flights in order to gather up-to-date imagery regarding the blooms' spatial extents and concentrations. Airborne hyperspectral imagery is collected using two hyperspectral imagers, HSI-2 and HSI-3. Hyperspectral imagery is necessary in order to conduct experiments on differentiation of algal bloom types based on their spectral reflectance. In this analysis, imagery from September 19, 2016 was utilized to study the subpixel variability within the footprint of arbitrary sized pixels using several analysis techniques. This particular data set is utilized because it represents a worst case scenario where there is significant potential for public health concern due to high concentrations of microcystin toxin found in the water on this day and the concurrent observational challenges to accurately measure the algal bloom concentration variability with a remote sensing system due to the blooms high spatial variability. It has been determined that the optimal spatial resolution to monitor algal blooms in the Great Lakes is at most 50 m, and for much lower error 25 m, thus allowing for greater ease in identifying high concentration blooms near the surface. This resolution provides the best sensitivity to high concentration areas that are of significant importance in regard to human health and ecological damage.     

基于SMDPSO算法的呼伦湖藻华遥感监测

水体富营养化所引起的藻华爆发现象是我国面临的重大环境问题之一。以内蒙古呼伦湖为研究区,采用基于离散粒子群优化的光谱匹配（SMDPSO）算法提取藻华,以浮游藻类指数（FAI）的分类结果作为验证数据进行精度检验。然后分析2009-2018年藻华的时空变化特征,并将此算法应用于黄海。结果表明：SMDPSO算法可以有效地识别呼伦湖藻华,与FAI分类结果之间的R²为0.97,RMSE为0.22 km²;呼伦湖藻华爆发于7-8月,且主要出现在湖泊边缘;SMDPSO算法既可以较好地识别以蓝藻为优势门的呼伦湖藻华,也可以提取黄海的浒苔（绿藻）;SMDPSO算法不仅保留了光谱指数法精度高的特点,而且它还具有成本低、参数少、无需人工干预的优势。该研究为藻华遥感监测提供了新的工具,有助于控制湖泊水体富营养化和改善水生态环境。     

Status,causes and controls of cyanobacterial blooms in Lake Erie

The Laurentian Great Lakes are among the most prominent sources of fresh water in the world. Lake Erie's infamous cyanobacterial blooms have, however, threatened the health of this valuable freshwater resource for decades. Toxic blooms dominated by the cyanobacterium Microcystis aeruginosa have most recently been one of primary ecological concerns for the lake. These toxic blooms impact the availability of potable water, as well as public health and revenues from the tourism and fishery industries. The socioeconomic effects of these blooms have spurred research efforts to pinpoint factors that drive bloom events. Despite decades of research and mitigation efforts, these blooms have expanded both in size and duration in recent years. However, through continued joint efforts between the Canadian and United States governments, scientists, and environmental managers, identification of the factors that drive bloom events is within reach. This review provides a summary of historical and contemporary research efforts in the realm of Lake Erie's harmful cyanobacterial blooms, both in terms of experimental and management achievements and insufficiencies, as well as future directions on the horizon for the lake's research community.     

太湖蓝藻监测及暴发情况分析

为了及时掌握太湖蓝藻发生和暴发状况,为保障流域供水安全和太湖富营养化治理提供必要的基础信息,以1996-2008年太湖各湖区藻类监测资料为基础,结合蓝藻历史变化状况,对太湖13 a的藻类群落组成、优势种的构成、数量和季节变化,以及蓝藻暴发情况进行分析,并对太湖9个湖区分区进行蓝藻暴发特征分析,探讨治理蓝藻水华的措施.结...     

Simulation of harmful algal blooms using a deterministic Lagrangian particle separation-based method

Algal blooms (red tide) are often observed in Hong Kong's coastal waters. These algal blooms can cause discoloration of the marine water, and may result in severe dissolved oxygen depletion and fish kills; most harmful algal blooms (HAB) are caused by diatoms and dinoflagellates. Diatoms are non-motile algae relying on water turbulence for suspension and nutrient supply. Dinoflagellates, on the other hand, can undergo diel vertical migration. At night, the algal cells swim down the water column to uptake nutrient and store it as internal nutrient reserve (cell quota). During daytime, they ascend to the water surface to carry out photosynthesis using the nutrient reserve. Diel vertical migration is an important adaptive strategy of dinoflagellates to form blooms in stratified waters.In this paper, the vertical migration behaviour of dinoflagellates is modelled using a simple deterministic Lagrangian model based on a NEighbourhood Separation Technique (NEST). The method is based on relative diffusion concepts, and simulates the diffusion process via an equivalent macroscopic motion; it uses far less number of particles than that required in random walk methods. The Lagrangian cell quota based algal dynamics is incorporated in a one-dimensional model to predict the vertical structure of water quality. Dinoflagellates are represented by a number of particles, with algal growth dependent on its nutrient reserve and the available light intensity. Swimming behaviour is simulated by the corresponding advective translocation of the particle. The model is applied to study species competition, resulting in a simple bloom prediction criterion based on nutrient availability and vertical diffusivity. In addition, the changes in water quality during an observed dinoflagellate bloom in Hong Kong coastal waters are well supported by field data; the role of stratification and diel vertical migration on the bloom formation and the signature of dissolved oxygen are discussed.     

Spatial and temporal variations in algal blooms in the coastal waters of the western South China Sea

Algal blooms occur frequently in the coastal waters of the western South China Sea (SCS). This paper reports spatial and temporal variations of algal bloom events in these waters from 1993 to 2007. Twenty-five algal bloom events occurred in summer in the coastal waters of South and Central Vietnam where they were associated with wind-induced, coastal, nutrient upwelling and river discharges; a further eight events occurred in the coastal waters of North Vietnam. A greater number of algal bloom events were observed in 1999 and 2002, and were accompanied by several previously unobserved species for the study period. These events may be related to the El Niño events of 1998 and 2002. Furthermore, the bloom-causative species Trichodesmium erythraeum (Cyanophyta) entirely dominated the phytoplankton community of algal blooms during 1993–1999 whereas the species Phaeocystis globosa (Haptophyta) dominated blooms after 2002. This study establishes a basis for further long-term research of algal bloom event variations, and provides a compiled scientific reference that may be used for later prediction of Harmful algal blooms (HABs).     

The MERIS Maximum Chlorophyll Index; its merits and limitations for inland water algal bloom monitoring

Satellite remote sensing methods adopting wavelengths in the red and near infra-red have been shown to be superior to the standard blue to green ratio based approaches in the detection of algal blooms under turbid, eutrophic conditions. Here, the MERIS Maximum Chlorophyll Index (MCI) has been explored as a tool for monitoring algal blooms in North America's inland waters where waters range from optically complex, turbid, eutrophic conditions, to low chlorophyll and oligotrophic conditions. Assessment of the MERIS MCI product is made for intense blooms of cyanobacteria in Lake of the Woods, algal blooms in turbid waters of Lake Erie, and low chlorophyll conditions in Lake Ontario. The MCI product is shown to be a versatile tool in monitoring intense surficial algal blooms with chlorophyll concentrations in the 10–300 mg m^? 3 range, while limited in its application to low-biomass conditions as observed in Lake Ontario. Wavelength shifts in the position of the MCI peak for different chlorophyll concentration ranges, as well as variations in the inherent optical properties of water colouring constituents, are anticipated to account for regional variations in MCI–chlorophyll relationships and potentially hinder a universally applicable quantitative MCI product.     

Future increase in harmful algal blooms in the North Sea due to climate change.

In temperate seas such as the North Sea harmful (toxic) algal blooms will probably increase as a result of climate change. This conclusion was reached after investigating the projected effect of climate change for the year 2100 in Dutch coastal waters (4 degrees C temperature rise and increased water column stratification) on the growth rates of six harmful and two non-harmful phytoplankton species. Micro algae form the basis of the marine food chain. However, toxin-producing species may seriously disrupt the food web and lead to fish kills and human intoxication. Two species with estimated doubled growth rates in 2100, F. japonica and C. antiqua, entered Europe via ship's ballast water or shellfish imports. This stresses the need to legally regulate such invasion routes in order to prevent the import of novel species. Future toxic phytoplankton blooms may further devaluate ecosystem deliverables such as fish production or recreational use. This devaluation can be estimated by monetary value assessments that are needed in cost-benefit analyses for policy guidance. The lack of understanding of future climate, ecosystem functioning and its response to climate change calls for a scientific effort to improve our knowledge on present day coastal ecosystem functioning and its resilience.     

河道型水库富营养化及水华调控方法和关键技术

本文提出了河道型水库富营养化及水华调控的系统研究方法,重点探讨了水利水电工程影响下的河道型水库富营养化及水华监测、模拟及调控方法及关键技术,包括流域水环境监测评估与水华预警系列技术,大型水库多维、多场耦合富营养化模拟系统,以及改善河道型水库支流库湾水温层化进而抑制水华暴发的调控方法等,以期为抑制河道型水库支流库湾水华暴发、改善水库水质提供参考和依据。     

三峡水库支流水华机理及其调控技术研究进展

三峡水库自2003年蓄水以来,水库干支流水环境状况及支流水华问题已成为广泛关注的问题,国内外不少科研单位及学者对此进行了大量的研究。本文在介绍三峡水库蓄水以来水库水质状态及支流水华情势的基础上,系统总结了关于三峡水库干支流水动力特征及其环境效应、水华机理及其调控措施的研究发现,并提出了有待进一步研究的内容。主要研究发现包括:(1)三峡水库蓄水后支流库湾普遍存在分层异重流现象,产生的原因是干支流温度差及泥沙浓度差引起的水体密度差,其中水体温度差是主要因素;(2)在分层异重流的驱动下,支流库湾水体呈现"双混斜"及"半U"型特殊水体分层模式,支流库湾营养盐也主要来自于水库干流倒灌;(3)流速变缓只是支流暴发水华的表观原因,分层异重流驱动下的混合层(Zm)与临界层(ZCr)的关系变化才是决定水华生消的关键;(4)水库水位升降可通过影响分层异重流的形态、改变支流水体分层状态进而调控支流水华的生消过程,基于此提出了防控支流水华的"潮汐式"生态调度方法。如何将上述新发现上升为具有三峡水库特色的系统理论与方法,实现支流水华的精准预测预报,开展能够协调水库传统效益和防控支流水华等生态效益的三峡及上游梯级水库群联合多目标优化调度实践,应是今后进一步努力的方向。     

Algal bloom transport in Lake Erie using remote sensing and hydrodynamic modelling: Sensitivity to buoyancy velocity and initial vertical distribution

In this study, we simulate three-dimensional transport of algal blooms in Lake Erie using a combination of remote sensing and hydrodynamic modelling. The remote sensing algorithms use data from the Sentinel-3 OLCI satellite sensor to derive chlorophyll-a concentration from cyanobacteria blooms in Lake Erie. The derived chlorophyll-a concentration initializes an algal bloom transport model driven by the lake component of the Water Cycle Prediction System for the Great Lakes, a system of coupled atmosphere-lake-hydrological models operated out of Environment and Climate Change Canada. The bloom is modelled as Microcystis aeruginosa, a buoyant species that is often dominant in harmful algal blooms in western Lake Erie. Short-term (a few days) predictions of algal bloom transport from July 27 to October 8, 2017 are modelled in both Eulerian and Lagrangian frameworks. The Eulerian framework is used to evaluate the sensitivity of model results to the initial vertical distribution of the bloom. In this work, the Lagrangian framework is limited to two-dimensional surface confined particles. We use several error metrics to evaluate model predictions. We find that results are sensitive to the buoyancy velocity for cases where the bloom was initially distributed over a large portion of the water column. An initial vertical distribution selected from modelled chlorophyll-a half depth shows the highest accuracy for the entire range of buoyancy velocities tested. We also find that the Pierce skill score is difficult to interpret, particularly in cases where bloom intensity is greatly overpredicted by the model.     

超声波技术预防性抑制蓝藻水华的研究

指出传统的蓝藻水华治理方法中存在的问题:大规模地杀灭蓝藻,造成大量藻细胞破裂,细胞内藻毒素等有害分泌物释放到水中,引发二次污染。介绍蓝藻水华的预防性调控方法,即在水体形成水华前,通过抑制蓝藻细胞生长,将其藻类生物量始终控制在一定水平以下,避免蓝藻水华的暴发。综述了超声参数对除藻抑藻效果的影响,以及超声对藻细胞生理系统的影响,探讨超声除藻抑藻的机理,并针对以往研究存在的不足,对后续研究重点进行了展望。     

The impact of phytoplankton community composition on optical properties and satellite observations of the 2017 western Lake Erie algal bloom

Since the early 2000s Lake Erie has seen a dramatic increase in phytoplankton biomass, manifested in particular by the rise in the severity of cyanobacteria blooms and the prevalence of potentially toxic taxa such as Microcystis. Satellite remote sensing has provided a unique capacity for the synoptic detection of these blooms, enabling spatial and temporal trends in their extent and severity to be documented. Algorithms for satellite detection of Lake Erie algal blooms often rely on a single consistent relationship between algal or cyanobacterial biomass and spectral indices such as the Maximum Chlorophyll Index (MCI) or Cyanobacteria Index (CI). Blooms, however, are known to vary significantly in community composition over space and time. A suite of phytoplankton and optical property measurements during the western Lake Erie algal bloom of 2017 showed highly diverse bloom composition with variable absorption and backscatter properties. Elevated backscattering coefficients were observed in the Maumee Bay, likely due to phytoplankton cell morphology and buoyancy regulating gas vacuoles, compared with typically Planktothrix dominated blooms in Sandusky Bay. MCI and CI calibrated to historical chlorophyll observations and applied to Sentinel 3's OLCI sensor accurately captured the 2017 bloom in Maumee Bay but underestimated the Sandusky Bay bloom by nearly 80%. The phycoerythrin-rich picocyanobacteria Aphanothece and Synechococcus were found in abundance throughout the western and central basins, resulting in substantial biomass underestimations using blue to green ratio-based algorithms. Potential misrepresentation of bloom severity resulting from phytoplankton optical properties should be considered in assessments of bloom conditions on Lake Erie.     

Extending the forecast model: Predicting Western Lake Erie harmful algal blooms at multiple spatial scales

Lake Erie is a classic case of development, recovery from, and return to eutrophication, hypoxia, and harmful algal blooms. Forecast models are used annually to predict bloom intensity for the whole Western Lake Erie Basin, but do not necessarily reflect nearshore conditions or regional variations, which are important for local stakeholders. In this study we: 1) developed relationships between observed whole basin and nearshore bloom sizes, and 2) updated and extended a Bayesian seasonal bloom forecast model to provide new regional predictions. The western basin was subdivided into 5 km near-shore regions, and bloom start date, size, and intensity were quantified with MODIS-derived images of chlorophyll concentrations for July–October 2002–2016 for each subdivision and for the entire basin. While bloom severity within each subdivision is temporally and spatially unique, it increased over the study period in each subdivision. The models for the 5 km subdivisions explained between 83 and 95% of variability between regional sizes and whole bloom size for US subdivisions and 51% for the Canadian subdivision. By linking predictive basin-wide models to regional regression estimates, we are now able to better predict potential bloom impacts at scales and in specific areas that are vital to the economic well-being of the region and allow for better management responses.     

SeaPRISM observations in the western basin of Lake Erie in the summer of 2016

In the summer of 2016, a robotic sun photometer called the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) Photometer Revision for Incident Surface Measurements (SeaPRISM), was deployed at a Coast Guard channel marker in western Lake Erie, measuring atmospheric properties and spectral water-leaving radiance. The instrument was deployed by the National Oceanic and Atmospheric Administration (NOAA) to support remote sensing validation and harmful algal bloom (HAB) satellite products. The Lake Erie SeaPRISM is also part of the international federated AERONET program maintained by the National Aeronautics and Space Administration (NASA), and more specifically is part of the AERONET Ocean Color (AERNOET-OC) network. The main purpose of this component of AERONET is specific to calibration/validation efforts for ocean color. The AERONET-OC network currently consists of 23 field radiometers at aquatic sites around the world. The Lake Erie site is the second freshwater lake location world-wide after the Palgrunden site in Sweden. During its operating period from mid-July to early September 2016, various environmental conditions were observed including a cyanobacteria bloom. Water-leaving radiance observations were generated on 43 out of 51 days, and varied by a factor of five. The variability in the above-water radiometry tracked that of in-water measurements made by a nearby buoy. During this brief operating window, satellite matchups were generated for several satellites. We highlight the first year's observations in relation to remote sensing validation and report on observations of cyanobacteria blooms from hourly to weekly time scales.     

Spatial and temporal scales of variability of cyanobacteria harmful algal blooms from NOAA GLERL airborne hyperspectral imagery

NOAA GLERL has routinely flown a hyperspectral imager to detect cyanobacteria harmful algal blooms (cyanoHABs) over the Great Lakes since 2015. Three consecutive years of hyperspectral imagery over the Great Lakes warn drinking water intake managers of the presence of cyanoHABs. Western basin imagery of Lake Erie contributes to a weekly report to the Ohio Environmental Protection Agency using the cyanobacteria index (CI) as an indicator of the presence of cyanoHABs. The CI is also used for the weekly NOAA NCCOS cyanoHAB Lake Erie bulletin applied to satellite data. To date, there has not been a sensor comparison to look at the variability between the satellite and hyperspectral imagery on a pixel-by-pixel basis, as well as a time scale comparison between measurements from buoys and shipboard surveys. The spatial scale is a measure of size of a cyanobacteria bloom on a scale of meters to kilometers. The change in the spatial scale or spatial variability has been quantified from satellite and airborne imagery using a decorrelation scale analysis to find the point at which the values are not changing or are not correlated with each other. The decorrelation scales were also applied to the buoy and shipboard survey data to look at temporal scales or changes in time on hourly to daytime scales for blue-green algae, chlorophyll and temperature. These scales are valuable for ecosystem modelers and for those initiating sampling efforts to optimize sampling plans and to infer a potential mechanism in an observational study from a synoptic viewpoint.     

Trophic interactions among algal blooms,macroinvertebrates, and brown trout: Implications for trout recovery in a restored river

Positive correlation between trout abundance and dissolved metal concentrations along the Upper Clark Fork River (UCFR; Montana, USA) have forced restoration practitioners to seek underlying causes of reduced fish density beyond heavy metal contamination. Throughout the river, nutrient enrichment and summer algal blooms may be hindering full recovery of trout populations. In this study, we evaluated the community structure and metal body burdens of benthic invertebrates and characterized existing trophic linkages between brown trout and dominant invertebrate taxa before and during summer algal blooms in a downstream reach of the UCFR where fish densities are low (20–30 trout/km), and where metal contamination is relevant but minimal compared with upstream. In spring, estimated invertebrate abundance was 1,727 ± 217 individuals/m² and dominated by Ephemerellidae and Baetidae families. During summer algal bloom, invertebrate abundance increased 15‐fold (20,580 ± 3,510 individuals/m²) mostly due to greater abundance of Chironomidae, Hydropsychidae, and Simulidae. Copper body burdens (130 ± 42 ppm) were higher than any other heavy metal regardless of season, but detectable concentrations of arsenic, cadmium, and lead were also found. A Bayesian mixing model combining metal burdens and stable isotopes showed that in the spring, trout of average size (355 ± 65 g) relied mostly on epibenthic taxa (Ephemerellidae and Hydropsychidae), contrasting with small (<100 g) and large (>400 g) trout relying heavily on Baetidae, a major component of invertebrate drift. Foraging segregation related to trout size did not occur during summer algal blooms, which may reflect increasing influence of benthic algal proliferation or indicate the indiscriminate use of pool habitats as thermal refugia over summer conditions by trout of different ages.     

流速对藻类生长影响的试验研究

水华的发生除与营养盐、光照等条件有关外,还和水体的流速等水文条件有关.以故宫筒子河为例,分析了推流技术对水体水华的抑制效果,证明增加水体流速可以在一定程度上抑制水华.在此基础上介绍了水体流速对藻类生长影响的试验研究,探讨了水体流速与藻类生长的关系.     

Vertical distribution of Microcystis colony size in Lake Taihu: Its role in algal blooms

This study investigated the vertical distributions of Microcystis cell density and colony size in Lake Taihu where algal blooms occur frequently. Measurements were made from April 2011 to January 2012 to gain a seasonal outlook on the role of such distributions in the blooms. It was found that large colonies tended to accumulate on the water surface, but the cell density fluctuated widely. The cell density in the water column increased continuously from spring to summer (i.e., April to October) and decreased after late autumn, showing apparent seasonal variations. The abrupt occurrence and disappearance of Microcystis blooms over short periods of time were not caused by the rapid growth of Microcystis but by the rise and accumulation of large Microcystis colonies at the water surface, both of which are affected by colony size. The ascent velocity of large colonies was higher than that of small ones, which enables large colonies to more readily overcome the stirring effects of water flows, waves and perturbations to rise to the surface. The results of canonical correspondence analysis (CCA) of Microcystis vertical distribution in relation to environmental factors suggested that nutrient concentrations and temperature were the main influencing factors related to bloom formation by Microcystis in Lake Taihu during our investigation.     

Limnological characteristics, eutrophication and cyanobacterial blooms in an inland reservoir, Australia

Ben Chifley Reservoir, the only potable water supply for Bathurst, New South Wales, Australia, has been experiencing recurrent cyanobacterial bloom problems since 1991. A study was undertaken from June 1998 to July 1999 to assess the limnological characteristics pertinent to eutrophication and the associated cyanobacterial blooms. From January–May 1999, the reservoir exhibited significant numbers of cyanobacterial cells, totalling > 9000 cells mL^?1. The highest number of cells (> 27 000 cells mL^?1) was recorded during April 1999. The water quality characteristics of the reservoir, and the river inflow and climatic data, were grouped into three distinct periods; before, during and after cyanobacterial blooms. High water temperature (15–22°C), thermal stratification (ΔT = 2.7–2.8°C), depletion of dissolved oxygen and high nutrient concentrations, all of which are conducive to enhanced cyanobacterial blooms, were evident before and during the bloom periods. Based on its nitrogen to phosphorus molar ratio, Ben Chifley Reservoir can be considered as being phosphorus‐deficient, in contrast to nitrogen, which is readily available from a number of sources in its drainage basin, including atmospheric fixation. Thus, it is recommended that adopting management strategies to reduce the quantity of bioavailable phosphorus in the reservoir would be the most effective way to minimize the occurrence of algal blooms.