scholarly journals Unsteady Multi-Element Time Series Analysis and Prediction Based on Spatial-Temporal Attention and Error Forecast Fusion

2020 ◽  
Vol 12 (2) ◽  
pp. 34
Author(s):  
Xiaofan Wang ◽  
Lingyu Xu
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Short Term Memory ◽  
Sudden Change ◽  
Back Propagation ◽  
Red Tides ◽  
Model Errors ◽  
Chl A ◽  
Error Forecast ◽  
Concentration Prediction

Harmful algal blooms (HABs) often cause great harm to fishery production and the safety of human lives. Therefore, the detection and prediction of HABs has become an important issue. Machine learning has been increasingly used to predict HABs at home and abroad. However, few of them can capture the sudden change of Chl-a in advance and handle the long-term dependencies appropriately. In order to address these challenges, the Long Short-Term Memory (LSTM) based spatial-temporal attentions model for Chlorophyll-a (Chl-a) concentration prediction is proposed, a model which can capture the correlation between various factors and Chl-a adaptively and catch dynamic temporal information from previous time intervals for making predictions. The model can also capture the stage of Chl-a when values soar as red tide breaks out in advance. Due to the instability of the current Chl-a concentration prediction model, the model is also applied to make a prediction about the forecast reliability, to have a basic understanding of the range and fluctuation of model errors and provide a reference to describe the range of marine disasters. The data used in the experiment is retrieved from Fujian Marine Forecasts Station from 2009 to 2011 and is combined into 8-dimension data. Results show that the proposed approach performs better than other Chl-a prediction algorithms (such as Attention LSTM and Seq2seq and back propagation). The result of error prediction also reveals that the error forecast method possesses established advantages for red tides prevention and control.

scholarly journals LSTM Networks to Improve the Prediction of Harmful Algal Blooms in the West Coast of Sabah

2021 ◽  
Vol 18 (14) ◽  
pp. 7650
Author(s):  
Fatin Nadiah Yussof ◽  
Normah Maan ◽  
Mohd Nadzri Md Reba
Keyword(s):  
West Coast ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Time Series Data ◽  
Short Term Memory ◽  
Harmful Algal Bloom ◽  
Series Data ◽  
Severe Illness ◽  
The West ◽  
Chl A

Harmful algal bloom (HAB) events have alarmed authorities of human health that have caused severe illness and fatalities, death of marine organisms, and massive fish killings. This work aimed to perform the long short-term memory (LSTM) method and convolution neural network (CNN) method to predict the HAB events in the West Coast of Sabah. The results showed that this method could be used to predict satellite time series data in which previous studies only used vector data. This paper also could identify and predict whether there is HAB occurrence in the region. A chlorophyll a concentration (Chl-a; mg/L) variable was used as an HAB indicator, where the data were obtained from MODIS and GEBCO bathymetry. The eight-day dataset interval was from January 2003 to December 2018. The results obtained showed that the LSTM model outperformed the CNN model in terms of accuracy using RMSE and the correlation coefficient r as the statistical criteria.

scholarly journals Tracing the sources of nutrients fueling dinoflagellate red tides occurring along the coast of Korea using radium isotopes

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Hyeong Kyu Kwon ◽  
Guebuem Kim ◽  
Yongjin Han ◽  
Junhyeong Seo ◽  
Weol Ae Lim ◽  
...  
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Red Tide ◽  
Subsurface Layer ◽  
Vertical Mixing ◽  
Eastern Coast ◽  
Nutrient Concentrations ◽  
Red Tides ◽  
Radium Isotopes ◽  
Nutrient Sources

Abstract It is a well held concept that the magnitude of red-tide occurrence is dependent on the amount of nutrient supply if the conditions are same for temperature, salinity, light, interspecific competition, etc. However, nutrient sources fueling dinoflagellate red-tides are difficult to identify since red tides usually occur under very low inorganic-nutrient conditions. In this study, we used short-lived Ra isotopes (223Ra and 224Ra) to trace the nutrient sources fueling initiation and spread of Cochlodinium polykrikoides blooms along the coast of Korea during the summers of 2014, 2016, and 2017. Horizontal and vertical distributions of nutrient concentrations correlated well with 224Ra activities in nutrient-source waters. The offshore red-tide areas showed high 224Ra activities and low-inorganic and high-organic nutrient concentrations, which are favorable for blooming C. polykrikoides in competition with diatoms. Based on Ra isotopes, the nutrients fueling red-tide initiation (southern coast of Korea) are found to be transported horizontally from inner-shore waters. However, the nutrients in the spread region (eastern coast of Korea), approximately 200 km from the initiation region, are supplied continuously from the subsurface layer by vertical mixing or upwelling. Our study highlights that short-lived Ra isotopes are excellent tracers of nutrients fueling harmful algal blooms in coastal waters.

scholarly journals Red Tides

EDIS ◽  
2008 ◽  
Vol 2008 (3) ◽  
Author(s):  
Jorge R. Rey
Keyword(s):  
Human Health ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Marine Ecosystems ◽  
Red Tides ◽  
And Control

ENY-851, a 5-page illustrated factsheet by Jorge R. Rey, explains what these “harmful algal blooms” are, what causes them, their impacts on marine ecosystems, human health, and coastal economies, and strategies for mitigation and control. Includes references. Published by UF Entomology and Nematology Department, February 2008.

scholarly journals Fish Kill Incidents and Harmful Algal Blooms in Omani Waters

2011 ◽  
Vol 16 ◽  
pp. 23 ◽  
Author(s):  
Hamed Mohammed Al Gheilani ◽  
Kazumi Matsuoka ◽  
Abdulaziz Yahya AlKindi ◽  
Shehla Amer ◽  
Colin Waring
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Red Tide ◽  
Ecological Impacts ◽  
Red Tides ◽  
Fish Kill ◽  
Noctiluca Scintillans ◽  
Trichodesmium Erythraeum ◽  
Toxic Species ◽  
Desalination Plants

Red tide, one of the harmful algal blooms (HABs) is a natural ecological phenomenon and often this event is accompanied by severe impacts on coastal resources, local economies, and public health. The occurrence of red tides has become more frequent in Omani waters in recent years. Some of them caused fish kill, damaged fishery resources and mariculture, threatened the marine environment and the osmosis membranes of desalination plants. However, a number of them have been harmless. The most common dinoflagellate Noctiluca scintillans is associated with the red tide events in Omani waters. Toxic species like Karenia selliformis, Prorocentrum arabianum, and Trichodesmium erythraeum have also been reported recently. Although red tides in Oman have been considered a consequence of upwelling in the summer season (May to September), recent phytoplankton outbreaks in Oman are not restricted to summer. Frequent algal blooms have been reported during winter (December to March). HABs may have contributed to hypoxia and/or other negative ecological impacts. 

scholarly journals The Use of Sentinel-3 Imagery to Monitor Cyanobacterial Blooms

Environments ◽  
2019 ◽  
Vol 6 (6) ◽  
pp. 60 ◽  
Author(s):  
Igor Ogashawara
Keyword(s):  
Remote Sensing ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Lake Erie ◽  
Water Governance ◽  
Spectral Band ◽  
Cyanobacterial Blooms ◽  
Chl A ◽  
Cyanobacterial Harmful Algal Blooms ◽  
New Algorithms

Cyanobacterial harmful algal blooms (CHABs) have been a concern for aquatic systems, especially those used for water supply and recreation. Thus, the monitoring of CHABs is essential for the establishment of water governance policies. Recently, remote sensing has been used as a tool to monitor CHABs worldwide. Remote monitoring of CHABs relies on the optical properties of pigments, especially the phycocyanin (PC) and chlorophyll-a (chl-a). The goal of this study is to evaluate the potential of recent launch the Ocean and Land Color Instrument (OLCI) on-board the Sentinel-3 satellite to identify PC and chl-a. To do this, OLCI images were collected over the Western part of Lake Erie (U.S.A.) during the summer of 2016, 2017, and 2018. When comparing the use of traditional remote sensing algorithms to estimate PC and chl-a, none was able to accurately estimate both pigments. However, when single and band ratios were used to estimate these pigments, stronger correlations were found. These results indicate that spectral band selection should be re-evaluated for the development of new algorithms for OLCI images. Overall, Sentinel 3/OLCI has the potential to be used to identify PC and chl-a. However, algorithm development is needed.

scholarly journals Harmful algal blooms and environmentally friendly control strategies in Japan

2021 ◽  
Author(s):  
Ichiro Imai ◽  
Nobuharu Inaba ◽  
Keigo Yamamoto
Keyword(s):  
Aquatic Plants ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Control Strategies ◽  
Environmentally Friendly ◽  
Freshwater Ecosystems ◽  
Red Tides ◽  
Coastal Marine ◽  
Western Japan ◽  
Diatom Blooms

AbstractThe presence and status of harmful algal blooms (HABs) in Japan are reviewed, revealing a decrease in red tides; however, toxic blooms are found to be increasing in western Japan. Environmentally friendly control strategies against HABs are also compared with integrated agricultural pest management. Very high densities (105–108 CFU/g) of algicidal and growth-inhibiting bacteria were found in biofilm on seagrass and seaweed surfaces and in surrounding coastal seawater. The situation in freshwater ecosystems is similar to coastal seas for toxic cyanobacterium, Microcystis aeruginosa, and aquatic plants. These findings offer new insights into the ecology of influential bacteria and harmful algae, suggesting that protection and restoration of native seagrasses and seaweeds in coastal marine environments should be implemented to suppress HABs. Diatom blooms were successfully induced with bottom sediment perturbation to prevent the occurrence of harmful flagellates such as Chattonella spp. and Alexandrium catenella in the Seto Inland Sea; however, this method requires robust and reproducible verification. “Sato-Umi” is a helpful concept for HAB control in the sea and freshwater ecosystems when adequately managed by people (e.g., appropriate bottom perturbation; protection and restoration of seaweeds, seagrasses, and aquatic plants; application of polycultures of fish, seaweeds, etc.).

scholarly journals A prolonged red tide of Heterocapsa triquetra (Ehrenberg) F. Stein (Dinophyceae) and phytoplankton succession in a eutrophic estuary in Turkey

2015 ◽  
Vol 16 (3) ◽  
pp. 621 ◽  
Author(s):  
S. TAS
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Red Tide ◽  
Prorocentrum Minimum ◽  
Phytoplankton Succession ◽  
Chl A ◽  
Heterocapsa Triquetra ◽  
Golden Horn ◽  
Moderate Salinity ◽  
Near Future

A prolonged red tide of Heterocapsa triquetra and phytoplankton succession were investigated in a eutrophic estuary (Golden Horn) for a year. Runoff following the rainfall in winter supplied high amounts of nutrients and also created a mesohaline frontal zone in the middle and upper estuary. Red tide of H. triquetra was first observed with an orange-brownish water discoloration at the upper estuary in January. Highest cell density of H. triquetra was 2.7×106 cells l-1 in January and reached to 19.2×106 cells l-1 in April. Successive blooms continued with dinoflagellate Prorocentrum minimum in May and phytoflagellates Eutreptiella marina and Fibrocapsa sp. in summer. High chl-a and dissolved oxygen were measured in the spring depending on algal biomass. Findings indicate that H. triquetra might be adapted to moderate salinity and low temperatures and red tide events should be considered as a response to increasing eutrophication due to high amounts of nutrients. Eutrophication can lead to harmful algal blooms for this area in the near future.

Predicting water quality variability in a Mediterranean hypereutrophic monomictic reservoir using Sentinel-2 MSI: the importance of model functional form

2021 ◽  
Author(s):  
Ibrahim Alameddine ◽  
Mohamad Abbas
Keyword(s):  
Water Quality ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Multivariate Adaptive Regression Splines ◽  
Support Vector ◽  
Negative Consequences ◽  
Significant Drop ◽  
Chl A ◽  
Spatio Temporal ◽  
Sentinel 2

<p>Anthropogenic eutrophication is a pressing global environmental problem that threatens the ecological functions of many inland freshwaters and diminishes their abilities to meet their designated uses. Water authorities worldwide are being pressed to manage the negative consequences of harmful algal blooms (HABs) based largely on data collected from conventional monitoring programs that lack the needed spatio-temporal resolution for effective lake/reservoir management. This study assesses the potential of using Sentinel 2 MSI to predict and assess the spatio-temporal variability in the water quality of the Qaraoun Reservoir, a poorly-monitored Mediterranean hypereutrophic monomictic reservoir that is subject to extensive HABs during the growing season. The performance and transferability of water quality models previously calibrated based on Landsat 7 and 8 surface reflectance to predict Chlorophyll-a (Chl-a), total suspended solids (TSS), Secchi Disk Depth (SDD), and Phycocyanin (PC) levels in the reservoir are first assessed. The results showed poor transferability between Landsat and Sentinel 2, with all models experiencing a significant drop in their predictive skill. Sentinel 2 specific models were then developed for the reservoir based on 153 water quality samples collected over two years. Different model functional forms were then tested, including multiple linear regressions (MR), multivariate adaptive regression splines (MARS), and support vector regressions (SVR). Our results showed that for Chl-a, the MARS model outperformed MR and SVR, with an R<sup>2</sup> of 60%. Meanwhile, the SVR-based models outperformed their MR and MARS counterparts for TSS, SDD and PC (R<sup>2</sup> = 59%, 94%, and 72% respectively).</p>

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