Assessing vertical and horizontal movements of algal blooms in a coastal water using satellite remote sensing for optimal operation of desalination plants

2019 ◽  
Vol 19 (7) ◽  
pp. 2123-2130
Author(s):  
H. Chen ◽  
M.-H. Park
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Arabian Gulf ◽  
Warning System ◽  
Optimal Operation ◽  
Freshwater Resource ◽  
Emerging Issues ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Operating Strategies ◽  
Desalination Plants

Abstract Harmful algal blooms (HABs) are global concerns in coastal waters due to diffuse pollution and climate change. Emerging issues of HABs include their impact on desalination operations for water supply. This study utilizes composite satellite images to detect movement and propagation of algal blooms. Time series images from the Moderate-Resolution Imaging Spectroradiometer (MODIS) were used for monitoring chlorophyll-a in the Persian (Arabian) Gulf, which neighboring countries depend upon for desalination as their freshwater resource. Bi-daily MODIS data from the Terra and Aqua satellites were used to detect both vertical migration and horizontal movement of algal blooms. The results will be useful for creating an early warning system for desalination plants to anticipate operating strategies and intake locations to minimize impacts.

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 Mapping and Forecasting Onsets of Harmful Algal Blooms Using MODIS Data over Coastal Waters Surrounding Charlotte County, Florida

2018 ◽  
Vol 10 (10) ◽  
pp. 1656 ◽  
Author(s):  
Sita Karki ◽  
Mohamed Sultan ◽  
Racha Elkadiri ◽  
Tamer Elbayoumi
Keyword(s):  
Remote Sensing ◽  
Harmful Algal Blooms ◽  
Multivariate Regression ◽  
Algal Blooms ◽  
Wildlife Conservation ◽  
River Mouth ◽  
Warning System ◽  
Remote Sensing Data ◽  
Cost Effective ◽  
Color Processing

Over the past two decades, persistent occurrences of harmful algal blooms (HAB; Karenia brevis) have been reported in Charlotte County, southwestern Florida. We developed data-driven models that rely on spatiotemporal remote sensing and field data to identify factors controlling HAB propagation, provide a same-day distribution (nowcasting), and forecast their occurrences up to three days in advance. We constructed multivariate regression models using historical HAB occurrences (213 events reported from January 2010 to October 2017) compiled by the Florida Fish and Wildlife Conservation Commission and validated the models against a subset (20%) of the historical events. The models were designed to capture the onset of the HABs instead of those that developed days earlier and continued thereafter. A prototype of an early warning system was developed through a threefold exercise. The first step involved the automatic downloading and processing of daily Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua products using SeaDAS ocean color processing software to extract temporal and spatial variations of remote sensing-based variables over the study area. The second step involved the development of a multivariate regression model for same-day mapping of HABs and similar subsequent models for forecasting HAB occurrences one, two, and three days in advance. Eleven remote sensing variables and two non-remote sensing variables were used as inputs for the generated models. In the third and final step, model outputs (same-day and forecasted distribution of HABs) were posted automatically on a web map. Our findings include: (1) the variables most indicative of the timing of bloom propagation are bathymetry, euphotic depth, wind direction, sea surface temperature (SST), ocean chlorophyll three-band algorithm for MODIS [chlorophyll-a OC3M] and distance from the river mouth, and (2) the model predictions were 90% successful for same-day mapping and 65%, 72% and 71% for the one-, two- and three-day advance predictions, respectively. The adopted methodologies are reliable at a local scale, dependent on readily available remote sensing data, and cost-effective and thus could potentially be used to map and forecast algal bloom occurrences in data-scarce regions.

Hydrogeological and economical simulations: emergency water supply for Muscat

Water Policy ◽  
2013 ◽  
Vol 16 (2) ◽  
pp. 340-357 ◽  
Author(s):  
Slim Zekri ◽  
Ali Khamis Al-Maktoumi ◽  
Osman A. E. Abdalla ◽  
Jamila Akil ◽  
Yassine Charabi
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Low Cost ◽  
Market Price ◽  
Emergency Situations ◽  
Storage Reservoirs ◽  
Emergency Water Supply ◽  
Water Strategy ◽  
Desalination Plants ◽  
The Cost

Urban water in Gulf Cooperation Council countries is principally supplied from desalination plants. However, desalination could be interrupted by natural hazards such as cyclones or harmful algal blooms. Four scenarios have been considered to help public institutions in Muscat to establish a water strategy for emergency situations. The numerical simulations of groundwater pumping have shown that the aquifer can supply emergency water in a safe way without any apparent risk of seawater intrusion to the Al-Khod Aquifer. The results show that Muscat can be easily supplied by emergency groundwater for up to 10 consecutive days with volumes varying between 24 and 71 l/cap/day at a low cost of US$0.18 per m3. Covering up to 66% of the total regular demand during an emergency is technically feasible but would bring the cost up to US$1.49 per m3 for groundwater and a cost of US$38.6 per m3 for storage reservoirs made of concrete. The cost per m3 of using concrete reservoirs is close to the market price of bottled water. Finally, the Public Authority for Electricity and Water might think of decentralizing the water storage at house levels by requiring new houses to be equipped with reservoirs on the roofs.

scholarly journals Mapping and forecasting onsets of harmful algal blooms using MODIS data over coastal waters surrounding Charlotte County, Florida

2018 ◽  
Author(s):  
Sita Karki ◽  
Mohamed Sultan ◽  
Racha Elkadiri ◽  
Tamer Elbayoumi
Keyword(s):  
Remote Sensing ◽  
Harmful Algal Blooms ◽  
Multivariate Regression ◽  
Algal Blooms ◽  
Wildlife Conservation ◽  
River Mouth ◽  
Warning System ◽  
Remote Sensing Data ◽  
Cost Effective ◽  
Color Processing

Over the past two decades, persistent occurrences of harmful algal blooms (HAB; Karenia brevis) have been reported in Charlotte County, southwestern Florida. We developed data-driven models that rely on spatiotemporal remote sensing and field data to identify factors controlling HAB propagation, provide a same-day distribution (nowcasting), and forecast their occurrences up to three days in advance. We constructed multivariate regression models using historical HAB occurrences (213 events reported from January 2010 to October 2017) compiled by the Florida Fish and Wildlife Conservation Commission and validated the models against a subset (20%) of the reported historical events. The models were designed to specifically capture the onset of the HABs instead of those that developed days earlier and continued thereafter. A prototype of an early warning system was developed through a threefold exercise. The first step involved the automatic downloading and processing of daily Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua products using SeaDAS ocean color processing software to extract temporal and spatial variations of remote sensing-based variables over the study area. The second step involved the development of a multivariate regression model for same-day mapping of HABs and similar subsequent models for forecasting HAB occurrences one, two, and three days in advance. Eleven remote sensing variables and two non-remote sensing variables were used as inputs for the generated models. In the third and final step, model outputs (same-day and forecasted distribution of HABs) were posted automatically on a web-based GIS (http://www.esrs.wmich.edu/webmap/bloom/). Our findings include the following: (1) the variables most indicative of the timing of bloom propagation are bathymetry, euphotic depth, wind direction, SST, chlorophyll-a [OC3M] and distance from the river mouth, and (2) the model predictions were 90% successful for same-day mapping and 65%, 72% and 71% for the one-, two- and three-day advance predictions, respectively. The adopted methodologies are reliable, dependent on readily available remote sensing data sets, and cost-effective and thus could potentially be used to map and forecast algal bloom occurrences in data-scarce regions.

scholarly journals HABreports: Online Early Warning of Harmful Algal and Biotoxin Risk for the Scottish Shellfish and Finfish Aquaculture Industries

2021 ◽  
Vol 8 ◽  
Author(s):  
Keith Davidson ◽  
Callum Whyte ◽  
Dmitry Aleynik ◽  
Andrew Dale ◽  
Steven Gontarek ◽  
...  
Keyword(s):  
Early Warning ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Warning System ◽  
Environmental Data ◽  
Mitigation Measures ◽  
Traffic Light ◽  
Historical Trends ◽  
Index Approach ◽  
On Line

We present an on-line early warning system that is operational in Scottish coastal waters to minimize the risk to humans and aquaculture businesses in terms of the human health and economic impacts of harmful algal blooms (HABs) and their associated biotoxins. The system includes both map and time-series based visualization tools. A “traffic light” index approach is used to highlight locations at elevated HAB/biotoxin risk. High resolution mathematical modelling of cell advection, in combination with satellite remote sensing, provides early warning of HABs that advect from offshore waters to the coast. Expert interpretation of HAB, biotoxin and environmental data in light of recent and historical trends is used to provide, on a weekly basis, a forecast of the risk from HABs and their biotoxins to allow mitigation measures to be put in place by aquaculture businesses, should a HAB event be imminent.

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