31 Mar Combating HABs Threat to Desalination Plants in Oman: An Operational Model
Combating HABs Threat to Desalination Plants in Oman: An Operational Model
Red tide is a naturally occurring phenomenon, higher than normal concentration of microscopic, single celled, photosynthetic algae. The coastal waters of the Sea of Oman host many indigenous species of marine algae whose populations are greatly influenced by water quality. Changing water quality can trigger rapid growth in certain algal populations. These algal ”blooms” (commonly referred to as harmful algal blooms or HABs) occur naturally along the Sea of Oman. On the other hand, recent advances in membrane technology along with other technological innovations that reduce or even eliminate pre-treatment have increased the uptake and interest of RO technology in the Gulf countries including Oman (DesalData, 2012). HABs are a concern for desalination plants due to the high algal biomass present in source waters during these events, and the diversity of substances that some toxic algae produce. HABs can cause significant operational issues that result in increased chemical consumption, increased membrane fouling rates, and in extreme cases, a plant to be taken off-line. These impacts can be severe, as seen during a 2008 – 2009 HAB in the Gulf of Oman that negatively affected multiple desalination plants, including one that had to cease operations for 55 days in Barka site (Oman). In the US, Coastal HAB events have been estimated to result in economic impacts of at least USD82 million each year.
Implementation of a HABs early warning system
To address this challenge in Oman and the Gulf region, an international research team led by the Middle East Desalination Research Center (MEDRC) in Oman, in partnership with several organizations such as Sultan Qaboos University (Oman), MASDAR Institute of Science and Technology (UAE), the Regional Organization for the Protection of the Marine Environment (Kuwait), the University of California Santa Cruz (USA), and the National Oceanic and Atmospheric Administration (USA), implemented a project using the state‐of‐the‐art satellite remote sensing and numerical modeling technology to develop an early warning system. Such an early warning system will contribute significantly to combatting potentially lethal Red Tide phenomena in Oman and the wider Arabian Gulf region. This project was funded by USAID through the Middle East and North Africa Network of Water Centers of Excellence (MENA NWC). A potential synthesized approach was established within this project by combining multiple accessible satellite remote sensing approaches including visual interpretation, spectra analysis, parameters retrieval and spatial-temporal pattern analysis. Several parameters are monitored (Fig. 1) such as: Sea Surface Temperature (SST), chlorophyll fluorescence, wind
Figure 1: Oman HAB Transport forecasting system
This approach aimed at leading to a systematic and comprehensive monitoring of HABs based on satellite remote sensing from multiple oceanographic perspectives. To resume it, idealized Red Tide prediction for desalination systems consisted in this project in five phases:
1.Real-time satellite imagery using spectral shape algorithms to identify potential red tides,
2.Satellite data (e.g. TERRA/AQUA MODIS) used to seed particle-tracking numerical models,
3.Satellite and model data used to provide support (3-10 days) prediction,
4.In-water data at the intake location used to validate satellite models, and as warning system (change detection, identification of blooms), and
5.Integration of all data into models (statistical and numerical) to predict ecosystem conditions leading to impacts.
Results
The first phase of the project has concluded with a predictive model able to forecast the likely outbreak of HABs a full three days before the bloom can strike. This developed model works by combining the hydrographic modeling of a large part of the ocean, overlaying satellite data identifying HABs from space, overlaying weather forecasts, with particle tracking to create the forecasts. The project developed also a desalination guidance manual to help the desalination utilities in Oman in preventing the blooms’ invasion three days in advance and adopting adequate measures to safeguard their assets and secure them from toxins, which are harmful to human and marine species health. The model will concretely alert desalination plant operators to the presence and predicted transport pathways of algal blooms. As a result, operators will have a broader view of their environment, allowing them to observe and understand approaching algal blooms and engage in more adaptive management and informed decision making. A demonstration project is proposed at Barka site, a desalination facility in Oman that was shut down during the 2008‐2009 HABs invasion. Other validation sites were included in Oman and also Fujairah in the UAE. Regional scientists will gain hands‐on training and experience in remote sensing analysis and algae bloom modeling. A website will provide bloom detection and forecasting for the pilot project coverage area. The results of this phase have been presented during a workshop hosted at MEDRC premises in Oman last January.
Urgent Training needed
During the workshop of last January at MEDRC, the attendees were given the opportunity to gain hands-on experience in the use of the predictive model over the internet to learn how to make their own HABs predictions. Examples from the NOAA’s HAB Operational Forecast System (USA) were used to show how this information can be distributed through a bulletin, akin to how bulletins are currently issued for the Great Lakes, Texas, and Florida. However, a wider capacity building activity should be launched to train teams from the region to assist the desalination plants operators monitor HABs using that developed model. This will teach them how to visualize and interpret model predicted weather and hydrodynamic fields as well as how to operate the HAB tracking model through web-interface and interpret predicted trajectories; SOPs for web interactions and analysis. MEDRC would continue leading this effort, including that training process as it falls within the core of its mission in the region. MEDRC has just launched the 2016 desalination training schedule under its Continued Professional Education and Training in Water program. The training courses are designed to suit various positions, from entry level to expert level regarding Pretreatment for Seawater Reverse Osmosis Desalination Plants, practical understanding of key pretreatment processes widely used in reverse osmosis (RO) desalination plants worldwide, and selection, operation, maintenance, monitoring, troubleshooting and optimization of conventional and membrane pretreatment technologies.
Perspectives and next steps
Climate change and increasing nutrient pollution remain potentially causing factors for HABs to occur more often and in locations not previously affected and it may worsen in some regions as well under future climate scenarios. Therefore, it’s important for the scientific community to deepen its research about how and why they form and where they are, as well as to evaluate the direct and indirect associations between HABs, climate change, ocean acidification, and human health; so that they can reduce their harmful effects. An effective early warning system with greater accuracy, speed, and geographic coverage; against HABs has become indispensable for countries in the region, especially as climate change threatens to accelerate the manifestation of environmental conditions conducive for more frequent and deadly HAB occurrences. A pilot HAB-forecasting system has been developed for the Arabian Gulf and Arabian Sea region, and now needs to be expanded and brought into operational use. More accessible data and methods can be integrated into the developed model for combined analysis, to help address the current problems in improving routine-monitoring and forecasting of HABs. The participation of all desalination plants operators in the region is required and most welcome.