Consensus Forecasting

On August 21, 2009, PTTEP Australasia (PTTEP) confirmed a continuous gas and crude oil condensate leak at the West Atlas offshore drilling platform in the Montara development located in the Timor Sea, approximately 250 km northwest of Truscott, Western Australia.

In August 2009, the Montara well head platform in the Timor Sea suffered a blowout resulting in oil being continuously released at the seabed over the next 3 months. Australia’s national oil spill response plan was activated immediately, triggering the Australian Maritime Safety Authority (AMSA), an agency of the Australian government, to mobilize. AMSA, supported by Asia-Pacific ASA, provided metocean data analysis, integration of remotely-sensed oil observations and oil spill trajectory forecasts on a daily basis. Through their subcontract agreement for these services, AMSA with APASA were able to apply new techniques and technologies to managing the problem of approximately 300-400 barrels of oil spilled each day (as estimated by PTTEP, September 2009).

The movement of oil (and other substances) on the water surface is driven by a combination of winds and ocean currents. One of the key challenges to providing oil spill trajectories is assimilating the wide variety of oceanographic and meteorological data. While atmospheric weather forecasting is now a routine part of everyday life for all of us, ocean forecasting is still a rapidly developing technology offering the potential for a better understanding of our offshore marine environment. Many countries now operate ocean forecasting models with regional or global coverage, such as NCOM operated by the U.S. Navy (global) and BLUElink by a partnership of the Royal Australian Navy, Australia’s CSIRO and the Australian Bureau of Meteorology.

Given the number of wind forecast datasets and now multiple ocean forecast datasets that are available, how does one choose which forecast to trust when planning a spill response or a search and rescue operation? One possible solution would be to test the various wind and ocean forecasts over time and decide which performs best for the particular problem being addressed. However, oil spills and chemical spills are infrequent events, and there is no guarantee that a particular data source will provide the best forecast at the time of the spill.

New Approach: Consensus Forecasting

OILMAP was used to perform consensus forecasting during the Montara spill.

Dr. Brian King, a senior oceanographer with APASA, says the growing view that oceanographers should follow the best-practice methodology used by weather forecasters to take full advantage of the multiple wind and ocean forecasting datasets available. “Weather forecasters use all available datasets and assess each of them to develop a consensus of opinion from the various weather forecast models on what might occur” says Dr. King, “and with multiple ocean forecasting datasets available now, the same approach can be applied.”

“For example”, says Dr. King, “oil spill models rely on good forecasts of both currents and weather to accurately predict the oil’s future drift and potential impact zones. We use both winds and currents as input data to ASA’s OILMAP and CHEMMAP spill models and have been able to successfully predict the movement of oil or chemicals over time if our winds and currents have been accurate.”

To enable forecasters to take full advantage of the wealth of metocean data available, ASA developed the Environmental Data Server (EDS) that provides ocean observations and forecasts to OILMAP, CHEMMAP, and other systems such as the U.S. Coast Guard’s SAROPS system. This allows maritime responders and scientists to undertake consensus forecasting for oil spills, chemical spills, and search and rescue incidents.

The EDS ensures that each of the multiple forecast datasets is readily available in a form that can be utilized immediately so that model predictions using different metocean data may be evaluated quickly during high pressure response planning missions.

Dr. King offers the example of how this works in practice. “When you have access to multiple ocean and weather forecast datasets, the latest approach is to run the same spill scenario with different datasets. When you do this, you sometimes get very close agreement in the predictions even though you used different forecast datasets of winds and currents, and this gives you a higher level of confidence in the spill predictions. If different forecast datasets result in disparate trajectories and outcomes, then you have multiple viable outcomes, but a low level of confidence in any one prediction. You can thus issue your spill forecasts with a confidence indicator, based on the degree of consensus obtained from the multiple analyses performed. We can also use field observations such as aircraft overflights, drifting buoys, or satellite-derived observations to help us estimate errors in the forecast data.”

New Technology: The Integrated EDS/OILMAP System

MODIS Terra satellite image taken October 19, 2009 showing oil slicks from the continuous release at Montara.

The OILMAP system connected to the EDS was used to respond to the Montara well blowout spill. Dr. King used the consensus forecasting approach with a matrix of different meteorological and oceanographic model forecasts to provide daily predictions of oil spill trajectories to the Australian response team. The system allowed ASA scientists to analyse hundreds of spill trajectories during the 3 month monitoring and response phase and provided decision makers valuable information in the successful response to this major spill.

The EDS: Environmental Data Server

The EDS system was built by ASA as part of the U.S. Coast Guard’s SAROPS Search and Rescue system and has since been adapted and enhanced for oil and chemical spill response by ASA for global application. The main capabilities of the EDS include:

1. The EDS caches very large met-ocean datasets (local and global) from servers around the world using various communication protocols and value adding to these datatsets (usually by adding tidal currents and increasing spatial and temporal resolution) to make them applicable for oil and chemical spill response purposes in both deep and shallow water environments. Consequently, EDS users do not need extensive technical knowledge of server architecture or the various dataset formats. This is handled automatically by the EDS servers and the built-in functionality within OILMAP, CHEMMAP, and SAROPS.
2. The EDS catalogues, archives and value-adds these massive datasets for later subsetting at anytime by EDS subscribers. Consequently, the EDS subscriber does not need extensive internet bandwidth expenditure or large data storage hardware.
3. The EDS provides temporal and spatial subsets of any EDS dataset via a web services request from remote users and also allows users to see an Environmental Common Operational Picture (ECOP)
4. The EDS automatically provides spatial and temporal aggregation services of tidal datasets into other forecast datasets such as those provided by the U.S. Navy (NCOM) and Royal Australian Navy/CSIRO/Bureau of Meteorology (BLUElink).
5. The EDS service used by AMSA includes an ongoing review from ASA/APASA oceanographers on data products sourced by the EDS and their suitability for oil and chemical spill response and search and rescue requirements. Consequently, new products may be offered to the subscriber as they emerge from the research community.

For more information about consensus forecasting or ASA’s EDS and spill models contact Brian King, bking@apasa.com.au.

Guidance for Dispersant Decision Making: Potential for Impacts on Aquatic Biota

When oil is spilled in the aquatic environment decision makers are required to make a rapid assessment of the situation and response options. Chemical dispersants are one of the many response tools available to decision makers and first responders. The decision to utilize dispersant hinges upon the expected level of resource injury; mainly, the likely water volume adversely affected by dispersed oil and dissolved hydrocarbons, and the surface area impacted by floating oil.

ASA has conducted research investigating the tradeoffs regarding the application, or not, of dispersants. These results, compiled as part of a project funded by the Coastal Response Research Center (CRRC) at the University of New Hampshire, have been synthesized into an Oil Spill Impact Guide (OSIG) which consists of a full report (currently under review), a hand-held field guide, and a Microsoft Excel-based dispersant use calculator. All of these materials will be provided to decision makers and first responders in the field.

The OSIG summarizes impacts to the water surface and column based on a matrix of model runs using ASA’s Spill Impact Model Application Package (SIMAP) physical fates, exposure and oil toxicity models. In order to allow the OSIG to be applicable throughout US waters, input parameters were varied. Variables included oil type, weathering state, oil volume, environmental conditions (e.g., wind speed, temperature), dispersant use, and aquatic biota sensitivity. Model results were presented as water volume where acute toxic effects would occur and the area of water surface oiled (which would impact wildlife, as well as socioeconomic uses). To put these impact volumes and areas in perspective, typical densities of biota in various geographical regions were used to provide a comparison of injury numbers with which to evaluate tradeoffs.

Page from the OSIG Field Guide showing effects of dispersant application on wildlife and plankton after 12 or 24 hours of weathering.

Results from the model simulations suggest that for small incidents with spill volumes below 500 gallons (2 m3), impacts due to dispersant application would be non-measurable to all water column biota, including the most sensitive species. Thus, as a general conclusion, the impact tradeoff between wildlife and water column biota is in favor of dispersant use for oil volumes less than 500 gallons. For larger spill volumes, 5,000 gallons (19 m3) of oil at a single location over a short period of time (less than 1 hour), application of dispersant could impact some water column biota. However, the volume of water in which water column biota would be affected would be much less than the area affected by floating oil thick enough to impact wildlife. Furthermore, the model predicts non-measurable impacts on water column organisms of average sensitivity to dissolved toxins, regardless of dispersant application or environmental conditions. Therefore, if dispersant applications are administered over large areas or long time periods, such that each localized application does not disperse more than 500 gallons (to protect all species) or 5,000 gallons (to protect the average species) of oil, water column impacts can be held low while reducing impacts due to the floating oil.

However, the area and volume of immediate impact are only one part of the total effects of an oil spill. In an actual incident responders must also consider the long-term effects when determining the best response; knowledge of local populations and habitats is critically important. Populations of long-lived species, such as birds and marine mammals, typically recover much slower from the impact of an oil spill than populations of species with higher turnover rates, such as zooplankton. We expect that the research and lessons learned from this effort will contribute to the development of decision-support tools and provide needed information related to spill response and biological impact.

Draft versions of the field guide and the Excel calculator are available for download on our website, Dispersant Use Impact Assessment and Decision Making. Please contact Eileen Graham, egraham@asascience.com, with comments or suggestions regarding these tools.

Europe’s DUET: Dispersant Usage Evaluation Tool

The European Maritime Safety Agency (EMSA) is the European Union (EU) agency charged with providing technical and scientific assistance to the European Commission and Member States in the development and implementation of EU legislation on maritime safety, pollution by ships, and security on board ships. EMSA is tasked with oil pollution preparedness, detection and response.

According to EMSA (2008 EU Maritime Accident Review) there were 232 confirmed oil spills in 2008 in and around EU waters. Every oil spill incident is unique in its circumstances and potential impact to the surrounding environment. Depending on the circumstances, the response to an oil spill may involve (1) use of booming to protect sensitive areas and/or contain floating oil; (2) mechanical recovery of oil; (3) use of chemical dispersants to facilitate dispersion of oil into the water at sea; or (4) simply monitoring the spill.

The primary oil spill response method in many jurisdictions is mechanical containment and recovery. EU Member States are currently reviewing their policies regarding the use of dispersants on oil spills and may consider them as a viable response option for the protection of vulnerable sea and estuarine areas.

There is considerable uncertainty about the efficacy of dispersant use and the trade-offs of impact caused by floating versus dispersed oil. An effective application of dispersant may reduce floating oil that would impact wildlife (e.g., seabirds), shallow water habitats and shorelines, but with the tradeoff that the dispersed oil may cause impacts to water column organisms. There is a need to quantify these tradeoffs so that informed decisions can be made during spill response.

The Dispersant Usage Evaluation Tool (DUET) was developed exclusively for EMSA by ASA and will be provided to all EU Member States and their appropriate Response Organizations. DUET contains guidance on dispersants and their use, and allows the user to evaluate the consequences of applying dispersant to oil at sea. The oil fates model contained in DUET was derived from ASA’s Spill Impact Model Application Package (SIMAP). It allows the user to evaluate tradeoffs of dispersant use, as well as plan monitoring activities for evaluating response effectiveness and impacts. The model estimates water concentrations of naturally and chemically-dispersed oil and dissolved hydrocarbons, as well as the surface area impacted by floating oil. These measures may be compared for scenarios with and without dispersant use to provide guidance to decision-makers.

An informed decision about dispersant use requires consideration of the location and circumstances of a spill. Environmental information is necessary to establish which resources (organisms on the water surface, on shore, in the near-shore, in the water column, and on/in the sea bed) are present. The probable effects of exposure to surface or dispersed oil should then be estimated to assess the consequences of using dispersants versus not using dispersants.

For more information about DUET or dispersant use tradeoff evaluations contact Deb French McCay (ASA), dfrenchmccay@asascience.com or Walter Nordhausen (EMSA), walter.nordhausen@emsa.europa.eu.

Vessel Traffic Information

AIS data integrated in an iPhone app.

ASA and Maritime Information Systems, Inc. (MIS) have formed a strategic partnership to connect ASA’s software to real-time vessel information supplied by the Automatic Identification System (AIS).

AIS is a short range coastal tracking system used to identify and locate vessels by electronically exchanging data with nearby ships and ground stations. Information such as unique identification, position, course, and speed can be acquired.

MIS provides AIS data to organizations such as PEMEX, the U.S. Coast Guard, and the U.S. Maritime Administration. ASA has been integrating AIS data for a number of years for Marine Spatial Planning projects requiring historical vessel traffic data. This new partnership adds access to historical analysis as well as real-time vessel locations.

AIS data integrated in ArcGIS with nautical chart and a chemical spill plume.

For more information, please contact Moses Calouro, mjc@mgn.com or Eoin Howlett, ehowlett@asascience.com.

Our many clients who fondly remember working with Nicole Whittier Mulanaphy when she was with ASA from 2000-2007 will be pleased to hear that she has returned. Nicole, an Environmental Chemical Engineer, is an expert in modeling the trajectory, fate, and impacts of chemical substances and oil in water and air. She will be involved with the ongoing development of ASA’s suite of models, client liaison for software support, and technical management of projects related to chemical pollution. During her time away from ASA, she oversaw environmental compliance for a chemical manufacturing facility with a focus on air permitting and waste reduction activities.

Tom Auer, a Geographic Information Science (GIS) specialist, joined ASA in November. Tom has experience in geovisualization methods for exploratory analysis of data. His focus is on environmental data or data that links human-environment relationships. At ASA, he is working on developing a Flash/Flex environmental data Web application and on improving the cartographic design of various map outputs. Prior to joining ASA, he received an M.S. in Geography at The Pennsylvania State University, studying change symbolization use in animated maps.

Shawn Buttrick joined ASA as a programmer, with a background in computer engineering and programming. He is proficient with C# applications and has developed client-server applications, graphical user interfaces, and Windows services. At ASA his focus is on developing data aggregation applications and OGC compliant Web Map Services. Shawn has a B.S. in Computer Engineering from the University of Massachusetts, Dartmouth.

Edna Donoughe joined ASA as a software engineer. She has a broad engineering and scientific background, including experience in software system architecture, analysis and design, web service development, CASE tools, workflow applications and geographic information systems (GIS). At ASA she will focus on design and development of GIS enabled next generation client prototypes for search and rescue as well as common operational data management. Edna holds a B.S. in Computer Science as well as a B.S. in Mathematics from Indiana University of Pennsylvania.