adapting a coastal ocean model to predict the movement of ... · adapting a coastal ocean model to...
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Adapting a Coastal Ocean Model to predict the movement of an Oil Spill Slick in the Gulf of Mexico – Case Study: Lake Pontchartrain.
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November 3, 2014
Gabriel Retana , Ezra Boyd, João Pereira, Alex McCorquodale, Andy Baker, John Lopez,
Ioannis Georgiou, Sina Amini
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Outline
• Overview of Oil Spill & Surface Slick Trajectory • GIS mapping & surveillance • Oil Spill Response Hydrodynamic modeling • Field reconnaissance • Results & Impacts • Real-time Forecasting Effort • Conclusions
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Overview of Macondo Oil Spill
Over 200 million gallons of oil. High volume deep sea oil spill created unique response challenges. Proximity to the leak and fragmented shoreline. Adverse impacts on fragile coastal wetlands.
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Three Component Surveillance Strategy
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Computational Fluid
Dynamics
Field Reconnaissance
GIS / RS
Situational Awareness of Surface Slick
Impacting Lake Pontchartrain
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GIS Mapping & Surveillance Environmental Response Management Application
(ERMA) website provided a common GIS-based platform for spatial data related to the spill response.
Downloadable layers include: • NESDIS derived oil slick outline • Imagery derived boom • Deployed response vessels
Additional layers include: • Environmental Sensitivity Index (ESI) • Forecast wind speed and direction
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Oil Spill Response Hydrodynamic Modeling
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Hydrodynamic Modeling
1. Background/Motivation
2. FVCOM (Finite Volume Coastal and Ocean Model)
3. Model Domain
4. Model Setup
5. Some Results
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Background/Motivation
• There was a need for a forecast of hydrodynamics in the Lake Pontchartrain Basin
• UNO had a calibrated and validated 3-D hydrodynamic model of Lake Pontchartrain.
• The model had a higher resolution and complemented NOAA’s work
• UNO was in close contact with response teams • Modeling results readily available
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3-D Model FVCOM
Description • 3-D Model • Estuarine Model • Finite-Volume Model • Developed by Chen et al. (2006) at UMASS • Unsteady Flow • Hydrostatic Assumption • Unstructured Grid • Parallel Code
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3-D Model FVCOM (Cont.) Upgrades we have made
• Spatially Variable Friction (Retana 2008) • Time-Variable Friction • Spatially Variable Winds (original formulation had a bug.
Pereira 2013)
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Model Domain and Grid
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Lake Pontchartrain Mississippi Sound
Breton Sound
Lake Borgne
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Salinity Bonnet Carre Spillway, 2008
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Salinity change between April 1st and April 29, 2008
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Salinity April 29, 2008 Salinity, ppt
25.0023.6822.3721.0519.7418.4217.1115.7914.4713.1611.8410.53
9.217.896.585.263.952.631.320.00
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Model Setup Wind Scenarios
1) Typical Summer Seasonal Winds (generally South and Southeast at 0 to 15 knots)
2) Tropical Storm 3) Low Pressure System in the Gulf of Mexico
Tidal Scenarios 1) Spring Tide 2) Neap Tide 3) Mid-Range Tide
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Model Setup (Cont.) Boundary Conditions
• River Boundaries: Water Discharge (Retana(2008) and USACE)
• Open Boundaries: Stage (from ADCIRC predictions used in Retana (2008) and modifications to reflect the close of the MRGO)
• Wind Direction and Speed or Shear Velocity Components (Forecast data Generated by World Winds Inc.; measurements from USGS, LUMCON and NOAA)
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Results (Cont.)
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FORECAST
Typical Summer Seasonal Winds
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Results (Cont.)
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FORECAST
Tropical Storm
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Results (Cont.)
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FORECAST - Typical Summer Seasonal Winds
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Field reconnaissance
• Weekly boat trip by Lake Pontchartrain Basin Foundation (LPBF) staff (Andy Baker) • Eight trips between June 2 – July 28
• Followed a 125 mile path to 16 designated monitoring sites • Path and monitoring sites designed to intersect the most likely
paths for oil intruding into Lake Pontchartrain
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July 4, 2010 Tarballs and Sheen Observed in Rigolets
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Progression of Surface Slick into Lake Pontchartrain
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Results & Impacts – July 1 to 5 2010
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- Three independent assessments showed general consistency
- Detailed tracking of the encroaching oil, quantified potential direction and speed toward Lake Pontchartrain
- Facilitated more aggressive response from Slidell command office
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Real-Time Forecasting Effort
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Real-Time Forecasting Effort
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• Variables include wind speed and direction, temperature, salinity and tidal constituents among others
• Data from USGS, NOAA and the US Army Corps of Engineers are also being used
• There is a lack of water discharge measurements for
some of the streams included in the model
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June 2010 Validation
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June 2010 Validation
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June 2010 Validation
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Conclusions • UNO modeling complemented NOAA’s modeling and
was used to help response efforts • Years of research were used to quickly respond to an
extreme event (adapted FVCOM source code allowed the application of bathymetric spatially varying friction and spatially varying wind conditions)
• Reasonable consistency between RS/GIS mapping, modeled trajectories, and field observations
• NGO/NPO, university research centers, and consulting firms have resources that can and should be used when needed
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Future Steps • Application to other coastal areas
• FVCOM models • Other numerical models, e.g., Delft3D, ECOMSED
• Adaptation of the existing ASCII inputs and outputs into binary format • Smaller, more precise, faster information transfer
• Putting in place an actual surveillance program • Apply for funding • Propose it to State Agencies?
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Future Steps • With proper initial and boundary conditions, the
adapted version of the model can be used to predict the fate and transport of pollutants in reservoirs, receiving waters, or major water bodies in Virginia, Maryland or Delaware.
• Modeling for the Chesapeake Bay, Atlantic Ocean,
among others.
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Acknowledgments Louisiana Coastal Area: Science & Technology Office
NSF - Northern Gulf Coastal Hazards Collaboratory Louisiana Optical Network Initiative
World Winds, Inc.
Dr. Chen and the FVCOM group (University of Massachusetts-Dartmouth)
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THANK YOU