1

A New Wave-Current Online Information System for Oil Spill Contingency Planning (WAVCIS)

Gregory W. Stone12 Zhang, X.P.1 Gibson, W.1 and Fredericks, R. 1

1Coastal Studies Institute, and 2Department of Oceanography & Coastal Sciences Louisiana State University, Baton Rouge, LA 70803, USA

gagreg@lsu.edu

Abstract An online oceanographic and meteorological observing system has been

developed and is being implemented off the Louisiana coast to provide critical information during offshore emergencies including oil spills. The program, WAVCIS (WAVe Current Information System), provides wave information (sea state) including wave height, period, direction of propagation, water level, surge, water column velocity profiles, and meteorological conditions on a near real time basis. Information of this sort does not exist for an area approximating 135,000 km2

off Louisiana’s coast. WAVCIS involves offshore deployment of instrumentation around the entire state in order to provide near real time data describing sea state, current velocity and meteorological conditions. Information from each station is transmitted via cellular satellite telephone to a base station at Louisiana State University where it undergoes quality control, post-processing and archiving in an online database. The information is then made available on the World Wide Web and is accessible to computers with an Internet connection and web browser. Various data displays are available for the near real time information, as well as a specified time history for archived data 1.0 Introduction

Mitigating the impacts associated with accidental release of oil and gas from offshore exploration, production and supporting infrastructure, in addition to spills, necessitates frequent updates on regional oceanographic and meteorological conditions. Recent efforts to provide this capability off the Louisiana coast involve the development and implementation of an ocean and meteorological observing system, WAVCIS (WAVe Current Information System). The ultimate objective of WAVCIS is to support Louisiana’s ability to anticipate and prepare for emergencies offshore (oil spills, hurricanes, winter storms, shipping accidents, etc.), assist numerical modeling efforts during storm events by measuring important oceanographic and meteorological parameters and making it available in near-real time or after archiving, as a customized time series. At present, attempts at numerical modeling of offshore conditions to assist in predicting oil spill trajectories in coastal Louisiana are stymied due to a severe lack of quality input information, namely sea state boundary conditions and atmospheric forcing. Efforts are also underway to integrate the Louisiana observing node with that of Texas, Mississippi and Florida to provide a considerably more comprehensive program for the Gulf of Mexico.

In this paper an overview of the WAVCIS program is provided in addition to sample data products being developed. Additionally, discussion is provided on how the program is expected to ultimately provide one of the more comprehensive offshore monitoring systems globally for direct application to oil and gas spill mitigation. Typically, several techniques are available to provide sea state conditions

and other environmental conditions; however, these are restricted to numerical simulations (Nakata et al., 1998) or qualitative estimates from satellite/visual observations (Fingas and Brown, 1998).

Emergency management planning is a critical component of coastal hazard preparedness. Well-conceived plans are known to have significantly reduced future risk to life and infrastructure and have assisted in mitigating the effects of oil spills and preventing such occurrences (see reviews in Beer, 1997). This approach may be broken down into two components: (1) short-term emergency preparedness and (2) longer term mitigative planning. Short-term emergency preparedness is essential to maximizing the success of emergency preparedness during potentially catastrophic occurrences off the Louisiana coast in the Gulf of Mexico. Critical to this effort is access to quality, real/near real-time information, which will lend itself to promoting earlier advance warning time in the event of impending disaster. This is followed by continuous real-time risk assessment using a continuous information feed thereby allowing enhanced lead time for emergency management and decision making and rapid information flow to oil spill response deployment. Longer term mitigative planning is critical to reduce or eliminate the long-term risk of the ecosystem, people and property to hazardous conditions. The continued monitoring of oceanographic phenomenon can lead to an enhanced comprehension of current and wave conditions and short-term response (on the scale of hours) of these conditions to changes in weather. 1.1 Need for the Monitoring Program Until recently, ongoing accurate reports on sea state off the Louisiana coast were not available with the exception of a National Data Buoy Center buoy (NDBC 42040) located approximately 100 km (62 miles) east of the mouth of the Mississippi River (see Figure 1 for location). The entire stretch of coastline from Breton Sound to the Louisiana-Texas border was completely devoid of instrumentation capable of supplying accurate sea state conditions on a regular basis. Only water level information is obtained from two CMAN stations at Grand Isle and the mouth of the Mississippi River. Until recently, the closest source of sea state information for south central Louisiana was 480 km (300 miles) south of the coastline (NDBC 42001 on Figure 1). Use of the information from this site for oil spill contingency planning is extremely limited. Since additional wind and wave data were not available between this buoy and the Louisiana shoreline, one must assume that environmental conditions have not changed over this 480 km distance. This is an unreasonable assumption since storms frequently generate and move across the shelf break parallel to the Texas and Louisiana coast thereby influencing significantly, wave and wind fields. In addition, a hurricane moving towards the Louisiana coast and has crossed over buoy 42001 may strengthen considerably during the next several days before landfall. Until implementation of WAVCIS, no sea state information was available between the offshore buoy and the Louisiana coast for advance warning to agencies involved in oil-related emergency management. 1.2 Objective of the Monitoring Program The objective of WAVCIS is to provide wave information (sea state) including wave height, period, direction of propagation, water level, surge, near surface current speed and direction and climatological conditions (wind speed and

Figure 1 Location Map of the WAVCIS Instrumented Platforms off the Louisiana Coast in the Gulf of Mexico.

direction, barometric pressure, air temperature) on a near real time basis around the entire Louisiana coast. The program is designed to provide critical information offshore during hurricanes and offshore accidents. The information is archived and/or used in real time for numerous hydrodynamic modeling applications dealing with process-linked studies on coastal erosion and model skill assessment between output and field measurement. 2.0 Monitoring Program Overview The ultimate objective of WAVCIS is offshore deployment of instrumentation around the entire state in order to provide near real time information on a frequent basis (3 hours or less). The instrumentation will provide information from deep to shallow water off the Louisiana coast. As summarized schematically in Figure 2, information from each station is being transmitted to a base station at Louisiana State University where it undergoes quality control, post-processing and archiving in an online database. The information is then made available on the World Wide Web and is accessible to computers with an Internet connection and web browser. As presented in detail later in this report, various data displays are available for the real time information as well as a specified time history for archived data.

Figure 2 Instrumented Platform Concept Illustrating the Various Instrument Arrays Being Used in the WAVCIS Program.

2.1 Methodology and Design Individual Remote Monitoring Stations are set up on existing oil industry structures off the coast. Use of such existing structures assures a stable platform even during periods of extreme weather conditions, and is more cost effective than erecting dedicated purpose structures offshore. The sensors and systems deployed at each site consist of three basic types: meteorological sensors, oceanographic sensors, and data logging and telemetry equipment. 2.2 Oceanographic Sensors

All oceanographic sensors are mounted underwater in properly designed and fabricated, pressure proof housings. These housing are rigidly affixed to the legs of the platform at two levels. Sensors used to determine wave height, period and direction are mounted no deeper than two meters below mean low water level. Sensors to measure current profile and precise tide are mounted on the sea floor at the base of the platform. Water temperatures are monitored at each of these levels. All cabling providing power and data lines to these packages is routed through a closed conduit running down the platform leg. Oceanographic sensors used are as follows: Marsh McBirney electromagnetic current meter to measure Current used to determine

wave direction. These sensors are mounted in a fixed, vertical orientation to measure the instantaneous U and V components of current. They are a rapid response sensor, capable of current measurements at wave frequencies, i.e., 0.25 second scans. Thus, through post processing along with wave height, wave direction can be determined. Furthermore, long term filtering and averaging of the U and V components will produce average current speed and direction. Waves and tide are measured by monitoring water level induced pressure changes above the sensor with a rapid responding pressure sensor. A precise determination of the pressure is desired, thus a Paroscientific digital pressure sensor is used. The Paroscientific transducer it a state-of-the-art, precision pressure transducer. The active element is a quartz crystal oscillator. Oscillation frequency is inversely proportional to the pressure applied to the quartz element. With a 0 to 45 psia range, instantaneous measurement of pressure induced water level can be made with an equivalent accuracy of 1 mm. With both the current meter and pressure sensor mounted as near to the surface as practical ( no more than 1-2 meters below mean low water), minimal pressure attenuation of short period wave components are experienced. Precise average water level (Tide) is separately determined by averaging the instantaneous pressure samples (total frequency count over 8 minutes). Current profile is provided using a bottom mounted Acoustic Doppler Current Profiler and is presented in more detail below. This instrument provides a profile measurement of water current from as close as one meter to the surface, to within one meter of the bottom. Water temperature is measured at the wave sensing level as well as at the bottom, providing a near surface and bottom temperature measurement. The temperature sensor is a YSI Thermoleaner thermistor, capable of producing accuracies of 0.1 deg. C. 2.3 Acoustic Doppler Current Profiler The Acoustic Doppler Current Profiler (ADCP) is an exciting addition to the WAVCIS program that not only provides current velocity profile data, but also wave data through newly developed software. The ADCP provides a profile measurement of water current from as close as one meter to the surface, to within one meter of the bottom. A considerable effort has been invested in working with RD Instruments to obtain wave data from the ADCP’s. Given that this is new technology, a more detailed description is provided below. 2.31 Principles of ADCP Wave Measurement The basic principle behind wave measurement, is that the wave orbital velocities below the surface can be measured by the highly accurate ADCP. The ADCP is bottom mounted, upward looking and has a pressure sensor for measuring tide and mean water depth. Time series of velocities are accumulated and from these time series, velocity power spectra are calculated. To get a surface height spectrum the velocity spectrum is translated to surface displacement using linear wave kinematics. The depth of each bin measured and the total water depth are used to calculate this translation. To calculate directional spectra phase information must be preserved. Each bin in each beam is considered to be an independent sensor in an array. The cross-spectrum is then calculated between each sensor and every other sensor in the array. The result is a cross-spectral matrix that contains phase information in the path between each sensor and every other sensor at each frequency

band. The cross-spectrum at a particular frequency is linearly related to the directional spectrum at a particular frequency. By inverting this forward relation we solve for the directional spectrum. 2.32 Background

The use of Doppler sonar to measure ocean currents is by now well established, and is documented in the RDI publication Acoustic Doppler Current Profilers, Principles of Operation (RD Instruments, 1989). Conventional acoustic Doppler current profilers (ADCPs) typically use a Janus configuration consisting of four acoustic beams, paired in orthogonal planes, where each beam is inclined at a fixed angle to the vertical (usually 20 - 30 degrees). The sonar measures the component of velocity projected along the beam axis, averaged over a range cell whose along-beam length is roughly half that of the acoustic pulse. Since the mean current is assumed to be horizontally uniform over the beams, its components can be recovered by subtracting the measured velocity from opposing beams. This procedure is relatively insensitive to contamination by vertical currents and/or unknown instrument tilts (RD Instruments, 1989).

The situation regarding waves is more complicated. At any instant of time the wave velocity varies across the array. As a result, except for waves that are highly coherent during their passage from one beam to another, it is not possible to separate the measured along-beam velocities into their horizontal and vertical components. However, the wave field is statistically steady in time and homogeneous in space, so that the cross-spectra of velocities measured at various range cells (either between different beams or along each beam) depend on wave direction. This fact allows us to apply array processing techniques to estimate the frequency-direction spectrum of the waves. In other words, each depth cell of the ADCP can be considered to be an independent sensor that makes a measurement of one component of the wave field velocity. The ensemble of depth cells along the four beams constitutes an array of sensors from which magnitude and directional information about the wave field can be determined. 2.33 ADCP Performance As a Wave Gauge

The ADCP can use its profiling ability (bins and beams) as an array of sensors. Because the ADCP can profile the water column all the way to the surface, it can be mounted in much deeper water than a traditional pressure (PUV triplet) based device. Higher frequency waves attenuate more quickly with depth below the surface. The ADCP can measure much higher frequency waves than a PUV and do so in deeper water, because it can make measurements higher up in the water column. Additionally, the ADCP has many independent sensors (bins-beams) so even when sampling at a 2Hz sample rate the data is as quiet as if it had been sampled at 200Hz by a single point meter. To achieve the best possible solution for wave height spectrum the height spectrum and the noise spectrum are fit to the bin-beam data using a least squares fit (see Height Spectrum for details). In addition to the orbital velocity technique for measuring wave spectra, the ADCP can measure wave height spectra from its pressure sensor (with frequency/depth limitations) and from echo ranging the surface. Within the frequency range of the pressure sensor the pressure height spectrum is an old reliable reference for data comparison. The surface track measurement of wave height is reliable most but not all of the time. The advantage

of the surface track derived height spectrum is that it is a direct measurement of the surface and can measure wave energy at very high frequencies, higher than 0.9 Hz in some installations. Having three completely independent measures of wave height spectrum that all agree very closely is a solid argument for data quality.

The directional spectrum is much truer and of higher quality than any sort of triplet (PUV, UVW, PRH) and is almost as good as large home-built arrays. The Maximum Likelihood Method used for inversion allows one to independently resolve the wave field in each direction. The full circle (360 degrees) is arbitrarily divided into as many slices as one chooses (up to 360 slices of 1 degree width). Because of this the RDI directional spectra algorithm can resolve two separate swells arriving from different directions at similar frequency. This feat is impossible using traditional triplet algorithms. The ADCP measures a sparse array and as such it cannot achieve the aperture of expensive home built arrays, however, the aperture of the beams gives the ADCP a significant improvement in directional accuracy over single point measurements. A traditional triplet algorithm uses only the first three terms in a Fourier series so it can identify a single directional peak particularly at longer wavelengths. However, bouys, PUV’s other triplets cannot accurately represent the multiple directional peaks or even the true directional distribution. In the ADCP wave algorithm there are many sensors giving an array with many degrees of freedom and some aperture. The Maximum Likelihood Method used to calculate the directional spectrum has a smearing kernal associated with the inversion. By using the Iterative Maximum Likelihood Method the spreading of the directional spectrum can be corrected. The process is repeated until the directional spectrum converges to what the data actually supports. The spectrum will get narrower and sweep up directionally spread power into the peak as long as the measured data supports it. The result is a directional spectrum that more accurately represents the true directional distribution. 2.4 Meteorological Sensors

All meteorological sensors are mounted at the top of the platform in a location providing clear air to the sensors from all directions. The meteorological sensors used are as follows: Wind Speed and Direction measured using a traditional propeller and tail fin, fuselage type (wind bird) anemometer. These units have been proven for ruggedness and reliability in marine measurement applications. Wind acting on a propeller shaft drives a DC generator which produces a voltage proportional to the wind speed. The wind direction signal results from sampling the position of a potentiometer wiper oriented into the direction of the wind by the fuselage tail fin. Barometric Pressure is measured by a Vaisala pressure transducer. This sensor has a range of 800 to 1060 mbar. Air Temperature is also be measured with a YSI Thermoleaner thermistor. In this case the sensor is mounted in a radiation shielded housing to prevent erroneous temperatures due to solar heating. Wind Shear is measured at some sites using a U, V, W, anemometer. These sensors are propeller driven anemometers oriented in the horizontal in the U and V directions, and in the vertical for the W axis. Each anemometer is bidirectional, providing true U, V, and W wind measurements. These wind components are analyzed at the data processing step to determine wind shear over the water.

2.5 Data Logger and Communications Package

All data logger and communications equipment are mounted above water in an environmentally sealed container. All batteries are housed in a separate container. Solar panels are mounted with a clear view to the south at a 30 degree elevation. The Data Logger used is the Campbell CR23 Data-Logger and it functions as the heart of the remote station. This unit operates under user (CSI) developed software to control the function of all other system components, and to record and log the outputs of the sensors for storage and transfer to the transmission system. The Telemetry Transceiver is a satellite cellular phone link which interfaces and transfers data between the Data Logger and LSU. Operating under control of the CR23’s resident program, after each hourly burst data are read from the data logger and transmitted ashore. The Power Controller is operated under control of the data logger, and provides power to the system’s various components when required. Batteries to power the site are sealed, lead/acid batteries of 70 ampere-hour capacity. These batteries are of sufficient capacity for a duty cycle of one data transmission per hour with additional “listening” periods for access to the system from the LSU Receiver. The Solar Panel Array supplies current to keep the batteries charged. The array of four 18 watt panels provides all the power needed for unattended operation. At LSU data are automatically processed and posted on the Internet. Sufficient terminals are set up at LSU so that all data from the offshore sites are processed and posted within one to three hours of measurement. Interface to the network via a dedicated telephone is accomplished through an internally installed Hayes compatible modem. If remotely recorded data needs to be accessed more frequently, the remote station can be called and data transmission requested on demand. 2.6 Fabrication, Testing, Installation and Operation

Once all equipment and material are acquired, fabrication of the remote station and setup of the receiving terminal at LSU is accomplished. Testing is then done, followed by installation at the site. In detail, these events are accomplished as follows: Once fabrication is complete, the remote sites are set up adjacent to the CSI Field Support Group facility on the LSU campus. A two week test is then conducted on the network as a whole, with the following objectives:

a. Testing initial station performance from a hardware and software point of view. b. Testing the communications link c. Verifying battery predicted operational duration under supplemental charging by solar panels. d. Training of operation, setup and service personnel. e. Training of the scientific party in operation of the LSU receiver, and data evaluation.

Upon successful completion of the on-campus test, the remote station

equipment is dismantled, packaged and transported to the various deployment sites. With the station in operation servicing every three months is required to perform routine maintenance and cleaning of the underwater sensors. If problems with the instrumentation are encountered during a service trip, the on site team is able to effect repairs. All anticipated spare units and parts are a part of the service team’s

transportable inventory. Moreover, because data are being reported hourly to LSU, major problems are immediately noticed. If a failure occurs, depending on suitable weather, a service team is on site the next day. Down time, therefore, is minimal. 3.0 WAVCIS Numerical Wave Modeling System

The WAVCIS Numerical Wave Modeling System is comprised of three major components: (1) a database containing all relevant WAVCIS data including processed station data and wave model results, (2) preprocessing routines for the CSI and NDBC station raw data, and (3) an operational wave model for the WAVCIS region. The WAVCIS web site has the capability to retrieve and display all of these data for viewing and analysis. 3.1. Database

All WAVCIS data are stored in a MS SQL Server 7.0 relational database including the bathymetry at various grid resolutions; wind, wave, and water level observations from all CSI stations; wind and wave data from NDBC stations 42001, 42007, 42040, 42041; and the wave model results which include wave height, period, and various directions at all grid cells, and the full 2-dimensional energy spectrum (frequency and directions domains) at grid cells corresponding to the CSI and NDBC station locations. The database resides on a server computer running MS Windows 2000, allowing concurrent read/write access to the database by the CSI and NDBC station preprocessing routines, the operational model, and the web site client.

3.2 Preprocessing of Station Data

Raw CSI and NDBC station data are processed to produce the information required for storage in the database. This is done generally every three hours but produces output at various time intervals. Output includes wind, wave, and water level data for all CSI stations, and wind and wave data for the NDBC stations. 3.3 Operational Model

The numerical wave model was developed based on the WISWAVE program provided by the Coastal and Hydraulics Laboratory (USACOE), though no original WISWAVE code has been retained. The wave model application was developed with MS Visual C++ 6.0 and MS Visual Basic 6.0 and is designed to run on MS Windows 2000. The application accesses the SQL Server database both to retrieve input data (bathymetry, winds, etc.) and to save model results (wave height, period, and direction). The application is object-oriented and designed with a generalized data structure and input/output scheme such that new models (theories) of wave generation and transformation can be added to the system in the future. In this manner, multiple models can be run with the same input data and an indication of the selected model is saved in the database with the results.

The wave model application is driven by four sets of input data: (1) general parameters including the model grid (row and column dimensions and representative cell resolution), frequency range to be modeled, and timestep increment, (2) the bathymetry, which can be updated at given time intervals based on interpolation of the water-level displacements from the CSI station data, (3) wave spectra provided by the NDBC station data and updated at given time intervals which provide the advection source term at the grid boundary, and (4) the winds necessary for local

wave generation, which can be updated at given time intervals based on interpolation of the wind speeds and directions from the CSI and NDBC station data. With the exception of input data set (1) which is set once at the beginning of the model run, each input set can be updated at time intervals independently of the others, though each will usually be updated at each hour of model simulation.

The wave model system produces a set of results at each timestep specified in (1) above, though these results will usually only be saved to the database at every hour, three hours, or six hours of model simulation. A result set includes significant wave height, peak period, average wave direction, sea wave direction, and swell direction at each grid cell. The full energy spectrum at each grid cell from which these parameters are derived is also available at each timestep but will only be saved for grid cells corresponding to the CSI and NDBC station locations, allowing spectral model/observation comparisons.

To date, not all of the above design specifications have been met. Currently, the numerical wave modeling system includes:

?? The MS SQL Server database, with completed schema, running on a workstation not a server.

?? Preprocessing and population to the database of the NDBC station data on a real-time basis.

?? Bathymetry of the WAVCIS region (the Louisiana coast out to the latitude of NDBC Station 42001) at 1000m resolution (1000m in north-south and 1000m in east-west directions).

?? The complete wave modeling application, including an MS Windows 2000 user interface, database access, and numerical processing functions.

Tasks yet to be completed are:

?? Real-time CSI station data are preprocessed but not saved to the database. ?? Bathymetry sets of resolutions as fine as 100m are necessary to resolve the

Louisiana coastline. ?? Routines for interpolation of winds from the CSI and NDBC station data, and

water-level displacements from the CSI station data. These interpolation routines will need to be run in real-time as the real-time station data are written to the database. The interpolated data can but need not be saved to the database permanently.

4.0 Data Products The on line data products are presented below. The URL address is:

http://wavcis.csi.lsu.edu

As shown in Figure 3, the main page showing the location and status of stations is presented. On selection of a station, the page shown in Figure 4 emerges, showing a photograph of the platform and the various measured parameters that can be accessed. The first panel on the left hand side shows the time of last data download, and the scheduled time for the next download. Time is CDT. These measurements are archived for a 24 hour and one month period on the panels below. Examples of several of the data displays are presented in subsequent figures with an explanation of the output. An example of a customized sequence of plots is also

provided (Figures 4 through 14) to demonstrate the flexibility of the data base for use in investigating previous environmental conditions, spills, accidents, etc. A password protected archive for the entire data set collected since the respective stations went online has also been established.

5.0 Benefits of the Program and Continued Effort

WAVCIS is evolving into a state-of-the-art monitoring program, which by virtue will provide a highly unique online information database for multiple uses. It is anticipated that the program presented here will provide numerous benefits to LOSCO for several reasons:

1. In the event of an oil spill a critical question is, “Where will the oil likely go?” The answer to the question is dependent on a knowledge of the present and future currents, waves and wind conditions in the area and will be provided by WAVCIS.

2. Access to accurate real-time information offshore will result in more accurate oil spill trajectories thereby affording an oil spill response team to stay one step ahead of the spill. Given the importance of trajectory modeling to spill response, WAVCIS even in its prototype phase, will rapidly provide critical information that would otherwise take precious hours to obtain by the conventional methods of aerial observations and drifter buoy deployments.

3. WAVCIS is designed with easy public access in mind. Individuals with internet access are able to preview and download data to their computer using one of the commonly available, graphical interface Web browsers in either a tabular or graphical format, depending on their needs.

4. Tabulated data may be downloaded and used to drive circulation and trajectory models for oil spill application.

5. Graphical data may be used by responders and vessel operators requiring a more general idea of current speed and direction for spill response.

6. The WAVCIS website will be linked to the TABS site and other internet links in Louisiana and Texas to maximize potential use (e.g., weather forecasts, Earth Scan at LSU, Southern Regional Climate center at LSU).

7. WAVCIS will also provide information on local currents required for the use of alternative technologies such as dispersants and in-site burning.

5.1 ADCP Wave Gauge Software

WaveView provides a “big picture” view of the wave climate as well as details of individual height spectra and directional spectra. Time-series of significant wave height, peak period, peak direction, water level, and height spectra make it easy to find significant events (Figure 15 for an example).

Figure 3. Location and Status of WAVCIS Stations and Other Hotlinks to Related

Sites

Figure 4. Data Display for Current Conditions, 24 Hour and 1 Month Archive

Figure 5. Display of Significant Wave Height Over the Previous 24 Hours NB: while these data are presented here in metric units, the option of English is also available.

Figure 6. Wave Direction Over the Previous 24 Hour Period. NB: wave direction is “to” and not “from.” Thus, in this example, wave direction is essentially to the north.

Figure 7. Wind Speed Over the Previous 24 Hour Period

Figure 8. Current Speed Over Previous 24 Hour Period

Figure 9. Current Direction Over the Previous 24 Hour Period

Figure 10. Water Level (tide) Over the Previous 24 Hour Period

Figure 11. Wave Height for Previous Month

Figure 12. Current Speed for Previous Month

Figure 13 Current Direction Over Previous Month

Figure 14. Example of a Customized Plot of Significant Wave Height, Wave Direction, Wind Speed and Wind Direction Over a Two Week Period.

Figure 15. Individual Height Spectra and Directional Spectra Obtained from Waves View

Figure 16. Output from WavesMon sSoftware Showing Current Velocity Throughout the Water Column, and Various Wave Parameters by Direction

An additional software package being developed with RDI is Wavesmon. Wavesmon is geared towards real time collection and processing of current and wave data. The displays are designed to make evaluation of the wave field and currents at a glance and are presented in Figure 16. 5.12 Height Spectrum

The ADCP has three different independent techniques for measuring non-directional wave height spectrum. The pressure sensor derived spectrum is a traditional technique, but is limited because the measurement must be made on the bottom. The orbital velocity can be measured up close to the surface then translated to a surface displacement spectrum. This method provides a much better frequency response because the measurements can be made farther up in the water column where the exponential attenuation of wave energy with depth, has not reduced the signal much. The surface track is direct measurement of the surface and is not frequency dependent except for the resolution of the echolocation of the surface. The ADCP has three independent measurements of wave height spectrum. As shown in Figure 17, the close agreement between pressure, velocity, and surface track derived spectra demonstrates the integrity of the data. In addition, redundant measurement also allows one to differentiate between measurement noise and environmental noise.

Figure 17. Three Independent Measurements of Wave Height Spectrum 5.13 Directional Spectrum

The directional spectrum algorithm has several features that are important. The ADCP bins and beams are used as a virtual array of sensors. This provides the many degrees of freedom required describing a potentially complex or sharp directional distribution. In contrast, a PUV or triplet type algorithm can only provide 3 degrees of freedom and only the first three terms in the Fourier series are actually derived from measured data. The array of sensors has a substantially greater aperture than a single point measurement (PUV, Bouy). A larger antenna or array aperture is required to measure finer directional resolution and accurately reproduce narrow

spectra. The Maximum Likelihood Method (MLM) used to construct the directional spectrum allows us to measure multiple directions arriving at the same frequency. The MLM process smears the directional distribution, however by iteratively applying the technique (IMLM), this smearing can be undone. The IMLM technique converges to a directional spectrum that matches the data for a reasonable number of iterations. Experience has shown 1, 2, or 3 iterations sweeps up most of energy back into the peak. The difference between a directional spectrum that was processed with 3 iterations and 20 iterations is small. As shown in Figures 18 and 19, the average directional spectrum is provided in an easily interpreted image. Clearly there is swell arriving from both the north and from the south. One can see the refraction in these data. It appears that the longer wavelengths are refracting more parallel to the coastline, and that the direction at higher frequencies is more representative of the deep-water wave direction.

Figure 18 ADCP Directional Spectrum Data Shows Waves Arriving Simultaneously from the North and the South. Refraction bends the longest waves to the coastline.

Figure 19. This directional Spectrum shows Waves Arriving from Three Different Directions at the Same Time.

6.0 Summary and Program Implications WAVCIS provides a highly unique online information database for multiple

uses. It is anticipated that the program will ultimately provide numerous benefits to oil spill contingency planning including: enhancing cursory assessment of oil spill migration; precision numerical modeling of nowcasts for oil spill trajectories; an important archived data set to skill assess trajectory modeling; real-time environmental conditions for vessel operators involved in the application of dispersants and in situ burning; and, in addition to nowcasts, assist in forecasting conditions and spills for neighboring states. References Beer, T. 1997. Environmental Oceanography. CRC Press. Boca Raton. 367p. Fingas, M.F. and C.E. Brown. (1998). Review of oil spill remote sensing. Spill Sci. Technol. Bull. 4(4): 199-208. Nakata, K., S-I Sugioka and T. Hosaka. (1998). Hindcast of a Japan Sea oil spill. Spill Sci. Technol. Bull. 4(4): 219-229. RD Instruments, 1996. Acoustic Doppler Current profilers: Principles of operation: A practical primer. San Diego, CA. Acknowledgements We gratefully acknowledge the Field Support Group in the Coastal Studies Institute for all assistance in developing the WAVCIS program. Thanks also to Ph.D. students Brian Alleva and David Pepper for assistance in the laboratory and field. Xiongping Zhang assisted in all web-based and data processing, and Mary Lee EggarT and Clifford Duplechin are thanked for cartographic work. This project has been funded by the Louisiana Oil Spill Coordinator’s Office, Louisiana Department of Natural Resources, Coastal Wetland, Planning and Protection Act, Louisiana Board of Regents, Center for Coastal Energy and Environmental Resources (LSU), Federal Emergency Management Agency, United States Army Corps of Engineers, National Oceanic and Atmospheric Administration and the National Park service. We acknowledge the cooperation of Texaco and the Louisiana University Marine Consortium for platform use.