SLICE has been developed by URS as part of the Office of Naval Research project STRATAFORM

MINE PURIAL PROGRAM

MODEL DESCRIPTION QUESTIONAIRE

4/1/02 (completed 4/15/02)

Modeler’s Name and Affiliation: Carl Friedrichs, Virginia Institute of Marine Science, Gloucester Point, VA 23062, email cfried@vims.edu, tel 804-684-7303

Model Name: Scour Burial Conditions Forecast Model

Model Author: Carl Friedrichs and Pat Wiberg

Model Code Developer(s): Carl Friedrichs, Pat Wiberg, Art Trembanis (VIMS), Grace Battisto (VIMS)

Coding Language: Matlab

Computer Platforms Supported: any running Matlab (potentially PC, Mac, Linux, Unix)

Time period for code development: 2002-present

Brief model Description:

SBCF will be a suite of simple parameterized models for forecasting conditions most relevant to scour induced mine burial. Regional NOAA forecasts of winds, waves and tides will be empirically transformed to local conditions. Simple theoretical relations will then used to predict nearbed velocity and bed stress. Next, bed stress and velocity will drive parameterized models for mine burial induced by local scour and bedform migration. The model will be applied to the ONR MBP field sites off Tampa and Marthas Vineyard. Model output will be updated daily and be available to MBP investigators through the MBP website. The model has been proposed as part of a FY 2003 ONR Marine Geosciences planning letter and (as of April 2002) is still in its early stage of development.

Processes Represented and Applicable Coastal Regions:

Initially, SBCF will only be applicable to sandy inner shelf environments where mine burial is dominated by scour and/or small-scale sandy bedform migration. Appropriate depths are from outside the surf zone offshore to the “closure depth” where initiation of sediment motion of sand by wind waves rarely occurs. The model will include forcing by local water velocities associated with waves, tides, and the wind. Sediment will be assumed to be non-cohesive. Scour and bedforms will be predicted by simple parameterized models.

Length Scales and Resolution Constraints:

The model will be applied to local conditions in the immediate vicinity of the mine without horizontal resolution. It will be parameterized such that it will predict overall percent burial rather than varying degrees of burial at various locations.

Time Scales and Resolution Constraints:

Its time step will be on the order of hours. The time-scale of the forecast will be limited by the availability of accurate forecasts of local wind and wave conditions. At present, reasonably accurate forecasts of wind and wave conditions are available five days into the future.

Describe any numerical limitations and issues:

The scour and bedform burial components of the model will be parameterized in order to keep computational overhead to a minimum. The most computer intensive component is likely to be frequent web downloads and updates to keep the model forecasts current.

Required Input:

The inputs which are anticipated to vary in time and from site-to-site are local depth, sand grain size and forecasts of regional winds, waves and tides. Regional forecasts of winds, waves and tides will be retrieved from existing NOAA websites.

Describe Key Physical Parameters:

Additional key parameters will be the empirical parameters inherent to parameterized models for scour burial and bedform development and migration.

Key Output:

Forecasts of near bed wave, wind and tide velocities and associated bed stress. Forecasts of local bedform height and length. Forecasts of percent burial by scour.

Output Formats:

ASCII text files downloadable from the web.

Typical Scenario Run Times and Memory Requirements on Designated Platforms:

Minimal.

Calibration & Test Data Sets:

As many existing laboratory and field data sets as possible documenting mine burial in sand.

Ideal Field Data Set for Testing your Model (Laboratory and/or Field):

MBP field site off Marthas Vineyard.

Are you currently, or do you presently have plans for, collaborating with other MBP investigators?

Collaboration for model development been established with Pat Wiberg and Joe Fernando. Comparison to lab and field observations would benefit from future collaboration with Marcelo Garcia and Peter Traykovski.