Review and evaluation of oil spill models (for application to North Carolina waters)

[From the U.S. Government Printing Office, www.gpo.gov]

Review and'Evaluation of
OU Spill Models
for Application to
North Carolina Waters

Bruce J. Muga
Consulting Engineer
Durham, NC

AUGUST 1982

. . . . . . . . . .

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North Carolina
Coastal Energy Impact Program
Office of Coastal Management
North Carolina Department of Natural Resources
and Community Development

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427
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CEIP REPORT NO. 31
M84
1982
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Series Edited by James F. Smith
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lot

REVIEW AND EVALUATION OF OIL SPILL MODELS

(for Application to North Carolina Wate

Bruce J. Muga
Consulting Engineer
-Durham, North Carolina

too

Prepared for

Office of Natural Resources Planning and Assessment
N. C. Department of Natural Resources and Community DO-velopment
-SE

tz
The preparation of this report was funded by a Coastal Energy
Impact Program grant f.-om the North Caroliz,.a Coastal Management
Program, through funds provided by the Coastal Zone Management
Act of 1972, as amended, which is administer,2d by the Office of
Coastal Zone Management, National Oceanic and Atmospheric
Administration. The CEIP grant was part of NOAA grant
NA-79-'AA-D-CZ097.

August 1982

CEIP Report No. 31

Acknowledgements

This study was funded by a'grant from the

Coastal Energy Impact Program (CEIP), Department of

Natural Resources and Community Development (DNRCD),

In particular,.the author wishes to acknowledge.the

efforts of Mr. Jim Smith, CEIP Coordinator, Office of

Coastal Management, DNRCD, and Mr. Roger Schecter,-Chief,

Permit Information and Assistance Section, Office of

Planning and Assessment, DNRCD, Mr. Smith arranged for

this particular study to be undertaken following

co mpletion,of the objectives of an earlier study under

the original grant. Mr. Schecter served as Contract

Monitor and was very helpful in securing certain

references. The author also wishes to acknowledge the

help of Mr. Eric Vernon, Office of Marine Sciences,

Department of Administra tion, who provided 'Some important

but difficult to obtain references.

Finally, the author appreciates the help of

Ms. Anne Taylor, Director of the Office of Planning and

Assessment, DNRCD. Ms. Taylor completed all of the

necessary but burdensome paperwork to ensure availability

of funds for the original grant objectives.

The encouragement, help, patience and under-

standing of all of the aforementioned personnel is greatly

appreciated.

Executive Summary

A review of the general status of oil spill

modeling is presented. The major processes of*importance

to oil spill motion are advection, spreading, dispersion

and evaporation. The relative importance of each of the

processes is depicted on a time-length diagram. This

diagram is also employed to indicate those processes

that are most important to the various North Carolina

waters. The relative importance of these processes, in

effect, dictate the model requirements.
it was-found that approximately twenty-five

distinct modeling efforts have been undertaken in recent

years. Summary information for each of these processes

are presented in the Appendix. A number of these models

were found to be suitable for adaptation to the offshore,

nearshore and inland and estuary waters of North.C arolina.

For each category, those models that are best suited are

identified. Finally, some recommendations regarding

prediction of oil slick behavior in North Carolina

waters are presented.

CONTENTS

Chapter Page

1 Introduction 1

2 Background . . . . . . . ... . . . . . . . 4
Problem Formulation. : . . . . . . . . 7
Spreading and Dispersion
model Solution . . . . . . . . . . . 11

3 Review of Literature . . . . . ... . . . . 17
Advection . . . . . . . . . . . . . . is
Wind . . . . . . . . . . . . . . 20
Surface Currents . . . . . . . . 23
Subsurface Currents . . . . . . 25
River Currents . . . . . . . . . 25
Waves . . . . . . . . . . . . . 26
Spreading and Dispersion . . . . . . . 26
Evaporation . . . . . . . . . . . . . ... 32
4 Evaluation of Oil Spill Models
for Use in North Carolina Waters . . . . 35
Inland Waters and Estuaries . . . . . .. 44
Nearshore . . . . . . . . . . . . . .. 46
Offshore . . . . . . . . . . . . . . . . 49
5 Summary and Conclusions . . . . . . . . . 54

Recommendations . . . . . . . . . . . . . . . 56

References . . . . . . . . . . . . . . . . . . . . 59

Appendix . . . . . . . . . . . . . . . . . . . . . . 60

List of Tables

Table Page

I Processes of Importance to the
Oil Spill and Transport Problem . . . . 6

II Spreading Laws for Various Regimes
According to Fay (1971) . . . . . . . . 12

III Oil Spill Models . . . . . . ... . . . 19

IV Wind Field Model Types . . . . . . . . . 21

V Types of Spreading Models . . . ... . . 28

VI Classification of Evaporation
Submodels . . . . . ... . . . . . . . . 33

VII 'Candidate Models.for Application
to North Carolina Waters . . . . . . . . 43

List of Figures

.Figure Page

1 Time-Length Stale Diagram for
Determination of Relative
Importance of Various Processes . . . . 15
2 Time-Length; Scale Diagram for
Evaluating Relative Importance
of Various Processes . . . . ... . . . 38

Chapter 1

Introduction

Recent interest in exploratory drilling for

hydrocarbon deposits off the coastlines of North Carolina

and neighboring sta tes has disclosed the need to under-

stand a number of environmental risks attendant to this

activity. Among the most important of these risks is the-

spillage of liquid hydrocarbons. Since risk is the

product of the probabil ity of occurrence of an event

and its'effect (should the event occur), the transport

mechanism's'of spills is a topic of critical interest.

This topic has been the object of numerous

studies in recent years. These studies have resulted

in the development of various'models for predicting the

movement of spills. Each of these models was developed

for a particular set of conditions. The result is that

no reliable prediction scheme has yet evolved which is

applicable to a general set of conditions. It is note-

worthy to mention that develoPment of such a scheme is

a formidable task.

Therefore, the main focus of this study is an

evaluation of the methods for predicting the movement

of oil spills under the particular environmental

conditions that exist in North Carolina waters. Although

the idea for this study stems from the potential drilling@

activity offshore, our interest in models for Predicting

spill movements is not limited to these occurrences.

To a parallel degree, we are interested in methods for

predicting spills that occur in connection with the

transportation and transfer of hydrocarbons,within and

adjacent to North Carolina waters. For example, methods

for predicting the movement of spills that occur in ports,

harbors and/or estuaries as well as along the adjacent

transportation routes of North Carolina, are also of

concern.

In response to the various needs, oil spill

models have evolved along two.separate paths. The earliest

models were developed to predict one-of-a-gind events

occurring in real time. These are after-the-fact models
and'depend upon reliable wind and current forecasts for

achieving even moderate success., Most frequently, these

models were roughly calibrated from real observations

taken during and following a spill. Such models, of

necessity, are programmed to accept real time data as

input. With the passage of time, other model types were

developed in connection with the evaluation of various

impacts. These models are much more sophisticated than

the earlier models and are designed to assist decision

makers in the environmental assessment and planning

processes. These models use the historical climatological

data as input and are programmed to generate sufficient

data to disclose all possible consequences of an event.

For other fundamental reasons, the former and

latter models tended to be deterministic and probabalistic

in nature, respectively. This characteristic will be

examined in more detail in the following section.

Bishop (1976) has categorized the model types according

to Type I, Type II or Type III, which he describes as

follows:

"Type I models: Multiple trajectory models

for long-term strategic forecasts based on

archived data.

Type II models: Single event (highly structur

models for specific day-to-day tactical forecasts

usually based on up-to-date data, and
Type III models: Type I or Type' II models

implement ed in a receptor (reverse) mode such

that one can project areas from which trajectories,

would impact resources."

We see that, Type III models are not really a

separate category but rather a unique application and use

of either Type I or Type II models. It is also interesting

to observe that the sequence of presentation is actually

the@reverse of the historical development. In other words,

Type II models evolved and preceeded the development of

Type I models.
3

Chapter 2

Background

There is a substantial volume of literature

dealing with oil spills, most of it of recent origin.

Surprisingly, there have been only a few attempts to

review the literature in a systematic manner within a

comprehensive framework of the overall problem. The

work by Stolzenbach, et.al. (1977) is an important

reference in this regard. Most of the studies as

published,in the open literature treat only one aspect

of the overall problem in an isolated context and often

under a narrow combination of circumstances that make it

difficult to apply the results to other situations with

reasonable confidence.

It is instructive to make a few preliminary

observations in connection with,the treatment of the

oil spill problem. This is a general problem in the

field of fluid mechanics, the solution for which requires

a broad understanding of chemical and biological processes.

The solution can be approached in one of two fundamental

ways; i.e., probabalistic or deterministic.

Because of the fact that (1) the environment

(i.e., winds, waves and currents) has an enormous

influence on the spill behavior, and (2) the environment

is a geophysical random process, one would expect that

the approach shoul d be a probabalistic one. In other

words, the solution approach should be compatible with

the nature of the problem. On the other hand, there are

some features of the problem which are decidedly deter-

ministic. An example would be the spreading of oil on a

quiescent sheltered body of water in the absence of any

winds, waves or currents. Also, the approaches are not

mutually exclusive since elements of deterministic methods

can be and are incorporated within probabalistic-based

approaches and vice-ver sa. In reviewing the literature,

it is important to recognize the existence of these two

fundamental solution methods.

In view of the'.realization that the probabalistic

nature of the problem derives from consideration of the

environmental influences (which have regional 'geographic'

dependency) and that the,determinist.ic influence is

based on the physical mechanics of the problem, we can

identify two broad categories of processes which are of

importance to the oil spill and transport problem. These

processes are depicted in Table: I, with some explanatory

notation.

The spreading and dispersion processes are, to

a large degree, geographic-independent, but are, neverthe-

less, dependent upon certain characteristics of the event

TABLE I.

Processes of Importance to the Oil Spill
and Transport Problem

Process Nature Dependency

Spreading Deterministic Oil properties at ambient
temperature, largely site
dependent

Dispersion Deterministic Turbulence intensities in
(with probabalistic water medium, weakly site
elements) dependent

Advection (Drift) Probabalistic Strength of advecting
(wind, currents; D@aves) (with deterministic fluids, strongly site
elements) dependent

Weathering and Other Probabalistic Various site dependent
Processes and Deterministic and site independent
biodegradation conditions
dissolution
emulsification
evaporation
oxidation (photo)
patch (large-size)
breakup
sinking and
sedimentation

OCLC: 10114549 Rec stat: n
Entered: 19831110 Replaced: 19950322 Used: 19941105
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Repr: Enc qtvqt: I Conf pub: 0 Ctry: ncu
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Desc: a Int qLvqL: Festschr: 0 Iqtqtus:
F/B: 0 Dat tp: s Dates: 1982, %
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$ 7 100 1 Muga, Bruce J. Iq (Bruce Jennings) %
S 8 245 10 Review and evaluation of oiql spiqLqL models (for application to
North Carolina waters) / Ic by Bruce J. Muga. %
S 9 260 Raleigh, N.C. : lb Coastal Energy Impact Program, Ic 1982. %
$ 10 300 107 p. ; Ic 28 cm. %
$ 11 440 0 CEIP report ; 1v no. 31 %
S 12 500 Prepared for office of Natural Resources Planning and
Assessment, N.C. Department of Natural Resources and Community Development. %
S 13 500 "August 1982.11 %
S 14 504 includes bibliographical references. %
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$ 18 710 1 North Carolina. lb Coastal Energy Impact Program. %
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such as spill size, rate of spill and other physical and

chemical characteristics which describe the spill material

and receiving waters. In contrast, the advection (drift),

weathering and other processes are directly related to

and dependent upon conditions that characterize the site

environment at the time of the spill and immediately

thereafter. In other words, the processes which characterize

oil spill movement consist of both site-dependent and

site-independent ones. A brief review of the various

processes governing the mechanics of the problem is

presented in the following section.

Problem Formulation. Stolzenbach, et.al.(1977)

have formulateCthe' essential boundary value problem for

oil slick transformations. The system of differential

equations were derived on the basis of some simplifying

assumptions and averaging approximations. The simplifying

assumptions seem to be well justified and are used to

some degree in all of the models that have been developed

and reported in the literature. Therefore, any error due

to the simplifying assumptions would not affect any

relative evaluation of the various models. With regard

to the averaging approximations, Stolzenbach, et.al. (1977)

states that it is justified "only for the'analysis of the

oil motion and may not be a good approximation for studying

the diffusion of oil through the slick boundaries."

The continuity equation which expresses the

conservation of mass relationship appears@as

@C-ih @uc @v@@c a a7F + a
-+ + k IT (h -) ay (h Lc)
at ax ay i x ax ay -Osi -Obi

The conservation of momentum relationship appears as

p -P
au + - au - au W ah b2E + sx
at U ax + V Ty 9 Tx Th ph
p

p -P
av + - 9v + -:--.Lu.= W Dh 'by'+ 'SY
at U ax V ay 9 p Ty ph ph

The boundary.condition on the slick boundary appears as

fn CF aw aoa a ow (3)

In the above equations,

x,y = variables of moving coordinate system
with respect to origin at center of
mass of oil slick

u,v = components of oil particle velocities
relative to the center of mass of'the
slick

C. = mass per unit volume of oil of the
1 ith oil fraction

h = local slick thickness

ki = molecular diffusion rate for ith oil
fraction within the slick

Ri = rate of removal of the ith oil fraction
per unit volume

@si = flux of the ith oil fraction outward
through the surface of the@slick
Obi flux of the ith oil fraction outward
through the bottom of the slick

p average density of oil mass within the slick
PW = density of water underlying--the oil slick

t = time

T T = shear stresses on oil slick surface
sl@- sy
Tbx'T b;y= shear stresses on oil slick bottom
g = acceleration due to gravity

fn = net surface tension per unit length
of oil slick boundary

a a a, = surface tension of air-water, air-oil
awl oa' ow and oil water interfaces, respectively

Equations (1) through (3) constitute, in a

simplified form, the boundary value problem of oil slick

transformations. In relating the physical processes

shown in Table I tc the various terms in the system of

equations, we can point out that the effects of weathering

(and other processes) are treated indirectly via the

concentration term C i for the different oil components
and directly by the last three terms of,Equation (1).

We can also note that the motions (,i,e., particle velocities

u and v) are given relative to the center of mass of oil.in

the slick. Therefore, motions resulting from the advection

processes (appropriate for the center of mass of the slick)

must be superposed on the.relative velocities to determine

the motions in an absolute sense.

In a preliminary review of the literature, we

found that models for the spreading, dispersion and

advection processes have been developed and compared

with model and Drototype data to a sufficient degree to

enable some reasonable conclusions and evaluations to be

made. Except for evaporation, this is not the case for

other weathering processes which remain incompletely
understood. Moreover, the interactions between weather

ing and the other processes is even more poorly understood.

As a consequence, the scope of this study is limited to

an assessment of the spreading,,dispersion and advection

models and their applicability to North Carolina waters.

In addition, some comments concerning evaporation models

and models of other weathering processes will be provided

but it is beyond the scope of the present study to consider

such models on the same level with spreading, dispersion

and advection models,

Spreading and Dispersion Model Solution s.

Returning to the fundamental system of equations, different

solutions can be obtained depending on the type of additional

simplifications that can be made. As indicated by

Stolzenbach, et.al. (1977) two broad categories of solutions

can be identified. These are the spreading and dispersion

solutions. The distinction between these two processes

(and solutions) depends upon the relative strength of the

external shear stresses acting on the oil slick. If the.

external shear forces (i.e., the last two terms of

Equations (2)) are absent,or negligible, then the solution

corresponds to the spreading.process since the resulting

motion depends upon the density differences and inter-

facial tensions. On the othe-r hand, if the external

shear forces are very large, then the solution corresponds

to the dispersion process.

Most2 if not all, of the spreading solutions

appear to be based on or related in some way to the work

of Fay (1969, 1971). Two sets of results have been

oktained which are based on certain idealistic assumptions

The one-dimensional set of results is appropriate when it

is assumed that the slick spreads in one direction only,

The two-dimensional case is based on radial spreading.

A summary of the spreading functions for the two different

sets of results is given in Table II. These functions

TABLE II

Spreading Laws for Various Regimes
According to Fay (1971)

Regime Spreading Formula
(Driving/Resisting Force) One-Dimensional Radial

Gravitational/Inertial L = kZ1 P PP gAt D 2k, Pw-P gvt2i 4
w P w

3
p p 3 P P 6
L k (-PW,,-P) At T/V 1-21 D 2k Pw_' V2
Gravitational/Viscous Z2 r
PW PW
Surface Tension/Viscous L k a 2 t3/p 2V D 2k [,Cr2t3/ 2
Z3 W r3 P@ V1

where Pw = density of water
P, = density of oil

9 = acceleration of gravity
L = length of one-dimensional oil spill from fix@d origin
to leading edge of oil slick solubility

D = diameter of radial (axisymmetric) spill

A = volume of oil per unit length normal to spill direction

V = volume of oil

V = kinematic viscosity of water

a = interfacial tension

t elapsed time from initial spill

From various sources, the coefficients k. may have the following values:

k; = 1.5 kr = 1.14
=t.98
kk = 1.5 kr 1.12@
2 z .45
kZ3 = 1.33 kr3 = 1.60

are presented with he unknown length (distance from

leading edge to center of gravity of spill) in an

explicit formulation. The other known or assumed

variables appear on the right-hand side (RHS) of the

equation.

The dispersion models result in the following

solution form:

4qm 4qx2
h exqIqD 2
27rqp8qa 8qX.a6qY 28qa0qx 4qC6qy 6qH6qY22

where

h average spill thickness

0qM =-to tal slick mass

p = density of oil

aqjad a and a are related to the dispersion coefficients,
4qX 6qy
respectively, as follows

q94qa 2 q34qa I
x 2k and qY 2k
q3qt 8qx at 2qy

As noted by Stolzenbach, et.al. (1977) observations

of real oi 1 slicks rarely fit the assumptions made in

formulating the spreading/dispersion models. Thus, compari-
sons between observations and predictions tend to be mixed.

As a result of this behavior, Stolzenbach, et.al. (1977)

conclude that

1. Both spreading and dispersion processes

may be important in determining the total

growth of the slick.

2, Existing techniques for estimating the

growth of surface oil slicks provide at

best only an order of magnitude estimate

of what the actual slick size will be.

3. Because of the complex and usually random

nature of the processes controlling slick

growth, it is unlikely,that a significant

improvement in deterministic capability

will be possible.. However, estimates of

the variance in slick sizes should become

more accurate as additional observations

are obtained.

4. The applicability of available@spreading

and dispersion models should be judged

on a case by case basis in terms of the

site specific conditions."

The usefulness of the modeling work as well as

Stolzenbach's, et. al. (1977) review lies in their develop-

ment of a time and length scale diagram, as shown in

Figure 1. Such a. diagram enables one to determine the

relative imp ortance of the various processes which affect

Hour Week Month Year
10 100 10001 104 105 106 107 108 Time
S@reading (seconds)
Evaporation Dispersion
Emulsification
Dissolution Other weathering
10 Vertical Dispersion processes

100
s4xct.
GROW,

3
10 Atmospheric
Boundary Layer
Fluctuations

104 Mesoscale Wind
Fluctuations

5
10
lm@sec 10 cm)sec 1-cm%/sec .1cm"/sec
106 Advective Velocities
Weather
Length System
Scale -Fluctuations
Advective Velo,
rWeather
Syst erik

(meters)

VICURE I Time-Length Scale Diagram for Determination
of 1@eiatlve Importance o@-. Various Processes
(After Stolzen'bach, et.al., 1977)

oil spill motions. This diagram clearly shows that

spreading is important during the early stages (or,

alternatively, over shorter distances) of a spill

whereas the opposite is true of dispersion, Other

processes are also indicated. An example of the use

of such a diagram in the case of selecting appropriate

models for North Carolina waters will be indicated in

Chapter 4.

Chapter 3

Review of Literature,

As noted in the introduction, there has been an

enormous volume of literature published within recent

years on the subject of oil spills. Approximately.

200 references constituting roughly 15% of the available

number of articles have been consulted in connection with

this report. Only a small number of these references

are cited in the bibliography, however, since many

references deal with the topic in only a peripheral way.

From these references, about 25 distinct modeling efforts

have been identified. For each of these efforts, a summary

report has been prepared identified by the model name and

citing the primary reference and accompanying abstract

along with the reviewers comments. These summary reports,

one for each modeling effort are presented in the Appendix,

In this section, a summary of the reviews is presented so

that the reader can gain a panoramic view of the current

status of oil spill models, To reiterate, our main

emphasis is concerned with advection, spreading, and

dispersion processes and with evaporation. For reasons

discussed in the introduction, less emphasis is placed on

other weathering processes. Also, we are concerned with

application of these models to North Carolina waters.

For that reason, a number of Canadian sources were not

consulted since, in many cases, they deal with Artic

conditions.

A satisfactory means of classifying models is

to take note of the 'processes that the model considers.

This has beeft done by Stolzenbach, et.al. (1977) and is

presented herein as an update in Table III. Discussions

are presented in the following paragraphs for each of the

major processes that are of interest to this study.

Advection. Advection is probably the most

important process by which oil spills are transported

over any sensible distance, and is treated by every oil

spill model-that was reviewed. Advection occurs as a

result of'wind and currents and to an unknown extent,

waves. Both wind and currents induce shearing stresses

on the top and bottom surfaces, respectively, df the oil

slick. These shearing stresses, in turn, cause the oil

slick to move. Because of the fact that the shearing

stresses are not, in general, uniform (or constant), the

oil slick experiences not only a net motion of its center

of mass but also differential motions of the oil slick

geometry about its center of mass. As a matter of fact,

the shearing stresses are, in the general case, time and

space dependent.

TABLE III

OIL SPILL MODELS
(Listed According to Date of Origination)

Model Name Date Processes Modeled*

1. U.S. Navy 11970 Advection
2. WGD Advection
3. Narragansett Bay 1973 Advection, Spreading
4. Tetra Tech, Inc. 1974 Advection, Spreading, Dispersion
5. CEQ 1974 Advection
6. BOSTM 1975 Advection, Spreading, Dispersion
7. USCG 19,75 Advection, Dispersion
(New York Bight)
8. Delaware Bay 1916 Advection, Spreading, Dispersion
9. USCG Advection, Spreading, Dispersion
(New York Harbor)
10. USC/API' 1977 Advection, Spreading, Dispersion,
Evaporation
11. SLIKTRAK 1977 Advection, Spreading, Dispersion,
(SLIKIFORCAST, Evaporation
OILSIM)
12. MOST 1978 Advection, Spreading, Dispersion
13. DPPO (Garver- 1978 Advection, Spreading, Dispersion,
and Williams) Evaporation
14. URI 1979 Advection, Spreading, Dispersion,
(Georges Bank) Evaporation
15. Puget Sound 1979 Advection, Spreading
16. CAES 1979 Advection, Spreading, Dispersion,
Evaporation
17. Riverspill 1979 Advection, Spreading
18. -NIVS/NOAA 1979 Advection, Spreading
19. USCG (Long 1980 Advection, Spreading, Dispersion'
Island Sound)
20. SPILSIM 1980 Advection
21. EDIS 1980 Advection, Spreading
22. PIC 1980 Advection, Spreading, Dispersion
23. OSTA 1980 Advection
24. OSSINI 1980 Advection, Spreading, Dispersion
25. DRIFT 1980 Advection, Spreading, Dispersion,
Evaporation

Weathering processes other than evaporation
are not listed.

Wind. A substantial effort has been devoted to the

development of wind field and current submodels. One

of the distinguishing features of oil spill models is

the degree of realism that has been incorporated into

their wind and current submodels. In the case of wind

models, this degree ranges from the simplest and crudest

approach to the most elegant and sophisticated. At least
FM
three different categories can be identified. These

include constant wind fields, time and spatially dependent

wind fields.

Table IV'is a listing of the types of wind field F1

input that is programmed for oil spill models that were

reviewed. A majority of the models can be operated to

accept eith er measured (or-real time data) 6r simulated

data. The measured data is, in general, time and spatially
dependent but this may not be a meaningful ch'aracteristic

if the grid size is large or if the elapsed time between

observations is long both relative to the volume of the

spill. The simulated data input capability is useful for

conducting contingency planning environmental assessment

studies.

As noted above,-the simulated wind field submodels

can be highly variable in complexity. However, the degree

of complexity is not an assurance of suitability for a

particular site dependent oil spill. Even a simple

TABLE IV

WIND FIELD MODEL TYPES

Oil Spill Simulated Other Measured
Model Name
Constant Time Dependent Spatiallyi
Random Markov Dependent
Walk Chain

1. U.S. Navy x x
2. wGD x
3. Narragansett x x
Bay .
4. Tetra Tech, Inc. x
5. CEQ x x
6. BOSTM x x
7. USCG x
(New York,Bight)
Delaware Bay x x
9. bSCG (New York x
Harbor)
10. USC/API x x
11. SLIKTRAK x x x
(SLIKFORCAST,
OILSIM)
12. MOST x
13. DPPO (Garver x x
and Williams)
14. URI x x
(Georges Bank)
15. Puget Sound x
16. CAES x x
17. Riverspill x x
18. NWS/NOAA x x
19. USCG (Long x
Island Sound)
20. SPILSIM x x
21. EDIS x
22. PIC
23. OSTA x x
24. OSSM x
25. DRIFT x x

constant wind field under a given set of circumstances

might be quite proper for predicting advection. Time-

dependent submodels consists of "random-walk" models,

for which there is no correlation between successive time-

steps, andautoregressive models (Markov chain) for which

there is limited correlation in time between successive

time steps. Most natural processes such as wind are

continuous functions of time, thus, Markov chain models

appear to be the superior type of time-dependent simulation.

However, wind is a'-so a spatially dependent function. A

number of models have been developed or are in the process

of development which simulate the w';.nd on the basis of r

its spatial dependence. These models are the most general

and represent the most,sophisticat ed of all types of wind

simulation models. Finally, a few models employ wind
field models that do not fit any of the above'-categories.

They are listed under "other" on Table IV. In 'some cases

there was insufficient information to categorize the wind

field submodel.

In nearly all cases (the CAES model being the

only exception) the determination of wind drift currents

follows the wind factor approach. In this approach, the

wind-induced surface current is assumed to be a fixed

percentage of the wind velocity taken at a height of

10 meters above the sea surface. Often a value of 3% is

assumed but this value can range from 2.0% to 4%. These

values have-been estimated from numerou s observations and

experiments. In at least two references, Madsen (1977)

and Huang (.1979), show theoretically that this factor

should be slightly in excess of 3% for@deep water. The

angle between the wind vector and the wind induced current
v@ctor is known as the wind drift angle. This angle has

0 0
been taken to vary from 0 to approximately 20 depending

on latitudinal influences. Huang (1979) also shows that
the wind drift angle can vary from 00 to a maximum (which

depends upon'the latitude) depending on the duration that

the winds have been blowing. This angle also depends
on the wate@ depth and approach a value.of o' for very

shallow water.

Surface Currents. Although wind-induced drift currents

are important mechanisms in the transport of oil slicks,

they ar e not the only ones of importance. Therefore, we

must examine. the role of residual and tidal currents as

well as waves. The residual currents include those

circulations due to *t hermohaline and geostrophic causes.

In general, the residual currents are most important for

open ocean spills in deep water whereas the tidal currents

are most important for near inshore and estuary (tidal)

spills in shallow confined waters. In many models, both

residual and tidal currents are considered together and

a procedure similar to the wind factor approach is employed

to estimate the surface drift current. The factormost

often used has a value of 56%. Many models are structured

to utilize information on currents as obtained from

prototype measurements or from estimates obtained from

circulation submodels. The circulation submodels are

often major components in the oil spill transport prediction

procedures.

The numerical circulation submodels are not true

three-dimensional models; rather they are two-dimensional

representations obtained by ma,king certain simplifications.

Among others, these simplifications include the averaging

(in the vertical) of the component velocities. This

averaging presents some difficulty in estimating the F

surface currents especially in regions iheire the wind and

tide are the dominant contributors to the circulation

pattern. Another difficulty is related to the.'model

boundaries especially whe re there is an interface with

major large scale circulations systems such as the

Norwegian current or the Gulf Stream. With the exception

of SLIKTRAK, none of the models attempt to model the

large scale circulation Dattern. SLIKTRAK attempts to

model the effect of the Norwegian current by providing

for acceptance of predicted values of velocities

(presumably obtained from another submodel) at the model

bounda ries.

The state-of-the-art consists of calibrating

the numerical circulation submodel with available field

measurements. The resulting currents predicted from

such a model are then combined with wind-induced drift to

estimate the advection.

Subsurface Currents. Because of the fact that oil

spills generally appear on the surface, little attention

has been directed to the advection by subsurface currents.

It is generally believed that subsurface advection is not

an important mechanism;.in oil slick transport. However,

it is known that advection of dispersed oil droplets occurs

as a result of subsurface currents. Two models include

this behavioral feature. One is the DPPO model (Garver

and Williams,1978) and the other is the URI (Georges Bank)

model.

River Currents. Even though a large number of spills

occur in river estuaries or harbors where there is

substantial fresh water inflow as well as other currents,

this aspect of oil Epill transport has received little

attention. One model, Riverspill, was developed specifi-

cally for river-type spills (Mississippi River).

Considerable effort has been directed toward determination

of advection by river currents. Another model,, USCG

(New York Harbor) has also been developed to consider

the fresh water inflows from the Hudson River. Both

models have been calibrated by comparison with numerous

field observations.

Waves. Advection by waves directly or by currents

generated by waves is one of the least understood aspects

of oil spill transport. Some authors believe that it is

an important mechanism but only three models (SLIKTRAK,

Delaware Bay and USC/API) have recognized the possibility

of considering its effect.

in summary, advection is one of the most

important processes by which oil spills are transported.

The prediction of advection resolves into a determination

of the wind,and current fields. From a knowledge of the

wind and current fields, a number of numerical techniques

have evolved from which advection of oil spills can be'

made. The role of subsurface currents is probably not

important in transport of large oil slicks but.,very.

iMDortant in advection of oil droplets. The contribution.

of waves to the advection process is very poorly.understobd.

Spreading and Dispersion We consider

Spreading and dispersion together'since these mechanisms

are responsible for the growth of an oil slick after the

initial spill. During the initial stages, spreading is

Not to be confused with emulsification or oil-in-water

formulation of.droplets.

clearly the most important of these mechanisms. Spreading

is dependent upon the oil properties at the time of the

spill whereas dispersion depends upon the external shear'

forces acting on the oil spill surfaces. A number of

investigators (e.g., Stolzenbach., et.al.,.1977) have shown

that, for a given spill volume, after a certain time, the

dispersion process becomes more important than spreading.

There are essentially three distinct approaches

that are employed in the treatment of spreading and

dispersion. Table V presents a listing of the spreading

submodels that have been employed by the oil spill models
that were .available for review.. Most of the models that
treat spr@ading do so by using a method that is related

in some way to Fay's (1971) Iheoretical analysis of

spreading. Some models combine Fay's spreading analysis

with a diffusion approach. Other models consider the

growth of oil slicks to,be dominated by diffusion'aspects

and ignore altogether the role of the oil properties

such as surface tension. For example, the Delaware,Bay,

model substitutes a diffusion equation in lieu of the

third stage (viscous-surface tension) of Fay's (1971)

three-regime spreading model. As anothe r example, the

USC/API model eliminates the second stage (gravity-viscous)

of Fay's (1971) model altogether. As mentioned above,

a few models treat -k-.he growth of oil slicks solely by

ion

TABLE V

TYPES OF SPREADING MODELS

Oil Spill Fay's Fayls Diffusion Independent
Model Name Spreading Spreading, Theory Statistical
Theory / with or Numerical
Diffusion Treatment

Narragansett Bay x
T.etra Tech, Inc. x
BOSTM x
1jSCq x
(New York Bight)
Delaware Bay x
USCG x
(New York Harbor)
USC/API x
SLIKTRAK
(SLIKFORCAST,
OILSIM)
MOST x
DPPO x
(Garver and Williams)
TJRI x
(Georges Bank)
Puget Sound x
CAES x
Riverspill x
NWS/NOAA x
USCG (Long x
Island Sound)
EDIS x
PIC ?
OSSM x
DRIFT x

means of a.diffusion theory such as that'developed by

Murray (1972) or a random Fickian diffusion model.

The rationale for this is based on observations of oil

spills that are continuous ly discharging (i.e., versus

instantaneous spills) wherein it was concluded

(Murray, et.al. 1972) that the growth a short distance

from the source, was controlled by the horizontal eddy

turbulence rather than surface tension effects. For

example, the USCG models use Murray's turbulent diffusion

theory while DRIFT uses a random Fickian diffusion

approach.

One approach which is decidedly deterministic
is the NWi/NOAA model wherein a numerical solution of

the equations of motion (oil) is envisioned. At the

opposite end of the philosophical spectrum is the
Pudget Sound model which is best.described as.an indepen-

dent statistical (probabalistic) model. It is based on

the use of a system of empirical regression equations.

In this connection, all of the models that treat spreading-

dispersion with a diffusion theory in any way require

some evaluation of a set of diffusion/dispersion

coefficients. In general, these coefficients must be

obtained empirically or from published values which

have been obtained from experiments. In some cases,

where there are actual observations of oil spills, the

diffusion coefficients have been employed as calibration

coefficients. This is illustrated by the USCG (New York

Harbor) model.

From a theoretical viewpoint, those models which

treat spreading-dispersion by use of Fay's spreading theory

in combination with a diffusion approach are probably

superior to the other approaches. However, all of these

models do not treat spreading-dispersion in the same way

because there are some subtle, minor differences in their

procedures which may have profound consequences in the

results. As a general obs'ervation, none of the models

contain any provision for eliminating or evaluating the

'numerical errors that may be present. This is an important

consideration in the treatment or diffusion/dispersion

because of the possible contamination of the real

physical dispersion with numerical dispersion. The latter

is merely an artifact of the computational scheme whereas
the former is real. This is cl@arly illustrated in the

case of the Tetra Tech, Inc., model about which

Stolzenbach, et.al. (1977) has commented in some detail.

One interesting treatment of spreading-dispersion

is the Delaware Bay model in which the third phase of Fay's

three-regime spreading model is replaced by a compatible

diffusion model. The justification for making this

substitution stems from the observation that whereas the

third phase exists in laboratory situations (where the

background turbulence levels are low), no such conditions

exist in the real world. Therefore, in the prototype case,

the higher turbulence levels require the existence of

a diffusion approach. This justification seems very

rational and plausible and is consistent with Murray's

et.al. (1972) observations and conclusions.

In summary, spreading-dispersion is an important

mechanism for the transformation and/or growth of oil

slicks. In the early stages, spreading is the dominant

process whereas after a critical time (for a given volume)

disper:gion seems to predominate. Models which seem best

suited for'a wide variety of time-dependent situations

are those which combine Fay's spreading theory with a

diffusion approach. Two extreme cases can be noted.

In confined nearshore areas, where the,time and distance

scales are relatively short, a model which employs only

Fay's spreading approach would be quite valid. In a

similar way for regions where the time and distance

scales are relatively long, such as far offshore, a model

which employs only a diffusion theory would be valid.

In the case of the latter, an independent statistical

or numerical approach might also be considered. In

any of the diffusion-statistical- or numerical-based

submodels, the degree of numerical diffusion (or dispersion)

should be determined.

Evaporation. Although evaporation is known

to be an important factor in the fate of oil spills -

especially in the case of spills far offshore, it has

received less attention from modelers than the other

processes. Only six (6) of the models reviewed include

an evaporation submodel. Moreover, because evaporation

usually occurs in the presence of other weathering processes

such as photo-oxidation, dissolution, biodegradation and

sinking and sedimentation, it is difficult to make

reasonable evaluations concerning the appropriateness

of the evaDoration submodels,. Of the oil spill models

reviewed, there seem to be no essential differences in

the manner in which evaporation was estimated. In
genera.l,. an evaporation function or d'ecay rate is derived

from the main factors which affect the evaporation.

These include: (1) the vapor pressures of the various

oil fractions, (2),the size of the spill (area and

thickness), (3) the evaporative mass transfer coefficient,

and (4) the environmental (climatic) conditions, including

wind speed.

All of the submodels employed a mass transfer

coefficient but some did not consider the spill area or

slick thickness in their evaluations. These.are indicated

in Table VI. Also, the basis for the submodel can be

categorized as being empirical; experimental- or

theoretically-related. These are also indicated in Table VI.

TABLE VI

CLASSIFICATION OF EVAPORATION SUBMODELS

Oil Spill Type Area Slick
Model Considered Thickness
Reviewed Considered

USC/API Theoretical

SLIKTRAK (includes Experimental X X
SLIKFORCAST AND
OILSIM)

DPPO (Garver Empirical
and Williams)

URI Empirical X
(Georges Bank)

CAES Experimental X X@

DRIFT Empirical X

In summary, only a few models attempt to

evaluate evaporation in spite of its importance to the

ultimate fate of oil spills. Unfortunately, there is

insufficient data to permit a rigorous evaluation of

the various approaches.

Chapter 4

Evaluation of Oil Spill Models
for Use in North Carolina Waters

In order to select a suitable model or family of

models for/predicting oil spill behavior in waters located

within and adjacent to North Carolina, it is necessary to

identify:the physical characteristics (and associated

mechanisms) that (1) govern this behavior and (2) serve

as adequate descriptors of the referred-to waters. The

analys@s carried out by Stolzenbach, et.al. (1977) and

summarized,in Chapter 2, provides a convenient means of

identifying these features, but it is,not the.only means.
An order oi magnitude analysis of the governing equations

could also be carried out. But, it is very convenient-

to use the work of Stolzenbach. Moreover, it provides a

clear visual representation of the conceptual framework.

Therefore, we can utilize Figure 1 which indicates

the major mechanisms of importance to oil spill movement

in terms of time and length scales. We can immediately

realize that two additional types of information are

needed to complete our analysis. One is a parameter that

describes North Carolina waters. For any given spill

locality, the parameter that seems natural is the

minimum distance from the spill source to shore

(i.e., x-number of meters). This can be used to describe

localities in inland waters (in the Cape Fear River,

for example) or localities nearshore or localities far

offshore (an oil drilling platform, for example). For

estuaries, bays, inland waters and other confined or

semi-confined waters, these distances can be scaled from

any hydrographic chari. We can assume that a value of

from 0 to 500 meters would be a reasonable value to use

to describe these waters. To distinguish between near-

shore and offshore areas, we can adopt the arbitrary.

criteria that offshore areas are those beyond.which

shoreline impacts from tidal currents are virtually

non-existent. On this basis, we can make the following

descriptions for North Carolina waters in terms of

single-length parameter:

Inland waters and
estuaries . . . . . . . 0 to-500 meters
Nearshore areas ..0 to 1000 or 10,000 meters
Offshore areas . . . . >1000 or 10,000 meter s

These values are not to be construed as actual

distances of any specific locality but are generally

representative of distances that characterize the indicated

regions for the purpose outlined above.

The other source of information that is needed

is derived from climatic data for the indicated regions.

Again, precise values are not needed; only an order of

magnitude is required. For' this purpose, we can assign

the following values of advection velocities (in the

direction of the distances indicated above) for the

three regions.

Inland waters and m m
estuaries 0.1 /see - 1.0 /see
Nearshore areas 0.01m/see - 0.1m/sec
Offshore areas 0.001m/see - 0.01m/see

More precise values can be obtained from detailed

examination of the climatic data (wind and currents).

The above advective velocities are related only

indirectly to the actual wind-induced surface currents

..and/or tidal or residual currents since we are interested

only in that component taken parallel to and along the

minimum trajectory path from spill source to impact

location.

These features can be illustrated by referring

to the length-time scale diagram shown in Figure 2. First,

consider a spill in an estuary or inland waterway where

the characteristic length is 500 meters and the

characteristic advection rate lies somewhere between

1.0 and 0.1 meters per second. We can see from Figure 2

that the total elapsed time from spill to impact is rather

short ranging from 425 to 4100 seconds. Figure 2 shows that

dispersion can be neglected and we also note (from ot her

information)that evaporation occurs along with other processes

Total lapsed time to impact
for various advection rates

Hour Week Month Year
0 10' 1-00 1@ , 1 1 5
@ 1000 140' 10' .10' Time
Atmospheric I Spreadin I (seconds)
F-11-aporat
boundary layer ion Dispersion
fluctuations Emulsifica4on .1 1
Dissolution; Other weathering
10 Vertical Dispersion Uyper processes
Lo "@r m1t
W
limio Upper
limit
Lower
100 s4et
Characte stic GPI
length in* a d
spill
103
___J@Lowe'@Ik. limit
Initial distan( e nearmore
from impact
00 location spil
4 Mesoscale Wind
10 Fluctuations

T dal

cu rents
Upper limit
105 nearshore
spill
cm1sec lcm7s N/sec
1M)sec 10 ec .1c
10 Advective Velocities
Weather
Length System
Scale Fluctuations
(meters)

FIGURE 2 Time-Length Scale Diagram for Evaluating Relative Importance
,@Zct ve @Te

Weather
ystem

of Various Processes (After Stolzenbach, et.al., 1977)

throughout the growth and transport of the slick.

However, evaporation and the other weathering processes

are still in their early stages of development by the

time of impact.

Therefore, modeling of oil spill behavior in

estuaries and inland waters should include the simulation

of advection, spreading and evaporation. From a knowledge

of additional details concerning the spill, such as spill

volume, and properties of the spill material as well as

detailed climatic conditions, we can evaluate the

relative importance of the growth (i.e., spreading) or

transport (i.e., advection) activities in causing impac ts.

For example, as a general trend for fixed advection rates,

the spreading activity increases in importance with

increases in spill volumes.

Finally, consider an offshore spill at a

distance greater than 10,000 meters from an impact

location and with characteristic advection rates

less than 0.01 meters per second. On this basis we

can determine that the impact time is greater than

830,000 seconds or 230 hours (almost 10 days). We

take note of the fact that dispersion is the dominant

process in the growth of the slick and that spreading

has been completed. Evaporation has been completed.

In some cases, advection may be an important mechanism

but advection by tidal currents is unimportant by definition.

Evaporation has been completed.

Therefore, modeling of spills in the offshore

region should include advection, dispersion and evaporation.

Dispersion is very important but advection by tidal currents,

in general, can be neglected.

Next, consider a spill in the nearshore region

(as defined above) such that the characteristic length has

a value of between 1000 and 10,000 meters and characteristic

advection rates of between 0.01 and 0.1 meters. Again,

using Figure 2, we can determine that the elapsed time
from initial spill to impact varies from 7700 to 83,000

seconds for the 1000 meter distance, and from 83,000

to 83G,,000 seconds for the 10,000 meter distance-.^

In the first instance where the distance from.
'the spill source to impact is 1000 meters, we' see that

spreading is almost complete and dispersion has not yet

become effective whereas in the'second instance (where

the source-impact distance is 10,000 meters), spreading

has been essentially completed and dispersion has become

an important activity - remember that scales are logarithmic.

In spite of the apparent low advection rates, the transport

process (including advection by tidal currents) plays an

important role in determining the time of impact.

Evaporation has been active throughout and,in the case of

the longer impact times, essentially has been completed.

Other weathering processes have become significant.

From these observations, then, we may conclude

that modeling of oil spills in the nearshore region

should include provision for simulating advection,

spreading, dispersion and evaporation.i. Advection by

tidal currents should definitely be included in the

modeling scheme.

From the foregoing, we can list the modeling

requirements for the various regions.

Inland;waters and estuaries Advection, spreadinE,
evaporation

Nearshore areas Advection, spreading,
dispersion, evaporation

Offshore areas Advection, dispersion,
evaporation

As stated in the Introduction, one of the goals

of this study is to evaluate and select models for the

prediction of oil spill behavior in North Carolina waters.

As implicitly suggested, the possibility of identifying

a single model, while attractive on a superficial level,

is not realistic. Among other objections, the use of a

single model for solution of all cases of interest would

require use of the most complex and sophisticated model

for all cases. Therefore, it would be too expensive

for the simplest cases and might require input data

that is not even available. Thus, the approach has been

to classify the number of cases into the categories of

inland waters and estuaries, nearshore areas and offshore

areas. Within these categories, we have attempted to

identify'faznilies, of models which would be appropriate.

In other words, there has been an attempt to gear the

model solution capability to the problem requirements.

At this stage, we can drop from further

consideration the U.S. Navy, WGD, CEQ, SPILSIM and OSTA
imodels, since they treat only@advection. The WGD model

has been applied to offshore spills and the CEQ model has

been applied to both nearshore and offshore spills but
-the-re are other models thet.include the otlier-processes

as well. The same is true to a lesser extent of SPILSIM

which was developed for application to the special case

of the Great Lakes.

We can then reclassify Cin a subjective way)

those mode ls that are suited for the three regions of
interest. This-is shown in Table VII, where it will be

noticed that some models can be applied to more than

one region.

TABLE VII

CANDIDATE MODELS FOR APPLICATION

TO NORTH CAROLINA WATERS

Inland Waters and Nearshore Offshore
Estuaries

Narragansett Bay USCG USC/API
Tetra Tech, Inc. (New York Bight) SLIKFORCAST
Delaware 0Bay BOSTM (SLIKTRAK)
CAES URI
USCG
(Georges Bank)
.(New York Harbor) Delaware Bay
DPPO
Puget Sound USC/API
(Garver and Williams)
Riverspill URI
NWS/NOAA
(Georges Bank)
USCG EDIS
(Long Island Sound) DPPO
PIC (Garver and Williams) OSSM
EDIS MOST

PIC DRIFT

OSSM

DRIFT

Inland Waters and Estuaries.
As shown in

Table VII, we have some eight (8) candidate models for

possible application to North Carolina.

The USCG (New York Harbor) model has been well''

calibrated by a number of oil spills in'New York Harbor

but it requires a comprehensive knowledge of the fresh

water inflows (Hudson River) and dispersion coefficients.

Fortunately for New York Harbor, thanks to the intense

interest over a long period of time, this information is

available. Essentially, the USCG (New York Harbor) and

USCG (Long Island Sound) models are empirical type models

which have the advantage of having been calibrated by

numerous observations and therefore have been validated.
Suct'@ infoimation is generally-not available for North

Carolina waters.

The Narragansett Bay model is a simplistic-

easy-to-understand model that could be applied to

North Carolina inland waters. However, two changes

would have to be implemented. The wind drift angle
would have to be changed to something other than 20 0

and the. spill-spill interaction effect would have to

be taken into account for non-instantaneous spills.

The latter may require a substantial reprogramming

effort.

Although the Tetra Tech, Inc., model has

been applied and calibrated to San Pedro Bay, California,

there are a number of reasons why this model should not.

be considered for application to North Carolina waters.

These reasons are given in a review by Stolzenbach,

et.al. (1977), but the major reason is that the dispersion

is a numerical dispersion that is not related to the

physical dispersion, if it exists.

The PIC model is theoretically sound and a very

fundamental approach but the difficulty with this model

is that it has not been proven or validated.

The remaining three models (Riverspill,

Delaware Bay and Puget Sound) constitute the three

candidates for potential application to North Carolina

inland waters. All three models have more or less been

validated by comparison with actual spills'or simulated

exercises. Riverspill was developed for the situation

.on the Mississippi River and is the simplest of the three

models to implement. Although it is intended for the

situation where there is substantial river current,

there is no reason, in principle, why it could not

handle the situation of tidal currents. Riverspill is

highly deterministic whereas the Puget Sound model is

statistical in nature.

The Delaware Bay model is also a deterministic

model and one that might prove to be better suited to

handle those cases of spills at estuary junctions with

the open ocean. Unlike the other two models, it includes

the advective drift due to waves as well as dispersion.

One of the difficulties in using the Delaware Bay model

is that the diffusion coefficients must be known or

assumed.

In summary, the following models seem well

suited for the prediction of oil spill behavior in

North Carolina inland waters and estuaries. These

are the Delaware Bay model, Puget Sound model and

Riverspill.

Nearshore. Some eleven (11) models reviewed

were selected as potential candidates for modeling spills

in the nearshore regions of North Carolina. For a number

of reasons, this is the most difficult region to model.

On the one hand, a very large area offshore must somehow

be considered and often this can only be done at a very

crude scale. On the other hand, in order to make

meaningful evaluations, modeling of details near coastal

impact locations requires-a smaller, finer scale. The

result is that none of the models listed in Table VII

can be applied with confidence directly to North Carolina

waters without some modification.

The USCG (New York Bight) has been applied to

the study of spills off the Delaware and New Jersey coasts

but it has been only partially validated. Moreover, as..

noted by Stolzenbach, et.al. C1977), many details are

lacking and some of the assumptions cannot be justified..

Neither the BOSTM or CAES model actually treat

dispersion (.in a strict sense)', and the BOSTM has the

additional disadvantage in that it does not consider

any of the,weathering processes. For continuous spills,

the BOSTM model neglects spreading, whereas, the CAES

model neglects the spill-spill interaction effect.

However, results of both models have been applied to

prototype oil spills or to simulated spills.

'If weathering processes were added to the
Delaware B@y model, it is possible that this model might

bd adapted to the nearshore regions off the North Carolina

coast. Other comments regarding this. model have been

provided in the previous section.
The'USC/API model is a very c6mprehensive,

composite model, but the model as a whole has not been

validated by comparison with prototype spills. Moreover,

many of the component parts are somewhat dated. More

up-to-date information is available that could be us-ed

in this model.

The EDIS model has been applied to the oil spill

in Campeche Bay (IXTOC-1) and to the Argo Merchant spill

but insufficient details are available to evaluate the

predictions. The model includes only advection and

spreading and therefore does not appear suitable for

the nearshore region off North Carolina.

The PIC model is still under development but

is very sound in a theoretical way and might be used

off North Carolina when the model has been completed and

validated-The OSSM model is still under development
although it has been applied to the IXTO&I blowout in

the Gulf of Mexico.

From the foregoing discussion, we are left

with the following three models as the leading candidates.

These are'the DRIFT, URI (Georges Bank) and DPPO (Garver
and Williamsj. DRIFT is a simple type model which takes

into account the tidal oscillations and which has been

applied to model a spill off Anglesey, North Wales.

The URI (Georges Bank) model is a substantially more

comprehensive model that. has,also been applied to a
prototype spill (i.e., Arg o Merchant). The DPPO (Garver

and Williams) is the most comprehensive of the three

models, yet many of the submodel formulations are quite

simple and crude. Different versions of the DPPO model

have been applied to oil spill simulations in the Gulf

of Mexico.

In summary, modeling of oil spill behavior in

:the nearshore region is a difficult task. None of the

models reviewed can be applied without some modification.

The following models seem best suited for this purpose:

DRIFT, URI (Georges Bank), and DPPO (Garver and Williams).

With slightly more modification, the Delaware Bay model

might also be a possibility.

Offshore. Recall that for the offshore

region, spreading and advection due to tidal currents

can, in general, be neglected. As a result of these

simplifications, modeling of oil spill behavior inthe

offshore region tends to be somewhat less difficult than

in the nearshore region, all other factors being equal.

Models which are appropriate for the offshore
region are listed in Table VII. Comments regarding ill

of the models except three have already been provided.

One of the deficiencies of the MOST model is that it

does not take into account evaporation. It has been

applied to the BRAVO blowout (North Sea) but the

agreement with observations needs substantial improvement.

The NWS/NOAA model is still under development but when

completed will probably represent the most comprehensive

and fundamentally sound basis for predicting offshore oil

spills. The remaining model, SLIKFORCAST (SLIKTRAK) has

been employed to simulate the BRAVO blowout and the

predictions seem to compare favorably with observations

at different locations. SLIKFORCAST is a very comprehensive

simulation program which can be used for both contingency'

planning and emergency tracking. The structure of the

program is in many ways similar to the DPPO model (Graver

and Williams).

In summary, SLIKFORCAST appears to offer the

greatest potential for modeling of oil spills in the

offshore region. However, the NWS/NOAA model, when

completed and validated, may be equally or better suited.

As secondary choices, the DPPO model (Garver and Williams)

and URI (Georges Bank) might also be considered.
All of the foregoing models require a certain F
quality of climatological and oceanographic data for

input irl order to obtain reasonable-predictions. Nearly

all of the models employ a numerical approach utilizing
a given areal mesh of fineness ratio s uch tha't the

following two requirements are satisfied. One require-

ment is that the spacing dimension be small enough so

that all important and relevant details are known. In

practical terms, this translates into selecting a mesh
size that utilizes all quality environmental'data. The

other requirement is that the area covered/be large

enough so that boundary effects are minimized. The

latter introduces another restriction in that the mesh

spacing cannot be too small; otherwise, a system

involving an unmanageable number of equations must be

solved simultaneously at each time step. At the same

time, both the time step and the spacing must be

selected in order to minimize error propagation.

The data of most concern is that which affects

advection and dispersion. Advection is determined from

the wind field, surface currents and subsurface currents

and to a lesser extent by the wave field. Although each

oil spill model is affected somewhat differently by the

quality of the input data, the relative evaluation of

the models is not very sensitive to data which is

availab'le for North Carolina waters. Therefore,:only a

few general observations concerning this data (as obtained

from a review of the available open literature) are made.

As a general rule, wind information appropriaite

for North Carolina inland waters and estuaries and for

the nearshore regi-on is.very poor. Wind data for the.

offshore region is only marginally better. Wind data

for the inland waters and estuaries is based on extrapo-

lation of data collected from nearby airports whereas

that for the offshore region is based on ship reports.

Obviously, the geographic distribution is not @iniform

since it is biased in favor of the more heavily traveled

shipping lanes.

The quality of current data for the inland waters

the estuaries is highly variable. Current due to tides.in

some locations (i.e., Cape Fear River estuary) is adequate.

In other locations, such data is spotty. Currents due to

fresh water inflows is also highly variable.

The quality of current data for the nearshore

region is also highly variable, In the case of the offshore

region, the three-dimensional circulation pattern for

currents appears to be adequate for that portion south

of Cape Hatteras. At the same time, knowledge of the

circulation pattern for that portion north of Cape Hatteras

is only grossly known or, at best, uncertain.

The foregoing comments are based on a review of

a large number-of references including but not limited to

those cited in connection with the Draft Environmental

Impact Statement, Proposed 1981 Outer Conti nental

Shelf Oil and Gas Lease Sale No. 56, Bureau of Land
Management Outer Continental Shelf Office, New Orleans,

Louisiana. Among those references reviewed were the

following in-house reports not available for general

distribution at this time (July, 1982).

1. Kantha, L.H., A.F. Blumberg, and G.L. Mellor
A Diagnostic Technique for Deducing the
Climatological Circulation as Applied to
the South Atlantic Bight, Report No. 69
Dynalysis of Princeton, Prepared for Bureau
of Land Management, U.S. Department of
Interior, Contract No. AA551-CT-9-32, 1981.

2. Kantha, L.H., A,F. Blumberg, H.J. Herring,.
and G.L. Mellor, The Physical Oceanographic
and Sea Surface Flux Climatology of the
South Atlantic Bight, Report No. 70,
Dynalysis of Princeton, Prepared for Bureau
of Land Management, U.S. Department of
Interior, Contract No. AA551-CT-9-32, 1981.

3. Blumberg, A.F.-and G.L. Mellor. Circulation
Studies in the South Atlantic Bight with
Prognostic and Diagnostic Numerical Models,
Report No. 71, Dynalysis of Princeton,
Prepared for Bureau of Land Management,
U.S. Department of Interior, Contract
No. AA551-CT-9-32, 1981.

4. Blumberg, A.F., H,J. Herring, L.H.Kantha,
and G.L. Mellor, South Atlantic Bight
Numerical,Model A-pplication--Executive
Summary--; Report No. 72, Dynalysis
of Princeton, Prepared for Bureau of
Land Management, U.S. Department of
Interior, Contract No. AA551-CT-9-32, 1981.

These reports were made available to the author through

the efforts of Mr. Eric Vernon, Office of Marine Affairs.

In summary, there is a need for additional coastal

wind buoy station data and for improved knowledge of the

current circulation pattern offshore north of Cape Hatteras.

CHAPTER 5

Summary and Conclusions

A brief history of the state-of-the-art in

oil spill modeling has been presented in Chapter 2,

along with an outline review of the fundamental problem

development as stated in mathematical terms. It has,

been shown that the major processes which have greatest

influence on impacts resulting from oil spills are

advection, spreading, dispersion and evaporation, but

that.all of these processes'are not necessarily active

in all cases.,

A review and classification of various models

as they are published in the open literhture is presented

in Chapter 3. Detail reviews for each Modeling effort are

presented in the Appendix. For each mod eling effort, the

name or description of the model is presented along with

the primary reference(s) and corresponding abstract(s).

Reviewer's comments are also presented.

Chapter 4 contains an analysis establishing

the criteria for evaluating oil spill models for use in

North Carolina waters. This is followed by an evaluation

of leading model candidates for each of the regions into

which North Carolina waters may be classified.

5 4-

It is concluded that the most appropriate

models for use in each of the regional classifications of

North Carolina waters are as follows:

Inland waters and estuaries: Delaware Bay Model, Puget
Sound Model and Riverspill..

Nearshore areas: DRIFT, URI (Georges Bank), DPPO
(Garver and Williams).

Offshore areas: SLIKFORCAST and NWS/NOAA, when
completed and validated.

RECOMMENDATIONS

As a result of this study, a number of findings

and observations stand out which could easily be formulated

into a set of recommendations. Rather than present a

formal set of recommendations (which always reflect the

biases of th e author), the nature of the study is such

that it is believed to be more appropriate to simply

present the most important observations and let the

reader form his (or her) own recommendations. These are

as follows:

1. For North Carolina regions, there are

two major deficiencies which-inhibit

-application of the more sophisticated

models (including those now available

and under development) in orde r to

realize maximum benefits. One of the

deficiencies has to do with the data

base (climatic and oceanographic) which

is not sufficiently fine in order to

make detailed coastal evaluations of

oil spill impacts with reasonable

confidence. The other has to do with

the lack of detailed knowledge concerning

resource inventories (both living and

non-living) and their exposure to various

oil spills.

2. As a general observation, both short-term

and long-term weathering processes are

very poorly understood. This will require@

a deliberate and sustained research effort
at the national level./'

3. None of the models re.viewed treat the

problem of continuous spills in a rigorous

manner. All of them make some assumptions

which introduce errors into the analysis.

4. There are a large number of models available

and under development. It seems more prudent

to adapt existing models to new situations

rather tha:n embark on a new model development

program. This is true even for the nearshore

zone where, in general, most models are

inadequate. Adaptation of existing models

to North Carolina waters still remains a

challenging task, however.

5. It is unlikely that any one model can be

developed or adapted that has general

applicability to a wide variety of

situations. It is more likely that a

single family of models can be developed,

all with similar procedural characteristics,

to meet this need. Therefore, the attempt

to develop or to find a single model to meet

all needs is probably a fruitless endeavor..

6. As a by-product of this study, it was

observed that there is a tremendous

communication (or understanding) gap

between various factions of different

communities concerning the matter of

oil spills and their impacts. This

includes both federal and state

administrators and decision makers,

scientific community, industrial community,

local community.leaders, concerned populace

and various state and local politicians.

References

(In addition to those documented in text and appendix)

Bishop, J.M., Editor, Proceedings of Workshop on
Government Oil Spill Modeling, Wallops Island,
Virginia, November 7-9, 1979.
F' , J.A., "The Spread of Oil Slicks on a Calm Sea,"
ay
Oil on the Sea Edited by D.P. Hoult, Plenum
i, pp. 53-63, 1969.
Press, New t-or

Fay, J.A., "Physical Processes in the Spread of Oil on
a Water Surface," Proceedings of Joint Conference
on Prevention and Control of Oil Spills,"
Sponsored by API, EPA, USCG, Washington, D.C.,
June 15-17, ;1971.

Huang, N., "A Simple Model of Ocean Surface Drift Current,"
Procee dings, Workshop on the Physical Behavior
,of Oi in the Marine Environment, Princeton, N.J.,
'May 8-9, 1979.

Madsen, O.S., "Wind*Driven Currents in an Infinite
Ho"mogeneous Ocean,"'Journafol Physical
Oceanography, 1977..

Murray, S.P. , "Turbulent Diffusion of Oil in the Ocean,"
Limology and Oceanography, Vol. 27 (5),
pp. 561-660, 1972.

Stolzenbach, K.D., O.S, Madsen, E.E. Adams, A.M. Pollack
and C.K. Cooper, A Review and Evaluation of Basic
Techniques for Predicting the Behavi-or of' Surface
Oil Slicks, Report No. 222, MIT, Cambridge,
Massachusetts, 1977.

59.

APPENDIX

This appendix contains summaries for each of

the modeling efforts identified during the course of this

investigation. The original publications, which describe

and provide details on the modeling efforts, have been

collected and reviewed in all but three cases. For each

effort, the summaries list the model name or description

followed by the primary reference(s) and by the author's

own abstract or one synthesized by the reviewer. The

reviewer's own concise comments follow the abstract.

In the cases of the three exceptions (BOSTM,

USC/API, ahd MOST), the abstract is not given and the

reviewer's comments 'are based on the numerous comments

provided by other reviewers or isolated comments appearing

in the open literature. The BOSTATI and USC/API models,have

been reviewed comprehensively by Stolzenbach, et.al.(1977).

Unfortunately, in spite of a deliberate and dedicated

search by several of the area librarians, the primary

references appropriate for these three models could not

be obtained in a reasonable period of time. In one (@`ase,

the reference was simply out-of-print and in another case,

permission to release the reference due to proprietary

restrictions has not yet been obtained.

Finally, the 1981 Oil Spill Conference is

scheduled for release in September 1982 and will contain.

additional material relevant to these models.

The order in which the modeling efforts are

presented is a historical one with the earliest developed

models appearing first.

Model Name or Description

U. S. Navy

Reference

Webb, L.E., R. Taranto and E. Hashimoto,
"Operational Oil Spill Drift Forecasting
Seventh U.S. Navy Symposium on Military
Oceanography, Annapolis, Maryland, 1970

Abstract

Recent incidents of large scale oil pollution
have had catastrophic effects on the ecology, recreation
and wild life resources of coastlines and coastal." waters
and caused worldwide public opinion to be very sensitive
to this problem. Fleet Weather Centrals should have the
capability to provide movement forecasts for oil spills
from naval vessels or other sources, identifying the
area of maximum threat and permitting containment action
to be taken most efficiently. A tentative method is
presented using surface current parameters based on
operational data available at most Navy Fleet Weather
Centrals.

The surface current parameters influencing
oil spill drift used in this proposed forecast method
are permanent currents, 'wind drift, geo-strophic and tidal
currents. A-basic operational forecast using the vector
sum of the pertinent parameters is presented. Modifica-
tions of the basic forecast method due to the location
of the spill (open water@, restricted water) are explained.
The method presented should provide an acceptable
forecast as an aid in effective control or containment
of oil spillage.

Reviewer's Comments

This is one of the earliest models proposed

and is a very simple advection-only model. The advection

is taken to be the vectorial sum of the various currents

which are assumed to consist of permanent geostrophic,

tidal and wind-drift types. This model is one of those

reviewed by Stolzenbach, et.al. (1977).

Model Name or Description

Warner, Graham, Dean (WGD) Model

Reference

Warner, J.L., J. W. Graham and R. G. Dean,
Prediction of the Movement of an Oil Spill
on the Surface of the Water," Paper No. 1550
Preprint of the Fourth Annual Offshore
Technology Conference, Houston, TexasMay 1972

Abstract

A calculation procedure is described to represent
the displacement of a surface oil spill under the action of
time-varying surface wind stress components; predictions using
this technique are carried out for the 1970 Arrow spill in
Chedabucto Bay, Nova Scotia.
The procedure presented is based on a convolution r
integral of the x- and y- components of a time-varying wind
stress and'is approximated in summation form for computer
application. For an impulsive wind stress, it is demonstrated
that the summa@tion form is in agreement with an analytical
solution by Fredholm.

The Arrow oil spill Occurred on 4 Fe bruary, 1970
and during the first week of March, oil was observed on the
beaches of Sable Island some 120 miles Southeast of the spill
location. Meteorological data in the form of reduced
.geostrophic winds have been published by Neu. These winds
were utilized to predict the oil spill trajector@ based on'.:
(1) a surface velocity equal to 3% of the wind speed and.
aligned with the wind direction,'and (2) a surface velocity
determined from the convolution procedure presented in this
paper. It was found that the convolution procedure predictionsg
provided better agreement with the available information relatin
to the spill transport to Sable Island. The importance-of an
adequate description of prevailing surface currents and
vertical eddy viscosity is illustrated.

Reviewer's Comments

This model has been reviewed by Stolzenbach,

et.al. (1977) who notes that this is purely an advection model

since it neglects spreading, dispersion and other processes

such as evaporation. The model does not provide for inclu.-

.sion of coastline boundaries; therefore, its application is

limited to far offshore regions where wind induced currents

dominate the movement mechanisms. The model has been applied

to the Arrow oil spill (Nova-Scotia) where, after calibration

via the eddy viscosity parameter, the measured trajectory

was satisfactorily simulated.

Model Name or Description

Narragansett Bay (or Premack and Brown) Model

Reference

Premack, J., and G.A. Brown, "Prediction
of Oil Slick Motions in Narragansett Bay,"
Proceedings of the Joint Conference on
Prevention and Control F? Oil Spills,
American Petroleum Institute, Washington, D.C.
1973
Abstract

In the develoDment of me-aningful oil spill
contingency plans, it is of great value in establishing
the response to a spill emergency to have predictions
of oil slick motions once the spill occurs. In an attempt
to evaluate some of the present technical literature on
oil spill motion, a calculationwas made for the oil spill
motion which occurred in Narragansett Bay in September,
1960, when-the tanker P.W. Thirtle ran aground and emitted
about 24j000 barrels of Bunker C oil over a 12 hour period
before the successful abatement of the source was completed.

The existing literature on oil slick spreading
was reviewed and the work of Tay was chosen to represent L
the slick's spreading characteristics. The existing
literature on the oil slick drift was reviewed and the
work of Teason, et.al.,.was used to establish'the drift
motion under the influence of,current and wind actions.
An available numerical hydrodynamic model of Nar!ragansett'
Bay was used to calculate the current characteristics in
the vicinity of the spills during the period of interest.
Appropriate wind data were combined with current data
in order to obtain the important hydrodynamic and meteoro-
logical conditions. Since no comprehensive theory -exists
at the moment for oil slick spreading and drift, a simple
model was taken in which the 24,000 barrels were emitted
from the source in the form of 12 hourly discharges of
2000 barrels each. These individual spills were then
handled on the basis of the available spreading theory
and the drift motion calculated as described above.
Although this is a crude approximation, it does give an
estimate of the location and area magnitude of the spreading
as a function of time after the spill.

The predicted results were compared with
documentation of this spill as presented in the Providence
Journal. The overall slick motion as calculated by this
procedure was in good agreement with the arrival times
..of the spill in Newport Harbor and other places in
Narragansett Bay and with the overall surface area involved

in the spill, This example of the calculation of the
oil slick motion in an estuary at least gives some
confidence to oil spill contingency planners that
numerical calculations can be made for use in planning
response and abatement to spills.

Reviewer's Comments

This model has been reviewed by Stolzenbach,

et.al., (1977) who note that this model treats advection

(both wind and current) and spreading. Advection due

to wind is considered to be directed at a wind drift angle

of 200 clockwise from the wind vector. The modified wind

induced motion is then added vectorially to the tidal

currents and both are superimposed on the slick spreading.

Spreading is treated via Fay's (1971) equations. The

model does 'treat the case of spills that occur with time

(as contrasted with instantaneous spills). This is

accomplished via a unif-orm discretization of the oil spill

volume, However, the resulting subspills are treated

independently of each other via simple superposition.

That is, the spill-spill interaction effect is neglected.

The model has been applied in one case to the Thirtle

oil spill where some limited comparisons have been made.

,klr.tdel Name or Description

Tetra Tech, Incorporated

Reference

Wang, S., and L. Huang, "A Numerical Model for
Simulation of Oil Spreading and Transport and
Its Application for Predicting Oil Slick Movement
in Bays." Tetra Tech, Inc., Sponsored by
U.S. Coast Guard Research and Development Center.

Abstract

A computer model for simulating oil spreading
and transDort has been developed. The model can be utilized
as a useful tool in providing advance information and this
may guide decisions for an effective response in control and
clean-up once an accidental spill occurs.

The spreading motion is simulated according to the
physical properties of oil and its characteristics at the
air-oil-water interfaces. The transport movement is handled
by superimposing the spreading with a drift motion caused by
winds and tidal currents. By considering an oil slick as a
summation of many elementary patches and applying the
principal of superposition, the Model is capable of predicting
the oil size, shape, and movement as a function of time after
a spill originates. I

Field experiments using either cardbo.ard markers
or soybean oil to simulate a spill were conducted at the
Long Beach Harbor. Computer predictions showed good agreement
with the field tracers. In order'to accommodate the model in
local port offices, two hardware candidates are proposed.

Reviewerls'Comments

This model considers the combined effects of

advection and spreading. The numerical scheme that is

employed is intended to simulatb the simultaneous

effects of advection, spre-ading and dispers-i.on. Both,

wind and tidal current advection are considered. The

differential spatial effects are modeled by use of elemental

.cells. However, the procedure is based on a linear

superposition of subspills (in the spatial sense) and the

effect of neighboring subspills is not considered. In

other words, during each time step an individual cellular

subspill is considered to react independently of its
neighbors. This is considered to be a''serious weakness

by Stolzenbach, et. al.(1977), who has reviewed this

procedure and who also points out that the numerical disper-

sion that results from this approach is not directly related

to any physical dispersion.

The model considers only instantaneous spills,

but, because of the fact that each cellular subspill is

considered to be "new" at the beginning of each time step,

there is no reason, in principle, why time-dependent spills-

could not be considered.

The model is intended for use where spreading

and advection are the dominant processes. Therefore, its

application is limited to mostly enclosed water bodies

such as harbors and bays and protected near-shore areas

having relatively short time and length scales. To derive

eaximum benefit, it is further limited to those situations

where detailed environmental data is available.

The model has been field teste-d and an example

using Long Beach harbor (San Pedro.Bay) is illustrated.

Some five different simulated spills using tracers were

conducted to validate the model. A computer code is

included in the Appendix of the above reference.

Model Name or Description

Council on Environmental Quality (CEQ)

Reference

Stewart, R.J., J.W.Devanney, III, and W. Briggs,
Section III, "Oil Spill Trajectory Studies for
Atlantic Coast and Gulf of Alaska," Primary,
Physical Impacts of Offshore Petroleum Develop-
ment, Massachusetts Institute of Technology,
Sea Grant Program, MITSG 74-20, Report to
Council on Environmental Quality, April, 1974

Abstract

Oil spJ*lls can be transported many miles from
the site of an accident by the action of wind, waves and
currents. The purpose of this study is to obtain insight
.into the likely behavior of oil spill trajectories
emanating from each of the'thirteen potential Atlantic
Outer Continental Shelf (OCS) production regions and each
of the nine potential production areas in the Gulf of
Alaska as identified by the U.S. Geological Survey. In
addition, the likely behavior of oil spills emanating from
three potential nearshore terminal areas, Buzzards Bay,
Delaware Bay and Charleston Harbor are examined in greater
detail. Major emphasis in @11 of Ithese analyses is placed
on the probability of a spill coming to shore, the time
to shore and in the case of the terminal (areas) analyses,
the wind conditions at the time the spill first reaches
shore.

Reviewer's Comments

This model has been reviewed in detail by

Stolzenbach, et.al, (1977). It is essentially an advection

model with two versions. One version can be applied to

nearshore areas and the other version is intended for

application to offshore areas. Advection by wind, tidal

currents and 'residual' currents are considered. Application

of the model requires a knowledge of the tidal currents,

residual currents (in the case of the offshore version) and

wind measurements appropriate for the region under study.

Model Name or Description

U.S. Coast Guard (New York Bight)

Reference

Miller, M.C., J.C. Bacon and I.M. Lissauer,
A Computer Simulation Technique for Oil Spills
Off the New Jersey-Delaware Coastline, DOT
U.S. Coast Guard, Washington, D.C. 1975
Abstract Predictions for the movement of oil slicks
and their impact implications along the shoreline of
New Jersey and Delaware were determined for two potential
deepwater ports and two potential drilling sites. A hydro-
dynamic numerical model for the New York Bight area was
coupled with a wind generating model to produce temporal
patterns of concentration of oil. Shoreline impact
determinations were made for the four spill sites for
the averagewinter storm conditions and average summer
high pressure systems generated by the model.

Reviewer-Is Comments

This model.has been r@eviewed by Stolzenbach,

et.al.(1977), who Doints out that many detailslare lacking

in the report. The model consists of essentially.a numeric@Ll

hydrodynamic system which utilizes a wind field generating

submodel to predict fluid particle velocities. The latter,

in turn, are employed to yield the oil spill trajectories.

Model Name or Description

Batelle Oil Spill Transport M-odel (BOSTM)

Reference

Ahlstrom, S.W., A Mathematical Model for 0
Predicting the Transport of Oil Slicks in
N
Marine Waters, Batelle Pacific Northwest
Laboratories, Richland, Washington, 1975

Abstract (not available)

Reviewer's Comments

This model has been reviewed by Stolzenbach,

et.al. (1977) and numerous references to it appear in the

open literature. From;these reviews and citations, it

appears that.the model.treats advection, spreading and

dispersion'but does not treat weathering. The CAES model

appears to be based on the BOSTM model with the addition

of weathering so that the CAES comments also apply to the

BOSTM model.

Inherent in the Discrete Parcel Random Walk

method is the assumption. that'each parcel (subspill)

behaves independently of the other parcels. Stolzenbach,

et.al. (1977) points out that this assumption has not been

proven and that it gives rise to a numerical dispersion

which may not be realistic. Moreover, the model employs

some arbitrary empirical factors whose origin is

uncertain.

Model Name or Description

Delaware Bay (Wang, Campbell, Ditmars) Model

Reference

Wang, H., J.R.Campbell, and J.D. Ditmars,
Computer Modelling of Oil Drift and Spreading
in Delaware Bay, CMS-RANN-1-76, Ocean Engineering
Report No. 5, University of Delaware, Newark,
Delaware, 1976

Abstract

A generalized two-dimensional model and an
interactive computer code for the determination of-the
oil slick dispersion are presented. The model considers
two mechanisms to dominate,spreading and dispersion.
Drifting refers to the drift of the center of mass of the
slick and is influenced by winds, water currents and the
earth's rotation (Coriolis force). Spreading refers to
the spre@Ld of the oil slick with respect to its center
of mass and a function of first, a gravitational force;
second, a viscous force; third, a diffusion process.
Relevant details and user options of the computer code
are discussed. An import-ant adjunct of the computer code
is the capability for interactive grapfiibs. This paper
concludes with a comparison between this model and field
data taken in Delaware Bay.

Reviewer's Comments

This model has beenreviewed by Stolzenbach,

et.al. (1977) who notes that this is the.only model that

includes the effect of advection due to waves. The model

treats advection due to wind and current also, as well as

spreading dispersion. Spreading is treated by using a

modified approach to Fay's (1971) equations. The first

two phases (gravity-inertia and gravity-viscous) are

treated unchanged. However, in lieu of the third phase

(viscous-surface tension), the modellers substitute a

Fickian diffusion relation which requires evaluation of a

dispersion coefficient. The authors state that the reason

for this substitution lies in the fact that while the

third phase exists in the case of small scale laboratory

experiments, its existence is questionable in the proto-

type (or field) experiments. Therefore, the influence

of dispersion completely dominates behavior beyond the

second*phase. The model results have been compared with

some field tests of drifting as carried out in Delaware Bay.

Model Name or Description

U-.S. Coast Guard (New York Harbor)

Reference

(a) Lissauer, J.M., ."A Technique for Predicting
the Movement of Oil Spills in New York Harbor,"
U. S. Coast Guard Research gnd Development
Center, Groton: Connecticut (1974)

(b) Kollmeyer, R.C., and M.E. Thompson,"New York
Harbor Oil Drift Prediction Model," Proceedings
of the Joint Conference on Prevention and
Control of Oil Spills, American Petroleum
Institute, Environmental Protection Agency,
and U. S. Coast Guard, Washington, D.C. (1977)

Abstract (Reference (b))

An operational predictive oil slick,movement
model i@ developed and applied to New York Harbor. This
computer simulation employs hourly tidal currents for all
stages of the tide as input data, combined with river flow
and continuous wind data to predict oil slick movement.
Slick spreading and trans
.port is accomplished using a
conservative- form of the diffusion/advection equation.
The shape of the slick as well as its possible separation
into multiple slicks due to current divergence is
predicted. Time steps on the order of three minutes and
grid spacing of 200 meters allow short term, small scale
sli ek position and shape predictions -co facilitate quick
response for location of sites for containment or cleanup
activities. Hindcasting features allow for possible
source location of the initial spill.

Reviewer's Comments

Reference (a) has been reviewed by Stolzenbach,

et.al. (1977). Reference (b) is an update and an enhance-

ment of the work begun by Lissauer (1974). Advection is

by wind, tidal currents and fresh water inflows from the

Hudson River. In reference (a), spreading followed

Fay's (1971) model. However, in reference (b), spreading

follows Murray's (1972) turbulent diffusion approach.

Both approaches require a moderate amount of field data

under a variety of conditions in order to calibrate the

model. Stolzenbach, et.al. (1977) notes that although

the model can be applied to other harbors, estuaries

and bays, its usefulness is hampered by the data require-

ments including knowledge of/the fresh water inflows.

He also points out that the accuracy drops off in areas

close to shore.

As reported in reference (b), the model has

been extensively calibrated1by a physical model

(U.S. Waterways Experiment Station, Vicksburg, Mississippi)

and by numerous observations in New York Harbor. Both the

time step-interval and grid.size appear to be small enough

to minimize num6rical errors but error analysis has not

been conducted.

Model" Name or- Desbription

USC/API

Reference

(a) Kolpack, R,L. , N-.B, Plutchak and R.W, Stearns,
Fate of Oil in a Water Environment, Phase II --
A Dynamic Model of the Mass Balance for Released
Oil, Chapter 19, "Settling", American Petroleum
T-nstitute, Publication No. 4313, Washington, D.C.
1977.

(b) API, Publ.ication No, 4212 -

(.c) API, Publication No. 4213

(.The above publications are out-of-stock)

Abstract (not available)

Reviewer's Comments

This model has been reviewed by Stolzenbach,

et.al. (1977). It is known that the model includes

advection, spreading and weathering with particular

attention on the weathering processes.

Mode'l-Name or Des:criptibn
Reference SLIKFORCAST (with OILSIM and SLIKTRAK)

(a) Audunson, T., V. Dalen, J.P. Mathisen,
J. Haldorsen and F. Krogh, "SLIKFORCAST
A Simulation Program for Oil Spill Emergency
Tracking and Long Term Contingency Planning,"
Exploration and Production Forum, London, England,
1980

(b) Det Norske Veritas, et.al., OILSIM -Oil Spill
Simulation Model Phase 1, Veritas Report No.77-441
Det Norske Veritas Research Division, Norway, 1977

(c) Blaikley, D.R., G.F.L. Dietzel, A.W. Glass, and
P.J. Vankleef, "SLIKTRAK - A Computer Simulation
of Offshore Oil'Spills, Cleanup, Effects and
Associated Costs, Proceedings of the 1977 Oil
Spill Conference, American Petroleum Institute,
Environmental Protection Agency and U.S. Coast Guard,
1977

Surfimary (Reference (a))

The oil spill simulation progi7am Slikforcast is
an integrated program system where the main components are
a deterministic oil sDill simulation program, Ia statistical.
o*il spill simulation program, a hydrodynamical model for
tidal currents, a data preprocessor, and various*output
routines. Wind data and data on residual -currents must be
supplied from outside sources. The wind data may be from
(i) meteorological wind models with winds on a gridded
net; (ii) from time series of wind from one or several
observational stations; (iii) from statistical wind data
from given locations. The data preprocessor is used to
arrange the data on a unified format suitable for the
simulation models.

Simulation of oil spill drift and fate may be
carried out using either the deterministic or statistical
model or using the two simulation models in a coupled mode.
In the latter case, the results from the deterministic
simulations are used as starting conditions for the
statistical model. This permits oil spill forecasting
bot.h on a short term and long term basis. The deterministic
model is interactive allowing for continuous updating of the
simulation results against f.ield observations.

The prokram package may be used both for cont.in-
gency planning and for oil spill forecasting and hindcasting
during an emergency situation. Great care has been taken to
obtain a general program structure suitable for implementation
in different geographical regions of interest. The access to
sufficient and relevant ambient data and boundary conditions
is, however, paramount to the quality of the simulation results..

Abstract (Reference (c))

The reasons are introduced for the development of/
a siumlator sufficiently simple to enable weather data normally
acquired for E & P operations to be used. "SLIKTRAK",
developed by Shell, applies a slick description and combat
concept, developed within the E & P forum for well blowouts'
in the North Sea, but applicable to other areas. This concept
includes costs for cleanup, damages and effects of phenomena
such as evaporation and natural dispersion. These factors are-
based on industry experience and vary primarily with sea
conditions.

The computer program simulates the.continued
creation ofan oil spill and applied weather data to predict
movements of each day's spillage for successive days at sea
and quantities of oil left after each day until the oil
either-disappears or t-eaches a-coastline.

Cumulative probability curves for thip oil volumes
cleaned up, oil arriving at specified shores, total costs,
etc., are produced by random selection of input variables
such as well location, weather data, the possibility of well.
bridging, etc', and repetition'of simulated spill incidents
over a large number of cycles. Trace plots of individual
spills may also be generated.

In association with the E & P Forum's position
as technical advisers to the North West European Civil
Liability Convention for Oil Pollution Damage from Off8hore
Operations, a study based on the North Sea areas has been
made. These results and further developments of the program
are discussed.

Reviewer's Comments

References (a), (b) and (c) described a main

program and two subroutines for simulating oil spills,

respectively. Reference (b) deals with deterministic

trajectory analysis. Reference (c) is the subroutine that..

deals with the statistical trajectory analysis. This is a

general oil spill simulation program designed specifically

for accidents (particularly blowouts) in the North Sea

but it.is intended for application to different geological

areas. It simulates wind from measurements or from historical

data. It also simulates dispersion into the water column

.and evaporation but does not simulate biodegradation and

photooxidation because these are very slow relative to other

phases. This oil spill simulation model is not designed for
and not sufficiently accurate for detailed coastal effect'

evaluation. However, both short term deterministic and

long term probabalistic oil spill forecasts are possible.

Model Name or Description

MOST

Reference

Paily, P.P., and B.N. Rao, MOST-The Model for
Oil Spill Transport, Hazelton Environmental
Laboratory, Northbrook, Illinois, 1978

Abstract (not available)

Reviewer's Comments

This model treats advection, spreading and

dispersion but no weathering. Both wind drift and

surface currents are apparently treated. Spreading
is treated by Fay's (1671) approach combined with

diffusibn. The model has been applied to the BRAVO

.blowout (Nbrth Sea) but.apparently overestimated the

slick size.

Model Name or Description

Deepwater Ports Project Office (DPPO) Model
(LOOP, Inc., and SEADOCK, Inc.)
Also referred to as SEADOCK Model

References

(a) Williams, G.N., R. Hann and W.P. James,
"Predicting the Fate of Oil in the Marine
Environment," Proceedings of the Joint
Confer-en-.e on Prevention and Control of
Oil Sp lls held in San Francisco,,California.
American Petroleum Institute, Washington, D.C.,
1975.

(b). SEADOCK Deepwater Port Final Environmental
fm-pact Statement, Volume III. Prepared by
Arthur D. Little, Inc., Cimbridge, Massachusetts,

(_c) LOOP Deepwater Port License Application,
*Volume I. Prepared by Arthur D. Little, Inc.,
Cambridge, Massachusetts.

(d) Garver, D.R. and G.N. Williams, "Advancement
in Oil Spill Trajectory Modelling," Proceedings
of Oceans 178, Marine Technology Society,.
Washington, D.C., 1978,

Abstract

The continuing increase in offshore crude oil
production and transportation is presently coupled with
widespread concern over protection'of the environment. This
has led to interest by members of the petrochemical community
in the developnent of suitable methods for quickly predicting
the probable transport path and coastal irrnpact time of a
possible oil spill in the offshore environment. An oil slick
simulator of the stochastic trajectory type has been enhanced
in.an effort to provide such methods.

In particular, four areas will be addressed.
First, both the Fay radial spreading equations and a long-
term dispersive algorithm are now provided. Additionally,
the slick may now assume an elliptical shape. Secondly,
wind and current forcing functions may now be generated with
.the use of Markov state transition matrices as well as through
the use of input time histories. Thirdly, the model will
adaptively calculate coefficients for'the transport equations
in an attempt to correct for deficiencies in the particular
equations used. Finally, the model will now execute in a
real-time mode with an on-line computer terminal to allow
tracking to occur during an actual spill.

Reviewer's Comments

Stolzenbach, et.al. (1977) reviewed reference (a)

above which is referred to as the SEADOCK model as well as

predecessor reports to references (b) and (c) which he refers

to as the DPPO model. Actually, all four references taken
together,constitute a continuing effort to predict the
probable/ transport path and coastal impact time of an oil

spill/occurring in the offshore region. Reference (d)

describes the most recent enhancements to this model but,

unfortunately, many of the details are not provided. There-
fore, some details are assumed to be similar to those reported

in refert@-nces (a), (b) and (c).

'The model objectives dictated the need to follow

a probabalistic approach, but the model incorporates various

levels of deterministic elements. In addition, an option

exists for operating the model in a deterministic mode.

The Fay (1971)@equations are used for modeling spreading

and advection is modeled for both wind and current by using

the available data for the region. Garver and Williams state

that although the vector combination approach to slick

advection is poorly supported, the behavior of actual oil

spills does not justify the use of a more rigorous modeling

method. They do, however, use a weighted average approach

to evaluate the proportionality constants and provision is

made to incorporate new values as more data becomes available.

An algorithm for modeling long-term dispersion

is provided. This algorithm is based on a very.limited

number of observations but does permit the slick to assume

an elliptic shape. In addition, the subsurface transport

processes are modeled.

The movement of the slick is tracked for a

specified duration of time-via employment of actual data

(if measured) or of simulated data (based on a Markov

chain model) if data is not available. Thus, the model

is suitable for both environmental assessment and planning

studies as well as for operational purposes during

emergencies and clean-up. The latter is known as the

adaptive tracking feature.

Certain.submodels that account for-we.athering

and degradation of the slick are also included. These

follow the first order model of Moore, Dwyer and Katz
(1973) for evaporation and dissolution and arbitrary'

empirical functions for emulsification and sedimentation.

In summary, this model represents a very

comprehensive approach to the Problem of predicting oil

spill trajectories in the offshore region and even

though many of the submodels are elementary, the

fundamental stochastic approach is will justified.

Model Name or Description

University of Rhode Island (URI) Georges Bank

Reference

Cornillon, P.C., M.L. Spaulding, and K Hansen-,
"Oil Spill Treatment Strategy Modeling for
Georges Bank," Proceedings of the 1979 Oil
Spill Conference, Los Angeles, California,
American Petroleum Institute, Environmental
Protection Agency, and U.S. Coast Guard.

Abstract

As part of a larger project assessing the
environmental impact of treated versus untreated oil spills,
a fates model has been developed-which tracks both the
surface and subsurface oil. The approach used to spread,
drift and evaporate the@,surface slick is similar to that
in most other oil spill models. The subsurface technique,
however,.makes use of a modified particle-in-cell method
which di-ffuses and advects individual oil/dispersant droplets
representative of a large number@of similar droplets. This
scheme predicts the time-dependent oil concentration distri-.
bution in the water column, which can then be employed as.
..input to a fisheries population model. In addition to
determining the fate of the untreated sp--11, the model also
allows for chemical treatment and/or mechanical cleanup of
'the spilled oil. With this capability, the effectiveness of
different oil spill control and removal strategies can be
quantified.

The model has been applied to simulate a 34,840
metric ton spill of F_ No. "0-type oil cn Georges Bank. The
concentration of oil in the water column and the surface
slick trajectory are predicted as a function of time for
chemically treated and untreated spills occurring in April
and December. In each case, the impact on the cod fishery
was determined and is described in detail in a paper by
Reed and Spaulding presented at this conference-.

Reviewer's.Comments

This model considers spreading, advection

dispersion and evaporation. Spreading is based on a

modified version of Fay's (1971) theoretical development.

Ocean currents were simulated by averaging estimates

obtained from a lon,--term study of surface drift'er returns.

The model envisions that detail information from ocean

surface transport or continental shelf circulation studies

will be available as input. Advection is then simulated

by the vectorial addition of ocean and wind-induced currents.

Evaporation is simulated by application of a numerical

solution to the procedures developed by Wang, Yang and

Hwang (1976).

The subsurface transport of the dispersed oil

is simulated by a three-dimensional mass transport equation

which is solved by a "quasi Monte Carlo technique."

Although it is stated that extensive model testing was

performed in order to assure tfiat the sub-process models

correctly interfaced with one another, it appe,ars that the

model contains a mixture of numerical as well as physical

dispersion.

The model has been applied to four different

versions of a simulated spill. Unfortunately, there are

no comparisons with field observations.

Model Name or Description

Puget Sound Model

Reference

Karpen, J., and J. Galt, "Modeling of Oil
Migration in Puget Sound," Proceedings of
Oceans 179, Marine Technology Society,
Washington, D. C.

Abstract

The oil migration is simulated with a mixed
Lagrangian-Eulerian model. The movement of the oil is
modeled with Lagrangian point masses or Lagrangian elements
(LE). Time dependent dispersion is applied to the
individual LE's. Eulerian current and wind fields are used
to advect the LE's.

Several scenarios for hypothetical spills in the
'Straits afid upper Puget Sound are shown. The model accurate-
ly predicted,the migration of the diesel oil spill at
Ancortes, Washington.

The model is general enough so that submodels
from currents and winds aeveloped for other regions ca:n
be easily integrated into the simulation.

Reviewers Comments

A model named the Puget Sound Model was reviewed

by Stolzenbach, et.al (1977), but the model described in the

above reference is an entirely different one than that

reviewed by-Stolzenbach. The model simulates advection

and the combined effects of spreading and dispersion.

Spreading, using the theoretical approach developed by

Fay (1971) was not employed. Instead the available data

was used to determine a spill length scale as a function of

time. The spill length corresponding to the spill size

was then used in a modified random walk scheme to simulate

the combined spreading and dispersion. It is stated that 'm

this approach is comparable to diffusion by continuous

movements for discrete particles or Fickian diffusion.

The advection for wind and tidal currents are then super-

imposed on the combined spreading and dispersion.

Most of the data used in the regression

equations to determine the spill length, size and time

relations do not consider spill rates. There is some

question how this technique can be used in situations

where spill rate is an important factor. Also, there

may be other factors (i.e.,-boundary conditions) that

effect the spill length-time relationship.

Model Name or Description
Reference Canadian Arctic Environment Service(CAES)

Venkatesh, S., S.H. Sahota and A.S. Rizkalla,
"Prediction of the Motion of Oil Spills in
Canadian Arctic Waters," Proceedings of the
1979 Oil Spill Conference, Los Angeles,
California, American Petroleum Institute,
Environmental Protection Agency, and
U.S. Coast Guard (1979)

Abstract

An oil spill movement prediction model operating
as part of a real-time Environmental Prediction Support
System for the Canadian Beaufort Sea has been developed.
The present version of the model considers spills only in
open waters, that is, the sea surface is considered to be
ice free.- The model has been partially verified with
data obtAined from,oil simulation experiments conducted
in the Bay of Fundy, off the@coast of Canada during the
months of Ai1gust and September 1978. With the use of
observed winds, the model-predicted locations'of "Orion"
buo*ys used to-simulate the motion of oil o@ water, agreed
fairly well with their observed locations. These verifi-
cation tests also pointed out the need for high-resolution
surface wind forecasts-essential data for computing wind-
driven water currents which move the oil.

Reviewer's Comments

This model uses the numerical technique known

as the Discrete Parcel Random Walk method. This method

is identical to that used by Ahlstrom (1975). In a sense,

this model is an adaptation of Ahlstrom's model (BOSTM).

Spreading follows Fay's theory. Of the weathering processes,

only evaporation and emulsification are considered because

of their predominance in the first few days of slick

formation. Treatment of both evaporation and emulsification

follows the procedures developed by Mackay and Leinonen

(1977). Advection is considered to be due only to wind-

induced surface currents and is based on the work of

-eady surface drift
Madsen (1977). The expression for st

becomes a very simple relation,

. The computational method assumes that the sub-

spills act independently of each other. Therefore, the

effect of neighboring subspills is neglected as is the

spill-spill interaction effect. The model has been applied

to four separate simulation experiments conducted in the

Bay of Fundy.

Model Name or Des cription

Riverspill

Reference

Tsahalis, D.T., "Contingency Planning for
Oil Spills: Riverspill - A River Simulation-
Model," Proceedings,1979 Oil Spill Conference,
Los Angeles, California, American Petroleum
Institute, Environmental Protection Agency,
and United States Coast Guard (1979)

Abstract

A simulation model., Riverspill, has been
developed for the prediction of transport, spreading, and
associated land contamination of oil spills on rivers. The
effects of volume and type of oil, use of Oil Herder or
not, type, location, andtime of occurrence of the oil spill,
geometry, and hydrographic characteristics of the river and
wind speed and direction are taken into account. The model
is capabie of operating in either deterministic or stochastic
mode. When'the model is used in the deterministic"mode, it
predicts th6 path and associated land contamination of a
specific oil spill as a functi-on of time. When the model
is used in the s'tochastic.mode,,it estimates the probability
that an oil spill will be transported into a specific region
after an accidental discharge within another specified
region. In the present study, the model is specifically
applied to the lower Mississippi River. However, the model
is general and can be applied to any river. The predictions
of the model are in very good agreement with the observed
behavior of actual oil spills on the Mississippi River.

Reviewer's Comments

This model was developed specifically for river
flows. Spreading followj Fay's (1971) theory, in which all

three regim-es are modeled. Advection due to wind and current

is modeled by some derived relationships which depend on the

direction of the wind velocity vector relative to the

current vector. Some experimentally d,-@termined coefficients

9.1

are employed in the derived relationships. Cross flows

(i.e., secondary) are also considered. The model has been

applied.to two accidents on the Mississippi River. The

agreement between observed and model predicted deposition

sites ranged from good to excellent.

Model Name or Description

National Weather Service (MVS) Model

References

(a) Hess, K.W.J. The National Weather Service Oil'
Spill Motion Forecasting Program," Workshop
on-the Physical Behavior of Oil in the Marine
Environment, Princeton, University, Princeton,
New Jersey, May 8-9, 1979

(b) Hess, K.W., and C.L. Kerr, "A Model to Forecast
the Motion of Oil on the Sea, Proceedings of the
1979 Oil Spill Conference, Los Angeles, California.
American Petroleum Institute, Environmental
Protection Agency and U.S. Coast Guard,
Washington, D.C. 1979
Abstract (From Reference ('a) Text)

The purpose of this model is to provide an
operational method to forecast the movement of oil spilled
in the ocean The model utilizes the National Weather
Service (NWS) meteorological forecasting capabilities to
provide scientific prediction of the medium or long-range
(up to 5 days) future oil behavior. In this time range,
oil motions are strongly influenced, if not dominated,
by wind effects (wind stress, wind-driven ocean currents,
wind waves.and evaporation). Forecasting using numerical
models of the atmosphere give better results for this time
range than the use'of either a statistical (climatology),
or a presistence approach..

. The present model does not use the-trajectory
and point-mass simplifications of oil behavior; instead
a two-dimensional approach is employed to predict the
spatial variation of oil thicknesses. The oil spill model
consists of three major segments, relies heavily on finite
difference techniques and is driven by output of NWS I
atmospheric models. The three separate parts are: (1) a
model of the atmospheres near-surface planetary boundary
layer, (2) a dynamic model of the upper mixed-layer of the
ocean, giving surface currents, and (3) a dynamic model of
two-dimensional variable thickness oil distribution on the
sea. In general, the first two segments provide input to
the third in the form of stresses at the upper and lower oil
boundaries. The most important simplifications of the
present model are neglect of tide and wave effects and absence
of weathering. Reference (b) provides additional details
on this model which is under continuing development.

Abstract (From Reference (b))

A model to forecast the motion of oil spilled
on the surface of water was established by combining
separate models for the motion of oil, the motion of
water, and the motion of air. The model for the motion
of oil is based upon the hydrodynamic equations as they
apply to oil on water. This model requires information
at both the lower and upper boundaries of oil. At the
oil lower boundary, the information is obtained from a
m6del for the motion of water. This model is formulated
by combining Ekman dynamics and continuity for the upper
mixed layer of the sea. At the oil upper boundary, a
model for the motion of air provides the required
information. This model is based upon an analysis of
output obtained from one of the National Weather Service's
multi-level atmospheric models. A number of case studies
demonstrate the features of the seDarate models and the
composite oil spill model.",

Reviewer's Comments
This is a very comprehensive model which takes V

advantage of the operational wind forecasts made-available
by the National Weather Service. Separate7model's for the

motion of oil, water and air are combined into,a composite

model which is undergoing continuing development and

improvement. The model has been applied in preliminary

form to the Argo Merchant spill. The model results in

comparison with observations indicate the potential

applications and limitations of this model. The model

approach appears well suited for making real time fore-

casts of oil motion in locations far offshore and

especially where wind is the dominant driving force.-

Model Name or 'Description

U.S. Coast Guard (Long Island Sound)

Reference

Kollmeyer, R.C., "Long Island Oil Spill Drift
Prediction Model," Proceedings of Workship on
Government Oil Spill Modeling, November 7-9,1979,
Wallops Island, Virginia, NOAA, Washington, D.C.
February 1980

Abstract

Because of the sensitive nature of the Long Island
area and the complex nature of the surface currents in the
Sound, the On-Scene Coordinator (OSC) must be able to predict
oil spill trajectories accurately in order to deploy cleanup
equipment and to protect sensitive areas. Present oil spill
movement prediction models are inadequate for this need and
are not.readily accessible to the OSC.

The goal of the project is the production of a
real-time prediction model that will forecast the movement
and spread of -an oil spill in Long Island Sound. Upon
command, the model will, for a given period, produce a
time series of charts displaying the location, shape and
coficentrations of the oil spill.

The model will be constructed on the computer
facilitie's provided by the Department of Computer Science
U.S., Coast Guard Academy. Captain R.C. Kollmeyer will be
the'overall project coordinator. A:close liaison will be
maintained ainong all interested and contributing units.
At present, the following Coast Guard units are involved:

1. Coast Guaxd Academy
2. Commander, CG Group, Long Island Sound
3. USCG Research and Development Center, and
4. USCG Oceanographic Unit.

The oil drift mechanisms to be modeled will
include the following:

1. predicted tidal currents,
2. Stokes drift, considering both
duration and fetch limitations
3. leeway of oil slick caused by the wind, and
4. wind drift currents of the surface layer.

A relatively sophisticated computer graphics
output is desired in the form of segment maps showing the F
spill, its location, areal size, and concentration
gradients. These maps would be produced on a time basis,
showing the oil spill's predicted location every 15 minutes
from the time of the s-oill.

The preparation of the tidal current data set
will include the use of overlays for the NOS tidal current
charts to allow the@_r transfer to the model matrix. A scaling
program (inverted smoothing) will then determine the currents
for all other points on the matrix for each of the 13 current
charts available. Currents along the shore boundaries will
be made zero unless other information is available.

A planned program of verification and testing
will be develoDed aL; part of the mod-1 completion. Proce-
dures will be proposed by which small oil spills in
Long Island Sound may be monitored and used in a hindcast r
mode. In addition a testing program will be drafted that
would use oil drift simulators which can be tracked and
compared with model predictions.

Reviewer's Comments

The above reference simply describes a program
being undertaken to develop a model with certain specific'

goals and features. It likely will be similar to the

model developed by USCG for New York Harbor.

Model Name or 'Description

SPILSIM

References

(a) Pickett, R.L., "A Surface Oil Spill Model for
the Great Lakest Proceedings of the Workshop
on' Government Oil Spill Modeling,
November 7-9, 1979, Wallops Island, Virginia
KOAA, February 1980
(b) Boyd, J. D., "A'Surf'ace'Spill Model for thd
Great Lakes," Great Lakes Environmental Research
Laboratory,- Ann Arbor, Michigan, 1979

Abstract (Edited from Reference (a))

This model was developed as an operational
forecast model for the movement of surface-pollutant spills
on the Great Lakes with special emphasis on oil spills. Oil
,spills a:te of particular concern because of their environ-
mental impact and the substantial quantities of oil transported
on the Great Lakes, both as cargo and as fuel. The Great Lakes
Environmental Research Laboratory (GLERL) undertook this
modeling effor t because a number.-of'models were being developed
for oceanic spills but none were being developed for those on
the Great Lakes. The resulting model, SPILSIM, is a batch
oriented model derived form oil spill models from the Canada
Center for Inland Waters (CCIW) and NOAA's Pacific Marine
Environmental Laboratory (PMEL). It predicts.the movement
of an insoluble surface spill,anywhere within the Great
Lakes, given spill size and location and surface currents
and winds in the area of interest, Modifications to make
the model interactive are strai ghtforward.

Reviewer's Comments

This is a simple model that simulates advection

by wind and currents.

Model Name b3@ De'scriptlon

Environmental Data and Information Service r
(EDIS) Model

Reference

Bishop, J.M., A Climatological Oil Spill
Planning Guide, No. 1, The New York Bight.
NOAA, Washington, D.C., 1980

Abstract

Over the past 4 years. the Environmental Data
and Information Service (EDIS) of NOAA has developed a
multiple trajectory oil spill model. The model is based
on the archived wind and current data available within
EDIS's--National Climate Center (NCC) and National
Oceanographic Data Center (NODC). The model was
originally designed for assessment of possible environ-
mental impact due to construction of a deepwater port
off the Texas coast, but has been used effectively in
the Argo Merchant and Compeche oil spills for a rapid
estimate of the impact areas. The successful use of
this model for climatological assessments of large ocean
spills leads to the conclusion that this type of
climatological forecasting technique sliould be a part
of our overall response to major oil spills.
Although the utility of this appro@ch has been
shown in these two examples of large open-ocean oil spillsf
a better application of this climatological (Type I) model
is in contingency planning (prespill resource allocation).
In this mode, one can map most probable imnact zones
over known local resources (biological or economic). Such
a use has been initiated in a recent EDIS. publicafion
produced for use by the 3d Coast Guard District contingency
planners..couples key environmental data (both physical
and biological) with climatological oil spill trajectory
forecasts.

Reviewer's Comments

This model is an enhancement of the DPPO model

but in an empirical-simplified direction rather than in

the fundamental-comprehensive direction taken by Garver

and Williams (1978). Advection due to wind and currcnt is

determined using measured data. These, in t,-.,.rn, are coupled

with Pay's spreading theory to predict the spill trajectories.

Model Name or Description

Particle-In-Cell (PIC) Model

Reference

Tingle, A.G., "Perturbation Analysis of the
New York Bight," Proceedings of the Workshop
on Government Oil Spill Modeling, November 7-9,
1979, Wallops Island, Virginia, NOAA,
Washington, D.C., February 1980.

Abstract

The physical transport of pollutants, their
modification by the coastal food web, and transfer to men
are problems of increasing complexity on the continental
shelf. In an attempt to separate cause and effect, a
computer modeling technique is appliedto problems involving
the transport of pollutants as one tool in assessment of
real or potential@coastal perturbations. Approaches for
further model development of.the biological response within
the coastal marine ecosystem are discussed. Our present
perturbation analyses consist of 1) a circulation submodel,
2) a simulated trajectory of a pollutant.particle within
the flow field, and 3) a time-dependent wind input for each
case of the model. The circulation model is a depth-
integrated, free surface formulation that responds to wind
stress, bottom friction, the geostrophic pressure gradient,
the coriolis force, and the bottom topography.' The transport
diffusion model is based on Lagrangian mass points, or
"particles" moving through a Eulerian grid. The trajectories
of material moving on the surface and in the water column
are computed. It has the advantage that the history of each
is known. With these models, we have been able successfully
to: 1) reproduce drift card data for determining the
probabilities of a winter oil spill beaching within the
New York Bight, 2) analyze the source of floatables
encountered on the south shore of Long Island in June 1976,
and 3) predict the trajectory of oil spilled in the Hudson
River after it had entered the New York Bight Apex. For
future analyses, the shallow water model can be modified
or replaced with a numerical model that contains a more
sophisticated parameterization of the physical circulation.
Also, the particle-in-cell model can be modified to
explicitly include chemical reactions and interactions
with the biota. A model should be used in the context
of the level of resolution or aggregation that is known
about the ecosystem and the management decision to the made.
Mode'ls are used also as an aid in selecting situations
that merit further analysis with more comprehensive ecologi-
cal reasoning.
100

Reviewer's Comments

This model is based on a numerical hydrodynamic

model of the area under study. One of the difficulties

in applying models of this type to other regions is the

determination of the model boundaries and treatment of the

boundary cells (free, fixed, no-slip, reflecting). A

disadvantage in the use of models of this type is the

required cost of computation-even on the largest, most

sophisticated computers.

101

Model Name or,DescriDtion

The U.S. Geological Survey Oil Spill Trajectory
Analysis (OSTA) Model

Reference

Samuels, W.B., "The USGS Oil Spill Trajectory
Analysis Model," Proceedings of the Workshop
on Government Oil Spill Modeling, November 7-9, 1979,
Wallops Island, Virginia, NOAA, Washington, D. C.,
February 1980.

Abstract

The USGS oil spill trajectory analysis model
(OSTA) is used to calculate the probability of oil spills
occurring and contacting environmental resources and sections
of the coastline. A grid system is superimposed on the
study area with a maximum of 480.miles on a side. The
dimension of the grid cell is variable depending on the size
of the study area. Locations of environmental resources
proposed and existing lease tracts, and oil transportation
routes (pipeline and tanker) are determined by their
positions in the model's grid system. Data from different
map projections can-be digitized and fitted into the model's
grid system by coordinate conversion subroutines. A maximum
of 31 categories of resources and up to 100 segments
(2 different sets) of the coastline can be included in the
analysis.
Oil spills are simulated in a Monte Ca@lo fashio,n.
Typically, 500 simulated oil spills are launched per season
from each launch point (platform location, pipeline, or
tanker route). Spills are transported by monthly currents
and by winds sampled from wind transition matrices, These
matrices, composed of 41 wind velocity states, are based
on historic wind records. They are constructed for each
.season for up to six wind stations. Surface ocean currents
are incorporated in a deterministic manner by representing
monthly current fields in the model's grid system. The
spill movement algorithm consists of computing the vector
sum of a wind and current vector for successive 3-hour
increments. Each grid cell in the path of the spill is
checked for the presence or absence of each environmental
resource. Spill movement ends in one of three ways:
1.) the spill contacts land, 2) the spill decays at sea,
or 3) the spill moves off the map.

102

Conditional probabilities of contact are reported
for 3-, 10-,.and 30- day travel times. Oil spill occurrence
is treated as a Poisson process, in which the exposure
variable is the volume of oil produced or transported.
Scenarios outlining proposed oil production and transportation
arp constructed for various.alternatives. The overall risks
are determined by combining spill occurrence probabilities.
Recent applications of the model have been: Sale 55 (Northern
Gulf of Alaska., Sale 53 (Northern and Central California),
and Sale 46 (Kodiak Island).

Reviewer's Comments

This model uses a vectorial approach of wind and

current to simulate advection. The use of input data is

very similar to the DPPO model. The movement of the slick

is tracked for a specified duration of time via employment

of actual data or of simulated data (based on a Markov chain

model) if real data is not available. This model has been

used !or environmental assessment in connection with a

number of offshore lease sales (e.g., Alaska, Gulf of

Mexico, Southern California and North-, Mid- and South

Atlantic).

103

Model Name or Description

On-Scene Spill Model (OSSM)
Pacific Marine Environmental Laboratory
NOAA, Seattle, Washington

Reference

(a) Torgrimson, G.M., and J.A. Galt, "An On-Scene
Spill Model for Pollutant Trajectory Simulation,"
Workshop on the Physical Behavior of Oil in the
Marine Environment, Princeton University,
Princeton, New Jersey

(b) Galt, J.A., and G.M. Torgrimson, "On-Scene
Trajectory Modelling for the U.S. Response
to the.IXTOC-1 Blowout," Proceedings of the
Workshop on Government Oil Spill*Modeling,
November 7-9, 1979, Wallops Island, Virginia,
NOAA, Washington, D.C., February 1980,

Abstract

(a) The,Pa cific Marine Environmental Laboratory's
Hazardous Materials Scientific Support Team (PMEL/HMSST)
has developed a data ma:nagement*system for the rapid
simulation of'pollutant trajectories in the marine
environment. The On Scene Spill Model (OSSY) has been
designed to function at several different levels of
complexity depending on user requirements and'available
environmental data. OSSM may be utilized as an environ-
mental assessmeht tool to predict pollutant trajettories
and coastal impact areas, given hypothetical pollutant
spills. General cautions about interpreting the output
are included. Planned modifications and additions to
the existing program are listed. The data management
system was used to document and predict pollutant
trajectories during the PECK SLIP oil Spill off the
east coast of Puerto Rico on December 19, 1978.

(b) During the spill event associated with the
IXTOC I well blowout, the U.S. National Contingency
Plan was activated. In anticipation of this ' the NOAA
Hazardous Materials Response Project requested the
Hazardous Materials Scientific Support Team (for physical
processes) to supply trajectory information through the
scientific support coordinator. This was done beginning
June 12, 1979. During the summer, this plan required a
variety of activities including: (1) collecting available

104

background information, (.2) carrying out observational
field programs, (3) coordinating data and information
presented by other researchers (Federal, State and private)
and (4) analyzing trajectories.

During the spill, trajectory models were used
in basically three different forms. The first was in a
long-term statistically controlled form (strategic) for
planning call up and retirement of scientific or-cleanup
units. The'second was a short-term localized forecast
(tactical) for input into day-ta-'day planning. The third
was in a receptor mode that identified danger zones that
could impact scientific high-valued regions, This, in
turn, was used to develop optimal mapping strategies for
overflights.

The basic model for IXTOC I studies was a new
version of OSSM (On-Scene Spill Model) incorporating a
number of advanced features. In addition, several
auxiliary programs to analyze circulation data were also
used for the first time in a real spill situation. both
hindcas@s and forecasts from the models have provided
useful input to the overall response program.

Reviewer's Comments

This model is undergoing continuing development"

and improvement. The model is designed to be utilized

as a real-time spill trajectory model, Advection is

handled in vector fashion from both wind and current.

Diffusion is cu rrently modeled via a "llonte Carlo" approach

to the governing diffusion equations. Other algorithms are

being considered which would more accurately simulate spread-

ing and diffusion. Additional details will be provided in

the 1981 Joint Conference on Prevention and Control of

Oil Spills which will be available in September, 1982.

105

Model Name or Desc-iption

DRIFT

Reference

Hunter, J.R., "An Interactive Computer Model
of Oil Slick Motion," Oceanology International '80.

Abstract (from text)

An interactive computer model has been developed
.to predict the motion of an oil slick on the sea surface
which is particularly suited to the shallow waters of the
sea shelf. Wind-induced-drift and spreading are considered
to be the most important mechanisms in this motion. The
wind-induced drift is modeled via an empirical relationship
and the spreading, mixing and decay are modeled using Monte
Carlo techniques.

The model has been applied to an area of Irish
sea near Anglesey, U.K., and has predicted at least one
recent spill successfully.

Reviewer's Comments

This model is a classical deterministic approach

which incorporates the major mechanisms of importance to the
prediction of the motion of an oil spill in the area for

which it was designed. One of the underlying assumptions

in this model is that spreading is caused by turbulence

andlateral velocity shears. As a consequence, this model

should not be used to predict oil spill behavior during

early stages following the initial spill. The justification

for the approach that has been employed is based on a few

observations of very large spills wherein.it was noted

that spill diameter increases with the first power of

time. With proper imput, the model appears to provide

106

reasonable predictions. However, for predictions nearshore,

the model is very sensitive to errors in certain input

information. Therefore, use of the model in an operational
mode'requires continuous updating of input information.

107

CEIP Publications

1. Hauser, E. W., P. D. Cribbins, P. D. Tschetter, and R. D. Latta.
Coastal Energy Transportation-Needs to Support Major Energy Projects
in North Carolina's Coastal Zone. CEIP Report #1. September 1981. $10.

2. P. D. Cribbins. A Study of OCS Onshore Support Bases and Coal Export
Terminals. CEIP Report #2. September 1981. $10.

3. Tschetter, P. D., M. Fisch, and R. D. Latta. An Assessment of
Potential Impacts of Energy-Related Transportation Developments on
North Carolina's Coastal Zone. CEIP Report #3. July 1981. $10.

4. Cribbins, P. S. An Analysis of State and Federal Policies Affecting
Major Energy Projects in North Carolina's Coastal Zone. CEIP Report
#4. September 1981. $10.

5. Brower, David, W. D. McEiyea, D. R. Godschalko and N. D. Lofaro.
Outer Continental Shelf Development and the North Carolina Coast:
A Guide for Local Planners. CEIP Report #5. August 1981. $10.

6. Rogers, Golden and Halpern, Inc., and Engineers for Energy and the
Environment, Inc. Mitigating the Impacts of Energy Facilities: A
Local Air Quality Program for the Wilmington, N. C. Area. CEIP
Report #6. September 1981. $10.

7. Richardson, C. J. (editor). Pocosin Wetlands: an' Integrated Analysis
of CoAstal Plain Freshwater Bogs in North Carolina. Stroudsburg (Pa):
Hutchinson Ross. 364 pp. $25. Available from School of Forestry,
Duke University, Durham, N. C. 27709. (This proceedings volume is for
a conference partially funded by N. C. CEIP. It replaces the N. C.
Peat Sourcebook in this publication list.)

8. McDonald, C. B. and A. M. Ash. Natural Areas Inventory of Tyrrell
County, N. C. CEIP Report #8. October 1981. $10.

9. Fussell, J., and E. J. Wilion. Natural Areas Inventory of Carteret
County, N. C. CEIP Report #9. October 1981. $10.

10. Nyfong, T. D. Natural Areas Inventory of Brunswick County, N. C.
CEIP Report #10. October 1981. $10.

11. Leonard, S. W., and R J. Davis. Natural Areas Inventory for Pender
County, N. Ce CEIP R;port 11. October 1981. $10.

12.. Cribbins, Paul D., and Latta, R. Daniel. Coastal Energy Transporta-
tion Study: Alternative Technologies for Transporting and Handling
Export Coal. CEIP Report #12. January 1982. $10.

13. Creveling, Kenneth. Beach Communities and Oil Spills: Environmental
and Economic Consequences for Brunswick County, N. C. CEIP Report
#13. May 1982. $10.

CEIP Publications

14. Rogers, Golden and Halpern, Inc., and Engineers for Energy and the
Environment. The Design of a Planning Program to Help Mitigate Energy
Facility-Related Air Quality Impacts in the Washington County, North
Carolina Area. CEIP Report #14. September 1982. $10.

15. Fussell, J., C. B. McDonalds and A. M. Ash. Natural Areas Inventory
of Craven County, North Carolina. CEIP Report #15. October 1982..
$10.

16. Frost, Cecil C. Natural Areas Inventory of Gates County, North
'Carolina. CEIP Report #16. April 1982. $10.

17. Stone, John R., Michael T. Stanley, and Paul T. Tschetter. Coastal
Energy Transportation Study, Phase III, Volume 3: Impacts of Increased
Rail Traffic on Communities in Eastern North Carolina. CEIP Report #17.
August 1982. $10.

19. Pate, Preston P., and Jones, Robert. Effects of Upland Drainage on
Estuarine Nursery Areas of Pamlico Sound, North Carolina. CEIP
Report #19. December 1981. $1.00.

25. Wang Engineering Co., Inc. Analysis of the Impact of Coal Trains
Moving Through Morehead City, North Carolina. CEIP Report #25.
October-1982. $10.
26'. Anderson & Associates, Inc. Coal Train Movements Through the City of
Wilmington, North Carolina. CEIP Report #26. October 1982. $10.

27. Peacock, S. Lance and J. Merrill Lynch. Natural Areas Inventory of
Mainland Dare County, North Carolina. CEIP Report #27. November 1982.

28. Lynch, J. Merrill and S. Lanc e Peacock. Natural Areas Inventory of
Hyde County, North Carolina. CEIP Report #28., October 1982. $10.

29. Peacock, S. Lance and J. Mer rill Lynch. Natural Areas Inventory of
Pamlico County, North Carolina. CEIP Report #29. November 1982. $10.

30. Lynch, J. Merrill and S, Lance Peacock. Natural Areas Inventory" of
Washington County, North Carolina. CEIP Report #30. October 1982.
$10.

31. Muga, Bruce J. Review and Evaluation of Oil Spill Models for Applica-
tion to North Carolina Waters. CEIP Report #31. August 1982. $10.

33. Sorrell, F. Yates and Richard R. Johnson. Oil and Gas Pipelines in
Coastal North Carolina: Impacts and Routing Considerations. CEIF
Report #33. December 1982. $10.

34. Roberts and Eichler Associates, Inc. Area Development Plan for Radio
Island. CEIP Report #34. June 1983. $10.

35. Cribbins, Paul D. Coastal Energy Transportation Study, Phase III,
Volume 4: The Potential for Wide-Beam, Shallow-Draft Ships to Serve
Coal and Other Bulk Commodity Terminals along the Cape Fear River.
CEIP Report #35. August 1982. $10.

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