PB83-2381Q8
    Effects of Suspended  Sediments on
    Penetration of  Solar  Radiation into
    Natural Waters
    California Univ., Santa  Barbara
    Prepared for

    Environmental Research Lab.,  Athens, GA
    Jul 83
U.S. Department of Commerce
      Technical information Service

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                                         EPA-60,0/3-83-060
                                         July 1933
EFFECTS OF SUSPENDED SI DIMENTS ON PENETRATION
   Of SOLAR RADIA110N INTO NATURAL WA1ERS
                     by

            Raymond C.  Smith1'2
             Karen S.  Baker ^
            J.  Benjamin Fahy1

          •^Department  of Geography
 University of  California at Santa Barbara
      Santa Barbara,  California 93106

      2lnstitute of Marine Resources
    Scripps Institution of Oceanography
   University of California at San Diego
        La Jolla,  California 92093
            Grant No. 806372019
              Project Officer
              Ric-hard G. Zepp
      Environmental Processes Branch
    Environmental Research Laboratory
            Athens, Georgia 30613
     ENVIRONMLNTAL  RESIARCH  LABORATORY
     OFFICE Of  RESEARCH AND  DEVELOPMENT
    U.S.  ENVIRONMEN1AL PROTECTION  AGENCY
          ATHENS,  CEOIU.LA 30613

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                                   TECHNICAL REPORT DATA
                            (/'/ £!( nail tiu'nii inns on i/u nu;u ">< Ion i
        NO
   EPA-600/3-83-060
J TITLE A\D SUBTITLE
   Effects of Suspc-nde^ Sednents on Penetration
   of  Solar Radiation into .Natural Waters
                  Nl t, ACCES<;iOr#NO
                  ft  $   ?5818K
           b REI'OIU DA IK
            July  1983
           6 PERFORMING ORGANIZATION CODE
   Raymond C.  Smith1'? Karen S. linker2, and J.  Benjamin
                                                          8PEHIORMINGOIIGANIZA1IONIUIOHINO
   Fay
     ir-*-
•3 PERFORMING ORGANIZATION NAME AND ADDRESS
   •1-L'nivcrsity of California at Santa Barbara,  Santa
    Barbara, CA 93106
   2Scripps Institution of Oceanography, University of
    California at Fan Diego, La Jolla, CA 92093
 12 SPONSORING AGENCV NAME AND ADDRESS
   Environmental  Rcse rch Laboratory—Athens GA
   Office of  Research and Levelopment
   U.S.  Environmental Protection Agency
   Athens,  GA 30613
           10 PROGHAM ELEMENT NO
             CCUU A
           11 CONTI'ACT/GHANT NO

             80f> "J7-J019
           13 TYPI Ol nU'ORT AND PERIOD COVCHF.O
             Final,  2/79-12/92
           14 SPONSORING AGENCY CODC
             EPA/600/01
 IE SUPPLEMENTARY NOT?S
 16 ABSTRACT
         Aquatic photochcn-Lcal and photobiolrgical  processes depend on both the .unount
   and the spectral compot>ition of solar radiation  penetrating to depths in natural wa-
   ters.   In turn, the depth of penetration, ar  a function of wavelength, depends on  the-
   dissolved and suspended material in  these waters.   As a consequence, the rates of
   photochemical transformation as well as  the  impact  on photobiological processes, de-
   pends  on the optical properties, of these water bodies as determined by their dissolve.
   and suspended material.  In particular,  because  pnoto-chemical processes are frequent
   ly governed b> radiation in the ultraviolet  region  of the spectrum, the optical pro-
   perties of natural wacers in this spectral region are especially important.  In this
   study, several theoretical models were developed and some unique experimental data
   were developed for the purpose of characterizing the optical properties of various
   natural waters.  Particular e-.i,>hasis was placed  on  optical properties in the ultra-
   violet region of the spectrum.  Optical  properties  of water bodies  were modeled in
   terms  of their dissolved materials and suspended sediments so that the solar radiant
   energy penetrating to dept."- in tnese waters  can be calculated from available, or
   easily collected, experimental uita.  The theoretical models, with imput of these
   data,  can then be used to calculate  the  rates of photochemical and photobiological
   processes in various aquatic environments.
                               KEY WOHOS AND DOCUMENT ANALYSIS
                  DESCRIPTORS
                                             h IDENTIFIERS/OPEN ENDED TERMS
                          COSATI I ltlll/(.liill|i
14 DISTRIBUTION STATCMfcNI

   RELEASE TO PUBLIC
SECURITY CLASS /Ilin K,f/
                                                JNCLASsIFim
                                                                        22 PRICE
EPA Form 2220-1 (9 73)

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                               DISCLAIMER

      Although the research described in this report ha.s been funded
wholly or in part by the United States Environmental Protection Agency
through Grant No. 8063720J9 to the Universit> of California at San
Diego, it has not been subjected to the Agency's required peer and
policy review and therefore does not necessarily reflect the views of
the Agency and no official endorsement should be inferred.
                                   ii

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                                   FOREWORD

      Environmental protection efforts are increasingly dliecteu towards
prevention of adverse health and ecological effects associated with specific
compounds of natural or hutvan origin.  As part of this Laboratory's research
on the occurrence, movement, transformation, impact, and 
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                                    PREFACE

     Within an aquatic environment  the  presence  ot  solar  rauiation  as   in
cneigv  source  is  ot  fundamental importance.  Uur ability to unuer&iand anu
manage our aquatic resources is theretore strongly  linked to  our  aoility   to
understand  the  penetration  of radiation into a body ot water acd  its appor-
tionment among various components of dissolved and  suspended material  in  the
water.   This  report  presents  a  study  in hydrologic optics which included
assembling t data base of relevant  optical measurements, deriving mathematical
models  for  the  solution of the equation of radiative transfer,  and deducing
from these both simplified theoretical and practical results.  This  study will
have  long  term benefits, not only to the investigators of hydrologic optics,
but also to a wide variety of other fields concerned  with  understanding  and
predicting phutoprocesses in an aquatic environment.
                                      iv

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                                   AU SIR ACT

     The relationsnip oetween dissolved and suspti.dcd  cons t1 tucr.t s   in  water
and the optical properties ol a range oi water types has been  investigated and
anlytically characterized using  several  approaches.   This   characterization
permits  the spectral radiant energy throughout the water column  to be predic-
tive ly modeled.  This in turn provides a basis for the  quantitative  calcula-
tions of photo processes such as photolysis rates, in aquatic  environments.

     A series of new laboratory experiments has provided a set  oi  data  upon
which the Bio-optical Component Model (Baker and  Smith. 1981)  could be further
dej^ioped.  The investigation into the humic acid component has   been  contin-
ued.  A new component dealing with a terrigenous  clay has been added.  Both  of
these components are parameterized and hence remain within the  intended  sim-
plicity of the original model.

     A briet introduction to underwater modeling  is presented  as  an   introduc-
tion  to  the  development  of a Monte Carlo model.  The Uio-optical Component
Model allows calculation of the diffuse attenuation coefficient of Irradiance.
howeNPr  it does not permit calculations with respect to sun angle or investi-
gations into the changing light field as a function of depth.  The Monte Carlo
method  is  a  photon tracking technique, essentially a random walk procedure,
using the apparent optical properties ot the water.  Ibis oojc 1   can  then   be
used  to investigate the influences of depth and  sun au^lo on  the lijut field.
Technical anu practical considerations limit the  collection ot aata  pertinent
to  all  lijjht  conditions.  Indeed,  this is the  advantage ot  a model.  It can
serve as an organizational tool as well as a deductive and predictive tool.

     To organize field data to test the developed models, it v.as  first  neces-
sary  to uecermine the best available values tor  the optical properties ot the
clearest natural waters.  An extension and a completion of the set 01 apparent
anu  iniicrent  optical  properties  for  the  clearest natural waters has been
described.  Also,  other optical field data sets have been collected and organ-
ized.

     This report was submitted in fulfillment of  grant //S06-372-019 under  the
sponsorship of the U.S. environmental Protection  Agency.  This report covers  a
period from February 1979 to December  1982  and  v/ork  was  completed  as   of
December 1982.

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                               TABLE  OF  CONTENTS


List 01 Figures ..................................................   v'

List of Tables [[[     j .•
I .  INTRODUCTION ..................................................     1

II .  CONCLUSIONS ..................................................     4

III .  RECOMMENDATIONS .............................................     5

IV .  liXPUlLMLNTAL .................................................     7
      A.  Tan* Data ...............................................     7
      U.  DOil [[[    10
      C.  Other Field Data ......... . ...............................    11
V .  Til^OiiiiTlCAL [[[    12
      A.   '1 10  Code .............................................    13
      J .   Jjvc LOce .............................................    13
      L.   .on '« Cjrlo noc!eliii{, ....................................    14
      D.   POOP [[[    15
      i).   >>iocel Cnecjts ............................................    16

VI.  liESULTS [[[    18
      .i.   vuuosj-acre .............................................    12>
      J.   TII..J data  - . lejr viator ................................    iy

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                                LIST OF FIGURLS

I-igure 1.  ite lationsnips between experimental  tielu  liata  and  toisputcr  aodcls.  24

Figure 2.  The spectral  l.ght attenuation  in each  ot   the  Clay   Group   water
types #1 - #8 listed  in Table 1.                                               25

Figure 3.  The spectral  light attenuation  in each  of  the  DOM  Group water  types
#9 - #16 listed in Table 1.                                                    25

"Mg'.re -! .  "he spectral Kclay component  for each of  the Clay  Group water  types
,'2 - J 8  1 -iied in Table 1.                                                     26
       5.  Int Kclay component for  the wavelength  range  from  275nu  to  74Snm.   26

Fifui  >   The Kclay component for  the wavelength  550am  for a  range   of   clay
Ippm] where *h: x s are experimental data  and  the  line  is  a polynomial  fit.    27

Figure 7.  The Kclay component for  five wavelengths  where   5B300niL.  ll»450nm,
13=550nn, and 15=650nm where  these  points  represent  data and  the  solid  line  is
the model fit.                                             -                    27

figure 8.   ihe  spectral  u'uoa  component   (with   scattering  material   still
present;  see teit) for a UXI  Group  water  types  >/ll  - £16 listed in  Tablo  1.    28

Figure 9.  The spectral iCdco  component for  the  DOM  Group water  types #11  - #16
listed in Table 1.                                                             28

Figure 10. The Kdotn component tor two wavelengths where  the   points are   data
and the solid line is a fit.                                                   29

Figure 11. The spectral (kaoa^&clay ) component  where  the x's  are  data  aad the
line is the aodel fit.                                                         29

Figure 12.  The spectral Ktot data  points  and   analytic  model   fit as   solid
lines for the Clay Group.                                                      30

Figure 13.  The spectral Ktot data  points  and   analytic  model   fit as   solid
lines for the DOM Group.                                                       30

Figure 14.  The total scattering b  for a variety of  water  types from molecular
scattering to clear water to  ocean  to river.                                   31

Figure 15.  The spectral a (solid line),   b   (dashed  line),  c  (dash  dashed
line),   and  b/c  (notched  line)   for SCOR  Discoverer  station  21 Sargasso Sea
waters.  The D points  are  the  field  data  measurements ot   total   diffuse
attenuation  coefficient whereas the 1,6 are  the Monte  Carlo  calculations of  K
for 10 degree and 60 degree sun angles.                                        32

Figure 16.  'Ihe a (solid line), b (dashed  line), c  (dash dashed line),  and b/c
(notched  line.)  for San Vicente waters.   The circled 1,6  points  are the  field
measurements of total diffnse  attenuation  coefficients  for  tun   angles  10
degrees and 60 degrees whereas the  1,6 points are  the Monte Carlo predictions. 33
                                      VI11

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Figure 17.  The particle volume  scattering  function   for   fairly   clear   ocean
water  (Oceanus  cruise  station  4)  tor  wavelengtns 440nm,  490nm,  520nra,  610nm,
and 670nn.                                                                      J4

Figure 18.  The calculated  total volume scattering   function  for  very   clear
ocean  water  (SCOR Discoverer  station 21) for  wavelengths  440nm,  490run,  520nm,
6lOno, and 670nn.                                                               35

Figure 19.  The Baker-Smith III  component model  prediction  of  spectral  Ktot
(X) for a range of chlorophyll,  dissolved organic material and clay.   The  fol-
lowing explains the composition:                                                36
line
chl
DOM
.,,
solid
0 .5 5.
000
000
dashed
0 0
.5 5.
0 0
dashed dot
0 0
0 0
5 25
hatched
.5 5
.5 5
5 25
r--g.  20.  The Monte Carlo  calculation  of  KO..z,0)  for   waveler.gth  S50"-«  for
son  angles  10,  30, 60, 70,  SO  degrees plotted  versus  optical  depths  cz when
using only a direct  oeaa  input  to the water  column.                             37

Fig.  21.  The Monte Carlo  calculation  of  Jx(X, z.O)  tor   wavelength  55Own  for
sun  angles  10.  30, 60, 70,  80  degrees plotted  versus  optical  depths  cz when
using both a direct  and a diffuse  input  to the  water  column.                    38

Fig'-re 22.  The 'lonte Carlo calculation  of HO., z. 0) for  cleir  waters of   SCCK
Discoverer  for sun  angle 10 degrees  (solid  line) and 40 degrees (broken  line)
for wavelengths 440nm, 490iun,  515nm,  and 550nn.   The  straight  line j-uperim-
posed is the field measured value  which  is an  average for the  day.              39

Figure 23.  The Monte Carlo calculation  of K(X.z.O) for  San Vicente  waters for
sun angles 10,  30. 60, 70,  80 degrees for  wavelengths 440nm, SSOnm,  and 670nm.
The straignt lines superimposed are  the  field measured values  for  10   and  60
degree sun angles.                                                              40
                                LIST OF TABLES
Table 1.  Tank study water  types.
23
                                      ix

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                                ACKNOWLEDGEMENT

     Xichard Zcpp recognized the recessity for those studies and acted as pro-
ject  officer  during  the course ot this research.  Uc continually encouraged
our researcn and provided valuable  scientific  input through  informal  discus-
sions  and  the  practical  utilization  of oui results.  An earlier EPA grant
RG806489010, under the BAGIil program and concerned with the penetration of  UV
radiation   into natural waters, supported the  development of the UV spectrora-
diometer used in this research.

     The tank data were obtained with the  help  of  the  Marine  Application*
Group  at NASA Langley Research Center,  especially Wayne Esaxas. Lament Poole,
and Charlie Whitlock - who made the facilities available -   and  Al  Gurganut
and  Jim  Usry  who helped obtain the data.  Lamont Poole also collaborated in
the development of the Monte Carlo modeling.  This  node ling  built  upon  tag
earlier work of J.V. Oave and John Kirk.

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                                   SECTION 1

                                 INfiiODUCTlUN

     Aquatic photochemical and photob loiog ical processes depend upon both   the
amount  of  solar radiation penetrating to depths in natural waters as well  as
upon its spectral composition.  It  is  the  influence ot dissolved  and suspended
material  in  the water combined with  the characteristics ot clear water which
determine the attenuation ot light  in  a  water  column.   Our  maiu  research
objective  was  to characterize varuus natural waters, in terms  of their  con-
stituents and consequent optical  properties  so  that  the  spectral  radiant
energy  versus  depth  can  be  estimated.   Waters  containing humic acid and
suspended sediments were of particular interest.   This  characterization   can
then be used to calculate rates of  photochemical and photobiological processes
in aquatic environments.  This in turn allows a quantitative assessment of  tae
photochemical process that may account for the transf ormai j on of  pollutants  in
aquatic environments.  Some new r ad i one trie laboratory field studies have  been
made  and  combined  with information  from previous bio-optical field studies.
This has allowed the further development  cf models and  theory  which  can  in
turn be defined and checked by tae  data.

     Pre iseadorier '1976) has defined  the  inherent  optical  properties  of   a
uetliou  to be those itnuch are iuue pendent  of the lignt-iield within the  vatcr.
iuciuueu witiim tais set are tne  beam  absorption  toei i ice int   c.  tae   bean
scattering  coefficient  b.  and the total  attenuation coefficient c, wnere  c  =
ai-b.  The parameter b is actually the  integral  over  all  angles  ot  another
inherent optical property, the volume  scattering coefficient

                              b = /   k (0) dU .                            <1)
Preisendorf er has shown the set  (c, p) of inherent optical properties  to   be   a
sufficient and complete set for  describing the optical properties  of  the  opti-
cal medium under any circumstances.  That  is,  knowing   (c,p),   and   an   input
radiance  distribution  illuminating  the  optical  medium,   which is  arranged
within some known geometry, one  can  in principle deduce  the resulting  radiant
ilux distribution.

     If an optical property does vary with respect  to cnanges in the   radiance
distribution,  it is said  to be  an apparent  optical property.  To  describe  the
penetration of solar  radiation  into  natural  waters,  we   use  the  diffuse
attenuation coefficient for irradiance, which is an apparent  optical  property,

                         K(z.X)  = -1/EU.X)  dE(z.X)/dz                       (2)

or alternatively,

                   E(z2,X) =E(zrX) expt-K(z.X) •  (Zj-Zj)]                 (3)


wnere K has units of reciprocal  length,  z.  and   z,  are   the   depths   which
increase  positively  with increasing depth  at which E(z.)  aid E(z_)  are  meas-
ured.  In particular, if  the spectral downward   irradianco   just  beneath  the
water  surface, b(0~, X),  and K(z,X)  are known,  tnen the  spectral irraaiance  at
                                      -1-

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depth,  z.  can be calculated.

                      E«z.X) = fc(0~, X) expl-K(z.A)  »zl.                    14)
     Miller and Zepp (1979) have  shown  that  the  average  photolysis   rate   at
depth z and wavelength X can be expressed by

          -UP/dt)  , = 2.303 / * • eU)  • L(z,X)  •  D(t)  *  [P]   *  dX        (5)
                  z. X                                         z

where 6 is the quantum yield for  the  reaction, e is  the molar absorptivity   of
the  pollutant, E(z,X) * L)(z) is  the  scalar  irradiauce at depth  z, 0(z)  is  the
distribution function at depth z.  and IP]  is  the  pollutant  concentration   at
depth  z.   Thus.   given the chemical characteristics of  the pollutant and  its
concentration, a knowledge of E(z.X),  or  oquivalently k(z,*.), is sufficient  to
quantitatively calculate the photolysis rato of  the  pv/llutant under considera-
tion.

     The diffuse attenuation coefficient  is  a  function of the  total   attenua-
tion and scattering coetf ic icnts.  It provides a way  <.i crura. tuti..us variOL->
natural waters lu terns of the  dissolved  and   suspended   uutoriai   in  tticse
waters.   \iuile  the potential for character iz ing  waters  in  tins way  is widely
recognized, there are very few data relating the diftuso  attenuation   coeffi-
ceint for irradiance to the concentration of suspended material  in waters con-*
tainiuj relatively  nigh  concentrations.   The   spectral  diffuse  attenuation
co«tficieat.   X(z,X),   can  be expected to be  dependent upon the sizes,  shapes
and, concentration of suspended catena!.  Thus,  beiore natural waters  of   this
type  can  be  characterized  by  an appropriate  K-fuDctiou,  iI is  necessary  to
obtain concurrent K(z, X) and suspended material  data.

     There are few  data available  in  the  ultraviolet  portion of  the   spectrum,
the spectral region most critical  for modeling photolysis rates.  The  UV radi-
ation is important  for  studies   of   pbotoreactions   because  many  pollutants
absorb  sunlight  most  strongly  in this  wavelength  region.  Hence, particular
eupnasis has been put on collecting data  in  several   water   typos  in   tne   UV
region and decking the snort wavelength  predictions  of uodels.
                                                          •          >
     Modeling has been used to organize data into  a  classification  scheme   as
well  as  to  permit  predictive  estimates to  be made,  blnco the diversity  of
possible water types and ot radiant energy   geometries  is   so   large.   it   is
necessary  to augment data gathering  with the  development of predictive  models
which will allow limited data to  be extrapolated to  situations which  have   not
been defined by a complete set of  field measurements.

     The component  model developed by Saith  and  Daker  (1978n,   1978b,  1982)
presents  the  diffuse  attenuation coefficient  of irradiance as a function  of
wavelength defined  by water constituents  of  clear  water, chlorophyll  and dis-
solved  organic  material.   This  oodel  defines  an  average   Ktot(X)  which
represents an intcgxated value of  K to  the ISo  light  level.  Tank studies have
furthered  the  development of this model.   New  information  regarding  the dis-
solved orcanic material has been  gathered and  a  new  clay  component   has been
added.   The  use of this modal is enhanced  by the fact that it  is simple,  and
                                      -2-

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easy to use.

     Uowcver, a core coup.eto  understanding  rec,uni,s uout Is  wnich  can  oe   used
to  predict  behavior  of   light  as  a  function  of  angie  and  depth  as well  as  a
tunction of wavelength.  Existing radiative  transfer theory  and variations  ot
Mio  scattering theory as well as Monte  Carlo modeling have  been  investigated.
This has resulted  in the development of  a  phenomenological model  of  radiative
transfer  which permits calculations of  upwelling  and dowuwelling  radiance  and
irradiance.

     An important  test of   the   limits   of   such   models   is  comparison   with
clearest  natural  waters as well  as  with turbid waters.   Since  the clear water
optical properties are one  of  the components of all other  water  types,   it   is
important  to  have  as  complete  a set  of  these  properties as possible.   The
angular scattering and total  scattering  data for  such waters have  been  incom-
plete.   In  the   work  reported  herein   these  daca  have  been  assembled  anu
extended thus completing the  set  of  inherent and  apparent  optical  properties
tot  the  clearest  waters.   When inherent optical properties  are  input  to  the
Monte Carlo model, it has been shown to  reproduce  the apparent  optical proper-
tic*.   The  oouel is usea  to  extend our  knowledge of the  beuavior ot  apparent
optical properties as a function  of  wavelength, of depth,  and  of  solar  zenith
angle.

     To simulate realistic  and quantitative  aquatic lignt  fields,  it  is  r.ei.es-
sary  to define an input light tiold to  the  surface of the water  column.  This
requirement uas stiaulateu  research  into the etlcct ot varying  solar angle  aud
atmospheric condition* on the  underwater  light  fi.:ld.

     l-igure 1 summarizes the  relationship  between the   experimental   anu   the
theoretical  WOIK  discussed   hero.  Tic  triangles represent, licld aata.  They
serve as inputs and cuecks  on  the classification  schcucs  and predictive nouels
wuich  are  portrayed  as boxes.  The  calculated  parauetcrs  are represented by
circles.  In this  diagram,   the lower dashed  area   relers   to  the  UaLcr-Smith
component  model   of  the   diffuse attenuation  coefficeint of  irradiance.   Tne
upper dashed box describes  oar Monte Carlo modeling showing  its inherent opti-
cal  property  inputs along with  the atmospheric  lighting  geometry, LO,  input.
The output iron tais model  is  the apparent optical  properties,   MX,z,0)   and
hence  E(X. z.O)  aud  K(X,z,0).  Tae left  Band  side of the diagram snows water
type constituents  wneroas the  right  hanu siue  ot  tiie diagram snows tne node Is
with their inputs  and outputs.
                                      -3-

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                                   SECTION 2

                                  CONCLUSIONS

     The organization and further  analysis  of  data  lias  allowed  a  full  suite  of
inherent  and  apparent optical properties  tor clear  waters  to  be  deduced.   In
addition, laboratory investigations  of  clear water  with additions  of   clay   as
well  as  humic  acid  have  allowed  the  further  development  ot  the Uio-optical
Component Model.  Although  this model  is  sinplo  and easy  to  use  in  predicting
the  light field underwater,  it deals  only  with  an  average K and  does  not  per-
mit a further understanding  of  the underlying  processes contribution to  light
attenuation.   The  development   of   the  Monte   Carlo  model has  furthered our
understanding of both the inherent and   the apparent  optical   properties  of
natural waters.

     The Bio-optical Model  III  is  described by liquation 9.    With  this taodel
and  a  knowledge  of  the   chlorophyll,  bunic acid,  and  the clay  content  of a
water system, the average diffuse  attenuation  coefficient  for  irradiance   can
be  calculated.  Given an input irradiance  field,  it  is then possible  to esti-
mate the light field at any  point  in the  water coluun.    Having   thus   defined
the  environment  in terms  of  the  light present,  it is  possible  to investigate
various photo processes such as that describee by  equation 5.

     It xus  oi:t,n demonstrated  taut the  ilonte Carlo  uouci  provides  closure  uuen
applied  -0  the  problem of  calculating  the apparent optical^properties of  an
underwater light field when  given  the  inherent optical   properties.    Further.
by use of the model we have  uncovered  several  important facts.  The  importance
of dealing with  the total light field  (direct  and diffuse) has  been   discussed
and  explained. lUc diffuse  attenuation coefficient has, oeeu »noun to  be rela-
tively insensitive to the act-al  cot-position of  thu luul  li^Jt  fiulJ  la n-rj;,
of  the  ratio  oi  direct   sunlight to diftuso  i».> light.  Further,  k  has  been
louna to be  only weakly sensitive  to the  wavelength dependence  of   the  volunc
scattering   tunction.  This  has the  important  consequence  that  the data from a
volume scattering meter at  one  wavelength  may   be   reliably extrapolated  to
obtain K estimates at another wavelength.

     Uy use  oi the model we  have  demonstrated, with more  completeness,  -than  is
practical  with field data,  that  the diffuse attuuuatiou  coefficient for irra-
diance will  ruacu an asymptomatic  value  wuen the  gvviaging ettcct  ot  depth  on
the  direct  and  diffuse components begins to take effect.   bioilarly,  it has
been shown that there is a  significant  change  in K  ai a function  of  sun angle.
This effect  is more pronounced  in  turbid  waters  than  in clearer  wacers.

     The investigations that  are  summarized are  being described  in  detail  in
several  publications.  Manuscripts  currently  in preparation are  summarized  in
the Appendix.
                                      -4-

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                                   SECTION  3
     The data gathering, description and predictive modeling of  environmental
processes  11  practical  situations  is  complex and expensive.  The research
sponsored here has  demonstrated  the  cost  ef tectiveness  of  an   integrated
theoretical  and  experimental program where limited, but specifically chosen.
data have been utilized to test and refine models.  These models are  in  turn
utilized to simulate realistic field data for  sensitivity analyses and further
invesitgation  and  predictive  modeling  of   the  fundamental  processes    of
interest.   Given todays limited resources allocated to  the study of  important
environmental problems, ve strongly  recommend   (.bat  the  methodology  demon-
strated in this research program be utilized more frequently.

     Our investigations have obtained valuable new data  and created   theoreti-
cal models which will provide solutions to a wide range  of environmental prob-
lems dealing with natural waters.  This work also suggests new directions   for
iurther  productive research.  Specific recommendations  include: (1) more com-
plete experimental work in controlled environments (such as tank experiments),
especially  to  obtain  the optical properties of important organics  and clays
and the optical effects when these are •ai.xed,-  (2) work to increase   the  speed
anil  cificicucy of the !>.outo Carlo model and tne use ol  this uouel tor contin-
ued sensitivity analysis uirecteu toward speciiic practical problems,- (3)   the
development and application of other solutions of the radiative transfer equa-
tion wuich can be expected to provide increased  insight  into  the  fundamental
processes  underlying  practical  environmental  problems:  (4) the  use of  Hio
scattering theory to compute the inherent optical properties dop) of  various
natural sediuents and tiic subsequent use ot these lop's  in our component model
to1 compute the apparent optical properties (aop) for haters of interest.
     The quantity and quality of valuable data  that was  efficiently  obtained
in  our  tank  experiments  demonstrates the usefulness of this approach.  New
valuable data could be obtained  if similar experiments were performed using   a
range  of  dissolved organics (especially different humic acids) and different
suspended clays  and  other  materials.   Future   investigations   should  also
induce  investigation  ot  the  eifccts  ol the mutual interaction of organic
material on the optical properties of «ator.  Such tank experiments are essen-
tial  in  order  to define the relationship between optical properties and tne
constituents of our water systems and for a  more  complete  understanding   of
photolysis in natural waters.

     Considerable value,  both for theoretical development and  the  solut en   of
practical  problems,  can  be obtained from the use and further development  of
our Monte Carlo model.  Increasing the efficiency  of  the  model  will  propor-
tionally  increase  its usefulness.  Valuable future  applications  of the model
include sensitivity studiei. of  atmospheric parameters influencing the  under-
water  radiant  energy  distribution,-  of variability  in the volume scattering
function,  due to chemical and physical modification of suspended particle size
and morphology,  and how this influences  the distribution of radiant energy;  of
key variables for the purpose of parameterizing  the  most  important  effects
into  simple  practical  mouols  of  photolysis 'rates;  of the scattering and
absorption properties of various waters  containing   representative  sediments
and  how these inherent optical  properties effect  the distribution function  in
                                      -5-

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these waters.

     The usefulness ot tnlie scattering theory, inputting the relatively  large   data   bases   ot
total suspended and particle  size information for natural waters,  to  calculate
the innerent optical properties dop) for  these  waters.  The lop's  can  in  turn
be  utilised to calculate  the apparent optical properties (aop) and  then  input
to our bio-optical component model for  the  estimation  of  radiant  energy   pene-
tration into these waters.

     The "trade-otf" between computing  po»er   and  flexibility   has   led   the
authors  into  the consideration of another approach to  the problem  of  finding
one model which is capable of providing both power  and flexibility  at the  same
time.   It  is  our conclusion that perhaps the  ideal  solution  lies within  the
realm of "semi-analytic" models which have the merit of focusing computational
power  where it is most needed but which still retain  the flexibility of  bring
easily adaptable to diverse geometries.

     Finally it should be  noted that we believe  in  many cases  tliat   investiga-
tions  which  are still in an exploratory  stage  are best  served by  approximate
methods such as Delta-Hddington approximations.   These models   provide   quick.
albeit  rough results, which  allow the  the  investigator to determine  whether a
given path of inquiry if  likely to be fruitful.   Once  an  approximate   method
has  been used to determine a basic level  feasibility, a  Monte  Carlo  model  can
be applied to provide extensive theoretical understanding into  the   nature   of
the phenomenon of interest.   If the results of such an understanding  then war-
rant continued ivestigation   where  the  utmost   efficiency  and   accuracy   is
required,   either  a  matrix  operator,  spherical  harmonic, or  similar analytic
method, should be specifically adapted  to  solve  the problem more  rigorously.
                                      -6-

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                                   SECTION 4
     Considerable work has been done  in  Che  past  using  optical  instruments   in
acquatic  field work.  However, as waters  become  more  turbid  (hence  often more
complex anu variable), a more controlled  investigation  of  the water   types   is
warranted.   Several  optical  studies of  turbid  witters  simulated  in a  defined
tank environment have been carred out.  This information,  in  addition  to   our
own previous optical  data base as well as  the  data  base  of  colleagues who have
worked in more turbid river environments,  has  yielded   a  relatively complete
picture of the optical properties for a broad  range  of  water  types.

TANK DATA

     iutown  amounts   of  dissolved   organic  material   (DOM)  and   terrigenous
material  (clay) were added to a tank of  filtered water  while the  optical pro-
perties were continually monitored.  These data may  be  used then   to describe
the  influence  of  each  substance  individually  on  the  attenuation  of  radiaut
energy in water.  A further analysis yields  possible par ame tcr izations  of each
attenuating  component.   This series of  experiments was run  using  the  Luugley
Research Center tank  facility and solar  simulator.

     The tan.it facility consists ot an enclosed labor itory,  the  tank  and asso-
ciated filtering and  pumping capabilities, and a  solar  simulator.  The  tank is
a stainless steel cylinder paintea black  on  the inside.  The  diameter  is   2.4
meters;  the  depth   is  3  meters/  the volume is approximately 11,600  liters.
Siu.-e the measurements used were relative, the absolute  spectral output of  the
solar  simulator  was not critical.  However,  becauic  tue  simulator  had a hi{,'>
0V output, optical data coulo be obtained  in this spCvlral  region  whicu woulu
otherwise have been impractical under natural  conditions.

     The organic material added came from  the  Aldrich   Chemical  Company.    It
was  listed as a humic acid vith catalog 111, 675-2  in  crystalline  form. Tiiese
crystals were dissolved in filtered  deionized  water  before  adding   the  tank
water.   The  terrigenous  material  added  was  a calvert  clay  which  in powdered
form had a readi&h tinge cnarac ter istic  of some   soil   sites  in   the  eastern
United  States.   A   summary  of  all water  types created  is  given  in Table 1.
Note tnat measurements 
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1979) capable of measuring  at  any  chosen wavelength  in  the  range  froti  270
nanometers   to  750  nanometers.  This  inscrucunt has a 1 nm lull width at halt
i_ax pass oanu ana  »a:>  uc signed  spec il ica 1 lj   to  er.aoli,  accurate  uudt iwa tor
measurements in the  ultraviolet  region  to be  cade.
     The component model  defines

                       Ktot(X) = (1/z   )/ftQaX £(z.X) dz                    (6)
                                     ciai  0


where z     is  the  lv>  light  level.   Equation (4)  reduces to

                  Ktot(X) = (-1/z   ) • lnU(z   ,X)/Eo(0,X)J               (7)
                                 max          max

Thus from  tie E(X)  versus  depth measurements,   a  total  diffuse  attenuation
coefficient may be  calculated by making a linear least  squares fit through the
data.

     The spectral  diffuse  attenuation coefficient for tne  irradiance  can  oe
partitioned into components:

                               ) -i- tCw(/.) + iic(A)  + Kt(X,                      (u;
       .w(X)  is  the  attenuation due  to pure seawatcr,  Lc(X) is the  attenuation
due  to  chlorophyll,   Ku(X)   is   the  attenuation duo to DOM and kt(A) is the
attenuation  due  to  terrigenous material.   The Kw component has  been  measured
ana  'uiscusscu  previously  (Suitu  and Uaicr,  19bl;  uaicer and Smitn,  iyii2).  Ine
.>.c component lias  oecn  parameterized based u(-on extensive ticld cata (liuith anu
lialer,   197oa,o,'  L>a^er   ana  Smith,  19(52).  taom component investigations have
oeen carried out  based upon spectral irradiance ficlu measurements (llaker  and
Smith,  19S2) wnich  were  limited due to lack of quantitative bio-chenical meas-
urements Of  the IX) 11 present.   And finally,  the  Kt  component  has  not  been
investigated previously  by  these  authors.  The present data set permits inves-
tigation into the Kd(/J  and Kt(X.)  components.

     Equation 8 will be  written for this  work

                       KtotU)  = KwU) + KcU) + Kclay(X)                   (9)


ir order to  emphasize  that  the terrigenous component investigated consists  of
only  one  type  of clay.  Until further such studies are completed,  one can not
be sure what the  influence  of  different terrigenous materials will be  on  the
light attenuation.

     In the  Clay  Group of measurements made,  we may assume that Kc(X) ° 0  and
the  twd(X) = 0.   Any   attenuating   substances that are present in the initial
filtered water  are  thus  lumped into the Kw(X) base line measurement:

                           Kclay(X)  = Ktot(X)  -Kw(X)                   *  '  (id)
                                      -8-

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Thus the Kclay component  for measurements  #2  through /<8  ol   Table   1   can  be
caluclated.   f  plor   fur  tni:  resultant  clay  coraponn*-s  is  shown  in Figure  4
lais component can  jc  «riitea

                            KclayU) = itclayU) • T                        (11)
where kclayU)  is  the  specific  attenuation  coefficient  of   irradiance   due   to
clay  and T is  the measure  of clay  particles  in  parts  per  million  [pprnj.   1'tg-
ure 5 plots this data  for  all wavelengths  in  the range  from 2/5 nm to   745   am
as  a  function  of   the   amount  of  clay present.   To  look in more detail,  the
wavelength 550  on  is  shown  in Figure  6  where  the actual data points are  given
as x's.  The form  of  this  curve suggests a  polynomial  fit  of the form:

                       KclayU) = (BU)  +  CU)  » T)  *  T                   (12)
This fit is forced  through  the  origin  in order  to conform to the  reality  that
•when there is no  terrigenous material  present,  there  can be  no attenuation due
to the terrigenous  component.   When  such a fit  is made,  the  resulting  CU)  •»
found to be relatively  constant such that

                                 CO.) = -.0043                             (13)
waich is wavelength  independent.   When  this  assumption  i«  presumed  true,  a now
linear least squares regression can  be  made  to obtain  a new set  of  BU).   Thit>
parameter can be described  by  a line  fit:

                               3(X) =  A  + B  * (X)                           (14)
wnere a linear  least  squared fit yields

                A =  .408
                B =  -.000317.

In succiary. this gives

                  KclayU)  = [.408 -,000317*U) ] *T -.0043*T*T              (15)


where kclay = (.408 -000317*U) -0043) «T which  is   the   specific   attenuation
coefficient  for  this   clay.   To  indicate  the  accuracy  of  this  fit.  Figure  7
shows the  original  data  as  points and  the parameterized fit  as  a   solid  lino.
Because  of  the nature  of  the data, an  inverse  wavelength dependence  was  also
investigated in order  to see whether a better  fit could be obtained.   Using   a
technique  similar to  that described above,  it  was found that

                KclayU)  =  [.119 -.201*(X/Xo)(-1) ] *T -,0043*T»T         *"  (16)


where Xo = 375  in this case.  This  parameterization did not  improve the fit  to
the data.
                                      -9-

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DOM

     Note  chat  the DOM Croup  contains  what  night be  called two sets  ol   ouse-
ll ne  measurements.  The  //9  in Table  1 is  the  filtered clear  water case.   How-
ever, a small amount of clay  has  be in  added to all  1X)M  waters  in  order  to
increase   the light absorption and  thus  decrease the possible influence  ot the
tank walls.  The diameter  of   the   tank  is  approximately  1.2  meters.    The
instrument  was  no  longer   visible   at 1.2 m when  6.47  ppm  was in the  water.
Thus the amount of clay added was chosen to be the #4 case of the Clay Group.

     The Kdom component can  be calculated

                    KdomU)  = KtotU)  - [KwU) + KclayU)]                (17)


where the  case  #10 in Table  1 is  taken to  represent  Xw +  Kclay  for  the  OOfl
Group  of  vater  types.   The plot  of  the  DOM components  is shown in Figu/.e 8.
Previous workers have  investigated  the DOM absorption and  have  always   found
that the absorption approaches zero  as the  650 run wavelength  is reached.   This
certainly  is not the case  with the  curves  in Figure  8.  Instead,  these  curves
would  lead  cue  to  believe that  there  is a scattering agent present  in the
hucic acid added to the water.  This  in  fact  agrees  with  observations   frcr
i ther  investigators  wno have used  siuilar sources  of L0'
-------
                       la[Kdon.U)/«LoUo)»U)J  = kd'(X-Ao).                   (21)
Solving this equation  ,*itli  a  linear  Jcast  squares  lit through tnu origin gives
a s.'ope of kd' = ~.01C4 wuich  is  found  to  be  relatively wavelength independent.
Thil is exactly the value for  the  slope  toucd by Zepp (1981)  in bis laboratory
wor)    Jt  has  been  found mth ocean field data  (Haker and  !-rnit.h,  1982)  that
kd' ranges froia -.014  to -.020.

     This then gives us a defined  component  for  tue Aldrich uumic acid

                   KdoinU)  = D • 1.54 • expi-.0104»U-375) i.               (22)


The extent to which this reproduces  the  original uata is shown  12  Figur.  11
where  the points  are  the actual data  and  the solic line is deiivca froc. equa-
tion 22 with the appropriate D.

     A final look  at the fit.,  of the analytic model io the   experimental  d*ta
is  shivn in Figures 12 and 13  *here the  total attenuation  coefficient K(X) is
plotted versus wavelength.  The  x's  represent actual data whiK the solid line
i«  the nouel prediction.
                                                                            ^

OTUCa FIELD DA.TA

     The data collected oy  Smith and others  at the   Visibility  Laboratory  at
Scripps  Institution   of  Oceanography  covered  a  wide range yt oceanic water
types.  Measurements maue in a  local reservoir aeipou extend  tue 1'iruiu  water
types.   At  the NASA Langley  research Center,  instr--L.cr.ts  Lave \,atiz devulopeu
for (he express purpose of  measuring   optical  properties  in  turuid  waters.
Through  collaboration  with   this group,  -\n extensive set  ot data for a wider
range of water types was available for our. modeling studies.   Figure 14  give*
a sacpling of this data from very  clear  waters to  quite turbid waters.
                                      -11-

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                                   SECTION 5

                                  TliEOltETItAL

     Modeling has played, and will continue  to play,  an  important  rclc  in   the
understanding  and prediction of  spectral radiation behavior  underwater.   This
is because field data is difficult and relatively  expensive  to   obtain.    Also
once  a  working  model  exists,   it can  be  useu to extend a.id  extrapolate  the
necessarily limited field data  sets. Use  of  the node Is   also  pernits   one   to
investigate  problems   that are particularly difficult  in  the field  (i.e.,  low
sun angles or great depths), and  to  investigate   unsampled   water  types,   to
simulate  variations in  o/c or  >,  and  to  do  general sensitivity studies.   Such
modeling helps verify our understanding of  sub-microscopic processes and   pro-
vides  an  important  theoretical  link between  the constituents of  an  optical
medium end its resultant optical  properties.

     Much of radiative  transfer modeling  has been  concerned  with  the  atmo-
sphere.  An excellent summary ot  atmospheric work  is  given by the  IAMAP Radia-
tion Commission  (1977).  TLene  models  were  studied to determine their   adapta-
bility  to  our  needs   for a flexible yet  accurate solution  to the  problem of
propagation of radiation within a  variety of aquatic  environments.

     Atuospnuric nouels  jay be  classified m several  *uys.    Tor  instant.).,   a
few ncthoti are  suuuarizeo  acre with notes  inclaaec to  oriel ly  mencion  ioue ot
the investigators using  the techniques.   It  is mentioned whether the  investi-
gator  has #orked on tae method in ihe past, uas a currently  working uouel,  or
is developing it now.

          i^xact Anal) tic .Method*
          1. Singular tigeafunction method
          2. Wiener-ilopf technique

          Computational  Analytic Methods
          I, Spherical liarmonics  (Dave now)
          2, Matrix Upcrutor method (Plass-tattawar now, Gordon now)
          3. Doubling or adding method (Herring, Fitch)
          4. Iteration Methods  (Dave past)

          Computational  ("non-analytic") Methous
          1. Monte Carlo (Plass-Kattawai  past, Gordon past.  Kirk,  Fahy-Poole)
          2. Successive Orders  of  Scattering or natural  solution
             (Preisneuorfer).

          Approximate Methods
          1. Eudington  approximations  (Delt&-Eddington)
          2. single scattering  -  approximate Monte Carlo (Gordon past)
          3. two stream  approximations
          4. approximate diffusion theories


     The above lift is by no means complete  but does  pcntion  the  models  we
have  devoted the most  time to  e-xplor.ing, and which appear to be receiving the
most attention in the literature.  It  should be  noted   that  tha   approximate
methods  usually  yield  only   an  irradiance solution  nhereas  the others  give
                                     -12-

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radiance solutions.  Our  investigation  of  computational   methods   focused   oo
Dave's coue for an iterative  solution and  a Monte  Carlo code  adapted  from ilirk
wuich oad cue adued virtue oi being a .vator model  rather  than  an   atnoi, j/acr ic
taoue1.   Both  of  these  codes were extensively moditied  to  suit our  purposes:
the Dave code became  it  did  not directly  apply to aquatic media and  the  Kirk
code  because  it was  comparatively <.nef f icient.   It  should  be  recognized that
despite the adaptability  of the Monte Carlo code  to  the   demands   of   aquatic
geometry.   the  spherical harmonics and matrix operator methods are more effi-
cient in terms of computation tine.

     We have also utilized the solution to the Mie scattering •  of   light  with
which  we  can  deduce  the   inherent optical properties  from particle  size  of
suspended sediments.   This in turn can  be  used as   inputs  to  either   of   the
above two models.  An  overview of our modeling to  date  is summarized  in Figure
1.
MIE CODE

     Hie scattering theory represents  an  analytic  solution  of   the   scattering
of  light by small spherical particles.   The  solution  due  to Mie  dates  back  to
the turn of the century and relies  solely on  Maxwell's   discovery  that  light
may  be  represented  in  teras  of  corresponding electric  and magnetic  fields.
Given a spnencal particle of a  given  inuei ot refraction,  one  may   calculate
the  absorbing  and scattering effects of that particle.   Given a distribution
of such particles, one nay build up a model of the   particular  component*   of
absorption  and   scattering,  within   
-------
t).c Rayleigh-scattoring optical depth oi  tne atmosphere.  This  code  was  modi-
fied  so that the bottom was made Frcsnul, which  is  appropriate  for  an  aquatic
interlace.  Ihe changes required v,ere not  trivial  siuce  tne  Uave coilo had  par-
titioned  photons  into unreflected and reflected  histories,  and for reflected
photons used the Lambert tan assumption to  remove  the  azimuthal   dependence   of
the reflected radiance.  The objective in  modifying  this coue was  to use it  to
obtain accurate input radiance distributions to a  water model which  would  then
be  able  to calculate the desired optical properties within the water  column.
The separation of the atmosphere/ocean problem into  first   an  atmosphere  and
then  a  water  problem requires the assumption that  photons which backscatter
from water to air and back into the water  represent  a negligible  'contribution
to the flux received by the water.  The functional layout of the Dave code was
presented in a previous report (Interim Progress Report, EPA Grant  #806-372-
010),   and  thus  it will not be repeated  here.  This converted version of the
Dave code for the atmosphere was running  on  the IBM  360.
MONTE CARLO JiODELING

     Because the Dave code requires  inputs which  are  not  routine   measurements
for  most  investigators,  an   alternative  modeling   approach was followed in
parallel with the modification  of  the  Dave Code.   This   alternative   apprcach
wai  to  pursue  the development of  a  lioaie Carlo procedure  whicii would use as
inputs the innerent optical properties wuicii  had  been measured  previously   oy
our  group;  ana  whose  outputs,  or  "predictions",  could be  checLed  against a
corresponding set of apparent optical  properties  also available   from   earlier
studies.

     j.lonte Carlo solutions for  the atmosphere-ocean  system   were   reported   in
the  literature in 1969  by Plass and ilattawar.  The  .Monte Carlo u.etlioU is  fun-
damentally less accurate than the  analytic methods but was among  the  first   to
be  adapted  to  an  atmosphere-ocean  system because of  its flexibility.   The
early calculations were  restricted to  sun  positions directly  overhead   and
input phase functions were calculated  from Rjyleigh  and Hie  scattering theory.
Over time, solutions have oeen  carried out by several authors  under   a  wide
variety  of  conditions  (Plass  and Kattawar,  1969;  Gordon,  1975.  1977; Kirk,
1981).  Indications of the power of  such  simulations  have been demonstrated in
the  form of papers which propose  empirical relations between the inherent  aau
apparent optical properties, as derived via uionte Carlo exploration (Ooraon et
al..  1975; Kirk,  1981).  Yet due  to problems strictly associated with obtain-
ing sufficiently complete data  sets, none of  these authors have been   able   to
confirm  the  model  within a comprehensive set of water  types as found within
nature.

     Briefly, a. Monte Carlo technique  is  a  "random walk" procedure in which a
computer simulates and keeps track of  the path  of a  large number  of individual
photons as they scatter  through, and are  eventually  absorbed by,   the   optical
medium.   It  is the set of inherent optical  properties of the water,  i.e., a.
b. and JJ, which define the  probabilities  of  events,   i.e.,   scattering   and
absorption,  within  a   given   photon's  "life history".  Thus the  input to the
Kuk code was exactly what we were looking for:- the  inherent  optical   proper-
ties of the water.
                                      -14-

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     The meaning of the tern  "large number of photons"  is   defined   operation-
ally.   As  with any statistical  sampling  procedure  involving  the  avenge  of  a
tatasured quantity over uany trials,  tne variance  ol  Cue  output  decreases  wita
the number of samples.  Thus,  tor  example,  perfectly  smooth curves 01  li versus
depth aie expected if an  infinite  number  of  photons  are  run.  If  less   photons
are  run, less than perfectly  smooth curves  are  obtained.   In  practice a large
number of photons are run and  the  resultant  curves examined.   If   the  curves
arc  not  considered smooth enough,  more  photons  are  'uii.   The  number  required
to achieve some arbitrary standard of  "smoothness"  is a function  of  the  ratio
of  absorption  to  scattering  as  well   as   of   the  optical   property being
estimated.  High absorption will  generally  require more  photons   to  get   the
some smoothness,  au.d upwelling properties  will almost  always require many  more
photons than their downwelling  counterparts.   Thus   the   number   of   photons
required to get good estimates of  a given  parameter  may  be  anything  from a tew
tens of thousands up to the hundreds of taousaads.   Uue  can understand that an
iterative  solution  of   the   equations of  radiative  transfer,  such  as used by
Dave, is inherently more  accurate  than the  Monte  Carlo type solution since  it
is an exact solution.

     A copy of Kirk's lionte Carlo  procedure  was  gratefully  obtained   from   Dr.
Kirk  and modified.  Th«.  Kirk  Monte Carlo  code is ruu'.^ug  on a  Prime 550,  750.
The results were cneckcd  against  lira's,  and  were fotnd  to  agree.


PUGF

     It was decided that  the Monte Carlo  technique -,vjs an   appropriate  method
to  investigate  further  the attenuation  of  light underwater,   liowever,  it was
I'o mi u necessary to sake ^ajor  Alterations  to  cue  original  uirk  code   in  orucr
to improve cor.puta t lona 1  effic:ency.  Further, the original Uirk  eout  a^^ro^i-
natet! the i..put radiaac-'  U.L str loutiou as  a  uelta  function,  which  is   appropri-
ate  for sun high in the  sky out w'uicn is  known  to be  a  pool approximation for
low sun.  After considerable improvements  baa  been made,   we  cooperated  with
another  researcher  in   the   field (Poole.  1932)  in  oruer  to  proauce  an effi-
cient,  state-of-the-art vionte  Carlo code.   THIS  code  is  a  significant  improve-
ment  upon  the  original  code   and is detailed  elsewhere  (Fahy  and Poole,  in
prepartion).  It is iiaceu POOF after its  authors  (Poole  anu Fahy).
          uses an important approximation  ol  the  input   rauiance   uistriuution
by  approximating  it as a delta function  plus  a  diffuse  "skylight"  component.
The method by which it incorporates data measured in  the  field   to  produce   a
representative input distribution  is  discussed  below,  in  the  results section.

     A severe problem with the Kirk model  was the number  of   photons  required
as  input  at the surface in order to obtain  a  usable  number  at  depths below a
tew attenuation lengths.  A photon was  highly unlikely  to survive  long,  enough
before  absorption  to reach significant depths.   To  address  this  problem pho-
tons were given statistical weights which  are decremented at  each   interaction
with  the  medium.  The decrement  factor is  simply b/c,  which gives the  proba-
bility of scattering  (i.e.,  surviving)   instead  of   absorbing  in  a   given
interaction.   Thus.  a  photon  does not  perish  by being absorbed but rather,
lives on, albeit with a lower weight  than  before.  Eventually  the  weight  of
the  photon becomes insignificant  aad the  photon  is discarded and  a new photon
is sent on its way.
                                      -15-

-------
     Other improvements fall  under  the  category  ot  precalculating  information
that   i»  needed  repeatedly.    l-or  instuucc  at  cvcrv collision the collection
"sins" in wcicb a photon oclongs uust  be  v.,)Ua.tevi.   \iLcrc   tut:   puoton  ociun,,^
typically involves taking an  arcsin  or  arc<.o*. wtiich is a  lengthy computat 101. .
But since we know in advance  which  bins correspond  to  which  cosines,  it  is
possible  to  pre-ct Iculate a mapping  from thi direction cosines of the photon
(which describe its direction)  to  the  bin  in  which   it  belongs.   This  saves
considerable  time.  Another  example  is the not hod  by wkica a scattering anglo
is determined.  It involves sampling  froct  a  unilorm ranuom variable  and  then
doing  a  table  look-up  to  get a  corresponding angle.  Hut the table loot-up
procedure aay be represented  as a mapping  which  cau also be precalculated.   A
table  look~up can thus be reduced  to  sampling withiu a linear array,  the ele-
ments of which correspond to  values of  the uniform  random variable.

     The most significant improvement  of 1\X)F over   previous  efforts  is  it*
partitioning  of  the  problem   mto  two separate "passes "; the first of wLich
aepends only on the volume scattering  function,  and the secon.  which uses  the
output  of  the first, and the  remaining input  (a.b) to obtain the final solu-
tion.  The product of  the first phase  is a series of count arrays,  which in  a
very  real  sense contain the same  sort of iiuornatiou as  is calculated by the
so-called Natural Solution of radiative transfer,  also known as the Successive
Uroers of bcattenns Solution.   Thus,  1HX)1" nay  accura to !;•  be cclloii a cci.'ji.'a-
tico at ..omo Carlo 
-------
lience, we will show here a comparison  of  the  Mcnto   Carlo  lesults  with  both
clear  water field measurements  and  ban Vicente  tield iacas irctacuts wnich arc a
core  turoiu *ater type.  fhc rcseivoir  is  representative  ot   core  productive
waters  !icv mg a chloropayll concentration of  approximately  7  nj, v,nl/n3 and an
attenuation length of 1/3 meter.

     The consistency of  tk? model's  predictions  with values  of K  measured  in
clear  waters  is  demonstrated   by  Figure 15.   Plotted versus wavelength are
several inherent and apparent  optical  properties ot  the  water.   Also  plotted
arc   the model's predictions of  the  value  of  K at one optical  depth for zenith
angles 10 and 60 degrees (labeled  '!'  and  '6', respectively),  along  with  the
measured  values  of  K  from  the cruise  data.   Note that the values over the
water column,  because technical  difficulties  maae it impossible to measure  an
instantaneous  value  of K at  any  given depth.   1'urther,  the  k's obtained trotu
the data represent averages over  suti  angle,   since   measurements  were  taken
slowly  compared  to  the  movement  ot'  the sun.   With these  limitations ot the
cruise data in mind, one sees  that the model  compares extremely well with  the
field data, wuich in every case  fall between  the 10  degree and 60 degree pred-
ictions.  This is to be  expected  since measurements   were  only  taken  for  a
range of sun angles within these  lioits.

     T'.ie consistency of  the model's  predicitons  for  a tore   turbiu  vatcr  is
sho»u  1.1  Figure  16.   In  this  li^uru   tuo uasheu liuoi  give cue pruumuu
(uuucl) vaiuos 01 average attenuation  uott i ic lent o\«.r tue tir»t seven  tauter*
obtained  by  fitting a  straight  line  to  the  log of  the  irradiance predictions
given by the siouel.  The solid linos give  the  values  obtained  in  a  similar
manner  frou the data.  Note the wide  variance in value* of  & over wavelength,
and the ability of the model to  truck   this   variance.   even   the  turn-aiouna
wjvo Icnjih ol  uini.ua 1 'L, 550 nm.
                                     -17-

-------
                                   SJCCTiON 6

                                    RLSULIS

      The  results of this work can be broken  into  several  related  sections.
 fust  a  con;ideration of atirnsphcnc influences of light was made.  '1 ho input
 irradiance alfects the underwater ligl>t fieJd and thus affects both tho  field
 data  and  the  modeling  of such data.  Next,  the field data needed was taken
 and/or analyzed.  including  specifically  an  investigation  of   clear  witer
 scattering,  of clay and UOM attenuation from a series of tank experiments, and
 of the suite ot data with complete sets ot inherent optical properties  avail-
 able.  Finally, the results of the Monte Carlo Model, which involves knowledge
 both of the  atmosphere and of the field data, are given.
 AIMOSPUERE

      In developing models of aquatic environments, one must first consider  the
 input   radiance   distribution.   We  have  considered   two  quite   dill irent
 approaches; an an I ay tit. approach and an experimental approach.   The   analytic
 method  is that of Dave,  an iterative solution to radiative transfer  aquations
 discussed earlier.  This code has the advantage  that it allows  definition   of
 the atmosphere oased on its coustituleuts.

      The second technique involves definition of  the input radiance   distr-bu-
 tion  as a delta function plus a uniform diffuse  component.  This however is  a
 crude approximation of the sky component.  In fact, the Dave code  will   serve
 as  a  useful  check of the validity of this distribution assunption  since  the
 Dave code gives an  "exact   soJition".    However,  the  field  tia'a   ?vnilaole
 describes  a  sky  and  a  direct beam,  he ace the cn.puasis on the e*pcr i»ik..tal
 approach.

      The total atmospheric radiation at the water surface nay be  approximated
 as a direct solor beam plus a diffuse sky component.

                           Etot(0, A.) = Edirect •*• Esky                      (23)


 It is possible to measure Esky ana Ltot in the field.   It  is  the   ratio   of
 these quantities

                                  y " Esky/Etot


 that the model uses to approximate an input xadiance distribution.  It is pos-
 sible to pick an arbitrary Esky and then to calculate

                   Edxrect =  (1-y)  • Etot  =  (1-y)  •  (Esky/y)               (24)


.We then integrate Esky using a uniform radiance and add this  to  Edirect   and
 propagate through the surface using Frosnel transmittance.
                                      -18-

-------
     Field measurements  of y  in  both an oceanic  atmosphere as  »ell  as  in  a
desert-like  atmosphere nave been made.   These  measurements were available onl>
tor  «ravti Ici.gths  above 400 nci.  Using another uoue)  loreer. e_t u 1.,  197b;  uater
o t   a 1.. 1981),  this aata can  be extended  to  the  2i>0 nu region.  Using both of
these  sets of  data  as surface  irradiance  input to  the Monte Carlo  model,  the
influence of  two very different  atmospheres could  be detected.
FIELD DATA - clear water

     The measurements  in  the  clearest  natural  wacers of  the inherent  and  the
apparent  optical  properties  are  limited.  As  a result,  we combine data from
the  laboratory with  uata  fron the field.   Our  objective  is to  obtain  a  data
set  representative  of  the  clearest  waters one might expect to find  naturally
in  the environment.

     Tbe most recent and  most reliable data  of the  total   absorption  coeffi-
cient  of  pure water,  aw(wl)  in the 200-800 nm  spectral region are summarized
in Table 1 (from Smith and  Baker. 1981).   There  is no such information regard-
.1 g  the  scattering of clear water.  The  total  volume scattering function can
be descried as composed  of two components,  one  due to molecular scattering of
pure  sea wter, pia,  and one aue to  all other cocpcr.er.ts  -vaicn we will refer to
as  "particles",  pp.

                          p(e. x)  =  pm(y. x) + pp(e, /.)        *              (25)


where Morel has shown
  >
                   (,3(9.30  =  b=(X)/16.06  * (1  +  .S4cos2(H))               (26}


The molecular scattering  of clear water,  bm  (X)  is given elsewhere (Smith  and
Baker.  1981).

     A comparison of all  currently  available clear water  scattering  measure-
uenti  uas  snown  tuat the SCCii  Discoverer  Station 21 uata (1973) is the most
accurate and representative r-casurcucct  of p(/J  for the   clear  waters.    This
station  was  in the Sargasso Sea wnicu  is rccognizec to be among tne clearest
of ocean waters.  Since the scattering data  in this set  exists  only  for  the
wavelength  515  nm,   it  is   necessary   to  find an extrapolation technique to
obtain p(0) at other wavelengths.    Tbe   volume   scattering  function  at  the
wavelengths  440, 490.  520,  and 670  no,  exists for the Uceanus Station 4 data,
as is shown in Figure  17, where the  molecular  scattering has been removed.   A
very  simple  method  which  is  consistent  with a "diluted water" treatment,
assuming that the data  sets dealt  nth are essentially the  same  water   type,
has been adopted.  Suppose  we have  two water samples,  the  second of which is a
simple dilution of the  first.   Thus  the  first  sample has an instantaneous par-
ticle  size  distribution  of  N.(D),  and the  second has a distribution N_(D),
where D refers to particle  diameter.  Then

                              N2(D)  = K21  • N1(D)                          (27)
                                      -19-

-------
where i^..  is a constant which does  not  depend   on   L>.    Let  p(A,D, 0)   be  the
scattering  Jue  to a particle  oi diameter  L).  m direction 0,  at waveleijth >..
Tu en
                         d(J jU.y)  = d(X.U,9)*N1(D) dU                     (28)


and it can be shown

                           p-U,W)  = K   • (JU.e)                       (29)
Since this result  is wavelength  independent,  we  can use  it to extrapolate  the
water dependence of water  sample 2  to  water  sample  1 by
where

                          :-ue)  =  j,  2Uo.e)/(,  jUo.e)                       (3D


Giver. Cue similarity ot \«ater  samples  taKeu on the so  two cruises,  we tell  tue
diluted  solution approximation to oe  a  reasonable  approximation.   The validity
of tins  technique was checked  using several other  complete  uata  sets.   iJencc
the  extrapolation  from  one   data set to  tue next could be checked since the
second set of measurements had been made.   When  such  comparisons  were  made
betueeu  sirailar water  types,  tue uctnod  prouucod  vcr>  accurate reproduction:,.
Given Equation 30, we can no-*  caKulatt, tlio   voluuc  ;>wa ttLriiig  Tuiiotiou  for
other wavelengths for clear  water as  is shown in Figure 18.


FICL1J DATA -  tank

     Figure 19 shows what the  Baker-Smith component model gives for a range of
C,  U,  and f  values.  The experiuent.il  component analysis has tuus yielueu not
only a cescription of a set  of  water  types, out  the   ability  to  generate  a
range of tauter types oaseo upon a 'cuoice  ol culropiiy 11>  iXA>i,  anu  clay.


FIELD DATA -  other

     All of the field measurements  of  scattering must be integrated  over  all
angles   to  yield  a  total  volume  scattering function.  This was done using a
program  designed to take into  account  the geometry  ot the  scattering  instru-
ment  used (Petzold, 1972).  This program was converted to the RilME 750. 550,
from an  IBM 360.


POOF fcODEL

     The limitation of  cruise  data  is  that  the values of K  usually  represent
averages  over depth and sun angle  due  to changing  light and water conditions.
                                      -20-

-------
The model is not confined by such problems and  thus   it  becomes   possible   to
look  in  detail  at  the variation of  tue apparent optical properties  with  sun
angle and with depth.

     Figures 20 and 21 demonstrate a need to  include  a sky component  in model-
ing calculations.  The graphs ot i.d,  the downwelling  diffuse attenuation  coef-
ficient, show a much  greater variance  with solar  z;nith  angle   for   a   model
using   input of a direct beam only.  .Jan is evidenced in the POOF  calculation.
Direct  comparisons for solar zoutih ^nrlcs of 5   to   35  degrees   show  little
difference  bjtvcec   the  t>o models while the models differ significantly  for
solar zenith aiiglei. of 75 to 85 degrees.  Of  particular interest  is  the rever-
sal  of  order  of  tht» vertical positioning  of the 70 and 80 degree  curves in
Figure  16.  For tae direct beam model,  the 80 degree  curve lies above  the   70
degree  curve.  whilo for POOF the 80  degree  curve is less extreme  than  the 70
degree  curve.  This is oeiause in POOF, the   model  takes  into   account  that
alnost  all  the  input  into  the  uater  for  the 80 degree curve  is diiiuse
skylight/ the Fresnel transiaittance through the water at  80  degrees zenith
angle   being  extremely  low.  'Ihe gsneral pattern of light entering  the  water
therefore,  closely resembles tho diffuse skylight, which represents   something
of  an  average of the direct bo am results for solar zenith angles  from 0  to 90
degrees.
            that the values for £ in these figures lor  SO  degrees   are   less
extreme  than  are the values tor the 60 degree curve.  It can ue  snowu  that  it
increases with theta until a thota-max at which poiut  it  decreases   since  an
averaging  effect  swamps  out the direct beam.  That  is. there are few  of  the
photons entering the water that are actually due to  the direct solar  bean.  as
is understandable witrin the context of Freshnel's law; the dominant  source of
iiynt is diffuse styiigi.t wun.li represents an aveargt:  of  Direct   solar   beuoj
t'ron 0 to 90 degrees.  This effect lias not previously  been rc^urccu since uuch
of our previous understanding comes trom field data  which is  limited  by   the
instrument  technology  which  takes finite time to  make measurements.   During
this time interval,  the lighting conditions can change rapidly.  It is   diffi-
cult  to  measure  values  of  k over largo depths and for instantaneous  solar
positions when the sun is low in the sky.  Such an effect is  important to  take
into  consideration  when  one is calculating the total availability  of  energy
ever one day.

     The change in K as a function ol depth is illustrated in Figures  22   and
23.   Such  calculations  provide  previously  unavailable  insifht into depth
dependence of K.  For  instance, Figure 23 shows three  different wavelengths at
several  solar  zenith angles.  It should be noted that the spread between  the
10 degree and the 60 degree curves decreases with depth, demonstrating that   K
approaches  an asymptotic value at great depths which  is wholly independent of
the input radiance distribution.

     The dependence of K on solar zenith angle  is   seen  to  be   small   here.
agreeing  with  previuus observations (Daker and Smith, 1979) that X  is  quasi-
inherent for this type water.  Uaker and Smith fit a straight line through  the
log  of  the  downwelling irradiance measurements to obtain Kd and as  such  the
single value of Kd m&v be seen to be an average of Kd  over the top 7-10  motors
of -the water column.   Clos* scrutiny of the curves reveals that the asymptotic
value of lid, known as  £00,  is reached  extremely  rapidly.  as  early  as   4-5
meters  depth.   Thus, the average computed by Baker and Smith to  represent Kd
                                     -21-

-------
is swamped out by Ldo, which  is ot course  independent ot  solar  zenith  anlge.
This explains the "quasi-inherent" nature of .-id as reported previously.

     It is now important  to note  that for  80 degrees, the asyuptotic value   is
reached almost immediately.  This  suggests that  scientists  taking ucasureme-.s
in tne fielu would do well to  take data for  low  sun  positions,   in  order   to
measure directly this nighly  important parameter.

     The sensitivity of the model  to Y is very small wnen a dry   desert  atno-
sphere  was  used compared with a  coastal  ocean  atmosphere.  It is only at  low
sun angles approaching 80 degrees  that  the  atmospheric  component  ratio   is
found to have aoro than a 3 per cent influence on  the resultant apparent opti-
cal properties.  It  is   also  found  that   !£  is  relatively   insensitive   to
wavelength  variation in  p. especially at  the surface where the effect  is less
than 1 percent.
                                     -22-

-------
TABLE  1.  TANK STUDY WAfFIl IM'CS
tt

I/
2/
3/
4x
5/
6x
7/
Sx
9x
ID/
1 I/
12'
lix
I4x
15'
16/
fi le

1
4
5
6
. 8
10
11
12
13
14
1*
17
13
19
20
21

gm
0
25
50
75
125
175
225
275
0
75
75
75
75
75
75
75
CLAY
ppm
0
. , 2. 16
4.31
6.47
10.78
15.09
19.40
23.71
0
&. 47
(-.4?
c.47
o.47
6.47
•5.47
ۥ. 47

gru
0
0
e
o
0
0
0
0
0
e
^
5
10
15
10
40
DOM
frig/ 1
0
3
e
0
0
0
0
0
0
f)
0.17
0.4:
0. ?6
1.2?
1.71
3.45
aate

- ?o;t32
3octS2


9oct32



13oc to2

1 4 o c t : 1





                                                  Reproduced from
                                                  best available copy
                                -23-

-------
	  	  	  	
I	
        Figure 1.  Relationships between experimental field data
        and computer models.
                                 -24-

-------
                         CLRY
                        #l-#8
            10
          E
          \
          o
          •p
          y.
                350  450   550  650  750
                 hflVELEN'GTM  Cnm3
Tiguru 2.  The spectral light attenuation in each of the
Clay Cro'ip water types //l-#8 listed in Table 1.

                      CLRY+DOM
                           -tie
                        trS
            10F
                 350  450  550  650  750
                  WnVELENGTH  CnrrD

Hyurc 3.  The spectral light attenuation in each of the
OOM Group water types //9-//16 li:,ted in Table 1.
                  -25-

-------
                        CLRY
         o
           10
           9
           B
           7
          250  350   450  550  650  750
                 WRVELENGTH  Lnm3
 Figure 4.  The spectral Relay component for each of  the
 Clay Group water types  IU-tl8 listed In Table 1.
                       CLRY
                       #2-t8
          10
           9
           8
        i-i

        £  S
        X5


           2
           I
           0,
            0    5    10   15    20
                    CLflY  CppmD
25
Figure 3.   The Relay component for the wavelength range
from 275 ran to 745 rim.
                     -26-

-------
                           CLflY
                    WRVELENGTH-550
            E
           \
            X
            * 4
            u
              0
               '0
5    10
   CLRY
15
                        20
  Figure 6.  The Relay component for the wavelength 550 nm
  for a range of clay (ppm) where the x's are experimental
  data and the line is a pol>nonial fit.
                         CLRY
         a
         "o  2
0     5    10    15    20
         CLflY  CppmJ
                                        25
Figure 7.  The Relay component for five wavelengths where
5=300 nm, 11=450 nm, 13=550 nm,  and 15=650 nm where these
points represent data and the solid line is the model fit.
                    -27-

-------
                           DOM
                        #1 1-#16
            250   350  450   550
                                    650  750
                     HflVELENGTH  Cnm]

Figure 8.  The spectral Kdom component (with scattering
material still present; see text)  Cor a  DOM Group water
types //11-//16 listed in Table 1.
             10

             9

             8

          •i 7
          ^ 6
          L-l
             5
           £
           O 4

          * 3

             2

             1
                           DOM
                        #11-#16
            250   350  450   550  650   750
                   WRVELENGTH  Lnm]

Figure 9.  The spectral Kdom component for the DOM Group
water types //11-//16  lisccd  In lable 1.
                    -28-

-------
                           BOM
             10
             9
             8
           £ 7
          ^ 6
          i_i
             5
           £
           O 4
          T3
          * 3
             2
             I
             0
X  375 NM
0  450 NM
              012345
                       DOM  Cmg/ll

  Figure 10.  The Kdom component  for two wavelengths where
  the points arc data and the solid line Is a fit.
                          DOM
                       #11-#16
          \
            250  350   450  550   650  750
                   WRVELENGTH   Cnm!)
Figure 1J.   The spectral  (Kdom+Kclay) component where the
x's are d.ita and the line is the model fit.
                      -29-

-------
         E
         \
         o
         +J
         *
                        CLflY
                       #2-#8
               350   450  550  650  750
                 WRVELENGTH
Figure 12.  The spectral Ktot data points and analytic nodcl
fit as solid linos for the Clay Croup.
                    CLRY+DOM
                     #11-#16
           10
               350  450   55'   650  750
                 WRVELENGTK  CnmJ
 Figure 13.   Die sptctuU KLot dat.i  points and analytic model
 fit as solid lines for llie DOM Croup.

-------
1E+02
1E+01  t
                                  san  Vicente
1E+00  -
1E-01  r
I EH
    •theoretical mo'^cu'ar
      300   400   503   600   700   800

              WRVELENGTH
Figure 14.  'Ihe total seal tor UIR b for a variety of water
f'pes from molecular scattering to clear watoi to ocean
to river.
                    -3L-

-------
1E+0B
1E-01
                  SCOR/DISCOVERER
                                                b/c
1E-0H
   400
500           600
WHVELENGTH  Cnm]
700
 I'lgurc 15.  The  spectral a (solid line), b (dashed line) c
 (dash dashed line), and b/c (notched line for  SCOK Discovers
 suition 21 Sargasso Sea waters.  The }) points  are the  field data
 measurements of.  total diffuse attenuation coefficient  whereas
 the 1,6 are the  Monte Carlo calculations of K  for 10 degrees
 and 60 degrees  sun angles.
                      -32-

-------
 1E+01
                    SRN VICENTE
                    500            600  _
                     NRVELENGTH  Unroll
700
Figure 16.  Ihe a (solid  line),  b  (dashed line), c (dash dashed line)
and  b/c (notched line for San Vicente waters.  The circled 1,6
points are the field measurements  of total diffuse attenuation
coefficients for sun angles 10 degrees and 60 degrees whereas
the  1,6 points are the Monte Carlo predictions.
                          •-33-

-------
   •   1E+00
         0  20  40  62  80 183 123 140  160 160

                   RNGLE  [decrees3
                                 N^

Tigure 17.  The particle volume scattering function for  fairly
clear ocean water (Occanus cruise station 4) for wavelengths
440 nm, 490 urn, 520 nra, 610 nm,  and 670 nm.
                         -34-

-------
                 SCOR/DISCOVEPER
         0  20  40  60  80 100 120 M0 160 180

                  RNGLE  [degrees]

Figure 18.  The calculated total volume scattering function
for very clear ocean water (SCOR Discoverer station 21) for
wavelengths 440 nm, 490 nm, 520 nm, 610 nm, and  670 nm.
                      -35-

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                       BSIII  MODEL
                   353   453   550  653  753
                              HL
Figure  19.  The Uakor- Smith III component model orcdiction of
spectral  Ktot (A)  for a range of Chlorophyll, dissolved organic
material and clay.  The following explains  the composition.
1 line
1
1
1 chl
1 DOM
I clay
1
I
1
1 0
1 0
1 0
solid
.5
0
0
1
1
1
5. 1
0 I
0 1
dashed
0
.5
0
0
5.
0
dashed
0
0
5
dot
0
0
25
hatched
.5
.5
5
5 1
5 1
25
                          -36-

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                SRN  VICENTE  DIRECT
N
U
     0
     8
     10
    12
    14
    16
    18
                  10  30"
UO-   TO"
               .4
.6
.8
                             K
   Figure 20.  The Monte Carlo calculation of K (A,z,0) for
   wavelength 530 nm  for sun angJcs 10, 30, 60, 70, 80 decrees
   plotted versus optical depths cz wlicn using only a diiecl l>uam
   input to the water column.
                                -37-

-------
                       SRN  VICENTE
N
U
     0
     8
     10
     12
     14
     16
     IB
                    10" 30*
                .4
.5
.7
.8
                               K
  Figure 21.  The Monti! (,arlo calculation of K(A,z,0)  for wavelength
  550  nm for sum nnj'.los 1.0,30,  60, 70, 80 degrees plotted versus
  optical depths a. wlu'n using botli a direct and a diffuse Jnput
  to the water colu.in.
                                -38-

-------
N
U
     0
     16
     18
       0
                             DISCO
.02
04
.06
.08
.1
                                K
   Figure 22.  The Monce  Carlo calculation of K(A,z,0)  Cor clear
   waters of SCOR Discoverer for sun angle 10 degrees (solid line)
   and  40 demises (broken line) for wavelengths 440 nm,  490 nm,
   515  nm, and 550 nm.  The straight line superimposed  is  the
   field measured value which is average for the day.
                              -39-

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                      SfiN  VICENTE
N
U
     0
     14
     16
     18
       0
.4
,8
1.2
   K
1.6
2.4
 Figure 23.  The Monte Carlo calcualtiuu of K (X,z,0) for San
 Vicente waters for sun angles 10,  30, 60, 70,  80 degrees for
 wavelengths 440 nm, 550 nm, and 670 ran.  Tbe straig'it lines
 superimposed are the field measured values for 1U and 60
 degree sun angles.
                          -40-

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                                   KEFLRlINCLS

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                                      -Al-

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Miller,  (».C. and K.G. iepp  (1978):  Effects of  suspended  sediments   on   photo-
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                                     -42-

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