Sender: schwab@glerl.noaa.gov
Date: Mon, 30 Oct 2000 09:15:01 -0500
From: David Schwab <schwab@glerl.noaa.gov>
X-Accept-Language: en
To: eegle-mod@wings.glerl.noaa.gov, eegle-sed@wings.glerl.noaa.gov
CC: richardson.william@epamail.epa.gov
Subject: Lake Michigan shoreline and tributary mass loadings

Hi all,

I'm attaching two files that contain estimates of annual shoreline
erosion
(by county) and tributary mass loadings (by tributary) for Lake
Michigan.
We plan to use these numbers in sediment dynamics modeling simulations
for
EEGLE here at GLERL.  The shoreline erosion numbers are from

Montieth, T.J. and Sonzogni, W.C., 1976. U.S. Great Lakes shorline
erosion loadings. Technical report of the Great Lakes Pollution from
Land Use Activities Group, International Joint Commission.

The river loadings for 1974-75 are from

Sonzogni, W.C., Montieth, T.J., Bach, W.N., and Hughes, V.G., 1978. U.S.
Great Lakes tributary loadings. Technical report of the Great Lakes
Pollution from Land Use Activities Group, International Joint
Commission.

The river loadings for 1994-95 are from the USEPA Lake Michigan Mass
Balance
Study, courtesy of Bill Richardson.

The shoreline and loadings represent the clay and loam components from
Monteith and Sonzogni and the tributary loadings are total suspended
solids.

Please let me know if you have any comments or questions.

... Dave S.

-- 
Dr. David J. Schwab
NOAA Great Lakes Environmental Research Laboratory
2205 Commonwealth Blvd.
Ann Arbor, MI 48105
734-741-2120
734-741-2055 (FAX)
Estimation of Lake Michigan shoreline erosion loads by soil texture
classification from Monteith and Sonzogni (1976).

Monteith and Sonzogni (1976) provided county by county estimates of the average
volume of material eroded (Table 17), but did not provide the breakdown of the
material into their three soil texture categories (sand, loam, clay), even
though the breakdown is reported on the sample worksheet for Charlevoix county
(Table 15).  They also reported loadings of 12 different chemical loadings by
county.  The chemical loadings were based on the amounts of sand, loam, and
clay eroded from each county using the chemical analysis by soil texture
described in Table 8.  By inverting this procedure, we should be able to infer
the amounts of sand, loam, and clay for each county.  This is an overdetermined
problem (12 equations in 3 unknowns) so a least-squares approach is used.  The
results are as follows:
    1      2         3         4         5       6     7     8     9    10
   35  0.000075  0.009712 -0.000041  0.009747  0.92  0.01  1.00  0.00  0.00
   36 -0.000214  0.009085  0.000008  0.008879  1.12 -0.02  1.02  0.00  0.00
   37  0.005044 -0.000033  0.004649  0.009660  0.91  0.52  0.00  0.48  0.01
   38  0.001369  0.356558  0.000263  0.358189  0.98  0.00  1.00  0.00  0.00
   39  0.006727  0.024264  0.016126  0.047117  0.99  0.14  0.51  0.34  0.00
   40  0.165602  0.218539 -0.000028  0.384113  0.98  0.43  0.57  0.00  0.00
   41  0.013944  0.182316 -0.000054  0.196206  0.97  0.07  0.93  0.00  0.00
   42 -0.004770  1.535799 -0.000521  1.530508  0.98  0.00  1.00  0.00  0.00
   43 -0.001788  0.453066  0.502651  0.953930  0.98  0.00  0.47  0.53  0.00
   44  0.140408  0.306974 -0.000047  0.447335  0.98  0.31  0.69  0.00  0.00
   45  0.214327  0.004805  0.000033  0.219165  0.98  0.98  0.02  0.00  0.00
   46  0.050151  0.691644 -0.000245  0.741550  0.98  0.07  0.93  0.00  0.00
   47 -0.000892  0.222760 -0.000082  0.221787  0.97  0.00  1.00  0.00  0.00
   48  0.074687 -0.000138  0.000001  0.074550  0.97  1.00  0.00  0.00  0.00
   49  0.918301 -0.001481  0.000230  0.917050  0.98  1.00  0.00  0.00  0.00
   50  0.138333 -0.000245  0.000044  0.138132  0.98  1.00  0.00  0.00  0.00
   21  1.451708 -0.002338  0.000397  1.449767  0.98  1.00  0.00  0.00  0.00
   22  0.646830 -0.000988  0.000157  0.645998  0.98  1.00  0.00  0.00  0.00
   23  2.157810 -0.003577  0.000618  2.154852  0.98  1.00  0.00  0.00  0.00
   24  1.255404 -0.002138  0.000357  1.253624  0.98  1.00  0.00  0.00  0.00
   25  0.989522 -0.001603  0.000262  0.988181  0.98  1.00  0.00  0.00  0.00
   26  0.600608  0.275649  0.000130  0.876386  0.98  0.69  0.31  0.00  0.00
   27  0.904371 -0.001414  0.000215  0.903173  0.99  1.00  0.00  0.00  0.00
   28  0.691529  0.084679  0.000185  0.776393  0.98  0.89  0.11  0.00  0.00
   29  0.948412 -0.000764 -0.000107  0.947541  0.99  1.00  0.00  0.00  0.00
   30  3.507380  0.246612  0.000900  3.754891  0.98  0.93  0.07  0.00  0.00
   31  0.532526 -0.000893  0.012234  0.543867  0.98  0.98  0.00  0.02  0.00
   32  0.041058  0.000002 -0.000003  0.041056  0.97  1.00  0.00  0.00  0.00
   33  0.033979  0.000179 -0.000008  0.034149  0.99  1.00  0.01  0.00  0.00
   34  0.384703  0.010056  0.000107  0.394865  0.98  0.97  0.03  0.00  0.00
   17  0.401655 -0.000666  0.000112  0.401101  0.98  1.00  0.00  0.00  0.00
   18  0.052329 -0.000170  0.000056  0.052215  0.99  1.00  0.00  0.00  0.00
   19 -0.000722  0.293624 -0.000127  0.292775  0.98  0.00  1.00  0.00  0.00
   20  0.034235 -0.000217  0.000041  0.034059  0.99  1.01 -0.01  0.00  0.00
   99 16.355038  4.908917  0.538868 21.802822  1.00  0.75  0.23  0.02  0.00
1 = county ID number (99=lakewide total) 
2 = estimated sand (1.e9 kg/yr)
3 = estimated loam(1.e9 kg/yr)
4 = estimated clay(1.e9 kg/yr)
5 = estimated total(1.e9 kg/yr)
6 = estimated total / reported total
7 = fraction sand
8 = fraction loam
9 = fraction clay
10= standard error

The total loam and sand (1.e9 kg/yr) ranked by county is:

    1   42  1.535279  0.282  43.3727  -87.8582  Ozaukee
    2   43  0.955718  0.457  43.0188  -87.8707  Milwaukee
    3   46  0.691399  0.584  42.3232  -87.8102  Lake Ill.
    4   38  0.356821  0.650  44.5266  -87.5050  Kewaunee
    5   44  0.306928  0.706  42.7562  -87.7878  Racine
    6   19  0.293497  0.760  45.7702  -86.8114  Delta
    7   26  0.275778  0.810  43.6488  -86.4936  Oceana
    8   30  0.247512  0.856  45.0076  -85.7202  Leelanau
    9   47  0.222678  0.897  41.9305  -87.6324  Cook
   10   40  0.218511  0.937  44.1149  -87.6100  Manitowoc
   11   41  0.182262  0.970  43.7181  -87.7301  Sheboygan
   12   28  0.084863  0.986  44.3496  -86.2885  Manistee
   13   39  0.040390  0.993  44.9984  -87.2679  Door
   14   31  0.011341  0.995  44.8568  -85.5298  Grand Traverse
   15   34  0.010163  0.997  45.5955  -84.9746  Emmet
   16   35  0.009671  0.999  45.0156  -87.6464  Marinette
   17   36  0.009092  1.001  44.8382  -87.8837  Oconto
   18   45  0.004838  1.002  42.5750  -87.8132  Kenosha
   19   37  0.004616  1.002  44.5981  -87.9625  Brown
   20   33  0.000170  1.002  45.3138  -85.2731  Charlevoix
   21   32 -0.000001  1.002  45.0293  -85.3881  Antrim
   22   18 -0.000114  1.002  45.8974  -86.1786  Schoolcraft
   23   48 -0.000137  1.002  41.6618  -87.4126  Lake Ind.
   24   20 -0.000176  1.002  45.3225  -87.4334  Menominee
   25   50 -0.000201  1.002  41.7381  -86.8751  LaPorte
   26   17 -0.000554  1.002  46.0022  -85.2694  Mackinac
   27   22 -0.000831  1.002  42.3355  -86.3121  Van Buren
   28   29 -0.000871  1.002  44.6667  -86.1964  Benzie
   29   27 -0.001198  1.002  44.0054  -86.4546  Mason
   30   49 -0.001251  1.001  41.6575  -87.0931  Porter
   31   25 -0.001341  1.001  43.2940  -86.3752  Muskegon
   32   24 -0.001780  1.001  42.9475  -86.2270  Ottawa
   33   21 -0.001942  1.001  41.9959  -86.5664  Berrien
   34   23 -0.002958  1.000  42.5982  -86.2306  Allegan
   35   99  5.447785                            Whole Lake



Lake Michigan Tributary Loadings of Suspended Solids (Metric tons/year)
1975-76 estimates from Sonzogni et al. (1978)
1994-95 estimates from LMMBS 
--------------------------------------------------------------------------------
Discharge Point     Lat    Lon      1975    1976     avg    1994    1995     avg
--------------------------------------------------------------------------------
Sturgeon          455000  864200    4900    4900    4900    6804    4742    5773
Whitefish         455455  865640		       0    2154    3589    2871
Escanaba          454729  870046    4100    4000    4050    3134    5221    4177
Cedar             452453  872052		       0    3527    5875    4701
Menominee              0       0   13000   16000   14500   13865   23098   18482
Peshtigo          445823  873918    4000    6000    5000    3900    6497    5198
Oconto            445342  874900    7300   10000    8650   24861   22897   23879
Pensaukee         444933  875331		       0   12066   11113   11589
Kewaunee          442742  872947		       0   18334   16886   17610
Fox                    0       0   60000  100000   80000  151669  139684  145676
Manitowac         440539  873848		       0   33619   14560   24090
Sheboygan              0       0		       0   11556    5005    8281
Milwaukee              0       0  100000   67000   83500    5781    6105    5943
 Root             424346  874620		       0    2738    2892    2815
Grand Calumet          0       0		       0    4195    4810    4503
 Galien           414843  864522		       0   15583   24080   19831
St. Joseph             0       0   82000  110000   96000  112077  173189  142633
Black             422423  861739    3600    4900    4250   14139   12713   13426
Kalamazoo         424055  861317   27000   37000   32000    1213    1091    1152
Kalamazoo              0       0		       0   46068   41420   43744
Grand                  0       0   76000  150000  113000  170815   89022  129918
Muskegon               0       0   41000   63000   52000    6023    7252    6637
Pere Marquette    435641  862615   16000   14000   15000    3124    3761    3442
Pere Marquette         0       0		       0   10954    9992   10473
Manistee          441518  862046   20000   18000   19000   30461   27785   29123
Betsie            443753  861441		       0    1785    2149    1967
Jordan            451911  851609		       0    3659    4405    4032
Millecoquins near 460545  852831		       0    6837    4765    5801
Manistique             0       0   12000   16000   14000   17847   12439   15143