During the past 11 days I have completed 1064 simulations of the river, using the combination of parameters described previously. Runs are performed on 2 Apple Macintosh computers having 2.0 and 2.4 GHz Intel dual-core CPUs running OS X 10.5.5. When I am not doing anything else with the computers, 2 simultaneous simulations (as Unix processes) can be run, taking less combined time than 2 sequential simulations.
Because the runs are progressing well, I have decided to perform an additional 768 simulations using the same combinations of the 5 variables {width, depth, diam, flow, sdist}, but with an initial erosion rate of 1.8 ha/yr/km, so that 4 values of initial erosion will be used: {1.2, 1.8, 2.4, 3.6}. This is partly because many of the simulations decrease their erosion rate over time (so that some end with erate << 1.2), but also because after viewing the initial results I feel that an intermediate value between 1.2 and 2.4 is needed, whereas there is less final difference between runs started at 2.4 and 3.6 ha/yr/km. This will yield a new total of 3072 rather than 2304 distinct simulations. At the current rate of 96/day, this should take a total of 32 days, allowing all runs to be completed by the end of October, barring unforseen problems.
I have also written a simple database to collect, display, and manipulate the results, in both numerical and graphical form. This database has a programming and query syntax similar to some other common programs, so I have elected to call it 'RiverSquirrel', after 'my squirrel' (MySQL) or 'post grey squirrel' (PostgreSQL). A database creation program peruses all simulation files and accumulates several numerical results, creating a large table of values. The database query program can perform the following operations on the table:
Currently the query interface is a programming one (from Python), but it could be modified to either read text command files, or to take interactive input from the terminal. At present it is sufficient to perform rudimentary searches and display subsets of results as text and images. It is expected that this interface and its capabilities will evolve as necessary over the next few months as the data are analyzed.
Here are several fields from the table showing the 6 independent, discrete, input parameters (sorted by width->depth->diam->flow->sdist->erate) and 5 dependent, continuous, output values:
> ../RiverSquirrel.py runs.rsq
Reading: runs.rsq...
1064 entries read
1064 entries:
file avwidth0 depth diam flow sdist erate0 avwidth length cArea eArea erate
------------------------------ ---------------- ---------------- ---------------- ---------------- ---------------- ---------------- ---------------- ---------------- ---------------- ---------------- ----------------
iMac/test0000.mnrr 433.661987 2.750000 0.000500 800.000000 0.750000 1.199998 437.179789 148234.005405 214.250000 11188.422908 0.886913
iMac2/test5000.mnrr 433.661987 2.750000 0.000500 800.000000 0.750000 1.800001 440.097217 174636.130130 265.500000 17384.646105 1.127514
iMac/test0001.mnrr 433.661987 2.750000 0.000500 800.000000 0.750000 2.400007 441.617137 177842.965221 319.750000 23891.941898 1.492773
iMac/test0002.mnrr 433.661987 2.750000 0.000500 800.000000 0.750000 3.599992 439.382579 167536.841460 395.000000 36242.357280 2.462988
iMac/test0003.mnrr 433.661987 2.750000 0.000500 800.000000 1.000000 1.199999 438.327311 157784.485527 228.000000 12822.685652 0.946889
iMac2/test5001.mnrr 433.661987 2.750000 0.000500 800.000000 1.000000 1.799999 440.352742 171500.594897 286.500000 19754.559753 1.347048
iMac/test0004.mnrr 433.661987 2.750000 0.000500 800.000000 1.000000 2.400005 441.954097 181279.258680 342.750000 26948.249198 1.700486
iMac/test0005.mnrr 433.661987 2.750000 0.000500 800.000000 1.000000 3.599994 435.376554 164998.048398 410.000000 39488.989870 2.714484
iMac/test0006.mnrr 433.661987 2.750000 0.000500 800.000000 1.250000 1.199998 440.585635 172485.286508 249.500000 15000.749204 0.998835
iMac2/test5002.mnrr 433.661987 2.750000 0.000500 800.000000 1.250000 1.800002 441.104491 185249.360552 315.500000 22951.506781 1.331328
...
MacBook/test1657.mnrr 548.391695 3.500000 0.001000 800.000000 0.750000 2.399998 569.720380 154960.473825 300.250000 20249.570461 1.449807
MacBook/test1658.mnrr 548.391695 3.500000 0.001000 800.000000 0.750000 3.599997 569.411951 164236.967117 365.750000 30577.516346 2.052708
MacBook/test1659.mnrr 548.391695 3.500000 0.001000 800.000000 1.000000 1.200000 565.412960 142317.306038 236.000000 12126.988516 0.961104
MacBook/test1660.mnrr 548.391695 3.500000 0.001000 800.000000 1.000000 2.399999 571.851009 166821.030775 337.250000 24538.043265 1.599996
MacBook/test1661.mnrr 548.391695 3.500000 0.001000 800.000000 1.000000 3.600003 570.268799 165831.200249 391.000000 36116.163596 2.589623
MacBook/test1662.mnrr 548.391695 3.500000 0.001000 800.000000 1.250000 1.200000 569.830171 144333.457406 255.500000 14002.956943 1.107369
MacBook/test1663.mnrr 548.391695 3.500000 0.001000 800.000000 1.250000 2.400001 562.370133 143929.554365 353.750000 27202.992166 2.021015
MacBook/test1664.mnrr 548.391695 3.500000 0.001000 800.000000 1.250000 3.599989 568.442438 166832.196873 411.750000 40639.004881 2.800044
MacBook/test1665.mnrr 548.391695 3.500000 0.001000 1000.000000 0.750000 1.200001 558.115380 144798.917813 227.000000 11134.616033 0.928373
MacBook/test1666.mnrr 548.391695 3.500000 0.001000 1000.000000 0.750000 2.400001 559.951468 157448.331464 328.750000 23593.496280 1.753849
Using the database, one can plot, say, the longest and shortest final river:
5 entries:
length file avwidth0 depth diam flow sdist erate0
---------------- ------------------------------ ---------------- ---------------- ---------------- ---------------- ---------------- ----------------
245477.926265 iMac/test0143.mnrr 433.661987 2.750000 0.001250 1400.000000 1.250000 3.599963
242306.678435 iMac/test0281.mnrr 433.661987 3.000000 0.001250 1400.000000 0.750000 3.600000
236444.152114 iMac/test0404.mnrr 433.661987 3.250000 0.001250 800.000000 1.250000 3.600008
235817.205567 iMac/test0413.mnrr 433.661987 3.250000 0.001250 1000.000000 1.250000 3.599998
234978.637504 iMac/test0245.mnrr 433.661987 3.000000 0.001000 1400.000000 0.750000 3.599993
5 entries:
length file avwidth0 depth diam flow sdist erate0
---------------- ------------------------------ ---------------- ---------------- ---------------- ---------------- ---------------- ----------------
132485.937320 MacBook/test1539.mnrr 548.391695 3.250000 0.001000 1400.000000 0.750000 1.199999
132274.379441 MacBook/test1326.mnrr 548.391695 3.000000 0.000500 1400.000000 1.000000 1.200000
132070.553290 MacBook/test1512.mnrr 548.391695 3.250000 0.001000 800.000000 0.750000 1.200000
131320.759969 MacBook/test1260.mnrr 548.391695 2.750000 0.001250 800.000000 0.750000 1.200002
130198.496148 MacBook/test1632.mnrr 548.391695 3.500000 0.000750 1000.000000 1.000000 1.200001

Or the ones with the most cutoffs (also the longest river) and with the longest average cutoffs:
5 entries:
nCutoffs file avwidth0 depth diam flow sdist erate0
-------- ------------------------------ ---------------- ---------------- ---------------- ---------------- ---------------- ----------------
60 iMac/test0143.mnrr 433.661987 2.750000 0.001250 1400.000000 1.250000 3.599963
55 iMac/test0116.mnrr 433.661987 2.750000 0.001250 800.000000 1.250000 3.600012
51 iMac/test0404.mnrr 433.661987 3.250000 0.001250 800.000000 1.250000 3.600008
44 iMac/test0080.mnrr 433.661987 2.750000 0.001000 800.000000 1.250000 3.599996
42 iMac/test0260.mnrr 433.661987 3.000000 0.001250 800.000000 1.250000 3.599987
5 entries:
avCLength file avwidth0 depth diam flow sdist erate0
---------------- ------------------------------ ---------------- ---------------- ---------------- ---------------- ---------------- ----------------
21548.912916 iMac/test0142.mnrr 433.661987 2.750000 0.001250 1400.000000 1.250000 2.399992
18132.580194 MacBook/test1289.mnrr 548.391695 2.750000 0.001250 1400.000000 0.750000 3.599988
16023.012955 MacBook/test1532.mnrr 548.391695 3.250000 0.001000 1200.000000 0.750000 3.600005
15947.509123 iMac/test0092.mnrr 433.661987 2.750000 0.001000 1200.000000 0.750000 3.600009
15674.649523 iMac/test0101.mnrr 433.661987 2.750000 0.001000 1400.000000 0.750000 3.599998

Or the 'wildest' and 'tamest' rivers (by final erosion rate):
5 entries:
erate file avwidth0 depth diam flow sdist erate0
---------------- ------------------------------ ---------------- ---------------- ---------------- ---------------- ---------------- ----------------
10.922526 iMac/test0143.mnrr 433.661987 2.750000 0.001250 1400.000000 1.250000 3.599963
8.472486 iMac/test0134.mnrr 433.661987 2.750000 0.001250 1200.000000 1.250000 3.600004
7.848543 iMac/test0137.mnrr 433.661987 2.750000 0.001250 1400.000000 0.750000 3.599998
7.526362 iMac/test0287.mnrr 433.661987 3.000000 0.001250 1400.000000 1.250000 3.599978
7.320121 iMac/test0140.mnrr 433.661987 2.750000 0.001250 1400.000000 1.000000 3.600050
5 entries:
erate file avwidth0 depth diam flow sdist erate0
---------------- ------------------------------ ---------------- ---------------- ---------------- ---------------- ---------------- ----------------
0.741212 MacBook/test1593.mnrr 548.391695 3.500000 0.000500 1000.000000 0.750000 1.200000
0.730534 MacBook/test1620.mnrr 548.391695 3.500000 0.000750 800.000000 0.750000 1.200000
0.717399 MacBook/test1440.mnrr 548.391695 3.250000 0.000500 800.000000 0.750000 1.200000
0.717024 iMac/test0432.mnrr 433.661987 3.500000 0.000500 800.000000 0.750000 1.200000
0.666959 MacBook/test1584.mnrr 548.391695 3.500000 0.000500 800.000000 0.750000 1.200000

By looking at the combinations of input parameters in the previous printout, one can see that the 'wilder' rivers tend to be narrower, shallower, have more discharge, larger grain size, depend on more upstream geometry, and have higher initial erosion rates (pretty much as expected).
Here are some 'more nominal' results (for length < 195 Km and erate < 1.95):
10 entries:
file avwidth0 depth diam flow sdist erate0 avwidth length cArea eArea erate
------------------------------ ---------------- ---------------- ---------------- ---------------- ---------------- ---------------- ---------------- ---------------- ---------------- ---------------- ----------------
iMac/test0025.mnrr 433.661987 2.750000 0.000500 1200.000000 1.250000 2.400003 439.860193 194729.247457 361.500000 30530.064193 1.765710
iMac/test0308.mnrr 433.661987 3.250000 0.000500 1200.000000 0.750000 3.600006 442.100802 194720.333067 384.000000 33110.756979 1.855819
iMac/test0337.mnrr 433.661987 3.250000 0.000750 1000.000000 1.000000 2.400002 441.005884 194194.613023 358.250000 29184.843497 1.805953
iMac/test0190.mnrr 433.661987 3.000000 0.000750 1000.000000 0.750000 2.400000 441.125405 193950.637765 343.250000 26738.039039 1.783816
iMac/test0334.mnrr 433.661987 3.250000 0.000750 1000.000000 0.750000 2.399995 441.602400 193822.916461 339.750000 25834.549258 1.661886
MacBook/test1474.mnrr 548.391695 3.250000 0.000500 1400.000000 1.250000 2.399994 557.226743 193648.949332 352.750000 25410.387029 1.357874
iMac/test0457.mnrr 433.661987 3.500000 0.000500 1200.000000 1.250000 2.399995 443.906511 192998.064211 346.750000 27170.359716 1.505281
iMac/test0311.mnrr 433.661987 3.250000 0.000500 1200.000000 1.000000 3.600000 435.604436 192996.759572 404.750000 36491.492542 1.932142
iMac/test0317.mnrr 433.661987 3.250000 0.000500 1400.000000 0.750000 3.600004 433.366096 192672.337384 385.250000 33417.286202 1.857648
iMac/test0199.mnrr 433.661987 3.000000 0.000750 1200.000000 0.750000 2.400005 436.158985 192262.792834 344.500000 26798.066912 1.829786

Relationships between all combinations of the output values can also be plotted (in the following, the single-point outlier in many plots is run 143 shown above):



Although these plots show only about 35% of all runs (and only 2 initial widths so far), they do inspire a few observations/hypotheses:
Further sorting and selecting of combinations of input variables (rather than all combinations lumped together as shown above) might show differences in these plots and allow one to see where specific trends form and change (i.e. for fixed subsets of the other variables, do variations in a single or pair of input variables lead to specific variations in output values?).
For this project, the most important result might be the cumulative common coverage of the river (i.e. showing the fraction of all simulations which pass through 2d points in the valley), and the average cumulative total erosion over 100 years (also at 2d points in the valley):


Notes:
I will post more intermediate results as they progress next month.