9633

• UCREFRP Catalog Number: 9633
• Author: Schmidt, J. C. and J. B. Box
• Title: Application of a Dynamic Model to Assess Controls on Age-0 Colorado Pikeminnow Distribution in the Middle Green River, Colorado and Utah
• USFW Year: 2004
• USFW - Doc Type: Annals of the Association of American Geographers
• Copyright Material: NO

466

Schmidt and Box

@

Entry rate
from
Yampa River

Reach A
population

Entry rate
into Reach A
backwaters

Speed of
larval drift
in Reach A

Reach A
backwater
population

Reach B
population

Entry rate
into Reach B
backwaters

Speed of
larval drift
in Reach B

Reach B
backwater
population

Reach C
population

Leakage rate
from Reach B
backwaters

Figure 6. Diagram of the model structure. Details of the model are
available, on request, from the senior author. The sequence dis-
played here is continued downstream through all of the reaches.
The time step for the runs is 0.0625 days.

Entry rate from Yampa River: LarVal fish enter study area at
Reach A, and the number of fish that enter at each time step is
based on the daily estimated influx of larvae. The daily rate is
divided by the time step to determine the influx of each time
step.
Reach population: These fish enter the main current of Reach
A and remain thete for a duration that is determined by di-
viding the reach length by the Speed of larval drift. The
Speed of larval drift is determined by (1) in text.
Backwater population: At each time step, a proportion of the
population in Reach population enter backwaters, as deter-
mined by Entry rate into backwaters. Entry rate into back-
waters is a proportion, and this proportion is determined by (2)
and (3) in text.
Leakage rate from backwaters: At each time step, a propor-
tion of the Backwater population reenters the main current,
and this proportion is determined by (5) in text.

Table 2. Discharge-Velocity Relations of Gaging Stations

Yampa River at Deerlodge Park, CO v = 0.34491 QO.25416
(applied to Yampa River)
Green River near Jensen, UT v = 0.1509 Q0.3782
(applied to Green River between
Yampa River mouth and Ouray)
Green River near Ouray, UT v = 0.0937 Q0.3845
(applied to Green River downstream
from Ouray)

v = velocity, in feet per second
Q = discharge, in cubic feet per second

number oflarvae transported into backwaters is primarily
controlled by the proportion of the main flow lined by
separation surfaces, or eddy fences, that divide the two
features. We assumed that the process is also controlled
by an arbitrarily defined water exchange rate and by the
rate at which larvae gain the ability to swim into back-
waters. The proportion of the main channel larval pop-
ulation entering backwaters, a, in each time step is;

a = b[cr + (1 - cr)(1 - NA)]

(2)

where b is the proportion of the main flow lined by sep-
aration surfaces, cr is the water exchange rate and as-
sumed to be 0.6, and NA is the proportion of the total
larval fish population that has no ability to swim. The
number of larval fish' entering backwaters was deter-
mined by multiplying a times the number of larvae es-
timated to be in the main current in each reach in each
time step. We had no basis to determine the value of cr,
and we chose a value that emphasizes hydraulic control
of the process. Differences in cr do not result in signif-
icant differences in predicted populations in late sum-
mer. The predicted date of arrival of the first larval fish
and the date when the majority of the total drifting
population pass a reach do not change for values of cr
between 0.5 and 0.8. Predictions of transport into back-
waters within this range of cr do not differ by more than
about 10 percent of the drifting population.
Since there are no data on the proportion of the main
flow lined by separation surfaces, we used a geomorphic
metric that would allow its estimation. We assumed that
the proportion of the main flow lined by separation
surfaces is a function of shoreline complexity, which was
measured or estimated. Shoreline complexity (SC), de-
fined as the ratio of total shoreline length to rea,ch length
(Gosse 1963), is typically used to characterize habitat
complexity (Sedell, Richey, and Swanson 1989) and
backwater abundance (Dudley and Platania 2000b). It is
an attractive metric and is readily determined from
topographic maps or photographs because shoreline
length can be measured. Rakowski (1997) found that