51 
5. Is there a seasonal effect? Not much . 
To address the seasonal issue, we compare models with and without month terms 
(Table D-5a,b,c,d). 
Table D-5a. Before adding Month and Month*trib. 
Source 
DF 
Type III SS 
Mean Square 
F Value 
Pr > F 
tributary 
16 
16.086 
1.005 
2.03 
0.0093 
rl_5turb 
1 
162.130 
162.130 
327.82 
<.0001 
rl_5turb*tributary 
16 
14.711 
0.919 
1.86 
0.0206 
Xchla 
1 
9.717 
9.717 
19.65 
<.0001 
xCH LA* tributary 
16 
21.609 
1.350 
2.73 
0.0003 
xlnSALINITY 
1 
0.057 
0.057 
0.12 
0.7339 
x!nSALINIT*tributary 
16 
18.498 
1.156 
2.34 
0.0021 
Table D-5b. Fit statistics. 
R-Square 
Coeff Var 
Root MSE 
K d l Mean 
0.748631 
31.26545 
0.703259 
2.249316 
Table D-5c. With Month and Month*Trib in the model. 
Source 
DF 
Type III SS 
Mean Square 
F Value 
Pr >F 
tributary 
16 
14.553 
0.909 
1.94 
0.0144 
Month 
6 
5.092 
0.848 
1.81 
0.0942 
Tributary*Month 
87 
62.849 
0.722 
1.54 
0.0016 
rl_5turb 
1 
93.206 
93.206 
198.72 
<.0001 
rl_5turb*tributary 
16 
16.690 
1.043 
2.22 
0.0037 
xCHLA 
1 
5.522 
5.522 
11.77 
0.0006 
xCHLA*tributary 
16 
19.573 
1.223 
2.61 
0.0005 
xlnSALINITY 
1 
0.125 
0.125 
0.27 
0.6055 
xInSALINIT*tributary 
16 
17.341 
1.083 
2.31 
0.0024 
Table D-5d. 
Fit statistics. 
R-Square 
Coeff Var 
Root MSE 
K d l Mean 
0.782748 
30.44734 
0.684857 
2.249316 
Of the two seasonal terms. Month and Trib*Month, the Month term is not significant 
(p=0.0942) and the Trib*Month term is significant (p=0.0016). The increase in r 2 is 
only about 3% which is a not a large increase for the additional 93 degrees of 
freedom in the seasonal model. The meansquares for the seasonal terms are small. 
appendix d • Derivation of Regressions 
