Comparision Of Model Predictions With The Measured Data

Comparison of model predictions of suspended sediment concentration with the measured data is shown in Figure 8.5. The test with the highest shear stress was used as the calibration test and the calibration coefficients a, b, and j were determined by matching the predicted concentration vs. time curve and the size distribution profiles with the measured data. The calibration was carried out using a trial and error approach. The starting values for the coefficients a and b were obtained from Lau and Krishnappan,21 and a range of values were tried for j. The predicted size distributions were then compared with the measured distributions and a value of j that gave a

Time (min)

FIGURE 8.5 Comparison between model predictions and measured concentration vs. time curves.

Time (min)

FIGURE 8.5 Comparison between model predictions and measured concentration vs. time curves.

reasonable match was chosen. Then, using this j value, the coefficients a and b were adjusted until the predicted concentration vs. time curve matched reasonably well with the measured curve. The procedure was repeated, and within a few iterations, all three coefficients were estimated. The calibrated values of these parameters were found to be a = 0.02, b = 1.45, and j = 0.075. The predicted concentration vs. time curves for the other two tests were produced using these calibrated values. From the comparison in Figure 8.5, we can see that the predicted concentration variation agrees reasonably well with the measured data for all the three tests.

Comparison of the predicted size distribution data with the measurement is shown in Figure 8.6 to Figure 8.9 for Test No 1 and in Figure 8.10 to Figure 8.13 for Test No 2 for various elapsed times. These figures show that the agreement between the model predictions and the measurement is reasonable for the size distribution data as well. The comparison carried out for Test No 3 is not shown here as it was similar to the other two tests.

Reasonable agreement between the model predictions of concentration vs. time curves and the size distribution of the flocs in suspension at various elapsed times imply that the model is capable of predicting the settling and flocculation process of the Kingston pond sediment in the rotating circular flume. For predicting the sediment behavior in the actual pond, the flocculation and the settling components of the model can be used in conjunction with a hydrodynamic model that is capable of predicting the flow conditions in the pond. Plans are underway to initiate such a study in a number of stormwater detention ponds in Ontario, Canada.

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