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<br />Summary <br /> <br /> <br />For Flushing Flow I, the most accurate modeling scenario was the HEC-6 robust <br /> <br />simulation, The model simulated between 75 and 80% of the field measured changes in <br /> <br />channel bed elevation in the Tick Pool. <br /> <br />Flushing Flow 2 <br />HEC-6 Default Simulation <br />By adding the spring snowmelt discharge to the default input file, the entire <br />hydrograph of Figure 2 was modeled for Flushing Flow 2, a duration of six months. The <br />higher discharge, longer duration input generated an increase in accuracy over Flushing <br />Flow I (Simulation I, Table 4). Sequentially adding to the complexity of the input file, <br />in subsequent simulations, HEC-6 overpredicted, by 175-600%, the bed changes that <br />actually occurred (Simulation 2, Table 4). An overprediction implies that there was scour <br />into the bedrock of the Tick Pool, because a limit to sediment thickness was not <br />designated within the input variables. <br /> <br />HEC-6 Robust <br />When the sediment thickness above bedrock was specified in both pools and <br />riffles. limiting the depth of scour, and deposition and erosion were also allowed, HEC-6 <br />predicted between 53-100% of the measured bed change in the Tick Pool (Simulation 3, <br />Table 4), This resulted in the best simulation of changes along the North Fork. However, <br />the result was only obtained when the input data represented a full, one-year monitoring <br />record, <br /> <br />CSTARS 2.0 <br />Flushing Flow 2 simulations in GST ARS 2.0 were likewise composed of a longer <br />duration, higher magnitude discharge. Results indicate no change between predicted and <br />observed bed changes for Flushing Flow I and 2, despite the differences in input <br />hydrographs (Table 3b). Apparently, GSTARS 2.0 was insensitive to magnitude and <br />duration of flows enlering the study reach, <br /> <br />12 <br />