【文章內(nèi)容簡(jiǎn)介】 equilibrium bed material gradation at the armoring layer is insensitive to Ls. Figure 1. Sensitivity of the Calculated Bed Scour Depth to Ls in Ashida and Michue’s (1971) Run 6 In addition, the influence of mixing layer thickness on the calculated scour depth and bed material gradation is examined by changing the value of mixing layer thickness from the median size of parent mixture to twice that value. Figure 2 shows that the thicker the mixing layer, the larger the equilibrium scour depth. The time to reach the equilibrium scour depth and the equilibrium bed material gradation increases as the thickness of the mixing layer increases. The mixing layer thickness is important in the case of bed scour. Figure 2. Sensitivity of the Calculated Bed Scour Depth to Mixing Layer Thickness in Ashida and Michue’s (1971) Run 6Case B: Channel Aggradation. The channel aggradation experiments performed at the St. Anthony Falls Hydraulic Laboratory (SAFHL。 see Seal et al., 1995) were used to test CCHE1D model (Wu, Vieira and Wang, 2000). Here, the experimental run 2 is used to conduct the sensitivity study. The experimental reach of the flume was 45m long and wide, with an initial bed slope of . The tailgate was kept at a constant height that was high enough to produce an undular hydraulic jump at the downstream end of the main gravel deposit. The sediment fed at the flume entrance was a weakly bimodal mixture prising a wide range of sizes, from to 64mm, which was transported mainly as bed load. Due to sediment overloading, an aggradational wedge developed. Its front gradually moved downstream while the upstream bed elevation continued to rise. In run 2 the water discharge was , the sediment feed rate was , and the tailgate water elevation was . The influence of the adaptation length Ls on the calculated bed profile is analyzed by setting Ls as , 2m and . Here, h is set to the average flow depth over the wedge from the inlet to the gravel deposit front, and equals to about 1m. As shown in Figure 3, Ls has little influence on the location, height and celerity of the gravel deposit front. It seems that Ls does not affect the top slope of wedge. The only noticeable influence of Ls is on the slope of the deposit front. The longer the adaptation length, the milder the slope of the deposit front. However this occurs over a limited distance, and the influence of L s on the calculated bed profile is limited. Figure 3. Sensitivity of the Calculated Bed Profile to Ls in SAFHL’s (1995) Run 2 Figure 4 shows the calculated bed profiles with the mixing layer thickness being given values of d50, 6d50 and ?. The difference among the calculated bed profiles is very small. As the mixing layer thickness increases six times, the deposit front just moves downstream about %. The influence of the mixing layer thickness on the deposition case is much less than on the previous scouring case.Figure 4. Sensitivity of the Calculated Bed Profile to Mixing Layer Thicknessin SAFHL’s (1995) Run 2 Case C: Goodwin Creek Watershed: Goodwin Creek in Panola County, Mississippi, is an experimental watershed for the DEC project. The drainage area above the watershed outlet is , and the average channel slope is about . Most of the channels in the watershed are ephemeral, with perennial flows occurring only in the lower reaches of the watershed. The runoff produced by storm events swiftly exits the watershed, and the discharge returns to base flow levels within one to three days. The sediments are transported in the channels as bed load and suspended load, and range from silt () to sand to gravel (65mm). Fourteen fullyinstrumented flumes were constructed in the channels to control degradation of the channel bed and to monitor runoff and sediment yield. Figure 5 shows the channel network of Goodwin Creek extracted from a Digital Elevation Model using TOPAZ. Ten instream measuring flumes and four culverts, located in the channels of Strahler order two or higher, are considered. The simulation duration is 18 years, from January 1978 to December 1995, with a total of 1192 storm events. The time step used in the calculation is 15 minutes. The runoff and sediment yield from the upland fields generated with SWAT (Bingner et al., 1997) are used as the inflow conditions for the simulation of flow and sediment transport in the channel network. The model calibration done by Wu, Vieira and Wang (2000) showed that the CCHE1D model provided good predictions of the channel evolution and sediment yield in this watershed. Here, the sensitivity analysis of this model to the nonequilibrium adaptation length and the mixing layer thickness is conducted. Figure 5. Channel Network with Hydraulic Structures in Goodwin Creek At first, the nonequilibrium adaptation coefficient α, which is used to calculate the nonequilibrium adaptation length for suspended load, is given values of , , and , while other parameters are kept invariable. Here, the sediment transport capacity is calculated by Wu, Wang and Jia’s (2000) formula. Figure 6 shows the parison of the calculated silt, sand and gravel yields using various α. Table 1 provides the quantitative information about this parison. As α increases from to , the gravel yield increases 27%, and the silt yield decreases 9%。 the sand yield decreases first and then increases with a net increase of 8%。 the total sediment yield slightly decreases 5% as a result. Figure 6. Sensitivity of the Calculated Sediment Yield to α Table 1 Calculated Sediment Yield at Watershed Outlet Using Various α Table 2 shows the calculated sediment yield at the watershed outlet using various nonequilibrium adaptation lengths for bed load Ls, with other parameters kept invariable. As the Ls for bed load increases from 20m to 200m, silt, sand and gravel yields decrease %, % and %, respectively, and the total sediment yield decreases %.