【正文】 s 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%。 ? Abk / ? t is the bed deformation rate of size class k. The bed material is divided into several layers. The variation of bed material gradation pbk at the mixing layer (surface layer) is determined by the following equation (Wu and Li, 1992) (4)where Am is the crosssectional area of the mixing layer。 Qt*k is the totalload transport capacity。 FAX (662) 9157796。 PH (662) 9155673 / (662) 9157788。 Qtk is the actual totalload transport rate。 Q*tk is the potential sediment transport rate, which is determined with SEDTRA module (Garbrecht et al., 1995), Wu, Wang and Jia’s formula (2000), the modified Ackers and White’s 1973 formula (Proffitt and Sutherland, 1983), or the modified Engelund and Hansen’s 1967 formula (with Wu, Wang and Jia’s correction factor, 2000). The bed deformation due to size class k is determined with (3)where p′ is the bed material porosity, which is calculated with the methods of Komura and Simmons (1967), Han et al (1981), or is specified by the user according to available measurement data。 p*bk is pbk of the mixing layer when ?Am/ ? t ? ? Ab/?t≤0 , and p*bk is the percentage of the kth size class of bed material in subsurface layer (under mixing layer) when ?Am/ ? t ? ? Ab/?t 0. Eq. (1) is discretized using the Preissmann implicit scheme, with its source term being discretized by the same formulation as that for the righthand term of Eq. (3) in order to satisfy the sediment continuity. Eq. (4) is discretized by a difference scheme that satisfies mass conservation. A coupled method for the calculations of sediment transport, bed change and bed material sorting is established by implicitly treating the pbk in Eq. (2) as pbkn+1and simultaneously solving the set of algebraic equations corresponding to Eqs. (1)(4) by using the direct method proposed by Wu and Li (1992). This coupled method is more stable and can more easily eliminate the occurrence of the puted negative bed material gradation, when pared to the decoupled method, in which the pbk in Eq. (2) is treated explicitly. However, the aforementioned coupling procedure for sediment transport, bed change and bed material sorting putations is still decoupled from the flow calculation. Model Parameters to be Analyzed The parameters in numerical models of flow and sediment transport in rivers can be classified into two groups: numerical parameters and physical parameters. The numerical parameters result from the discretization and solution procedures, while the physical parameters represent the physical properties of flow and sediment, or the quantities derived from the modeling of flow and sediment transport. In the CCHE1D channel network model, the numerical parameters include putation time step and grid length, and the physical parameters are