外文翻譯---cche1d渠道網(wǎng)絡(luò)模型的靈敏度分析（英文）

1、 1Sensitivity Analysis of the CCHE1D Channel Network Model Weiming Wu (1), Dalmo A. Vieira (2), Abdul Khan (3) and Sam S. Y. Wang (4) (1), (2), (3) and (4), National Center for Computational Hydroscience and Engineering

2、, School of Engineering, The University of Mississippi, MS 38677; PH (662) 915-5673 / (662) 915-7788; FAX (662) 915-7796; E-mail: wuwm@ncche.olemiss.edu Abstract The CCHE1D model was designed to simulate long-term flow

3、 and sediment transport in channel networks to support the DEC project. It uses either the dynamic wave or the diffusive wave model to compute unsteady flows in channel networks with compound cross sections, taking int

4、o account the effects of in-stream hydraulic structures, such as culverts, weirs, drop structures, and bridge crossings. It simulates non-uniform sediment transport using a non-equilibrium approach, and calculates ban

5、k toe erosion and mass failure due to channel incision. The CCHE1D model decouples the flow and sediment transport calculations but couples the calculations of non- uniform sediment transport, bed changes and bed materi

6、al sorting in order to enhance the numerical stability of the model. In this paper, the sensitivity of CCHE1D to parameters such as the non-equilibrium adaptation length of sediment transport and the mixing layer thick

7、ness is evaluated in cases of channel aggradation and degradation in laboratory flumes as well as in a natural channel network. In the case of channel degradation, the simulated scour process is not sensitive to varia

8、tion in values of the non-equilibrium adaptation length, but the determination of the mixing layer thickness is important to the computations of the equilibrium scour depth and of the bed-material size distribution at

9、the armoring layer. The simulated bed profiles in the case of channel aggradation and the calculated sediment yield in the case of natural channel network are insensitive to the prescription of both the non-equilibrium

10、 adaptation length and the mixing layer thickness. The CCHE1D model can provide reliable results even when these two parameters are given a wide range of values. Introduction The CCHE1D model was designed to simulate

11、long-term flow and sediment transport in channel networks to support the Demonstration Erosion Control (DEC) project, which is an interagency cooperative effort among the US Army Corps of Engineers (COE), the Natural R

12、esources Conservation Service (NRCS) and the Agricultural Research Service (ARS) of the US Department of Agriculture. The CCHE1D version 2.0 was based on the unsteady flow model DWAVNET (Diffusion WAVe model for chann

13、el NETworks, Langendeon, 1996) and the sediment transport model BEAMS (Bed and Bank Erosion Analysis Model for Streams, Li et al., 1996). It was significantly improved by implementing the dynamic wave model and the non

14、- equilibrium sediment transport model (Wu, Vieira and Wang 2000). The CCHE1D was integrated with the landscape analysis tool TOPAZ (Garbrecht and Martz, 1995) and with the watershed models AGNPS (Bosch et al., 1998) a

15、nd SWAT (Arnold et al., 1993), through an ArcView GIS-based graphical user interface (Vieira and Wu, 2000). The CCHE1D has been successfully tested in various experimental and field cases. Because several parameters in

16、 CCHE1D must be prescribed empirically, it is very important to know the response of the model Copyright ASCE 2004 World Water Congress 2001 Copyright ASCE 2004 World Water Congress 2001Bridging the Gap Downloaded from

17、ascelibrary.org by University of Liverpool on 04/19/15. Copyright ASCE. For personal use only; all rights reserved.3where Am is the cross-sectional area of the mixing layer; t Ab ? ? /is the total bed deformation rate,

18、defined as ∑ = ? ? = ? ? Nk bk b t A t A 1 ; N is the total number of size classes; * bk p is pbk of the mixing layer when 0 / / ≤ ? ? ? ? ? t A t A b m , and * bk p is the percentage of the kth size class of bed m

19、aterial in subsurface layer (under mixing layer) when 0 / / > ? ? ? ? ? t A t A b m . Eq. (1) is discretized using the Preissmann implicit scheme, with its source term being discretized by the same formulation as th

20、at for the right-hand 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 trans

21、port, bed change and bed material sorting is established by implicitly treating the pbk in Eq. (2) as 1 + n bk pand simultaneously solving the set of algebraic equations corresponding to Eqs. (1)-(4) by using the direct

22、 method proposed by Wu and Li (1992). This coupled method is more stable and can more easily eliminate the occurrence of the computed negative bed material gradation, when compared to the decoupled method, in which th

23、e pbk in Eq. (2) is treated explicitly. However, the aforementioned coupling procedure for sediment transport, bed change and bed material sorting computations is still decoupled from the flow calculation. Model Param

24、eters 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

25、 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 c

26、hannel network model, the numerical parameters include computation time step and grid length, and the physical parameters are the Manning’s roughness coefficient, non-equilibrium adaptation length of sediment transport

27、, mixing layer thickness, bed material porosity, etc. Usually, the numerical parameters can be more easily handled than the physical parameters. Some of these physical parameters, such as the Manning’s roughness coef

28、ficient and bed material porosity, have been studied by many investigators and may be determined by measurement. However, the non-equilibrium adaptation length and the mixing layer thickness are less understood and mus

29、t be prescribed empirically. Therefore, the main concern in this paper is to analyze the influence of these two physical parameters on the simulation results. The non-equilibrium adaptation length Ls characterizes th

30、e distance for sediment to adjust from a non-equilibrium state to an equilibrium state. Wu, Rodi and Wenka (2000) and Wu and Vieira (2000) reviewed in detail those empirical and semi-empirical methods for determining L

31、s published in the literature, such as Bell and Sutherland’s (1981), Armanini and di Silvio’s (1988), etc. It was found that those methods provide significantly different estimations of Ls. In CCHE1D, the adaptation

32、length for wash load transport is set as infinitely large because the net exchange between wash load and channel bed is usually negligible. The adaptation length for suspended load transport is calculated with Ls=uh/αω

33、s, in which u is the section-averaged velocity, h is the flow depth, ωs is the settling velocity of sediment particles, and α is the adaptation coeficient which can be calculated with Armanini and di Silvio’s (1988) me

34、thod, or specified as a constant value by the user. The adaptation length for bed load transport is suggested to set as the length of the dominant bed forms, such as 7.3h, the length of sand dunes Copyright ASCE 2004