# Morphodynamic model of the lower Yellow River: flux or entrainment form for sediment mass conservation?

←

**Page content transcription**

If your browser does not render page correctly, please read the page content below

Earth Surf. Dynam., 6, 989–1010, 2018 https://doi.org/10.5194/esurf-6-989-2018 © Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License. Morphodynamic model of the lower Yellow River: flux or entrainment form for sediment mass conservation? Chenge An1 , Andrew J. Moodie2 , Hongbo Ma2 , Xudong Fu1 , Yuanfeng Zhang3 , Kensuke Naito4 , and Gary Parker4,5 1 Department of Hydraulic Engineering, State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing, China 2 Department of Earth, Environmental and Planetary Sciences, Rice University, Houston, TX, USA 3 Yellow River Institute of Hydraulic Research, Zhengzhou, Henan, China 4 Department of Civil and Environmental Engineering, Hydrosystems Laboratory, University of Illinois, Urbana-Champaign, IL, USA 5 Department of Geology, Hydrosystems Laboratory, University of Illinois, Urbana-Champaign, IL, USA Correspondence: Chenge An (anchenge08@163.com) and Xudong Fu (xdfu@tsinghua.edu.cn) Received: 12 May 2018 – Discussion started: 12 June 2018 Revised: 17 October 2018 – Accepted: 22 October 2018 – Published: 6 November 2018 Abstract. Sediment mass conservation is a key factor that constrains river morphodynamic processes. In most models of river morphodynamics, sediment mass conservation is described by the Exner equation, which may take various forms depending on the problem in question. One of the most widely used forms of the Exner equation is the flux-based formulation, in which the conservation of bed material is related to the stream-wise gradient of the sediment transport rate. An alternative form of the Exner equation, however, is the entrainment- based formulation, in which the conservation of bed material is related to the difference between the entrainment rate of bed sediment into suspension and the deposition rate of suspended sediment onto the bed. Here we represent the flux form in terms of the local capacity sediment transport rate and the entrainment form in terms of the local capacity entrainment rate. In the flux form, sediment transport is a function of local hydraulic conditions. However, the entrainment form does not require this constraint: only the rate of entrainment into suspension is in local equilibrium with hydraulic conditions, and the sediment transport rate itself may lag in space and time behind the changing flow conditions. In modeling the fine-grained lower Yellow River, it is usual to treat sediment conservation in terms of an entrainment (nonequilibrium) form rather than a flux (equilibrium) form, in consideration of the condition that fine-grained sediment may be entrained at one place but deposited only at some distant location downstream. However, the differences in prediction between the two formulations have not been comprehensively studied to date. Here we study this problem by comparing the results predicted by both the flux form and the entrainment form of the Exner equation under conditions simplified from the lower Yellow River (i.e., a significant reduction of sediment supply after the closure of the Xiaolangdi Dam). We use a one-dimensional morphodynamic model and sediment transport equations specifically adapted for the lower Yellow River. We find that in a treatment of a 200 km reach using a single characteristic bed sediment size, there is little difference between the two forms since the corresponding adaptation length is relatively small. However, a consideration of sediment mixtures shows that the two forms give very different patterns of grain sorting: clear kinematic waves occur in the flux form but are diffused out in the entrainment form. Both numerical simulation and mathematical analysis show that the morphodynamic processes predicted by the entrainment form are sensitive to sediment fall velocity. We suggest that the entrainment form of the Exner equation might be required when the sorting process of fine-grained sediment is studied, especially when considering relatively short timescales. Published by Copernicus Publications on behalf of the European Geosciences Union.

990 C. An et al.: Morphodynamic model of the lower Yellow River 1 Introduction time for sediment transport to reach its equilibrium state (i.e., transport capacity). Using the concept of the adapta- tion length, the entrainment form of the Exner equation can Models of river morphodynamics often consist of three el- be recast into a first-order “reaction” equation, in which the ements: (1) a treatment of flow hydraulics; (2) a formula- deformation term is related to the difference between the ac- tion relating sediment transport to flow hydraulics; and (3) a tual and equilibrium sediment transport rates, as mediated by description of sediment conservation. In the case of unidi- an adaptation length (which can also be recast as an adap- rectional river flow, the Exner equation of sediment conser- tation time) (Bell and Sutherland, 1983; Armanini and Di vation has usually been described in terms of a flux-based Silvio, 1988; Wu and Wang, 2008; Minh Duc and Rodi, form in which temporal bed elevation change is related to 2008; El kadi Abderrezzak and Paquier, 2009). The adap- the stream-wise gradient of the sediment transport rate. That tation length is thus an important parameter for bed evolu- is, bed elevation change is related to ∂qs /∂x, where qs is the tion under nonequilibrium sediment transport conditions, and total volumetric sediment transport rate per unit width and various estimates have been proposed. For suspended load, x is the stream-wise coordinate (Exner, 1920; Parker et al., the adaptation length is typically calculated as a function 2004). This formulation is also referred to as the equilibrium of flow depth, flow velocity, and sediment fall velocity (Ar- formulation, since it considers sediment transport to be at lo- manini and Di Silvio, 1988; Wu et al., 2004; Wu and Wang, cal equilibrium; i.e., qs equals its sediment transport capac- 2008; Dorrell and Hogg, 2012; Zhang et al., 2013). The adap- ity qse , as defined by the sediment transport rate associated tation length of bed load, on the other hand, has been re- with local hydraulic conditions (e.g., bed shear stress, flow lated to a wide range of parameters, including the sediment velocity, stream power, etc.) regardless of the variation in grain size (Armanini and Di Silvio, 1988), the saltation step flow conditions. Under this assumption, sediment transport length (Phillips and Sutherland, 1989), the dimensions of relations developed under equilibrium flow conditions (e.g., particle diffusivity (Bohorquez and Ancey, 2016), the length Meyer-Peter and Müller, 1948; Engelund and Hansen, 1967; of dunes (Wu et al., 2004), and the magnitude of a scour hole Brownlie, 1981) can be incorporated directly in such a for- formed downstream of an inerodible reach (Bell and Suther- mulation to calculate qs , which is related to one or more flow land, 1983). For simplicity, the adaptation length can also be parameters such as bed shear stress. specified as a calibration parameter in river morphodynamic An alternative formulation, however, is available in terms models (El kadi Abderrezzak and Paquier, 2009; Zhang and of an entrainment-based form of the Exner equation, in which Duan, 2011). Nonetheless, no comprehensive definition of bed elevation variation is related to the difference between adaptation length exists. the entrainment rate of bed sediment into the flow and the In this paper we apply the two forms of the Exner equation deposition rate of sediment on the bed (Parker, 2004). The mentioned above to the lower Yellow River (LYR) in China. basic idea of the entrainment formulation can be traced back The LYR describes the river section between Tiexie and the to Einstein’s (1937) pioneering work on bed load transport river mouth and has a total length of about 800 km. Figure 1a and has been developed since then by numerous researchers shows a sketch of the LYR along with six major gauging sta- so as to treat either bed load or suspended load (Tsujimoto, tions and the Xiaolangdi Dam, which is 26 km upstream of 1978; Armanini and Di Silvio, 1988; Parker et al., 2000; Wu Tiexie. The LYR has an exceptionally high sediment con- and Wang, 2008; Guan et al., 2015). Such a formulation dif- centration (Ma et al., 2017), historically exporting more than fers from the flux formulation in that the flux formulation is 1 Gt of sediment per year with only 49 billion tons of water, based on the local capacity sediment transport rate, whereas leading to a sediment concentration an order of magnitude the entrainment formulation is based on the local capacity higher than most other large lowland rivers worldwide (Mil- entrainment rate into suspension. In the entrainment form, liman and Meade, 1983; Ma et al., 2017; Naito et al., 2018). the difference between the local entrainment rate from the However, the LYR has seen a substantial reduction in its sed- bed and the local deposition rate onto the bed determines the iment load in recent decades, especially since the operation rate of bed aggradation–degradation and concomitantly the of the Xiaolangdi Dam beginning in 1999 (Fig. 1b), because rate of loss–gain of sediment in motion in the water column. most of its sediment load is derived from the Loess Plateau, Therefore, the sediment transport rate is no longer assumed which is upstream of the reservoir (Wang et al., 2016; Naito to be in an equilibrium transport state, but may exhibit lags in et al., 2018). Finally, the bed surface material of the LYR is space and time after changing flow conditions. The entrain- very fine, as low as 15 µm. This is much finer than the con- ment formulation is also referred to as the nonequilibrium ventional cutoff of wash load (62.5 µm) employed for sed- formulation (Armanini and Di Silvio, 1988; Wu and Wang, iment transport in most sand-bed rivers (National Research 2008; Zhang et al., 2013). Council, 2007; Ma et al., 2017). To describe the lag effects between sediment transport and When modeling the high-concentration and fine-grained flow conditions, the concept of an adaptation length–time is LYR, it is common to treat sediment conservation in terms of widely applied. This length–time characterizes the distance– Earth Surf. Dynam., 6, 989–1010, 2018 www.earth-surf-dynam.net/6/989/2018/

C. An et al.: Morphodynamic model of the lower Yellow River 991 an entrainment-based rather than a flux-based formulation. This is because many Chinese researchers view the entrain- ment formulation as more physically based, as it is capable of describing the behavior of fine-grained sediment, which when entrained at one place may be deposited at some dis- tant location downstream (Zhang et al., 2001; Ni et al., 2004; Cao et al., 2006; He et al., 2012; Guo et al., 2008). How- ever, the entrainment formulation is more computationally expensive and more complex to implement. Because the dif- ferences in prediction between the two formulations do not appear to have been studied in a systematic way, here we pose our central questions. Under what conditions is it valid to use the entrainment form of the Exner equation, and under what conditions may the flux form be used? Or more specif- ically, which form of the Exner equation is most suitable for the LYR? Here we study this problem by comparing the results of flux-based and entrainment-based morphodynamics under conditions typical of the LYR. The organization of this paper is as follows. The numerical model is described in Sect. 2. In Sect. 3, the model is implemented to predict the morpho- dynamics of the LYR with a sudden reduction of sediment supply, which serves to mimic the effect of the Xiaolangdi Dam. We find that the two forms of the Exner equation give similar predictions in the case of uniform sediment, but show different sorting patterns in the case of sediment mixtures. In Sect. 4, we conduct a mathematical analysis to explain the results in Sect. 3; more specifically, we quantify the effects of varied sediment fall velocity in the simulations. Finally, we summarize our conclusions in Sect. 5. 2 Model formulation In this paper, we present a one-dimensional morphodynamic model for the lower Yellow River. The fully unsteady Saint– Venant equations are implemented for the hydraulic calcu- lation. Both the flux form and the entrainment form of the Exner equation are implemented in the model for sediment mass conservation. For each form of the Exner equation, we consider both the cases of uniform sediment (bed material characterized by a single grain size) and sediment mixtures. Since the sediment is very fine in the LYR, the component of the load that is bed load is likely negligible (e.g., Ma et al., 2017), so we consider only the transport of suspended load. Considering the fact that most accepted sediment transport relations (e.g., the Engelund and Hansen, 1967, relation) un- derpredict the sediment transport rate of the LYR by an order Figure 1. (a) Sketch of the lower Yellow River showing six major of magnitude or more (Ma et al., 2017), in our model we im- gauging stations and the Xiaolangdi Dam. (b) Annual sediment load plement two recently developed generalized versions of the of the LYR measured at three gauging stations since 1950. (c) Grain Engelund–Hansen relation, which are based on data from the size distributions of both bed surface material and suspended load LYR. These are the version of Ma et al. (2017) for uniform measured at six gauging stations of the LYR. sediment and the version of Naito et al. (2018) for sediment mixtures. In cases considering sediment mixtures, we also www.earth-surf-dynam.net/6/989/2018/ Earth Surf. Dynam., 6, 989–1010, 2018

992 C. An et al.: Morphodynamic model of the lower Yellow River implement the method of Viparelli et al. (2010) to store and time, here we introduce If into the time derivative of all gov- access bed stratigraphy as the bed aggrades and degrades. erning equations so that the flood timescale tf is implemented Since the aim of this paper is to compare the two formula- in the simulation. This notwithstanding, the results we ex- tions of the Exner equation in the context of the LYR rather hibit later in this paper are all cast in terms of actual timescale than reproduce site-specific morphodynamic processes of the t. Full hydrographs are considered in the Supplement. LYR, some additional simplifications are introduced to the model to facilitate comparison. The channel is simplified to 2.2 Flux form of the Exner equation be a constant-width rectangular channel, and bank (sidewall) effects and floodplain interactions are not considered. The When dealing with uniform sediment, the flux form of the channel bed is assumed to be an infinitely deep supplier of Exner equation can be written as erodible sediment with no exposed bedrock, which is justifi- able because the LYR is fully alluvial and has been aggrading 1 ∂zb ∂qs 1 − λp =− , (4) for thousands of years, as copiously documented in Chinese If ∂t ∂x history. Finally, water and sediment (of each grain size range) are fed into the upstream boundary at a specified rate, and at where λp is the porosity of the bed deposit, and zb is bed the downstream end of the channel we specify a fixed bed elevation. Sediment transport is regarded to be in a quasi- elevation along with a normal flow depth. These restrictions equilibrium state so that the sediment transport rate per unit could be easily relaxed so as to incorporate site-specific com- width qs equals the equilibrium (capacity) sediment transport plexities of the Yellow River. Because of the severe aggrada- rate per unit width qse . tion of the LYR developed before the Xiaolangdi Dam opera- When considering sediment mixtures, an active layer for- tion, the LYR is famous for its hanging bed (i.e., bed elevated mulation (Hirano, 1971; Parker, 2004) is incorporated in the well above the floodplain) and no major tributaries need be flux-based Exner equation so that the evolution of both bed considered in the simulation. elevation and surface grain size distribution can be consid- ered. In this formulation, the riverbed is divided into a well- mixed upper active layer and a lower substrate with vertical 2.1 Flow hydraulics stratigraphic variations. The upper active layer therefore rep- Flow hydraulics in a rectangular channel are described by the resents the volume of sediment that interacts directly with following 1-D Saint–Venant equations, which consider fluid suspended load transport and also exchanges with the sub- mass and momentum conservation, strate as the bed aggrades and degrades. Discretizing the grain size distribution into n ranges, the mass conservation 1 ∂h ∂qw relation for each grain size range can be written as + =0 (1) If ∂t ∂x 1 ∂qw ∂ qw2 1 1 ∂ ∂ ∂qsi + + gh2 = ghS − Cf u2 (2) 1 − λp fI i (zb − La ) + (Fi La ) = − , (5) If ∂t ∂x h 2 If ∂t ∂t ∂x Cf = Cz−2 (3) where qsi is volumetric sediment transport rate per unit width of the ith grain size range (taken to be equal to its equilibrium where t is time, h is water depth, qw is flow discharge per value qsei in the flux formulation), Fi is the volumetric frac- unit width, g is gravitational acceleration, S is bed slope, u tion of surface material in the ith grain size range, fI i is the is depth-averaged flow velocity, Cf is dimensionless bed re- volumetric fraction of material in the ith grain size range ex- sistance coefficient, and Cz is the dimensionless Chézy resis- changed across the surface–substrate interface as the bed ag- tance coefficient. In our model, the fully unsteady 1-D Saint– grades or degrades, and La is the thickness of the active layer. Venant equations are solved using a Godunov-type scheme For bedform-dominated sand-bed rivers, La is often related with the HLL (Harten–Lax–van Leer) approximate Riemann to the height of dunes (Blom, 2008) so that the vertical sort- solver (Harten et al., 1983; Toro, 2001), which can effec- ing processes due to bedform migration can be considered. tively capture discontinuities in unsteady and nonuniform In this paper, a constant value of La is implemented in the open channel flows. simulation. In this paper, the full flood hydrograph of the LYR is re- Summing Eq. (5) over all grain size ranges, one can find placed by a flood intermittency factor If (Paola et al., 1992; that the governing equation for bed elevation in the case of Parker, 2004). According to this definition, the river is as- sediment mixtures is the same as Eq. (4) upon replacing qs sumed to be at low flow and not transporting significant with qsT = 6qsi , where qsT denotes the total sediment trans- amounts of sediment for time fraction 1−If and is in flood at port rate per unit width summed over all size ranges. Reduc- constant discharge and active morphodynamically for time ing Eq. (5) with Eq. (4), we get fraction If . In the long term, the relation between the flood timescale tf and the actual timescale t is tf = If t. With the 1 ∂Fi ∂La ∂qsT ∂qsi consideration that a river is in flood only for a fraction of 1 − λp La + (Fi − fI i ) = fI i − . (6) If ∂t ∂t ∂x ∂x Earth Surf. Dynam., 6, 989–1010, 2018 www.earth-surf-dynam.net/6/989/2018/

C. An et al.: Morphodynamic model of the lower Yellow River 993 Therefore, the flux formulation Eqs. (4) and (6) are imple- For the sediment fall velocity vs , we compare two widely mented as governing equations for sediment mixtures, with used relations: the relation of Dietrich (1982) and the rela- Eq. (4) describing the evolution of bed elevation and Eq. (6) tion of Ferguson and Church (2004). Results show that these describing the evolution of surface grain size distribution. two relations give almost the same fall velocity for the bed The exchange fractions fI i between the active layer and the material load of the LYR, whose grain sizes typically fall in substrate are calculated using the following closure relation. the range of 15 to 500 µm. Therefore, only the relation of Di- etrich (1982) is implemented in our simulations in this paper. ∂ (zb − La ) Readers can refer to Sect. S1 of the Supplement for more fi |zb −La 0 In the entrainment formulation the sediment transport rate ∂t qs is not necessarily in its equilibrium state, but the dimen- That is, the substrate is transferred into the active layer dur- sionless entrainment rate E is taken to be at capacity. The ing degradation, and a mixture of suspended load and active sediment transport rate qs is calculated according to the fol- layer material is transferred into substrate during aggrada- lowing continuity relation. tion. In Eq. (7), fi |zb −La is the volumetric fraction of sub- qs = huC (9) strate material just beneath the interface, psi = qsi /qsT is the fraction of bed material load in the ith grain size range, and α For the dimensionless entrainment rate E, we assume that is a specified parameter between 0 and 1. The formulation is sediment transport reaches its equilibrium state (qs = qse ) adapted from Hoey and Ferguson (1994) and Toro-Escobar et when the sediment deposition rate and the sediment entrain- al. (1996), who originally used it for bed load. In this paper, ment rate balance each other (r0 C = E). Therefore, E can be a value of 0.5 is specified for α. back-calculated from qse as The method of Viparelli et al. (2010) is applied in our qse model to store substrate stratigraphy and provide informa- E = r0 . (10) qw tion for fi |zb −La (i.e., the topmost sublayer in Viparelli et al., 2010). The reader can refer to the original reference of Vipar- For the depth-flux-averaged sediment concentration C, an- elli et al. (2010) for more details or refer to An et al. (2017) other equation is implemented describing the conservation for a concise description of how to implement this method in of suspended sediment in the water column. a morphodynamic model. When solving the flux form of the 1 ∂ (hC) ∂ (huC) Exner equation, a first-order upwind scheme is implemented + = vs (E − r0 C) (11) If ∂t ∂x to discretize the spatial derivatives, and a first-order explicit scheme is implemented to discretize the temporal derivatives. The entrainment-form Exner equation for sediment mixtures also uses the active layer formulation described in Sect. 2.2. Mass conservation of each grain size range can be written as 2.3 Entrainment form of the Exner equation 1 ∂ ∂ The entrainment-based Exner equation for uniform sediment 1 − λp fI i (zb − La ) + (Fi La ) = If ∂t ∂t is − vsi (Ei − r0i Ci , ) (12) 1 ∂zb qsei 1 − λp = −vs (E − r0 C) . (8) Ei = r0i , (13) If ∂t qw In Eq. (8), vs is the fall velocity of sediment particles; E is where the subscript i denotes the ith size range of sediment the dimensionless entrainment rate of sediment normalized grain size. by sediment fall velocity; C is the depth-flux-averaged vol- Summing Eq. (12) over all grain size ranges, we get the ume sediment concentration; and ro = cb /C is the recovery governing equation for bed elevation. coefficient of suspended load, which denotes the ratio be- n tween the near-bed sediment concentration cb and the flux- 1 ∂zb X 1 − λp =− vsj Ej − r0j Cj (14) averaged sediment concentration C. By definition, r0 is re- If ∂t j =1 lated to the concentration profile of suspended load and is expected to be no less than unity in cases appropriate for a Reducing Eq. (12) with Eq. (14) we get the governing equa- depth-averaged shallow-water treatment of flow and morpho- tion for surface fraction Fi . dynamics. Therefore, the first term on the right-hand side of 1 ∂Fi ∂La Eq. (8), i.e., vs · E, denotes the sediment entrainment rate per 1 − λp La + (Fi − fI i ) If ∂t ∂t unit area; the second term on the right-hand side of Eq. (8), n X i.e., vs · r0 · C, denotes the sediment deposition rate per unit = fI i vsj Ej − r0j Cj − vsi (Ei − r0i Ci ) (15) area. j =1 www.earth-surf-dynam.net/6/989/2018/ Earth Surf. Dynam., 6, 989–1010, 2018

994 C. An et al.: Morphodynamic model of the lower Yellow River The governing equation for the sediment concentration of imply that the riverbed of the LYR is dominated by low- each grain size Ci can be written as amplitude bedform features (dunes) approaching the upper- regime plane bed. According to this finding, form drag is then 1 ∂ (hCi ) ∂ (huCi ) neglected in our modeling, and all of the bed shear stress is + = vsi (Ei − r0 Ci ) , (16) If ∂t ∂x used for sediment transport. and the sediment transport rate per unit width for the ith size range qsi obeys the following continuity relation: 2.4.2 Sediment mixtures qsi = huCi . (17) We implement the relation of Naito et al. (2018) to calcu- late the equilibrium sediment transport rate of size mixtures. In the entrainment formulation, the closure relation for fI i Using field data from the LYR, Naito et al. (2018) extended is the same as that used in the flux formulation (i.e., Eq. 7), the Engelund and Hansen (1967) relation to a surface-based and the substrate stratigraphy is also stored and accessed us- grain-size-specific form, in which the suspended load trans- ing the method of Viparelli et al. (2010). When discretizing port rate of the ith size range is tied to the availability of this the entrainment form of the Exner equation, a first-order up- size range on the bed surface: wind scheme is implemented for the spatial derivatives, and Ni∗ Fi u3∗ a first-order explicit scheme is implemented for the temporal qsei = , (22) derivatives. RgCf where Ni∗ is the dimensionless sediment transport rate in the 2.4 Sediment transport relation ith size range, and u∗ is shear velocity calculated from the 2.4.1 Uniform sediment bed shear stress τb . r To close the Exner equations described in Sect. 2.2 and 2.3, τb u∗ = (23) equations for equilibrium sediment transport rate qse (qsei ) ρ are still needed. For the simulations using uniform sedi- ment, we implement the generalized Engelund–Hansen re- The transport relation itself takes the form lation proposed by Ma et al. (2017). This equation is based Dsg Bi on data from the LYR and can be written in the following Ni∗ = Ai τg∗ , (24) dimensionless form: Di αs ∗ ns in which Di is the characteristic grain size for sediment in qs∗ = τ , (18) Cf the ith size range, Dsg is the geometric mean grain size in the active layer, and τg∗ is the dimensionless bed shear stress where qs∗ is the dimensionless sediment transport rate per associated with Dsg . The parameters τg∗ , coefficient Ai , and unit width (i.e., the Einstein number), and τ ∗ is dimension- exponent Bi are calculated as follows. less shear stress (i.e., the Shields number). They are defined τb as τg∗ = (25) ρRgDsg qse qs∗ = √ , (19) Di −0.84 RgDD Ai = 0.46 (26) τb Dsg τ∗ = , (20) ρRgD Di −1.16 Bi = 0.35 (27) τb = ρCf u2 , (21) Dsg where D is the characteristic grain size of the bed sediment If Ai and Bi are specified as constant values in Eq. (24), then (here approximated as uniform); τb is bed shear stress; and the sediment transport rate for each size range depends only R is the submerged specific gravity of sediment defined as on the flow shear stress and the characteristic grain size of (ρs −ρ)/ρ, in which ρs is the density of sediment, and ρ is the this size range, without being affected by other size ranges. density of water. The sediment submerged specific gravity But according to Eqs. (26) and (27), the coarser the sediment R is specified as 1.65 in this paper, which is an appropriate the smaller the values of Ai and Bi will be, thus leading to estimate for natural rivers and corresponds to quartz. reduced mobility for coarse sediment (and increased mobility In the relation of Ma et al. (2017), the dimensionless coef- for fine sediment) due to the presence of grains of other sizes. ficient αs = 0.9 and the dimensionless exponent ns = 1.68. Thus the relations in Eqs. (26) and (27) serve as a hiding These values are quite different from the original relation function that allows for grain sorting. of Engelund and Hansen (1967), in which αs = 0.05 and We note that a form of the Engelund–Hansen equation for ns = 2.5. Ma et al. (2017) demonstrated that such differences mixtures was introduced by Van der Scheer et al. (2002) and Earth Surf. Dynam., 6, 989–1010, 2018 www.earth-surf-dynam.net/6/989/2018/

C. An et al.: Morphodynamic model of the lower Yellow River 995 implemented by Blom et al. (2016). Blom et al. (2017) fur- metric standard deviation σg = 2.0, as shown in Fig. 1c. In ther extended this relation to a more general framework capa- the second case, we consider the effects of sediment mix- ble of including hiding effects. These forms, however, have tures. The grain size distribution of the initial bed is based not been calibrated to the LYR data and are thus not suitable on the bed material at the Lijin gauging station, as shown in for the LYR. Fig. 1c, but we renormalize the measured grain size distribu- tion with a cutoff for wash load at 15 µm as suggested by Ma et al. (2017). The renormalized grain size distribution for the 3 Numerical modeling of the LYR using the two initial bed as implemented in the case of sediment mixtures forms of the Exner equation is shown in Fig. 2, with a total number of grain size fractions of 5. In both cases, simulations start with an equilibrium state In this section, we conduct numerical simulations using both in which sediment supply rate, sediment transport rate, and the flux form and the entrainment form of the Exner equa- equilibrium sediment transport rate are the same so that the tion, with the aim of studying under what circumstances initial state of the channel is in equilibrium. Then we cut the the two forms give different predictions. Numerical simula- sediment supply rate (of each size range) to only 10 % of the tions are conducted in the setting of the LYR. We specify a equilibrium sediment transport rate and keep this sediment 200 km long channel reach for our simulations, along with a supply rate. This is to mimic the reduction of sediment load constant channel width of 300 m and an initial longitudinal in the LYR in recent years, as shown in Fig. 1b. The grain slope of 0.0001. Bed porosity λp is specified as 0.4. Based size distribution of sediment supply in the case of sediment on field measurements of the LYR available to us, we imple- mixtures is shown in Fig. 2. mented a dimensionless Chézy resistance coefficient Cz of The 200 km channel reach is discretized into 401 cells, 30, which corresponds to a dimensionless bed resistance co- with cell size 1x of 500 m. In the case of uniform sediment, efficient Cf of 0.0011. For the entrainment form of the Exner we specify a time step for morphologic calculation 1tm = equation, we specify the ratio of near-bed sediment concen- 10−4 years and a time step for hydraulic calculation 1th = tration to flux-averaged sediment concentration r0 (r0i ) = 1. 10−6 years. In the case of sediment mixtures, we specify a Such a value of r0 (r0i ) corresponds to a vertically uniform time step for morphologic calculation 1tm = 10−5 years and profile of sediment concentration and will thus give a max- a time step for hydraulic calculation 1th = 10−6 years. Com- imum difference between the prediction of the entrainment putational conditions are briefly summarized in Table 1. The form and the prediction of the flux form. More discussion computational conditions we implement are much simpler about the effects of r0 is presented in Sect. 4.3. than the rather complicated conditions of the actual LYR. But A constant flow discharge of 2000 m3 s−1 (corresponding it should be noted that the aim of this paper is not to repro- to a flow discharge per unit width qw of 6.67 m2 s−1 ) is in- duce specific aspects of the morphodynamic processes of the troduced at the inlet of the channel with the flood intermit- LYR, but to compare the flux form and entrainment form of tency factor If estimated as 0.14 (Naito et al., 2018). The the Exner equation in the context of conditions typical of the downstream end is specified far from the river mouth to ne- LYR. glect the effects of backwater. Therefore, the bed elevation is held constant and the water depth is specified as the normal 3.1 Case of uniform sediment flow depth at the downstream end of the calculational do- main. The above flow discharge per unit width qw combined In this case, we implement a uniform grain size of 65 µm for with the bed slope S as well as the bed resistance coefficient both the bed material and sediment supply. Such a grain size Cf leads to a normal flow depth of 3.69 m. In our simulation, is nearly equal to the observed median grain size (or geo- we use the height of bedforms in the LYR to determine the metric mean grain size) of bed material at the Lijin gauging thickness of the active layer (Blom, 2008). According to the station. The relation of Ma et al. (2017) is implemented to field survey of Ma et al. (2017), the characteristic height of calculate the transport rate of bed material suspended load. bedforms in the LYR is about 20 % of the normal flow depth, This relation provides an equilibrium sediment transport rate which can fall in the range suggested by the data analysis of per unit width qse of 0.0136 m2 s−1 under the given flow dis- Bradley and Venditti (2017). This eventually leads to an esti- charge, bed slope, and sediment grain size. With a flood in- mate of active layer thickness of La = 0.738 m. The sublayer termittency factor If of 0.14, this further gives a mean annual in the substrate to store the vertical stratigraphy is specified bed material load of 47.8 Mt a−1 . Adding in wash load ac- with a thickness of 0.5 m. cording to the estimate of Naito et al. (2018), the total mean Two cases are considered here. In the first case, the sed- annual load is 86.9 Mt a−1 , a value that is of the same order iment grain size distribution of the LYR is simplified to a of magnitude as averages over the period 2000–2016 (89– uniform grain size of 65 µm. This is based on the measured 126 Mt a−1 depending on the site), i.e., since the operation of grain size distribution of bed material at the Lijin gauging the Xiaolangdi Dam beginning in 1999 (Fig. 1b). The sedi- station, which has a median grain size of D50 = 66.6 µm, ment supply rate qsf we specify at the upstream end of the a geometric mean grain size of Dg = 65.5 µm, and a geo- channel is only 10 % of the equilibrium sediment transport www.earth-surf-dynam.net/6/989/2018/ Earth Surf. Dynam., 6, 989–1010, 2018

996 C. An et al.: Morphodynamic model of the lower Yellow River Table 1. Summary of computational conditions for numerical modeling of the LYR. Parameter Value Channel length L 200 km Channel width B 300 m Initial slope SI 0.0001 Dimensionless Chézy resistance coefficient Cz 30 Flow discharge per unit width qw 6.67 m2 s−1 Flood intermittency factor If 0.14 Ratio of near-bed concentration to average concentration r0 (r0i ) 1 Characteristic grain size in the case of uniform sediment 65 µm Submerged specific gravity of sediment R 1.65 Porosity of bed deposits λp 0.4 Cell size 1x 500 m Time step for morphologic calculation 1tm 10−4 years (uniform sediment) 10−5 years (sediment mixtures) Time step for hydraulic calculation 1th 10−6 years entrainment form predicts a 2.3 m degradation) and a more diffusive sediment load reduction. Such more diffusive pre- dictions of sediment load variation can be ascribed to the condition of nonequilibrium transport that is embedded in the entrainment form. This issue will be studied analytically in Sect. 4. Here we present the results for only 0.2 years after the cutoff of sediment supply, since the differences between the predictions of the two forms tend to be the most evident shortly after the disruption but gradually diminish as the river approaches the new equilibrium (El kadi Abderrezzak and Paquier, 2009). Modeling results over a longer timescale will be discussed in Sect. 4.3. To further quantify the differences between the predictions of the two forms, we propose the following normalized pa- rameter: Figure 2. Grain size distributions of both the initial bed and the sed- iment supply in the case of sediment mixtures. For the initial bed, yE − yF δ (y) = × 100%, (28) the surface and substrate grain size distributions are the same. The yF grain size distribution of the initial bed is renormalized based on the field data at the Lijin gauging station. The grain size distribution of where y denotes an arbitrary variable calculated by the mor- the sediment supply equals the grain size distribution of bed mate- phodynamic model, and subscripts F and E denote results rial load at equilibrium. Grain sizes in the range of wash load have using the flux form and the entrainment form, respectively. been removed from both distributions. Therefore, δ (y) denotes the difference between the predic- tion of the two forms yF and yE normalized by the prediction of the flux form yF . rate (i.e., the sediment supply rate is cut by 90 % from the Table 2 gives a summary of the maximum values of δ equilibrium state) such that qsf = 0.00136 m2 s−1 . along the channel at different times in the case of uniform Figure 3 shows the modeling results using the flux form of sediment. The values of δ for both zb and qs are presented. the Exner equation. As we can see in the figure, the bed de- As we can see from the table, the maximum value of δ(zb ) grades and the sediment load decreases in response to the cut- along the calculational domain stays within 4 % in the first off of sediment supply. Such adjustments start from the up- 0.2 years after the cutoff of sediment supply. This indicates stream end of the channel and gradually migrate downstream. that the flux form and the entrainment form can indeed give Figure 4 shows the modeling results using the entrainment almost the same prediction in terms of bed elevation in this form of the Exner equation. A comparison between Figs. 4 case. But in the case of the sediment load per unit width qs , and 3 shows that the entrainment form and the flux form give the maximum value of δ(qs ) can be as high as 20 %, indicat- very similar predictions in this case. The entrainment form ing that even though the two forms give qualitatively similar provides a somewhat slower degradation (at the upstream patterns of evolution in terms of sediment load as shown in end the flux form predicts a 3 m degradation, whereas the Figs. 3 and 4, a quantitative difference is clearly evident due Earth Surf. Dynam., 6, 989–1010, 2018 www.earth-surf-dynam.net/6/989/2018/

C. An et al.: Morphodynamic model of the lower Yellow River 997 Figure 3. The 0.2-year results for the case of uniform sediment Figure 4. The 0.2-year results for the case of uniform sediment using the flux form of the Exner equation: time variation of (a) bed using the entrainment form of the Exner equation: time variation elevation zb and water surface (WS), (b) sediment load per unit of (a) bed elevation zb and water surface (WS), (b) sediment load width qs of the LYR in response to the cutoff of sediment supply. per unit width qs of the LYR in response to the cutoff of sediment The inset shows detailed results near the upstream end. supply. The inset shows detailed results near the upstream end. to the more diffusive nature of the predictions of the entrain- grain size. With a much smaller, and indeed intentionally un- ment form. The value of δ(qs ) is largest at the beginning of realistic, sediment fall velocity the entrainment form predicts the simulation and is then gradually reduced with time. It very different results as shown in Fig. 5. The adjustment of should be noted that the values of δ(zb ) depend on the choice the sediment load becomes even more diffusive in space: it of elevation datum. In this paper bed elevation at the down- takes almost the entire 200 km reach for the sediment load to stream end is fixed as 0 m, which serves as the elevation da- adjust from the upstream disruption to the equilibrium trans- tum. In the simulation of this paper, the maximum value of port rate. Meanwhile, there is barely any bed degradation at δ(zb ) almost always occurs at the upstream end where bed the upstream end after 0.2 years, in correspondence with the elevation does not deviate far from the initial value of 20 m. fact that the spatial gradient of qs becomes quite small. In Ta- The above results show that the flux form and the entrain- ble 2 we also exhibit the δ values for this idealized run. It is ment form can provide similar predictions of the LYR when no surprise that both δ(zb ) and δ(qs ) are high, as the entrain- the bed sediment grain size distribution is simplified to a uni- ment form and flux form predict very different patterns with form value of 65 µm. To understand under what conditions such an arbitrarily reduced sediment fall velocity. the two forms will lead to more different results, we conduct In Sect. S2, we also conduct numerical simulations with an idealized run using the entrainment form in which the sed- hydrographs. Results indicate that our conclusions based on iment fall velocity vs is arbitrarily multiplied by a factor of constant flow discharge also hold when hydrographs are con- 0.05. That is to say, we keep the sediment grain size at 65 µm sidered: the flux form and the entrainment form (with the sed- in the computation of the Shields number, but let the sedi- iment fall velocity not adjusted) of the Exner equation give ment fall velocity in Eqs. (8) and (10) equal only 1/20 of the very similar predictions using a characteristic grain size of value calculated by the relation of Dietrich (1982) from this 65 µm. www.earth-surf-dynam.net/6/989/2018/ Earth Surf. Dynam., 6, 989–1010, 2018

998 C. An et al.: Morphodynamic model of the lower Yellow River Table 2. Quantification of the difference between predictions of the flux form and the entrainment form in the case of uniform sediment. The maximum values of δ(zb ) and δ(qs ) in the calculational domain are presented every 0.04 years. 0.04 years 0.08 years 0.12 years 0.16 years 0.20 years Original vs δ(zb ) 3.7 % 3.9 % 3.9 % 3.9 % 3.8 % δ(qs ) 20.5 % 15.1 % 12.3 % 10.5 % 9.2 % vs multiplied by 0.05 δ(zb ) 8.2 % 10.9 % 12.7 % 13.9 % 14.9 % δ(qs ) 74.8 % 68.1 % 63.0 % 58.9 % 55.4 % Naito et al. (2018) for mixtures, such a grain size distribu- tion combined with the given bed slope and flow discharge leads to a total equilibrium sediment transport rate per unit width qseT of 0.0272 m2 s−1 . With a flood intermittency fac- tor If of 0.14, this further gives a mean annual bed material load of 95.5 Mt a−1 . Adding in wash load according to the estimate of Naito et al. (2018), the total mean annual load is 173.7 Mt a−1 , a value that is of the same order of magni- tude as averages over the period 2000–2016 (89–126 Mt a−1 depending on the site), i.e., since the operation of the Xi- aolangdi Dam beginning in 1999 (Fig. 1b). The sediment supply rate of each grain size range is set at 10 % of its equi- librium sediment transport rate. This results in a total sed- iment supply rate of qsf = 0.00272 m2 s−1 and a grain size distribution of the sediment supply (shown in Fig. 2) that is identical to the grain size distribution of the equilibrium sediment load before the cutoff. That is, the grain size dis- tribution of sediment supply does not change; only the total sediment supply is reduced by 90 %. Again we exhibit sim- ulation results for only 0.2 years here, a value that is enough to show the differences between the two forms, flux and en- trainment, as applied to mixtures. Modeling results over a longer timescale are presented in Sect. 4.3. Figure 6 shows the simulation results using the flux form of the Exner equation. As a result of the reduced sediment supply at the inlet, bed degradation occurs first at the up- stream end and then gradually migrates downstream. The total sediment transport rate per unit width qsT is also re- Figure 5. The 0.2-year results for the case of uniform sediment duced as a response to the cutoff of sediment supply. More using the entrainment form of the Exner equation: time variation specifically, the evolution of qsT shows marked evidence of (a) bed elevation zb and water surface (WS), (b) sediment load of advection, with at least two kinematic waves being ob- per unit width qs of the LYR in response to the cutoff of sediment served within 0.2 years. Actually, as illustrated by Stecca supply. Sediment fall velocity vs is arbitrarily multiplied by a factor et al. (2014, 2016), each grain size fraction should induce of 0.05 while holding bed grain size constant in this run. The inset a migrating wave. As shown in Fig. 6b, the fastest kinematic shows detailed results near the upstream end. wave migrates beyond the 200 km reach within 0.06 years, and the second fastest kinematic wave migrates for a distance of about 60 km in 0.2 years. Figure 6c and d show the results 3.2 Case of sediment mixtures for the surface geometric mean grain size Dsg and geomet- ric mean grain size of suspended load Dlg , respectively. As In this section we consider the morphodynamics of sediment can be seen therein, both the bed surface and the suspended mixtures rather than the case of a uniform bed grain size im- load coarsen as a result of the cutoff of sediment supply. plemented in Sect. 3.1. The grain size distribution of the ini- This represents armoring mediated by the hiding functions tial bed is based on field data at the Lijin gauging station and of Eqs. (26) and (27). Such coarsening is not evident near is shown in Fig. 2. Using the sediment transport relation of the upstream end, possibly due to the inverse slope visible in Earth Surf. Dynam., 6, 989–1010, 2018 www.earth-surf-dynam.net/6/989/2018/

C. An et al.: Morphodynamic model of the lower Yellow River 999 Fig. 6a. Similarly to the variation of qsT , the patterns of time the channel, where the entrainment form predicts some slight variation of both Dsg and Dlg also exhibit very clear kine- degradation. Also, δ(qsT ) is quite large at t = 0.01 years and matic waves, with migration rates about the same as those of 0.03 years, even though the results for the case of increased qsT . fall velocities become qualitatively more similar to the pre- Figure 7 shows the simulation results obtained using the diction of the flux form. This is because the flux form and entrainment form of the Exner equation. In general, the pat- the entrainment form with arbitrarily increased sediment fall terns of variation predicted by the entrainment form have velocities predict different celerities for the fastest kinematic similar trends and magnitudes to those predicted by the flux wave. The error δ(qsT ) becomes smaller from t = 0.06 years form: the bed degrades near the upstream end, the suspended as the fastest kinematic wave migrates beyond the channel load transport rate is reduced in time, and both the bed sur- reach. The error δ(Dlg ) behaves similarly to δ(qsT ), with face and the suspended load coarsen as a result of the cutoff δ(Dlg ) being quite large at t = 0.01 years and 0.03 years near of sediment supply. But the results based on the two forms the fastest kinematic wave, but gradually becoming smaller exhibit very evident differences when multiple grain sizes as time passes. The error δ(Dsg ) stays low within the whole are included. That is, the results predicted by the entrain- 0.2-year period, possibly because the fastest kinematic wave ment form are sufficiently diffusive so that the variations of of Dsg has a small magnitude, as shown in Fig. 8c. qsT , Dsg , and Dlg (Fig. 7b, c, and d) do not show the advec- In Sect. S3, we present additional numerical cases that are tive character seen in Fig. 6. Figure 7c, however, shows the similar to the cases in this section, except that hydrographs same armoring as in the case of calculations with the flux are implemented instead of constant discharge. Results indi- form. No clear kinematic waves can be observed in Fig. 7. cate that our conclusions based on constant flow discharge Table 3 gives a summary of the values of δ in the case of also hold when hydrographs are considered. The flux form sediment mixtures. The prediction of bed elevation is not af- and the entrainment form (with the sediment fall velocity not fected much when multiple grain sizes are considered, with adjusted) of the Exner equation predict quite different pat- δ(zb ) being no more than 3.5 % within 0.2 years. The δ val- terns of grain sorting, with the flux form exhibiting a more ues of qsT , Dsg , and Dlg are, however, relatively large since advective character than the entrainment form. the two forms predict quite different patterns of variations, as shown in Figs. 6 and 7. 4 Discussion The results shown in Fig. 8 have also been calculated using the entrainment form of the Exner equation, but here the sed- 4.1 Adjustment of sediment load and the adaptation iment fall velocities vsi used in Eqs. (14)–(16) are arbitrarily length multiplied by a factor of 20. That is, we still apply the grain size distribution in Fig. 2, but the sediment fall velocities im- In Sect. 3.1, our simulation shows that in the case of uni- plemented in the simulation are 20 times the corresponding form sediment, the flux form and the entrainment form of fall velocities calculated by the relation of Dietrich (1982). In the Exner equation give very similar predictions for a given the case of uniform sediment in Sect. 3.1, we arbitrarily re- sediment size of 65 µm. However, if we arbitrarily reduce the duce the sediment fall velocity to force a difference between sediment fall velocity by a multiplicative factor of 0.05, the the predictions from the entrainment form and those from prediction given by the entrainment form will become much the flux form. Here we arbitrarily increase the sediment fall more diffusive in terms of both zb and qs . The diffusive na- velocity with the aim of determining under what conditions ture of the entrainment form and the important role played the sorting patterns predicted by the two forms converge. As by the sediment fall velocity can be explained in terms of the we can see in Fig. 8, with such a larger and intentionally governing equation. unrealistic sediment fall velocity, the general trend of varia- In the entrainment form, the equation governing sus- tions predicted by the entrainment form does not change, but pended sediment concentration is the results show a notably less diffusive pattern. The varia- 1 ∂ (hC) ∂ (huC) tions of qsT , Dsg , and Dlg show more advection compared + = vs (E − r0 C) , (29) If ∂t ∂x with Fig. 7, and at least two kinematic waves appear within 0.2 years. It should be noted that even though these kinematic i.e., the same as Eq. (11). The sediment transport rate per waves appear after we arbitrarily increase the sediment fall unit width qs = huC = qw C, and the dimensionless entrain- velocity, they are more diffusive than those obtained from ment rate E = r0 qse /qw . In order to simplify the mathemat- the flux formulation and also migrate with a slower celerity ical analysis, here we consider only the adjustment of sedi- compared with those predicted by the flux form, especially ment concentration in space and neglect the temporal deriva- for the fastest kinematic wave in the modeling results. tive in Eq. (29) so that we get Table 3 summarizes the δ values for this run. The values of ∂qs 1 δ(zb ) become smaller with arbitrarily increased sediment fall = vs (E − r0 C) = (qse − qs ) , (30) ∂x Lad velocities except for t = 0.06 years. A relatively large value qw of δ(zb ) at t = 0.06 years occurs near the downstream end of Lad = , (31) vs r0 www.earth-surf-dynam.net/6/989/2018/ Earth Surf. Dynam., 6, 989–1010, 2018

1000 C. An et al.: Morphodynamic model of the lower Yellow River Figure 6. The 0.2-year results for the case of sediment mixtures using the flux form of the Exner equation: time variation of (a) bed elevation zb and water surface (WS), (b) total sediment load qsT , (c) surface geometric mean grain size Dsg , and (d) geometric mean grain size of sediment load of the LYR in response to the cutoff of sediment supply. The inset shows detailed results near the upstream end. Table 3. Quantification of the difference between predictions of the flux form and the entrainment form in the case of sediment mixtures. The maximum values of δ in the calculational domain are presented at different times. 0.01 years 0.03 years 0.06 years 0.12 years 0.20 years Original vs δ(zb ) 2.3 % 3.2 % 3.4 % 3.4 % 3.2 % δ(qsT ) 54.7 % 76.1 % 41.1 % 10.5 % 11.8 % δ(Dsg ) 10.1 % 8.6 % 7.2 % 6.0 % 5.4 % δ(Dlg ) 27.1 % 31.9 % 23.7 % 7.2 % 7.7 % vs multiplied by 20 δ(zb ) 0.3 % 0.4 % 3.8 % 0.3 % 0.2 % δ(qsT ) 81.1 % 82.3 % 39.7 % 7.2 % 9.3 % δ(Dsg ) 2.8 % 2.8 % 2.0 % 2.7 % 3.4 % δ(Dlg ) 32.8 % 33.1 % 25.1 % 4.8 % 6.0 % where Lad can be identified as the adaptation length for boundary condition suspended sediment to reach equilibrium. This definition of adaptation length is similar to those in Wu and Wang (2008) qs |x=0 = qsf , (32) and Ganti et al. (2014). If we consider the spatial adjustment of sediment load Eq. (30) can be solved to yield shortly after the cutoff of sediment supply, we can further ne- − Lx glect the nonuniformity of the capacity (equilibrium) trans- qs = qse + (qsf − qse ) e ad . (33) port rate qse along the channel, and Eq. (30) can be solved Here qsf is the sediment supply rate per unit width at the up- with a given upstream boundary condition. That is, with the stream end. According to Eq. (33), qs adjusts exponentially in space from qsf to qse , which also coincides with our simu- Earth Surf. Dynam., 6, 989–1010, 2018 www.earth-surf-dynam.net/6/989/2018/

C. An et al.: Morphodynamic model of the lower Yellow River 1001 Figure 7. The 0.2-year results for the case of sediment mixtures using the entrainment form of the Exner equation: time variation of (a) bed elevation zb and water surface (WS), (b) total sediment load qsT , (c) surface geometric mean grain size Dsg , and (d) geometric mean grain size of sediment load of the LYR in response to the cutoff of sediment supply. The inset shows detailed results near the upstream end. lation results in Sect. 3.1, as shown in Figs. 3–6. The adapta- form and the entrainment form show little difference when tion length Lad is the key parameter that controls the distance Lad /L 1, where L is domain length. However, if we arbi- for qs to approach the equilibrium sediment transport rate qse . trarily multiply the sediment fall velocity by a factor of 0.05, More specifically, qs attains 1 − 1/e (i.e., 63.2 %) of its ad- then Lad becomes 37.60 km. With such a large adaptation justment from qsf to qse over a distance Lad . Therefore, the length, it is no surprise that the entrainment form gives very larger the adaptation length, the slower qs adjusts in space so different predictions from the flux form. that the more evident lag effects and diffusivity are exhibited The evolution of bed elevation zb can also be affected by in the entrainment form. In the flux form, however, the sedi- the value of Lad . For example, in the case of uniform sed- ment load responds simultaneously with the flow conditions iment in Sect. 3.1, the flux form corresponds to an adap- so that Lad = 0 and qs = qse along the entire channel reach. tion length of zero. As a result, the flux form yields a spatial For the case of uniform sediment in Sect. 3.1, qw = derivative of qs near the upstream end that is relatively large, 6.67 m2 s−1 and ro is specified as unity. Therefore, the value thus leading to fast degradation from the upstream end. In of Lad is determined only by the sediment fall velocity vs . the case of the entrainment form, however, the spatial deriva- Figure 9 shows the value of the adaptation length Lad for tive of qs is small with a large Lad , thus leading to a slower various sediment grain sizes, with the sediment fall veloc- and more diffusive bed degradation. This is especially evi- ity vs calculated by the relation of Dietrich (1982). From the dent when we arbitrarily reduce the sediment fall velocity by figure we can see that Lad decreases sharply with the in- a factor of 0.05 while keeping grain size invariant. crease in grain size, indicating that the lag effects between The above analysis also holds for sediment mixtures, ex- sediment transport and flow conditions are evident for very cept that each grain size range will have its own adaptation fine sediment but gradually disappear when sediment is suf- length. Here we neglect the temporal derivative in Eq. (29) ficiently coarse. For the sediment grain size of 65 µm imple- and analyze only the spatial adjustment of sediment load. If mented in Sect. 3.1, the corresponding Lad = 1.88 km, which we neglect the spatial derivative in Eq. (29) and conduct a is much smaller than the 200 km reach of the computational similar analysis for sediment concentration, we would find domain. In this case and in general, the predictions of the flux that the temporal adjustment of sediment concentration is www.earth-surf-dynam.net/6/989/2018/ Earth Surf. Dynam., 6, 989–1010, 2018

1002 C. An et al.: Morphodynamic model of the lower Yellow River Figure 8. The 0.2-year results for the case of sediment mixtures using the entrainment form of the Exner equation: time variation of (a) bed elevation zb and water surface (WS), (b) total sediment load qsT , (c) surface geometric mean grain size Dsg , and (d) geometric mean grain size of sediment load of the LYR in response to the cutoff of sediment supply. Sediment fall velocities vsi are arbitrarily multiplied by a factor of 20 in this run while keeping the grain sizes invariant. The inset shows detailed results near the upstream end. also described by an exponential function of time, in anal- Substituting Eq. (34) into Eq. (6), which is the governing ogy to Eq. (33). equation for surface fraction Fi in the flux form, we get 1 ∂Fi ∂La 1 − λp La + (Fi − fI i ) = If ∂t ∂t 4.2 Patterns of grain sorting: advection vs. diffusion Pn ∂ Fj qrj In Sect. 3.2 we find that the flux form and entrainment form j =1 ∂Fi qri fI i − . (36) of the Exner equation provide very different patterns of grain ∂x ∂x sorting for sediment mixtures: kinematic sorting waves are evident in the flux form but are diffused out in the entrain- Equation (36) can be written in the form of a kinematic wave ment form. The diffusivity of grain sorting becomes smaller equation with source terms as follows. and the kinematic waves appear, however, if we arbitrarily increase the sediment fall velocity by a factor of 20. In this ∂Fi ∂Fi + cFi = SFi (37) section, we explain this behavior by analyzing the governing ∂t ∂x equations. If qri cFi = (1 − fI i ) (38) First we rewrite the sediment transport relation of Naito et 1 − λp L a al. (2018) in the following form. n,j P6=i ∂ Fj qrj If Fi (1 − fI i ) ∂qri If fI i j =1 qsei = Fi qri (34) SFi = − + 1 − λp La ∂x 1 − λp La ∂x Bi u3∗ Dg Fi − fI i ∂La qri = Ai τg∗ (35) − (39) RgCf Di 1 − λp ∂t Earth Surf. Dynam., 6, 989–1010, 2018 www.earth-surf-dynam.net/6/989/2018/

You can also read