DVR toolbox for sediment management in the Rhine delta

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2 DVR toolbox for sediment management in the Rhine delta 1 DVR toolbox for sediment management in the Rhine delta Kees (C.J.) Sloff Abstract The DVR Toolbox is a modeling system developed to be used as an operational model for long-term morphological assessment of the Rhine branches in the Netherlands (10 to 50 years). The Toolbox consists of a 2D computational core (containing the Delft3D modeling system), a shell that controls input- and output, and a system for time/simulation management. The effects of different processes, e.g. helical flow and sediment sorting, on time-dependent bed topography and dredging-operations can be simulated. It has been designed and optimized to allow for relative short computation times: 40 year simulations for the full delta can be run in less than 1 week. The Toolbox is mostly used to calculate morphological impacts that affect the navigability of the Rhine, and the impact of measures to affect them. It is now also widely used as an official tool to study the impacts of flood-lowering measures in the Room for the River program. Also for future studies in the Rhine River this Toolbox will be widely used. 1 Introduction 1.1 DVR project for the Rhine delta The DVR Toolbox is a modeling system created for long-term morphological assessment of the Rhine branches in the Netherlands. It is developed for the project Duurzame Vaardiepte Rijndelta (DVR) (Sustainable Navigation Channel Rhine delta). The aim of the DVR project is to manage the recently enlarged navigation channel, stopping autonomic bed degradation, and compensating for impacts of climate change (Smedes, 2005). This project required a set of tools to analyze the morphological development of the river bed, and the impact of combined measures and sediment strategies. As the DVR Toolbox is presently set-up for the Rhine branches, it can also be called the Rhine-Branches DVR instrument. DVR is a consequence of increasing worries on the navigability of the Rhine on the long term. Because the Rhine River can be considered as one of the major transport routes between the North-Sea and Germany, it is necessary to maintain safe and optimal conditions for intensive and fast navigation. Due to natural and anthropogenic influences the morphology of the river-bed is continuously changing. The river-bed in the Dutch Rhine branches is not only gradually degrading, but also shows all kinds of fluctuations that may cause hindrance to navigation: such as bed forms, flood deposits,

3 2 K. (C. J.) Sloff points bars, groyne flames, and so on. To anticipate and react on these bottlenecks, presently a maintenance strategy is applied in which a combination of sediment management (dredging and dumping) and structural solutions (river-training) are applied. For the Dutch Rhine this maintenance is the responsibility of Rijkswaterstaat, part of the Dutch Ministry of Transport, Public Works and Water Management. Fig. 1: Map of the Netherlands, showing the reaches or main Rhine branches in the Rhine delta for which the DVR-Toolbox was set-up After an increase of committed fairway dimensions in the past 10 years, changes in the type of dredging-contracts and increased morphological variability due to floodplainrestoration projects (Room for the River program), Rijkwaterstaat has been facing important changes in fairway maintenance. The project DVR descends from the need to preparing more sustainable approaches for maintenance of the Rhine branches on the long-term, and aims for the definition of a combination of constructive meaures (river training), and sediment management (dredging and dumping, sediment feeding). It is

4 DVR toolbox for sediment management in the Rhine delta 3 required that these measures match the management and use of the river upstream (German Niederrhein) and downstream (Merwedes). Furthermore, these measures should connect to other programs and developments in the river, such as the programs Room for the River and implementation of the Framework Directive. DVR should guarantee, in addition to other infrastructural measures, that the Rhine and Waal rivers will remain the most important transport artery in Western Europe. In this paper we present the DVR Toolbox for morphological modeling that has been developed for the DVR project. It has been designed and optimized by Deltares such that long-term (>40 year) 2D (quasi-3d) simulation for the entire river reach (380 km) could be carried out in a computation time of about one week (single-core processor). Presently (2010) the DVR toolbox is widely used in operational practice of the Dutch engineering community for assessment of morphological developments in the river. It is not only applied in the development of sediment strategies for DVR, but is also officially used for optimal design of Room for the River measures, and testing their morphological impacts. In the following sections is shown which morphological features are considered, how the toolbox has been set-up, what approaches have been used to maximize computation speed, and how specific physical processes and measures are simulated. 1.2 Morphology, navigability and sediment management Both large-scale morphological development, i.e. autonomic erosion of all the upper reaches, and small-scale morphological developments (scales smaller than several kilometers), e.g. sand bars, determine the management strategies in the Dutch Rhine branches. In previous programs a part of the problematic morphological developments have been counteracted by using structural measures and river training works (such as fixed layers, groynes). Presently the river-channel is mainly managed by dredging and dumping strategies, in which dredging contractors are commissioned to maintain the fairway according to the agreed fairway dimensions and some specific rules for dumping. The contractors are paid (or fined) according to their performance. In the Rhine River in the Netherlands the navigation channel is maintained with a minimum depth of 2.80 m at the agreed low-flow level OLR (cf. GLW in Germany), and a minimum width of 150 m. Dredging operations become particularly important if minimum measured water-depths drop below certain values (such that ships cannot be fully loaded), which is also reflected in the rules for dredging operations. To prevent a further stengthening of the large-scale degradation in the Rhine branches, the dredged sediment has to be dumped in deeper areas in the vicinity of the dredging location.

5 4 K. (C. J.) Sloff Fairway width (150 m) OLR Depth 2.80 m Fig. 2: Agreed fairway dimensions in the Boven-Rijn and Waal, relative to low flow level OLR In the Rhine branches most of the bottlenecks for navigation are local spatially varying morphological features following from: Development of point bars in river bends (shallow inner bends, deep outer bends), caused by 3D curved-flow processes (helical flow and slope effects). An example is shown in figure 3. Shallow bars flaring out of the groyne fields into the fairway, also called groyne flames. These features are caused by contraction of flow and local scour at the groyne heads, followed by expansion of the flow in the groyne field. An example is shown in figure 3. Dunes (bed forms) propagating downstream with lengths of roughly 50 m, with heights of roughly 0,5 to 1 m. The highest dunes develop during high water levels, but after water levels drop, it will take some time for the dunes to diminish. Flood deposits, caused by local deceleration of flow in the main channel where the flood-flows enters a flood plain or side channel (similarly local erosion occurs if currents from flood plains flow back in the main channel). The highest deposition rate is found at the side of the flood-plain inflow-point. Each of these features have a spatially and time-dependent character, with variations in cross-section. In relation to the DVR program several measures have been proposed to guarantee navigability on the long term in a sustainable way. Each of these measures is designed to fight the processes mentioned above. The main measures are filling and stabilisation of outer bends, longitudinal dams with groyne removal, and continuation of the sediment management strategy of maintenance-dredging and dumping extended with a sediment-feeding approach (particularly aiming at stopping the degradation).

6 DVR toolbox for sediment management in the Rhine delta 5 Assessment of the impacts of the mentioned features and measures on navigability (considering figure 1) requires at least a 2D (depth-average) time-dependent approach. Fig. 3: Left panel: aerial photograph showing navigation and sedimentation in inner bend in Rhine branches in the Netherlands (courtesy of Rijkswaterstaat); right panel: multibeam sounding showing groyne flames, dunes and inner-bank deposits in a bend. 2 DVR Toolbox 2.1 General Toolbox set-up The DVR toolbox is designed to predict the morphological development of the river bed in space (2DH depth average) and time (decades). Because it has to be used in operational context, it is optimized for computation speed by using a relatively coarse grid, a schematized hydrograph, and simulation management. Yet, it is stipulated that the model correctly reproduces the relevant morphological features that affect the navigability. The DVR toolbox is capable of predicting large-scale 2D morphological response to a multitude of interventions, diagnosis of historical trends in navigation channel dimensions, and forecasting of future trends. Figure 4 shows the components of the system. The computational core of this system is the Delft3D flow and morphology solver, with a specific schematization for the Rhine branches. Delft3D (Lesser et al., 2004) is a

7 6 K. (C. J.) Sloff computational system for solving 2D and 3D hydrodynamics and morphology for a wide range of applications. Delft3D was a logical choice for this system, as it has proven its validity for this river during its development and use in the past 30 years. Around the computational core specific steering modules and in- and output facilities have been created as indicated in the figure. Baseline (GIS database: schematisation) Schematised hydrograph (high-flow & low flow) Time/simulation management (Python scripts) Dredging module Delft3D Dune height module Matlab, GIS, Open Earth (Google Earth) Pre-processing Computation Post-processing Fig. 4: Set-up of the DVR Toolbox 2.2 Optimising for computation speed Computation time was one of the important criteria imposed for the development of the tool. Specifically the structure of the computational core, as indicated in Figure 1, and the settings of the Delft3D model, originated from the need to gain computation time. In the following some relevant aspects are presented: The Delft3D computations are carried out on a structured grid (see section 2.4), using a semi-implicit flow solver (Lesser et al, 2004). Because of that the flow simulations are relatively fast. Still, flow is the most time-consuming part of the simulation (more than transport and bed-level change). The full yearly hydrograph (i.e., sequence of high, medium and low-flow periods) has to be introduced in the simulation. From experience it is known that the morphological changes calculated with a gradually/continuously varying discharge are more or less equal to the results from a simulation where the hydrograph is replaced by a sequence of steady-state steps. Such a quasi-steady approach allows for significant reduction of computational time in three ways (see also Yossef et al., 2008): 1. Morphological changes per time step are small (relative to flow), and it is possible to apply a morphological factor to speed up the morphological changes. By multiplying the computed bed-level change (each time step) with this factor, the morphology is accelerated. Hence, less flow time is needed to get an equivalent morphology time.

8 DVR toolbox for sediment management in the Rhine delta 7 Factors between 50 to 200 are applied (the higher the transport rate the lower the factor), without any noticeable difference in simulation results. 2. Each time the discharge changes to another level the flow field has to adjust to a new steady state before the morphological simulation can start. This play-in period can be reduced significantly if the new steady state can directly start from a previously computed steady state for the same discharge. This is done by storing computed flow fields (for each discharge level) in a separate database during the simulation. Before starting a new discharge level, the simulation is stopped, a flow field for the new discharge from the database is selected and written to the restart file, and then the simulation is continued. Only in the first year, starting from an empty database, the simulations require extra play-in time. The time/simulation management is set-up using Python scripts (Python programming language, In figure 5 a scheme is given of the simulation management for a regular calculation. database restart file Q1 restart file Q2 restart file Q3 ETCETERA hydrodynamic parameters morphodynamic parameters Fig. 5: Time management (Yossef et al, 2008) 3. Repeat a yearly schematised hydrograph (e.g., based on long-term statistics of discharge measurements). By repeating the same hydrograph it guaranteed that the database of flow fields remains up-to-date for all discharges. 2.3 Pre-processing The model schematization applied in the computational core is more or less similar to the official hydrodynamic schematization that is applied to calculate the design flood level ( MHW using the 2D modeling system WAQUA). The schematisation is generated for both the Waqua model and the DVR Toolbox from the GIS database and conversion tools of Baseline. Baseline was developed for standardization and facilitating of the 2D schematizations for the Rhine branches, and now commonly used. Baseline projects the topographic data, such as bed-levels, weirs and groynes to the relevant

9 8 K. (C. J.) Sloff modeling elements on the computational grid. Also spatially varying roughness data are compiled from land-use, vegetation and other characteristics are produced. The schematization of the yearly repeated hydrograph has become part of the preprocessing routines as well. The most optimal approach was to create a representative hydrograph from a discharge-duration curve that was derived from time-series of discharges at Lobith for a reasonably long period. In the example in figure 6 we used the data from The continuous discharge-duration curve is then replaced by a discrete number of discharge steps with a particular duration such that the continuous original curve is matched. The steps are chosen such that important flow situations (such as bank-full conditions, overtopping of summer dikes, etc.) are captured. Finally the discharge-duration curve is transformed to a yearly hydrograph with one flood period and one low-flow period: the duration of the periods and sequence of these periods is flexible, and depend on expert judgment. Q Boven Rijn [m 3 /s] max min mean schematisation Discharge Boven-Rijn (m 3 /s) New refined hydrograph days Days Fig. 6: Schematized hydrograph. Left: discharge duration curve based on recorded discharges for ; Right: resulting constructed hydrograph used for the simulations 2.4 Computational part: curvilinear grid The heart of the computational core is the Delft3D modeling system, applied to a schematization of the Rhine branches that covers the main channel, groyne fields and flood plains. The model covers about 380 km and is split into 15 domains. The reason for this split is twofold: At bifurcations the structured grid in Delft3D has to split into the two outflowing channels. The bifurcation point can then only be created if one cell is closed, causing an obstruction/stagnation at the head of the bifurcation. Furthermore, there will be no continuing grid lines left to cover the area that is existing between the two outflowing branches (i.e. the flood plain areas downstream). Separating the grids for each branch in domains resolves these limitations.

10 DVR toolbox for sediment management in the Rhine delta 9 In multi-processor computers the domains can be distributed over the processors, hence creating increased performance. However, communication between domains can be time-consuming (and may cancel out any gains), and the largest domain is still dominating the computation time (the other have to wait at each time step until the largest is finished). A further split in smaller domains therefore not necessarily leads to more time reduction. The example in figure 6 shows how the grid is cut in domains at the bifurcation, and preventing stagnation as well as allowing extension of the grid to the right flood plain in the South branch (Waal River). Although the grids of the two outflowing branches seem to overlap, there is no exchange of water between the two grids. This is acceptable as the exchange between the two branches is blocked by a guiding levee in reality as well. Fig. 7: Computational grids near the Pannerdensche Kop river bifurcation (flow is from right to left): different colors refer to different domains. Black lines indicate 2D weirs that are used to represent small dikes, elevated roads and groynes Figure 7 also shows the characteristics of the grid structure in main channel and flood plains. The total number of nodes in this model is roughly 500,000. In general in the main channel, which is constricted by the groynes, 10 to 12 grid cells are defined in transverse direction. Depending on the width of the branches the cell width varies roughly between 10 to 20 m. In longitudinal direction the size of these cells is about 3 to 4 times the width, hence roughly 30 to 80 m long. The grid in flood plains is somewhat

11 10 K. (C. J.) Sloff coarser. Essentially these grid cells dimensions have been chosen such that the most relevant large-scale and median scale features can be reproduced, while having a most optimal computation time. For specific small-scale studies it is very well possible and easy to refined the grid and rebuilt the model for a specific sub-domain (and still use the Toolbox). The grid-cell dimensions are too coarse to be able to reproduce the physics and characteristics of bed forms (dunes). These features have been introduced by a simplified parameterization in relation to the dredging module. This is shown in section 2.5. In general these dimensions are also too coarse to reproduce the flow and transport phenomena in groyne fields (groyne fields have a length of 2 to 3 grid cells). However, the exact physical processes of sedimentation in groyne fields (e.g. during floods) and erosion of sand in the groyne fields (e.g. due to shipping waves) are still rather uncertain and difficult to reproduce by models anyway. Presently the groyne fields are rather stable and the storage and release of sediments from these areas is supposed not to affect the main-channel morphology significantly. Only for investigating the effect of groyne-lowering (and subsequent erosion of the existing sand deposits in the groyne fields) these effects have been studied in more detail on basis of expert-judgment and separate models. 2.5 Computational part: process-based simulation The simulations with Delft3D are carried out in 2DH mode, i.e. a depth-average flow. Sediment-transport and morphology are computed at every time-step. In this approach some specific processed-based components have to be mentioned: The 3D processes of helical flow that are important for bends are approximated using a parameterized model (based on local flow curvature and transport of spiral-flow intensity with an advection-diffusion approach). Morphological evolution of flood plains and groyne fields is not included, as this tool is focusing on the navigation channel. In the model the flood plains and groyne fields are introduced as fixed bed (only sedimentation can occur). Groynes, dikes and other structures are represented by 2D weirs, in analogy with the official WAQUA hydrodynamic simulations. The impact of these elements on the main channel is included, but specific storage and release of sediments from groyne fields are not present. For the upper Rhine branches sediment-sorting processes are relevant. These processes occur vertically in the top-layers of the bed (e.g., sorting by dunes) and horizontally (e.g., transverse sorting in bends, sorting at bifurcation). Initially all schematizations were set up in a uniform-sediment mode. This means grain-size has been introduced varying in space, but constant in time. Sediment-transport models are

12 DVR toolbox for sediment management in the Rhine delta 11 then applied to one grain-size for all discharges, but hence appeared to under predict transport during low-flow conditions (or required unrealistic adaptation of parameters in the transport models, such as too low values of critical Shields values). For more detailed analysis of autonomic features and proposed measures, which influence the sorting processes, an additional schematization of the models has been created with non-uniform sediment. During calculations with this approach the bed composition can change as function of time and space (horizontal and vertical in the bed).we applied the default one-layer approach of Delft3D, with a bookkeeping system of under layers. For more details on the approach and lessons learned we refer for instance to Sloff and Ottevanger (2008). The model is applied with a varying mixing layer thickness (top-layer) related to water-depth (which represents a relation to dune-height). Non-erodible layers are applied to stabilize the flood plains and groyne fields. Also the existing non-erodible layers in the outer bends of Nijmegen and Sint Andries are introduced in the model. Delft3D computes non-erodible layers with a validated transport-capacity reduction approach as presented by Struiksma (1999), Sloff et al. (2006) and Sloff (2010). Bed forms, notably dunes with length scales of several tenths of meters are important for navigation. The dunes grow during floods, but after floods recede these dunes remain and may cause hindrance for navigation. Dredging operations in the Rhine branches are often triggered by dunes, and often it suffices to flatten the dunes to fulfill the criteria for navigability. The importance of dunes in DVR is therefore significant. Presently models to simulate the development and decay of 3D dunes are being developed, but due to their complexity and high-resolution they cannot be used in practical situations yet (Nabi, 2010). It is therefore chosen to apply a parameterized (semi-empirical) dune-height prediction that reproduces quantitatively the average dune-height development in time. The method is applied in two steps (Giri et al., 2008): o The equilibrium dune height is calculated using a form of the duneheight predictor of Van Rijn (1984), using the local flow and sediment conditions at each grid cell. o The actual dune height is calculated using a advection-diffusion approach (relaxation equation) with a discharge-dependent time scale. The result of these equations is an exponential decaying function of the difference between actual dune height and equilibrium dune height: the larger the difference the faster the change of dune size (see Giri et al, 2008). During calibration it was found that the advection does not have to be taken into account in the description of the lag of dune forms, since the effect of advection on dune-height evolution is small compared to the effect of relaxation, particularly when focusing on large-scale behavior.

13 12 K. (C. J.) Sloff In figure 6 an example is shown of calculated dune heights. The dune height grows rapidly during the rise of the flood, and continues to grow for a short period after the peak has passed. Then a gradual decay of dune height occurs over periods of several months. This typical response and consequent hysteresis effects represent the average dune-height observations in the Waal River quite well. Note that dune heights have a stochastic character, and it may be interesting to extend the approach with statistical properties for more extended analysis of dredging operations. To trigger dredging operations, the predicted dune height is used as an additional elevation on the (dune-average) bed level simulated with the 2D model. Also a correction of dredging volume is included, that accounts for the irregular distribution of dredging volumes in dunes (i.e., for dredging or ploughing of dune-crests). H dune H dune Q Q Fig. 8: Computed average dune height as function of time for a period of 2 years (dotted lines), in response to varying discharge (drawn lines) The model has been calibrated hydraulically and morphologically. For morphology calibration focused on both the long-term 1D (cross-sectional average) time-dependent development of the river bed, and the 2D (spatially varying) bar and pool pattern of the river bed (Yossef et al, 2009).

14 DVR toolbox for sediment management in the Rhine delta Computational part: dredging and dumping module Sediment management is an important measure in the DVR project. For that purpose an automatic dredging module has been developed in the DVR Toolbox. The module is specifically designed to simulate the triggering and dredging/dumping approach in the Rhine as presented in section 1.2. The main characteristics of this module are (see also for more details Yossef et al., 2008): The automatic module has integrated in the Delft3D software, and can therefore be applied at predefined times (and periods) during the simulation (e.g, each year a short period following a flood season). Polygons are introduced to define specific dredging as well as specific dumping areas. Dredged sediment is dumped in nearby dumping areas following user-defined searching rules. For example, first available dumping polygon with sufficient space at a certain distance upstream, followed by sequential dumping in following dumping blocks when the first block is filled, see figure 9. Dredged sediment can also be dumped outside the model, which assumes subtraction from the model. Similarly dumped material can be introduced form outside the model which assumes sediment feeding. Fig. 9: Example of dredging and dumping polygons in the Waal River near Sint Andries: arrows indicate that dredged volumes between km are dumped in the polygons upstream (flow is from right to left) To trigger dredging a constant low-flow water level (OLR) is prescribed (spatially varying on the grid) or directly taken from an intermediate low-flow calculation. The intermediate calculation of the OLR, and transfer of water levels, is organised with the Python script in the simulation management procedure.

15 14 K. (C. J.) Sloff Dredging in a polygon is triggered if the bed level (at one or more grid cells) in the polygon exceeds the threshold defined by the low-flow level minus the depth criterion, for example, OLR 2.8 m in the Rhine. If available the dune-height can be included in the bed level to trigger the dredging option. reference level threshold level constant per clearance dredge area (b) Fig. 10: Dredging criteria. Dashed line: threshold, trigger level is depth below a specified reference level; Dash-dotted line: dredge level is threshold minus clearance (Yossef et al, 2008) Dredging can also be specified as a constant dredging rate, irrespective of the available depth. Dredging is carried out including a clearance depth. There are different ways to distribute the dredging volume over the polygon, such as highest points first, or proportional to availability of dredge material, see figure 11. For dumping it is possible to choose from a method in which deepest points are filled first, or a method in which the area is filled uniformly. (a) (b) (c) Fig. 11: Dredging method: (a) dredge top first, (b) dredge proportional, (c) dredge uniform (Yossef et al, 2008) The dredging approach has been validated on several data sets for the Rhine branches. For instance in figure 12 the results of average yearly dredging volumes for the Waal River are shown. It was found that most relevant dredging locations and dredging volumes can be well reproduced. Nevertheless the results are relatively uncertain compared to average bed level differences, as they more sensitive to stochastic behavior of bed forms, bed slopes and discharge variations. The computed dredging volumes have to be used with some care.

16 DVR toolbox for sediment management in the Rhine delta 15 Fig. 12: Comparison measured and computed yearly dredging volumes along the Waal River 3 Case study: Vianen The DVR Toolbox has been applied to many studies in the Rhine branches the past years. In recent periods several morphological studies have been carried out for the Room for the River program, applying the DVR Toolbox. To illustrate the use of this approach we present a recent application in the Lek River, which is one of the lower Rhine branches as indicated in figure 13. VIANEN Fig. 13: Location of Vianen at the Lek River

17 16 K. (C. J.) Sloff For lowering water levels in the considered reach, a combination of lowering of floodplains, excavation of side channels, and lowering of summer dikes have been proposed. At the same moment also opportunities are created for nature restoration. During the design process with stakeholder and public participation, and negotiations with different specialist, several design-variants have been proposed. For each of these variants the Toolbox has been used to assess the combined morphological effects of the different measures. From the calculated results it was found that further optimization for reducing negative morphological impacts was not necessary. Figure 14 shows a map of the proposed measures for one of the variants. Fig. 14: Map of design-variant 4 for flood plain restoration at Vianen, flow is from right to left In figure 15 results are shown for the computed morphological impacts of one of the variants after a period of 40 years. The figure shows the difference in 40-year bed level computed with the measures, and 40-year bed level computed without the measures (reference simulation). From these results, while considering the set-up of the measures in figure 14, it can be observed that most relevant stable sedimentation occurs next to the entrance to lowered flood plains and flood-plain channels as expected. Only at locations with relative shallow bed, these sedimentation patterns can create hindrance for navigability. Another way to look at the results, and analyze the model, is to create longitudinal side views as shown in figure 16. This figure can also be made for other grid lines, and can be used to observe time-dependent evolution of the impacts of the measures. The advantage of the relatively short computation time (several days for 40 years) also provides the possibility to play with different management strategies to analyse the effect of including various options for dredging and dumping (e.g., dredging without dumping, or with dumping upstream or dumping downstream).

18 DVR toolbox for sediment management in the Rhine delta 17 Fig. 15: Map of morphological impact of design-variant 3b, showing difference in simulation with and without measures after 40 years Fig. 16: Side view of bed-level difference (bed level with measures minus bed level reference) along a longitudinal section (i.e. grid line) close to the left bank, shown for results for a number of consecutive years following the period of low flow The output of the dredging module can be shown in different ways as well. For the Vianen project we have analyzed dredging volumes as function of time in figure 17. In this figure we compared the yearly dredged volumes for the reference situation and for the situation with proposed measures. The difference of these volumes (lower panel in figure 17) shows that in the first 10 years some fluctuations are found. These are due to a combined dynamic initial response of the river to the implementation of the floodplain lowering, the play-in of initial conditions (measured bed levels at t=0), and interaction with fixed layers at the weir that is located a few kilometers upstream. After 10 years these play-in effects have declined, and the difference in yearly dredging volume becomes more stable. The difference is in the order of 5000 m 3 /year (i.e., volume as stored in the river bed, with bed porosity).

19 18 K. (C. J.) Sloff Fig. 17: Dredging volume calculated including a sediment-management strategy without sand-extraction for variant vka3b and for the reference situation, as function of time Although these presented volumes in figure 17 are uncertain, they indicate roughly the expected increase of maintenance due to the plan. They serve as important input for acceptance of the project and permission to execute the plan for river managers. 4 Conclusions and outlook The DVR Toolbox has been developed to be used as an operational model for long-term morphological assessment of the Rhine branches in the Netherlands. Although it originally aims on predicting navigability constraints, it can also be used to look at a wider range of functions that are affected by morphological changes (such as flood safety, stability of bifurcations, ecology). The Toolbox consists of a 2D computational core (containing the Delft3D modeling system), a shell that controls input- and output, and a system for time/simulation management. By optimizing the computation process (using the simulation management and optimizing the model schematization) the computational time for the full Rhine delta morphological simulation of 40 years takes less than 1 week (using 1 processor, situation 2010). Also sub-models can be used in this Toolbox (e.g., individual domains) with a further reduction of computation time. The model has

20 DVR toolbox for sediment management in the Rhine delta 19 been applied quite widely now for simulating the morphological impacts of measures on the river bed, and the navigability. Also, by applying the automatic dredging and dumping module, it is possible to simulate a wide range of sediment-management strategies for the Dutch Rhine branches. In 2011 the model will be applied for a evaluation of combined package of Room for The River (RvR) measures for the different branches. So far the impact assessment has only been done for individual projects within the RvR program. As part of the Delta Program, which aims at preparing the Dutch Rhine delta for long-term ( ) devlopments, the Toolbox will be used to assess different scenario s for both climate change and anthropogenic developments. Finally the Toolbox will be an important tool for preparing the pilots for nourishment in the Boven Rijn, and longitudinal dams in the Waal River. The DVR Toolbox benefits from a continuous upgrade of the front-end Baseline tool (for input data) and the Delft3D software, as part of a general development and support program. The recent transition of Delft3D to Open-Source creates possibilities for even a more widely spread of the DVR Toolbox among other communities. 5 References Giri, S.; Vuren, S. van; Ottevanger, W.; Sloff, K.; Sieben, A. (2008) A preliminary analysis of bedform evolution in the Waal during flood event using Delft3D. In: D. Parsons, T. Garlan and J. Best (eds.) Marine and River Dune Dynamics, Proc. Int. Conf. MARID April 1-3, 2008, Leeds, UK, pp Lesser, G. R., Roelvink, J. A., Van Kester, J. A. T. M., And Stelling, G. S. (2004): Development and validation of a three-dimensional morphological model. Coastal Engineering, 51(8-9), Nabi, M. (2010) Computational modelling of three-dimensional beform evolution. In: Dittrich, Koll, Aberle & Geisenhainer (eds.) River Flow 2010, Proc. Int. Conf. Fluvial Hydraulics, Braunschweig, Germany, ISBN , p Sloff, C.J., E. Mosselman and J. Sieben (2006) Effective use of non-erodible layers for improving navigability. In: Ferreira, Alves, Leal and Cardoso (eds.) River Flow 2006, Taylor and Francis/Balkema. Proceedings, p Sloff, C.J. and Ottevanger W. (2008) Multiple-layer graded-sediment approach: improvement and implications. In Altinakar, Kokpinar, Gogus, Tayfur, Kumcu & Yildirim (eds.) Proceedings River flow ISBN p Sloff, C.J. (2010) Mixed alluvial and non-alluvial bed topographies: observations, modeling and implications. In: Dittrich, Koll, Aberle & Geisenhainer (eds.) River Flow

21 20 K. (C. J.) Sloff 2010, Proc. Int. Conf. Fluvial Hydraulics, Braunschweig, Germany, ISBN , p Smedes, R.H. (2005): Toekomstige Waal; Duurzame vaardiepte Rijndelta. Projectplan, Rijkswaterstaat, Directie Oost-Nederland. Struiksma, N Mathematical modelling of bedload transport over non-erodible layers. Proc. IAHR symposium on River, Coastal and Estuarine Morphodynamics (RCEM), Genova, Sept. 1999, p Van Rijn, L.C. (1984) Sediment transport, Part III: Bed forms and alluvial roughness. J. Hydr. Engrg., ASCE, Vol. 110, No. 12, p Yossef, M. F.M., H.R.A. Jagers & S. V. Vuren (2008): Innovative techniques in modelling large-scale river morphology. In Altinakar, Kokpinar, Gogus, Tayfur, Kumcu & Yildirim (eds.) Proceedings River flow ISBN p Author, Adress Dr. ir. C. J. Sloff Deltares PO Box MH Delft Netherlands