3. Validation and application results of the model

## 3.1. Validation of bed morphological change and bank erosion models

The sediment transport and bed morphological change simulation model was tested using physical model data. Four experiment test cases with a different channel geometry, curvature, flow condition, and sediment size distribution ([36]) were simulated. The sediments of these three cases are uniform. Figure 4 shows the computed final water depth of the case with a 180° bend and comparison of the simulation to the measurement. Red and blue color indicates deep and shallow water depth, respectively. Table 1 shows the parameters of the experimental flume and flow. Channel plane geometry, slope, sediment size (in bed and from inlet) distribution, and Manning's n are needed to run the simulations; the flow rate and water depth are used for the upstream and downstream boundary conditions. Because the initial bed is horizontal and flat and the water depth almost constant, the resulting water depth distribution indicated more erosion along the outer bank and deposition along the inner bank. Although differing, the computed bed elevations along the channel agree reasonably well with the observation. The magnitude of the predicted erosion and deposition in the channels agreed very well with the measurement; the second water depth peak of the bed variation along the outer bank has some difference from the observed.

accordingly; the cross-section form of the channel also changes particularly at the beginning stage, and the water depth near the outer bank becomes larger, while that near the inner bank becomes smaller. This change makes it possible to form a point bar near the inner bank (Figure 5); then the point bar later becomes dry. Although the distance of the two banks increases, the width of the wetted channel remained approximately the same. Another feature of the simulated results is that when the main channel moves toward the outer bank due to bank erosion, a small channel near the inner bank is formed behind the point bar (Figure 5d, e). This probably is

Simulated bank erosion and channel morphologic change using bank-full discharge (the color contour indicates

Parameters Case 4 LFM flume

Flume width (m) 1.7 Water depth (m) 0.2 Flow velocity (m/s) 0.5

Modeling River Morphodynamic Process Using a Depth-Averaged Computational Model…

Chezy coefficient (m1/2/s) 26.4 Manning coefficient (n) 0.0280 D50 (mm) 0.78

Bend radius (m) 4.25 Bend length (m) 13.35

/s) 0.17

/00) 1.8

/s) 13 x 10<sup>6</sup>

Discharge (m<sup>3</sup>

Water surface slope (0

Sediment transport rate (m2

The conditions and parameters of the physical model.

DOI: http://dx.doi.org/10.5772/intechopen.86692

Table 1.

Figure 5.

41

flow velocity magnitude).

A qualitative study of sediment transport in conjunction with the bank erosion simulation is also presented (Figure 5). A river channel with the sine-generated shape, constant bed roughness, channel width, and longitudinal slope was generated for the simulation. The initial bed erosion simulation was performed with fixed banks. The bank erosion simulation started after the bed erosion has been performed for a while. When the bank erosion simulation is completed for one time step, the mesh bank line and internal points are shifted and the model re-discretized, and so on, as indicated in Figure 3.

The colors in Figure 5 indicate the flow velocity magnitude. One sees the phase difference between the shape of the channel bends and the velocity distribution. The highest flow velocity shifts downstream. In the process of bank erosion, the outer bank line retreats gradually, and the main channel of this bend shifts

Figure 4. Computed water depth and comparison of numerical results (curve) and experimental data (Case 4).

Modeling River Morphodynamic Process Using a Depth-Averaged Computational Model… DOI: http://dx.doi.org/10.5772/intechopen.86692


#### Table 1.

larger time than that for the flow and sediment. This strategy can save a lot of computing time. Figure 3 briefly illustrates the corresponding computation

3.1. Validation of bed morphological change and bank erosion models

The sediment transport and bed morphological change simulation model was tested using physical model data. Four experiment test cases with a different channel geometry, curvature, flow condition, and sediment size distribution ([36]) were simulated. The sediments of these three cases are uniform. Figure 4 shows the computed final water depth of the case with a 180° bend and comparison of the simulation to the measurement. Red and blue color indicates deep and shallow water depth, respectively. Table 1 shows the parameters of the experimental flume and flow. Channel plane geometry, slope, sediment size (in bed and from inlet) distribution, and Manning's n are needed to run the simulations; the flow rate and water depth are used for the upstream and downstream boundary conditions. Because the initial bed is horizontal and flat and the water depth almost constant, the resulting water depth distribution indicated more erosion along the outer bank and deposition along the inner bank. Although differing, the computed bed elevations along the channel agree reasonably well with the observation. The magnitude of the predicted erosion and deposition in the channels agreed very well with the measurement; the second water depth peak of the bed variation along the outer

A qualitative study of sediment transport in conjunction with the bank erosion simulation is also presented (Figure 5). A river channel with the sine-generated shape, constant bed roughness, channel width, and longitudinal slope was

generated for the simulation. The initial bed erosion simulation was performed with fixed banks. The bank erosion simulation started after the bed erosion has been performed for a while. When the bank erosion simulation is completed for one time

The colors in Figure 5 indicate the flow velocity magnitude. One sees the phase difference between the shape of the channel bends and the velocity distribution. The highest flow velocity shifts downstream. In the process of bank erosion, the outer bank line retreats gradually, and the main channel of this bend shifts

Computed water depth and comparison of numerical results (curve) and experimental data (Case 4).

step, the mesh bank line and internal points are shifted and the model

3. Validation and application results of the model

Current Practice in Fluvial Geomorphology - Dynamics and Diversity

bank has some difference from the observed.

re-discretized, and so on, as indicated in Figure 3.

procedure.

Figure 4.

40

The conditions and parameters of the physical model.

accordingly; the cross-section form of the channel also changes particularly at the beginning stage, and the water depth near the outer bank becomes larger, while that near the inner bank becomes smaller. This change makes it possible to form a point bar near the inner bank (Figure 5); then the point bar later becomes dry. Although the distance of the two banks increases, the width of the wetted channel remained approximately the same. Another feature of the simulated results is that when the main channel moves toward the outer bank due to bank erosion, a small channel near the inner bank is formed behind the point bar (Figure 5d, e). This probably is

#### Figure 5.

Simulated bank erosion and channel morphologic change using bank-full discharge (the color contour indicates flow velocity magnitude).

because the small channel shortcuts from one bend to the next, the local water surface slope, and sediment transport capacity are relatively large. This phenomenon appears also in some natural rivers ([21]).

active. The upstream part of the Chuoshui River between Mingchu Bridge (CS 106.5) and Zhangyun Bridge (CS 86.5) was used as a test site for the bank erosion model. Field bed material samples taken in July 2004 were used as the initial bed composition for the study reach. The average sediment compositions in three subreaches are shown in Figure 7 and Table 2. One notes that the sediment sizes range from 0.283 to 282 mm. The trend of sediment particle size decreases downstream (CS 55–CS 70) is quite significant. Particularly the portion of coarse particles decreases more (Figure 7). To gain computational efficiency, the original measured

Modeling River Morphodynamic Process Using a Depth-Averaged Computational Model…

The flow discharge in the Chuoshui River is highly variable, ranging from almost zero in dry seasons to more than 20,000 cms in some typhoon seasons. Because sediment transport is insignificant to channel change when the flow discharges are

(>4000 cms). Considering the bank-full discharge is 5700 cms in this channel, this criterion of simplification has included most significant flows. Figure 8 shows the simplified hydrograph including most of the typhoon events from June 8, 1998, to October 8, 2007. The corresponding downstream boundary condition, water surface elevation at the Zhongsha Bridge (CS 55), is also shown. Rating curves for the sediment transport rate were used for sediment boundary conditions with wash load being removed. The accumulated total time of these high flows is approxi-

The sediment discharge hydrograph at Mingchu (CS 106.5) and Zhangyun (CS 86.1) was also filtered accordingly to remove low flow events. Because there is

CS range D10 D20 D30 D40 D50 D60 D70 D80 D90 86.5–106.5 0.396 0.94 1.91 5.029 13.69 29.424 62.532 143.921 281.966 70–86.5 0.404 0.981 1.826 3.452 8.784 22.682 46.998 124.463 217.7 55–70 0.283 0.597 1.096 1.91 3.348 5.775 11.509 27.495 82.315

sediment distribution data was simplified from nine size classes to six.

mately 4 days and 20 hours.

DOI: http://dx.doi.org/10.5772/intechopen.86692

Figure 7.

Table 2.

43

Initial bed compositions.

Specified bed materials in three channel reaches (d/mm).

low, the bank erosion study was performed only when the flow rate is high

#### 3.2. Application of the bank erosion model to a field case in Chuoshui River

Chuoshui River is in the middle of the Taiwan inland which is located in the South China Sea across the Taiwan Strait. Originated from the central mountains, the river forms a large alluvial fan and then empties into the South China Sea. The channel slope in the mountain area is very steep. The valley of the river is wide, and a typical braided river pattern with multiple curved sub-channels can be observed from aerial photos and satellite imagery. The study reach is situated at the connection part of the mountain and the alluvial fan of the river. The channel slope is about 0.0069 for the mountain part, and it reduces suddenly to about 0.0041 over the alluvial fan. The hydrology is dominated by seasonal typhoon events and a large amount of sediments from the mountain watershed. The characteristic of braided river varies downstream somewhat, and the number of sub-channels decreases over the alluvial fan.

One should recognize that the predictability of bank erosion is limited by the facts that (1) not all the processes are understood and formulated accurately, (2) collecting field data necessary for the analysis is extremely difficult and costly, and (3) the accuracy of the flow simulation is affected by the modeling methodologies and computer capacity. When a real-world bank erosion problem is modeled, one focuses on the dominant processes and carries out appropriate calibration and validation. These processes could be related to several parameters: sediment properties of bed materials and bank, including bank slope, height, and bank material erodibility, as well as the conditions of the flow in the river channel (shear stress, water depth, channel curvature, etc.).

The flow discharge increases greatly, particularly during typhoon seasons. The multiple channels become a single one only when the discharge is very large during typhoon seasons. Due to the nature of the channel pattern, the main channel and secondary channels in the study reach change courses randomly and quickly. Sediment transport is dominated by the pattern of the flow discharge. The computational model, CCHE2D, was applied to simulate the bank erosion process in one reach of the river from Mingchu Bridge (CS 106.5) to Zhongsha Bridge (CS 52), a 26 km stretch (Figure 6).

Even in a braided river, each sub-channel is a curved one. Because sediment transport in curved channels is affected by the secondary current, creating a lateral sediment motion and channel change, the computational model should include this mechanism to reflect the realistic transport processes. Figure 6 shows the air photo of this reach in 2007, where the nature of the braided river is clearly seen. The flow discharges for this figure are unknown. It is certain the braided river process is very

Figure 6. Study reach of Chuoshui River.

#### Modeling River Morphodynamic Process Using a Depth-Averaged Computational Model… DOI: http://dx.doi.org/10.5772/intechopen.86692

active. The upstream part of the Chuoshui River between Mingchu Bridge (CS 106.5) and Zhangyun Bridge (CS 86.5) was used as a test site for the bank erosion model.

Field bed material samples taken in July 2004 were used as the initial bed composition for the study reach. The average sediment compositions in three subreaches are shown in Figure 7 and Table 2. One notes that the sediment sizes range from 0.283 to 282 mm. The trend of sediment particle size decreases downstream (CS 55–CS 70) is quite significant. Particularly the portion of coarse particles decreases more (Figure 7). To gain computational efficiency, the original measured sediment distribution data was simplified from nine size classes to six.

The flow discharge in the Chuoshui River is highly variable, ranging from almost zero in dry seasons to more than 20,000 cms in some typhoon seasons. Because sediment transport is insignificant to channel change when the flow discharges are low, the bank erosion study was performed only when the flow rate is high (>4000 cms). Considering the bank-full discharge is 5700 cms in this channel, this criterion of simplification has included most significant flows. Figure 8 shows the simplified hydrograph including most of the typhoon events from June 8, 1998, to October 8, 2007. The corresponding downstream boundary condition, water surface elevation at the Zhongsha Bridge (CS 55), is also shown. Rating curves for the sediment transport rate were used for sediment boundary conditions with wash load being removed. The accumulated total time of these high flows is approximately 4 days and 20 hours.

The sediment discharge hydrograph at Mingchu (CS 106.5) and Zhangyun (CS 86.1) was also filtered accordingly to remove low flow events. Because there is

Figure 7. Initial bed compositions.


Table 2.

Specified bed materials in three channel reaches (d/mm).

because the small channel shortcuts from one bend to the next, the local water surface slope, and sediment transport capacity are relatively large. This phenome-

3.2. Application of the bank erosion model to a field case in Chuoshui River

somewhat, and the number of sub-channels decreases over the alluvial fan.

Bridge (CS 106.5) to Zhongsha Bridge (CS 52), a 26 km stretch (Figure 6).

Figure 6.

42

Study reach of Chuoshui River.

Even in a braided river, each sub-channel is a curved one. Because sediment transport in curved channels is affected by the secondary current, creating a lateral sediment motion and channel change, the computational model should include this mechanism to reflect the realistic transport processes. Figure 6 shows the air photo of this reach in 2007, where the nature of the braided river is clearly seen. The flow discharges for this figure are unknown. It is certain the braided river process is very

One should recognize that the predictability of bank erosion is limited by the facts that (1) not all the processes are understood and formulated accurately, (2) collecting field data necessary for the analysis is extremely difficult and costly, and (3) the accuracy of the flow simulation is affected by the modeling methodologies and computer capacity. When a real-world bank erosion problem is modeled, one focuses on the dominant processes and carries out appropriate calibration and validation. These processes could be related to several parameters: sediment properties of bed materials and bank, including bank slope, height, and bank material erodibility, as well as the conditions of the flow in the river channel (shear stress, water depth, channel curvature, etc.). The flow discharge increases greatly, particularly during typhoon seasons. The multiple channels become a single one only when the discharge is very large during typhoon seasons. Due to the nature of the channel pattern, the main channel and secondary channels in the study reach change courses randomly and quickly. Sediment transport is dominated by the pattern of the flow discharge. The computational model, CCHE2D, was applied to simulate the bank erosion process in one reach of the river from Mingchu

Chuoshui River is in the middle of the Taiwan inland which is located in the South China Sea across the Taiwan Strait. Originated from the central mountains, the river forms a large alluvial fan and then empties into the South China Sea. The channel slope in the mountain area is very steep. The valley of the river is wide, and a typical braided river pattern with multiple curved sub-channels can be observed from aerial photos and satellite imagery. The study reach is situated at the connection part of the mountain and the alluvial fan of the river. The channel slope is about 0.0069 for the mountain part, and it reduces suddenly to about 0.0041 over the alluvial fan. The hydrology is dominated by seasonal typhoon events and a large amount of sediments from the mountain watershed. The characteristic of braided river varies downstream

non appears also in some natural rivers ([21]).

Current Practice in Fluvial Geomorphology - Dynamics and Diversity

Figure 8. Discharge and water stage hydrograph at Zhangyun and Zhongsha Bridge (CS 55), respectively.

little information about the sediment size composition for the estimated sediment load, it is assumed that (1) 95% of sediment load is suspended and 5% is bed load and that (2) 80% of suspended load coming from upstream is wash load. Considering that the sediment composition would be a function of the flow discharge, large sediment particles can be moved only when the discharge is large, and fine particle can be moved by any flow; the composition of bed sediment can be adjusted by the erosion and deposition process.

The time step for bank erosion was set to be 1.0 hour, while that for the flow and sediment transport was 30 seconds. The critical stress used was consistent with the field data ([34]) for low cohesive bank materials.

> To illustrate more clearly the bank erosion simulation, the computed bank lines are plotted together with the measured bed change in two cross sections (Figure 10). The green lines represent the bed cross-section profile of 1998; the red lines represent

Modeling River Morphodynamic Process Using a Depth-Averaged Computational Model…

DOI: http://dx.doi.org/10.5772/intechopen.86692

Comparison of computed bed change and bank erosion with observed.

Bank erosion comparison. The measured and simulated bed elevation change in CS 70 and CS 78 shows that the bank erosion was simulated well. The incision of the channel thalweg in these two sections was not captured.

Figure 10.

45

Figure 9.

The bank erosion was estimated using the difference between 1998 and 2007 DEM data. Figure 9 shows the measured and computed bed morphologic change of the second reach (II) from 1998 to 2007. The measured bed change is presented over the 1998 aerial photo with the initial mesh boundaries indicated by white lines (Figure 9a). The computed bed change is also presented in a similar fashion (Figure 9b), except that the part outside the computational mesh is contour lines rather than color shading. The initial mesh boundaries are indicated with white lines, while the final mesh boundaries due to bank erosion are presented with purple lines. The difference between these two colored lines represents bank erosion. As indicated in the figure, the simulated bank erosions are very close to the observed, particularly for those on the left bank. The lateral movement of the bank line ranges in several 100 meters. The most significant bank erosions occurred at the left bank. The white circles indicate the two significant bank erosion zones. The general shape and area of the simulated bank erosions are similar to the observed. The maximum erosion distance normal to the left bank line is more than 800 meters.

The simulated bed change has differences from the observed although they are generally consistent. Downstream of CS 70, the computed bed change is consistent with the measured. The location of the deposition and erosion is correctly predicted with the simulated results having a little more deposition. Near the entrance of the reach, the bed change is dominated by degradation. The computed results show two separated channels, one is being eroded and the other has deposition.

The big point bar indicated in Figure 9 was eroded in the numerical simulation, contributed a lot of sediment to its downstream, and affected the simulation results. However, it was found later that the sediment of this 6 meter high point bar could have been taken away by sand miners. To certain extend, this attributes why more deposition is predicted by the numerical simulations.

Modeling River Morphodynamic Process Using a Depth-Averaged Computational Model… DOI: http://dx.doi.org/10.5772/intechopen.86692

#### Figure 9.

little information about the sediment size composition for the estimated sediment load, it is assumed that (1) 95% of sediment load is suspended and 5% is bed load and that (2) 80% of suspended load coming from upstream is wash load. Considering that the sediment composition would be a function of the flow discharge, large sediment particles can be moved only when the discharge is large, and fine particle can be moved by any flow; the composition of bed sediment can be adjusted by the

Discharge and water stage hydrograph at Zhangyun and Zhongsha Bridge (CS 55), respectively.

Current Practice in Fluvial Geomorphology - Dynamics and Diversity

The time step for bank erosion was set to be 1.0 hour, while that for the flow and sediment transport was 30 seconds. The critical stress used was consistent with the

The bank erosion was estimated using the difference between 1998 and 2007 DEM data. Figure 9 shows the measured and computed bed morphologic change of the second reach (II) from 1998 to 2007. The measured bed change is presented over the

The simulated bed change has differences from the observed although they are generally consistent. Downstream of CS 70, the computed bed change is

consistent with the measured. The location of the deposition and erosion is correctly predicted with the simulated results having a little more deposition. Near the entrance of the reach, the bed change is dominated by degradation. The computed

The big point bar indicated in Figure 9 was eroded in the numerical simulation, contributed a lot of sediment to its downstream, and affected the simulation results. However, it was found later that the sediment of this 6 meter high point bar could have been taken away by sand miners. To certain extend, this attributes why more

results show two separated channels, one is being eroded and the other has

1998 aerial photo with the initial mesh boundaries indicated by white lines (Figure 9a). The computed bed change is also presented in a similar fashion (Figure 9b), except that the part outside the computational mesh is contour lines rather than color shading. The initial mesh boundaries are indicated with white lines, while the final mesh boundaries due to bank erosion are presented with purple lines. The difference between these two colored lines represents bank erosion. As indicated in the figure, the simulated bank erosions are very close to the observed, particularly for those on the left bank. The lateral movement of the bank line ranges in several 100 meters. The most significant bank erosions occurred at the left bank. The white circles indicate the two significant bank erosion zones. The general shape and area of the simulated bank erosions are similar to the observed. The maximum erosion

distance normal to the left bank line is more than 800 meters.

deposition is predicted by the numerical simulations.

erosion and deposition process.

Figure 8.

deposition.

44

field data ([34]) for low cohesive bank materials.

To illustrate more clearly the bank erosion simulation, the computed bank lines are plotted together with the measured bed change in two cross sections (Figure 10). The green lines represent the bed cross-section profile of 1998; the red lines represent

#### Figure 10.

Bank erosion comparison. The measured and simulated bed elevation change in CS 70 and CS 78 shows that the bank erosion was simulated well. The incision of the channel thalweg in these two sections was not captured.

the profile of 2007. The bank heights at the bank erosion zones were more than 6 meters. It is seen that the major bank erosion in the channel was reasonably predicted by the model. Although the simulated location and amount of the bank erosions do not match exactly to the observation, the general trend of the bank erosion simulation is quite satisfactory. The observed bank erosion at CS 70 and CS 78 were about 500 and 800 m, respectively. As discussed earlier, the model-predicted incision in the main channel was less than the observed. The error is mainly attributed to lacking of desirable data of sediment transport. Secondly, the Chuoshui River in the study reach is of braided pattern with several major branches. Even the general trend of channel aggradation/degradation can be simulated; the sedimentation trend in each branch is difficult to control. More research is necessary.

### 4. Major outcomes and conclusions

Morphodynamics of fluvial systems is complex involving channel bed change, bank erosion, and channel migration, and it results in soil loss, water quality deterioration, and property damages. Numerical models can be applied to simulate the system behavior by considering involved key physical mechanisms and processes, such as main and secondary flow, sediment transport processes and bank slope mass failure, etc.

The capabilities for simulating the secondary helical flow effects on suspended sediment and bed-load sediment transport have been developed and implemented to the CCHE2D model. The vertical profile for the main velocity and the secondary helical current were assumed to be the power law and linear distribution, respectively. Rouse's distribution for suspended sediment concentration was adopted. For general applications, the curvature of the flow instead of the channel was used for the helical flow calculation. The bank toe and surficial erosion and mass failure mechanisms have also been developed with the mass wasted bank materials being transported as bed load. The current model was designed for banks with cohesive and homogeneous materials. The mesh stretching technique was developed and used to adjust dynamically the moving boundary, internal mesh nodal position, and associated interpolation. These are important to simulate rivers with significant bank line movement due to erosion.

Several sets of curved channel experimental data with different channel geometries, flow rates, sediment sizes, etc. were utilized to validate the developed sediment transport and morphodynamic simulation capabilities in good agreement. Bank erosion capabilities were tested first using a sine-generated channel and then the field case of Chuoshui River, Taiwan. The developed dynamic meshing method handled the moving boundary problem satisfactorily. The simulated and observed bank retreats in the studied Chuoshui River reach can be 500–800 m, which is agreed reasonably well. Because bank erosion occurred mainly in typhoon seasons, simulations used only flow discharges larger than 4000 cms. The computed bed change and bank erosion in one reach of this highly mobile braided river were compared with reasonable agreements to observations.

Author details

\*, Yaoxin Zhang<sup>1</sup>

The University of Mississippi, MS, USA

National Chiao Tung University, Taiwan

provided the original work is properly cited.

, Keh-Chia Yeh2 and Chung-Ta Liao<sup>2</sup>

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

1 National Center for Computational Hydroscience and Engineering,

Modeling River Morphodynamic Process Using a Depth-Averaged Computational Model…

DOI: http://dx.doi.org/10.5772/intechopen.86692

2 Disaster Prevention and Water Environment Research Center,

\*Address all correspondence to: jia@ncche.olemiss.edu

Yafei Jia<sup>1</sup>

47

#### Acknowledgements

This work is supported by the Water Planning Institute, Department of Water Resources, Taiwan, the project of USDA Agricultural Research Service under Specific Research Agreement No. 58-6060-8-008, monitored by the National Sedimentation Laboratory, and the University of Mississippi.

Modeling River Morphodynamic Process Using a Depth-Averaged Computational Model… DOI: http://dx.doi.org/10.5772/intechopen.86692
