**5. Causes of corruption**

A lot of factors can contribute to the level of corruption in a country. The human nature is selfish and at all times pursues personal gain [3]. But most precisely, the factors that can fuel corruption are, but not limited to:


2.3.1. Calibration Study

The calibration study was performed in the biomechanical–physiological lab at the Center for Health and Performance, Gothenburg, Sweden. The participants were asked to refrain from food intake and strenuous PA 3–4 h prior to measurements. Body weight and height were measured and one Axivity AX3 triaxial accelerometer (Axivity Ltd., Newcastle upon Tyne, UK) was attached over the right hip in an elastic belt around the waist and another at the middle of the front side of the right thigh using medical tape. The accelerometers were set to record data at a sample rate of 100 Hz and an acceleration range of ±8 g and the raw triaxial data was extracted with the OmGUI software (Axivity Ltd., Newcastle upon Tyne, UK). Oxygen consumption was measured using the stationary metabolic system Oxycon Pro (Jaeger, BD Corporation, Franklin Lakes, NJ, USA) where the participants breath through a face-mask with a turbine flow meter and expired air-sampler. Oxycon Pro has shown high accuracy when evaluated with the Douglas bag method [22]. The activities included consisted of seated rest in an armchair for 20 min to determine resting energy expenditure (REE) followed by 4 min standing, walking at 3, 4, 5 and 6 km·h−1 and running at 8 and 10 km·h−1 on a treadmill during 4 min at each speed without interruption, in order to reach steady-state [23]. VO2 data was collected during all 20 min and respective 4 min activities.

The triaxial acceleration data were processed using our new algorithm to produce a measure of PA intensity expressed in mg, including a band-pass filter with the cut-point range of 0.29–10 Hz that was shown to include all relevant information to assess activity intensity and to minimize inclusion of noise [17,18]. However, acceleration data was down-sampled to 30 Hz and truncated to ±6 g before processing to match the corresponding ranges of the ActiGraph GT3X+ accelerometer used in the free-living measurements. VO2 data from the 20 min of resting was filtered with a moving average filter with a window size of 2 min and the minimum value was considered the individual REE. One minute of data (accelerometer, VO2) captured between duration 2:45 and 3:45 at standing and at each treadmill speed was used for calibration. VO2net was calculated by subtracting VO2stand from VO2gross divided by body weight (mL·min−1·kg−1), while MET-values were calculated by the quotient of the VO2gross and VO2rest.

In each age-group, the relationships between Speedabs and accelerometer output (mg), Speedabs and VO2net and Speedabs and MET were investigated, as well as the relationship between Speedeq and VO2net and Speedeq and MET. The Speedeq was calculated as Speedeq = V2·g−1·h−1 (V = Speedabs (m·s−1), g = gravity (9.81 m·s−2), h = body height (m)), and represent the Speedabs performed with similar kinematical effort in individuals of different body size [8,9,15]. Smoothing splines were fitted to the data from each age group, with the intercept forced to zero VO2net or 1 MET, and zero acceleration. Based on previous biomechanical and physiological research, we made the following assumptions:

MET cut-points at 1.5, 3.0, 6.0 and 9.0 were implemented to represent LPA, MPA, VPA and very vigorous PA (VVPA), respectively, which is in line with previous literature [12]. To calibrate accelerometer data to VO2net, the first step was to determine the VO2net corresponding to 3.0, 6.0 and 9.0 METs in adults by linear regression. The next step was to apply the same VO2net cut-points (and therefore the same effort) to all three age-groups to calibrate the corresponding accelerometer mg cut-points based on fitted smoothing splines. For comparison, accelerometer mg cut-points were also determined using the traditional 1.5, 3.0, 6.0 and 9.0 METs in all three age-groups.


*2.3. Calculation Method for the Lateral Distribution of Water and Sediment Factors* 2.3.1. Transverse Distribution of the Velocity

Through analyzing a large volume of measured data from the Yellow River, we observed that the transverse distribution of velocity was mainly related to water depth. Therefore, the formula for the velocity distribution along the transverse direction was as follows:

$$\frac{V\_{\text{i}}}{V} = \mathcal{C}\_{1} \left(\frac{h\_{\text{i}}}{h}\right)^{\frac{2}{3}} \tag{7}$$

where *V* and *V*i represent the average velocity of the section and the velocity at any point, respectively; *h* represents the average section and water depth at any point, respectively; *C*1 is the section shape coefficient of ~1, which can be obtained by mass conservation.

$$\mathbf{C}\_{1} = \frac{\mathbf{Q}}{\int\_{a}^{b} \frac{V}{h^{2/3}} h\_{\mathrm{i}}^{5/3} \mathrm{d}y} \tag{8}$$

where *Q* is the average flow of the section, *y* is the transverse coordinate, and *a* and *b* are the starting point distances between the two ends of the river width of the section (*b* > *a*).

Hundreds of measured data sets from the lower Yellow River were used to verify Equation (7). The average velocity range of the section was 0.10–3.56 m/s, of which the data range covered the pre-flood and flood seasons. The results are shown in Figure 3. Equation (7) could be used to accurately calculate the transverse distribution law of velocity before flood season and during the flood season. This formula has comprehensive considerations and convenient applications.

considerations and convenient applications.

1

=

*b a Q C V h y h*

where *Q* is the average flow of the section, *y* is the transverse coordinate, and *a* and *b* are the starting point distances between the two ends of the river width of the section (*b* > *a*). Hundreds of measured data sets from the lower Yellow River were used to verify Equation (7). The average velocity range of the section was 0.10–3.56 m/s, of which the data range covered the pre-flood and flood seasons. The results are shown in Figure 3. Equation (7) could be used to accurately calculate the transverse distribution law of velocity before flood season and during the flood season. This formula has comprehensive

5/3 2/3 i d

(8)

**Figure 3.** Verification of transverse velocity distribution by flow data before, and during flood season: (**a**) Tiexie, 24 April 1966 (before flood season); (**b**) Peiyu, 23 July 1966 (flood season); (**c**) Guanzhuangyu, 1 April 1966 (before flood season); (**d**) Huayuankou, 23 May 1966 (flood season); (**e**) Tiexie, 2 July 1966 (flood season); (**f**) Guanzhuangyu, 24 July 1966 (flood season). **Figure 3.** Verification of transverse velocity distribution by flow data before, and during flood season: (**a**) Tiexie, 24 April 1966 (before flood season); (**b**) Peiyu, 23 July 1966 (flood season); (**c**) Guanzhuangyu, 1 April 1966 (before flood season); (**d**) Huayuankou, 23 May 1966 (flood season); (**e**) Tiexie, 2 July 1966 (flood season); (**f**) Guanzhuangyu, 24 July 1966 (flood season).

#### 2.3.2. Transverse Distribution of Sediment Concentration 2.3.2. Transverse Distribution of Sediment Concentration

As the non-uniformity of water depth and resistance distribution along the river width of the wandering channel is prominent, the distribution of sediment transport capacity along the river width is quite different, resulting in obvious differences in the distribution of sediment concentration along the river width in the process of sediment transport. Through analyzing a large volume of measured data of the Yellow River, Enhui et al. [25] observed that the transverse distribution law of sediment concentration is not only related to hydraulic factors and sediment concentration but also closely related to the composition of suspended sediment. The finer the suspended sediment composition, the more uniform the transverse distribution of the sediment concentration. Therefore, in addition to introducing the sediment concentration factor, the suspension index *ω*/*ku*\* was also introduced to reflect the thickness of the suspended sediment composition, and the As the non-uniformity of water depth and resistance distribution along the river width of the wandering channel is prominent, the distribution of sediment transport capacity along the river width is quite different, resulting in obvious differences in the distribution of sediment concentration along the river width in the process of sediment transport. Through analyzing a large volume of measured data of the Yellow River, Enhui et al. [25] observed that the transverse distribution law of sediment concentration is not only related to hydraulic factors and sediment concentration but also closely related to the composition of suspended sediment. The finer the suspended sediment composition, the more uniform the transverse distribution of the sediment concentration. Therefore, in addition to introducing the sediment concentration factor, the suspension index *ω*/*ku*\* was also introduced to reflect the thickness of the suspended sediment composition, and the transverse distribution formula of sediment concentration was established as follows [25]:

$$\frac{S\_1}{S} = \mathcal{C}\_2 \left(\frac{h\_1}{h}\right)^{(0.1 - 1.6\frac{\omega\_k}{k\omega\_\*} + 1.3\text{Sv})} \left(\frac{V\_1}{V}\right)^{(0.2 + 2.6\frac{\omega\_k}{k\omega\_\*} + \text{Sv})} \tag{9}$$

 ω

s s V V \* \* (0.1 1.6 1.3 ) (0.2 2.6 ) ii i 2 () () *S S Sh V ku ku C Sh V* −+ ++ = (9) where *S* and *S*i represent the average sediment concentration of the section and at any point, respectively; *S*V is the volume sediment concentration, and *S*V = *S*/2650; *h*, *h*i , *V*i , and *V* have the same meaning as previously described. *C*2 is the section shape coefficient of ~1, which could be obtained from sediment conservation.

ω

$$\mathbf{C}\_{2} = \frac{Q}{\int\_{a}^{b} q\_{\mathrm{i}} \left(\frac{\hbar\_{\mathrm{i}}}{\hbar}\right)^{(0.1-1.6\frac{\omega\_{\mathrm{k}}}{k\mu\_{\mathrm{s}}}+1.3\mathrm{S}\_{\mathrm{V}})} \left(\frac{V}{\mathcal{V}}\right)^{(0.2+2.6\frac{\omega\_{\mathrm{k}}}{k\mu\_{\mathrm{s}}}+\mathrm{S}\_{\mathrm{V}})} \mathrm{d}y} \mathrm{d}y} \tag{10}$$

where *q*i is the unit width flow at any point of the section, *ω*s is the settling velocity of particles, calculated by Equations (11)–(14) [26]; *k* is the Carmen constant, which was calculated using Equation (15); *u*\* is the average frictional velocity of the section, and *u*∗ = p *gh J*, *J* = 2‱; *Q* has the same meaning as before.

$$
\omega\_{\rm s} = \omega\_0 (1 - \frac{S\_{\rm V}}{2.25\sqrt{d\_{50}}})^{3.5} (1 - 1.25S\_{\rm V}) \tag{11}
$$

s s V V \* \*

 ω

(10)

*q y h V*

V 3.5 s0 V 50 (1 ) (1 1.25 ) 2.25 *S S*

*d*

−+ + +

$$
\omega\_0 = 2.6(\frac{\text{d}\_{\text{cp}}}{\text{d}\_{50}})^{0.3} \omega\_{\text{p}} e^{-635d\_{\text{cp}}^{0.7}} \tag{12}
$$

=− − (11)

$$
\omega\_{\rm p} = \frac{1}{18} \frac{\gamma\_{\rm s} - \gamma}{\gamma} g \frac{d\_{50}}{\nu}^2 \tag{13}
$$

$$\frac{d\_{50}}{d\_{\rm cp}} = 0.75\tag{14}$$

$$k = 0.4 - 1.68\sqrt{S\_v}(0.365 - S\_v) \tag{15}$$

More than 150 measured data sets from the lower reaches of the Yellow River were used to verify Equation (9). The average flow sediment concentration of the section ranged from 3 kg/m3 to 480 kg/m3 , including both floodplain and non-floodplain flood data (Figure 4). The verification results showed that Equation (9) could not only accurately calculate the transverse distribution law of sediment concentration in non-floodplain floods but also calculate the transverse distribution law of sediment concentration in the floodplain flood main channel, beach, and mixing area. The formula is suitable for both general and high sediment-laden flows, and the factors considered in the formula are comprehensive and easy to apply. used to verify Equation (9). The average flow sediment concentration of the section ranged from 3 kg/m3 to 480 kg/m3, including both floodplain and non-floodplain flood data (Figure 4). The verification results showed that Equation (9) could not only accurately calculate the transverse distribution law of sediment concentration in non-floodplain floods but also calculate the transverse distribution law of sediment concentration in the floodplain flood main channel, beach, and mixing area. The formula is suitable for both general and high sediment-laden flows, and the factors considered in the formula are comprehensive and easy to apply.

*Water* **2022**, *14*, x FOR PEER REVIEW 7 of 18

which could be obtained from sediment conservation.

=

\* *u ghJ* = ,*J* = 2‱; *Q* has the same meaning as before.

ω ω

*a*

*Q C*

where *S* and *S*i represent the average sediment concentration of the section and at any point, respectively; *S*V is the volume sediment concentration, and *S*V = *S*/2650; *h*, *h*i, *V*i, and *V* have the same meaning as previously described. *C*2 is the section shape coefficient of ~1,

> 2 (0.1 1.6 1.3 ) (0.2 2.6 ) i i i() () d *S S b ku ku*

where *q*i is the unit width flow at any point of the section, *ω*s is the settling velocity of particles, calculated by Equations (11)–(14) [26]; *k* is the Carmen constant, which was calculated using Equation (15); *u*\* is the average frictional velocity of the section, and

*h V*

ω

**Figure 4.** Verification of formula 9 by flood data with different sediment concentration: (**a**) low sediment concentration flood; (**b**) medium sediment concentration flood; and (**c**) high sediment concentration flood. **Figure 4.** Verification of formula 9 by flood data with different sediment concentration: (**a**) low sediment concentration flood; (**b**) medium sediment concentration flood; and (**c**) high sediment concentration flood.

#### 2.3.3. Lateral Distribution of the Suspended Sediment Composition 2.3.3. Lateral Distribution of the Suspended Sediment Composition

In natural rivers, the distribution of velocity and sediment concentration along the river width is uneven, which also leads to an uneven distribution of suspended sediment In natural rivers, the distribution of velocity and sediment concentration along the river width is uneven, which also leads to an uneven distribution of suspended sediment composition along the river width, and the suspended sediment composition in the mainstream area is generally coarse.

Based on the analysis of the measured data in the lower reaches of the Yellow River, the following formula for the distribution of the average particle size of suspended sediment along the river width was obtained:

$$\frac{d\_{\rm cpi}}{d\_{\rm cp}} = \mathcal{C}\_{\rm 3} (\frac{\mathcal{S}\_{\rm i}}{\mathcal{S}})^{0.6} \left(\frac{V\_{\rm i}}{V}\right)^{0.1} \tag{16}$$

where *d*cp is the average suspended sediment particle size of the section, *d*cpi is the average suspended sediment particle size at any point of the section, and *C*3 is the section shape coefficient, which could be obtained from the sediment conservation.

$$\mathbf{C}\_{3} = \frac{\mathbf{Q}\mathbf{S}}{\int\_{a}^{b} \left[q\_{\mathrm{i}}\mathbf{S}\_{\mathrm{i}} \left(\frac{\mathbf{S}\_{\mathrm{i}}}{\mathbf{S}}\right)^{0.6} \left(\frac{V\_{\mathrm{i}}}{V}\right)^{0.1}\right] \mathrm{d}y} \tag{17}$$

Based on the suspended sediment gradation data measured by Tiexie–Xinzhai in the lower Yellow River in 1966 and corrected according to the suspended sediment gradation correction method, the average particle size was calculated and verified using Equation (16). The average *d*cp range of the section was 0.01–0.06 mm (Figure 5). The results showed that the calculated results were satisfactory regardless of the size and concentration of suspended sand. correction method, the average particle size was calculated and verified using Equation (16). The average *d*cp range of the section was 0.01–0.06 mm (Figure 5). The results showed that the calculated results were satisfactory regardless of the size and concentration of suspended sand.

composition along the river width, and the suspended sediment composition in the main-

Based on the analysis of the measured data in the lower reaches of the Yellow River, the following formula for the distribution of the average particle size of suspended sedi-

> cpi i i 0.6 0.1 3

*d S V C*

where *d*cp is the average suspended sediment particle size of the section, *d*cpi is the average suspended sediment particle size at any point of the section, and *C*3 is the section shape

*QS C S V qS y S V*

Based on the suspended sediment gradation data measured by Tiexie–Xinzhai in the lower Yellow River in 1966 and corrected according to the suspended sediment gradation

( )()

i i 0.6 0.1 i i [ ( ) ( ) ]d

*d SV* = (16)

(17)

cp

*b a*

coefficient, which could be obtained from the sediment conservation.

3

=

*Water* **2022**, *14*, x FOR PEER REVIEW 8 of 18

stream area is generally coarse.

ment along the river width was obtained:

**Figure 5.** Verification of Formula (16) with different suspended sand particle size data: (**a**) *d*cp = 0.0196 mm; (**b**) *d*cp = 0.026 mm; (**c**) *d*cp = 0.0357 mm; (**d**) *d*cp = 0.045 mm; and (**e**) *d*cp = 0.0509 mm. **Figure 5.** Verification of Formula (16) with different suspended sand particle size data: (**a**) *d*cp = 0.0196 mm; (**b**) *d*cp = 0.026 mm; (**c**) *d*cp = 0.0357 mm; (**d**) *d*cp = 0.045 mm; and (**e**) *d*cp = 0.0509 mm.

#### 2.3.4. Sediment-Carrying Capacity of Water Flow 2.3.4. Sediment-Carrying Capacity of Water Flow

Following sediment concentration, the physical properties and turbulent structure change, which impacts the flow energy loss, velocity, and sediment concentration distribution. Therefore, to obtain a sediment-carrying capacity formula suitable for both general flow and high sediment concentration flow, it is necessary to consider the influence of sediment on flow from the energy consumption graph of secondary flow. Hongwu et al. obtained a sediment-carrying capacity formula including all suspended sediments (for alluvial rivers, R ≈ h): Following sediment concentration, the physical properties and turbulent structure change, which impacts the flow energy loss, velocity, and sediment concentration distribution. Therefore, to obtain a sediment-carrying capacity formula suitable for both general flow and high sediment concentration flow, it is necessary to consider the influence of sediment on flow from the energy consumption graph of secondary flow. Hongwu et al. obtained a sediment-carrying capacity formula including all suspended sediments (for alluvial rivers, R ≈ h):

$$S\_\* = 2.5[\frac{(0.0022 + S\_V)V^3}{k\frac{\gamma\_{\rm s} - \gamma\_{\rm m}}{\gamma\_{\rm m}}gh\omega\_{\rm s}}\ln(\frac{h}{6d\_{50}})] \tag{18}$$

m γ Equation (18) adopts kg, m, and s as the unit system.

The verification process of the formula of sediment concentration distribution along the transverse direction, the formula for suspended sediment composition distribution along the transverse direction, and the general formula for flow sediment carrying capacity is detailed in a previous report [25].

The lower Yellow River channel is constantly adjusted with changes in incoming water and sediment and strives to adapt the water and sediment transport in the riverbed to the incoming water and sediment. Adjustment of the riverbed is reflected in the adjustment of the transverse shape of the river section. The cross-section of the lower Yellow River is a compound cross-section. Different water and sediment conditions determine the adjustment form and variation range of the cross-section. At the same time, the adjustment law of the cross-section of the beach and main channel in the lower Yellow River is different. This study mainly focused on the riverbed evolution under flat discharge, and the adjustment of its cross-section is primarily reflected in the adjustment of the main channel. Therefore, the change in the main channel was analyzed here.

#### **3. Results** 3.1.1. Overall Change in the River Cross-Sectional Shape before and after Construction

**3. Results**

#### *3.1. Asymmetry of Wandering Channel without Engineering Constraints* The year 1960 was selected as the representative year for the free development river

*3.1. Asymmetry of Wandering Channel without Engineering Constraints*

channel. Therefore, the change in the main channel was analyzed here.

*Water* **2022**, *14*, x FOR PEER REVIEW 9 of 18

Equation (18) adopts kg, m, and s as the unit system.

ity is detailed in a previous report [25].

3.1.1. Overall Change in the River Cross-Sectional Shape before and after Construction bend without engineering constraints, and the year 2019 was selected as the representa-

The verification process of the formula of sediment concentration distribution along the transverse direction, the formula for suspended sediment composition distribution along the transverse direction, and the general formula for flow sediment carrying capac-

The lower Yellow River channel is constantly adjusted with changes in incoming water and sediment and strives to adapt the water and sediment transport in the riverbed to the incoming water and sediment. Adjustment of the riverbed is reflected in the adjustment of the transverse shape of the river section. The cross-section of the lower Yellow River is a compound cross-section. Different water and sediment conditions determine the adjustment form and variation range of the cross-section. At the same time, the adjustment law of the cross-section of the beach and main channel in the lower Yellow River is different. This study mainly focused on the riverbed evolution under flat discharge, and the adjustment of its cross-section is primarily reflected in the adjustment of the main

The year 1960 was selected as the representative year for the free development river bend without engineering constraints, and the year 2019 was selected as the representative year under the action of the limited control boundary. According to the asymmetry index formula proposed above, the asymmetry of the cross-sectional morphology of the freedevelopment river bend without engineering constraints in 1960 and the river channel under the action of the limited control boundary in 2019 in the wandering section of the lower Yellow River was calculated (Figure 6). In 1960, most of the asymmetry indexes of the cross-section between Tiexie and Gaocun in the wandering section of the lower Yellow River were in the range of 1.01–1.50 and the average value of the asymmetry indexes of the entire wandering section was 1.19. Following construction of the project, most of the cross-sectional shape asymmetry indexes of the river reach in 2019 were in the range of 1.10–1.70 and the average value of the asymmetry indexes of the entire wandering section during this period was 1.33, indicating that there was a certain asymmetry in the crosssection shape of the river before and after the construction project and the asymmetry of the cross-section shape of the river after the construction project was greater than that without the project, and that the river after the construction project was constrained by the project boundary and the asymmetry of the cross-sectional shape was more prominent. tive year under the action of the limited control boundary. According to the asymmetry index formula proposed above, the asymmetry of the cross-sectional morphology of the free-development river bend without engineering constraints in 1960 and the river channel under the action of the limited control boundary in 2019 in the wandering section of the lower Yellow River was calculated (Figure 6). In 1960, most of the asymmetry indexes of the cross-section between Tiexie and Gaocun in the wandering section of the lower Yellow River were in the range of 1.01–1.50 and the average value of the asymmetry indexes of the entire wandering section was 1.19. Following construction of the project, most of the cross-sectional shape asymmetry indexes of the river reach in 2019 were in the range of 1.10–1.70 and the average value of the asymmetry indexes of the entire wandering section during this period was 1.33, indicating that there was a certain asymmetry in the cross-section shape of the river before and after the construction project and the asymmetry of the cross-section shape of the river after the construction project was greater than that without the project, and that the river after the construction project was constrained by the project boundary and the asymmetry of the cross-sectional shape was more prominent.

**Figure 6. Figure 6.**  Asymmetry of channel cross-section in wandering section of the lower Yellow River. Asymmetry of channel cross-section in wandering section of the lower Yellow River.

3.1.2. Calculation of the Asymmetry Index of Water and Sediment Factors in the Free Developing River Bend

In the 1950s and the 1960s, the lower reaches of the Yellow River belonged to a typical wandering channel. The channel was wide and shallow, scattered, densely covered with sandbars, the mainstream fluctuated, and the river regime changed sharply. It was difficult to determine the obvious and compliant curved top and transition sections. The planned river regulation in the wandering section of the lower Yellow River began in the 1970s and 1980s. Therefore, the lower Yellow River before 1980 can be regarded as a quasifree development bend in the period without engineering constraints. Therefore, 1979 was selected as the representative year for the free development of the bend before the construction of the wandering section of the lower Yellow River. To study the asymmetry of the distribution of water and sediment factors in a typical section of a free developing river, we selected the typical section based on two principles: (a) the river regime is relatively stable and (b) at the reach where the mainstream swing is obvious, a relatively obvious bend is observed as the bend top section, and the mainstream in the transition section is relatively stable.

Based on these principles, the section between the Heishi River channel in the wandering section of the lower Yellow River was selected as the representative section (Figure 7). According to the river regime map before the flood in 1979 and the measured large section

data of the section, the Liuyuankou and Jiahetan river channels were selected as the representative sections of the transition section, and Heishi, Gucheng, and Mazhai were selected as the representative sections of the bend top section without considering the variation of gradient along the river width, and the gradient value was 2‱and the roughness values were 0.01, 0.012, and 0.015, respectively. According to Manning's formula, the velocity was calculated, the discharge was inversely deduced, and the calculated flat discharge was 5000 m3/s. The flat water level, flat area, and other characteristic parameters of each section were calculated, and the transverse distribution of each water and sediment factor was calculated using Equations (6), (8), (15), and (17). Finally, the scouring and silting balance (*S* = 23 kg/m 3 ) of each section of the Heishi River section was determined using Equations ((1)–(5)) (scouring (*S* = 5 kg/m3 ), siltation (*S* = 50 kg/m3 )). The asymmetry indexes of the cross-sectional shape and water sediment factors under the three states and the calculation results of the asymmetry indexes under the three states were not different (Table 1). *Water* **2022**, *14*, x FOR PEER REVIEW 11 of 18

**Figure 7.** Wandering reach of the lower Yellow River (Heishi–Hedao): ① Sanguanmiao control project ② Weitan control project ③ Liuyuankou extension project ④ Dagong project ⑤ WANGan project ⑥ Gucheng project ⑦ Guantai project ⑧ Jiahetan project ⑨ Zhouying project ⑩ Laojuntang project ⑪ Yulin project ⑫ Wuzhuang vulnerable project ⑬ Huangzhai vulnerable project ⑭ Huozhai vulnerable project ⑮ Baocheng vulnerable project ⑯ Hedao project ⑰ Sanhecun project. A. Heishi section, B. Liuyuankou section, C. Gucheng section, D. Jiahetan section, E. Mazhai section, and F. Hedao section. **Figure 7.** Wandering reach of the lower Yellow River (Heishi–Hedao): 1 Sanguanmiao control project 2 Weitan control project 3 Liuyuankou extension project 4 Dagong project 5 WANGan project 6 Gucheng project 7 Guantai project 8 Jiahetan project 9 Zhouying project 10 Laojuntang project 11 Yulin project 12 Wuzhuang vulnerable project 13 Huangzhai vulnerable project 14 Huozhai vulnerable project 15 Baocheng vulnerable project 16 Hedao project 17 Sanhecun project. A. Heishi section, B. Liuyuankou section, C. Gucheng section, D. Jiahetan section, E. Mazhai section, and F. Hedao section.

**Table 1.** Asymmetry index of the Heishi–Hedao river reach. **Asymmetry Index Heishi (Bend Top Section) Liuyuankou (Transition Section) Gucheng (Bend Top Section) Jiahetan (Transition Section) Mazhai (Bend Top Section) Hedao (Transition Section)**  *AS*A 1.37 1.13 1.45 1.14 1.53 1.21 *AS*V 1.22 1.08 1.29 1.10 1.43 1.14 *AS*S 1.07 1.03 1.10 1.02 1.15 1.05 *AS*dcp 1.06 1.02 1.08 1.01 1.09 1.05 *AS*S\* 1.30 1.11 1.38 1.13 1.43 1.19 Table 1 shows that: (a) the asymmetry index of each section under the three scouring and silting states was >1, indicating that the river cross-section and the distribution of water and sediment factors during the free development period had certain asymmetry. (b) There was no obvious difference in the calculation results of asymmetry indexes of each section under the three scouring and silting states, indicating that the overall change in the asymmetry of the channel cross-sectional shape and water and sediment distribution under different scouring and silting states during the period of free development of the river bend was small. (c) Each asymmetry index of the section at the top of the river bend was significantly greater than that of the transition section, indicating that during the period of free development of the river bend, the shape and water and sediment distribution of the

Table 1 shows that: (a) the asymmetry index of each section under the three scouring

(b) There was no obvious difference in the calculation results of asymmetry indexes of each section under the three scouring and silting states, indicating that the overall change in the asymmetry of the channel cross-sectional shape and water and sediment distribution under different scouring and silting states during the period of free development of the river bend was small. (c) Each asymmetry index of the section at the top of the river bend was significantly greater than that of the transition section, indicating that during the period of free development of the river bend, the shape and water and sediment distribution of the section at the top of the river bend were more asymmetric than that of the

transition section.

section at the top of the river bend were more asymmetric than that of the transition section. **Table 1.** Asymmetry index of the Heishi–Hedao river reach.

Table 2 shows the verification of erosion and deposition balance, erosion, and deposition of each section of the Heishi River reach. The results showed that when the flow was 5000 m3/s, the sediment transport of each representative section under different scouring and silting states had the following laws: (a) when the sediment concentration was 23 kg/m3 , at left and right, the distribution of sediment concentration in the whole reach was relatively uniform, and the river channel was basically in the balance state of erosion and deposition, which is manifested in the micro-scouring state of the section at the top of the bend and the micro silting state of the section at the transition section. (b) When the sediment concentration was 5 kg/m3 , the whole reach was in the entire cross-section scouring state at the left and right. (c) When the sediment concentration was 50 kg/m3 , the whole reach was in the full section siltation state. According to the verification results, the calculation results of river flow sediment-carrying capacity under various scouring and silting states reflect the distribution of water and sediment factors in each section.

**Table 2.** Verification of scouring and silting state of each section of Heishi–Hedao river reach (5000 m3/s).

*3.2. Asymmetry of Wandering Channel under Finite Control Boundary*

3.2.1. Asymmetry of Channel Cross-Sectional Shape

The typical reach of the wandering section of the lower Yellow River was selected to study the asymmetry of the river cross-section under the action of finite engineering. The section selection principles were as follows: (a) the river regime of the reach is relatively stable; (b) the curved top section works are closely combined with the water flow, the main sliding works are better, and the river regime in the transition section is relatively stable. Based on these principles, the section between Fanzhuang and Yuanfang in the wandering section of the lower Yellow River was selected as the representative section (Figure 8). According to the river regime map before the flood season in 2018 and the measured large section data, the cross-sectional asymmetry indexes of the bend top section and transition section with good engineering slip in this section were statistically analyzed (Table 3). According to the river regime map, the sections of Sizhuang and Chenqiao are at the top of the bend, and the project is relatively smooth. The three sections of Fanzhuang, Gucheng, and Yuanfang are the transition section between the two curved tops. As shown in Table 3, compared with the transition section, the cross-section at the bend top section

had a stronger asymmetry. This shows that the shape of the river cross-section was more asymmetric under the action of a limited control boundary. *Water* **2022**, *14*, x FOR PEER REVIEW 13 of 18

> **Figure 8.** Wandering reach of the lower Yellow River (Fanzhuang–Yuanfang): ⑱ Liuyuankou extension project ⑲ Dagong project ⑳ Wangan project ㉑ Gucheng project ㉒ Fujunshi project G. Fanzhuang section, H. Sizhuang section, I. Gucheng section, J. Chenqiao section, and K. Yuanfang **Figure 8.** Wandering reach of the lower Yellow River (Fanzhuang–Yuanfang): 18 Liuyuankou extension project 19 Dagong project 20 Wangan project 21 Gucheng project 22 Fujunshi project G. Fanzhuang section, H. Sizhuang section, I. Gucheng section, J. Chenqiao section, and K. Yuanfang section.

> section. 3.2.2. Asymmetric Distribution of Water and Sediment Factors in the River Channel **Table 3.** Asymmetry index of wandering river bend top and transition section (scouring and silting balance, *S* = 32 kg/m3 ).

the reach and the distribution of water and sediment factors had a certain asymmetry. (2) The calculation results of cross-sectional erosion, deposition balance, and erosion state 3.2.2. Asymmetric Distribution of Water and Sediment Factors in the River Channel

were basically the same, which shows that the asymmetric distribution of river factors changed slightly under the two erosion and deposition states. Compared with these two states, in the state of cross-section deposition, the cross-sectional asymmetry index at the transition increased and the cross-section asymmetry index at the bend top decreased, indicating that in the state of cross-section deposition, the cross-section riverbed deformation at the bend top was small and the cross-section riverbed deformation at the transition was large. (3) Each asymmetry index of the section at the bend top of the river section was larger than that at the transition section, indicating that after the construction project, the distribution of water and sediment factors at the bend top of the river section was more asymmetric than that at the transition section. These results resembled the asymmetric results of the downstream swing channel without engineering constraints. The difference was that after construction of the project, compared with the cross-section scouring and silting balance and scouring state, the cross-To further analyze the influence of the asymmetric change in the cross-sectional shape on the asymmetry of river water and sediment-transport capacity, we selected the Fanzhuang–Yuanfang section of the lower Yellow River as the representative section. The gradient value was 2‱and the flat discharge was 5000 m3/s. The asymmetry indexes of water and sediment factors under various scouring and silting conditions at each section of the Fanzhuang–Yuanfang reach were calculated, as shown in Tables 3–5. The results showed that: (1) the asymmetry indexes of water and sediment factors in the Fanzhuang–Yuanfang reach were >1, indicating that after the construction project, the cross section of the reach and the distribution of water and sediment factors had a certain asymmetry. (2) The calculation results of cross-sectional erosion, deposition balance, and erosion state were basically the same, which shows that the asymmetric distribution of river factors changed slightly under the two erosion and deposition states. Compared with these two states, in the state of cross-section deposition, the cross-sectional asymmetry index at the transition

section riverbed deformation at the bend top was smaller and the cross-section riverbed

increased and the cross-section asymmetry index at the bend top decreased, indicating that in the state of cross-section deposition, the cross-section riverbed deformation at the bend top was small and the cross-section riverbed deformation at the transition was large. (3) Each asymmetry index of the section at the bend top of the river section was larger than that at the transition section, indicating that after the construction project, the distribution of water and sediment factors at the bend top of the river section was more asymmetric than that at the transition section.

**Table 4.** Asymmetry index of wandering river bend top and transition section (scouring state, *S* = 5 kg/m3 ).

**Table 5.** Asymmetry index of wandering river bend top and transition section (silting state, *S* = 90 kg/m3 ).

These results resembled the asymmetric results of the downstream swing channel without engineering constraints. The difference was that after construction of the project, compared with the cross-section scouring and silting balance and scouring state, the crosssection riverbed deformation at the bend top was smaller and the cross-section riverbed deformation at the transition was larger in the cross-section silting state.

Table 6 shows the verification of the erosion and deposition balance, erosion, and deposition of each section. The difference between the set sediment concentration and the calculated sediment-carrying capacity of the section under various states was small, indicating that the above calculation reflected the distribution state of water and sediment factors of each section.

Based on the above calculation results, when the flow was 5000 m3/s, under the condition of different sediment concentrations, the sediment transport of each section obeyed the following laws: (a) when the sediment concentration was 32 kg/m3 at the left and right, the sediment concentration distribution of the entire river section was relatively uniform and the river channel was basically in a balanced state of erosion and deposition. In particular, the section at the top of the bend was in a state of micro-erosion, and the

section at the transition section was in the state of micro-deposition. (b) When the sediment concentration was 5 kg/m3 , the entire reach was in a full cross-section scouring state on the left and right. (c) When the sediment concentration was 90 kg/m3 , the entire reach was in the full section siltation state. According to the calculation results of sediment concentration and sediment-carrying capacity under various scouring and silting states at a flow of 5000 m3/s before and after the construction project, the sediment concentration and sediment-carrying capacity under various scouring and silting states improved after the construction of the project, which indicated that the construction of a river regulation project could improve the sediment transport capacity of the river after enhancing the control effect on river regime stability.

#### **4. Discussion**


**Access to Clinical Trials Closer to Home Using Telehealth Tele-health**

**Access to Clinical Trials Closer to Home Using**

DOI: 10.5772/intechopen.70205

Sabe Sabesan and John Zalcberg

Sabe Sabesan and John Zalcberg Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.70205

#### **Abstract**

The purpose of this chapter is to outline key considerations for increasing access to clinical trials for people with cancer living in rural and remote locations, and outline the contribution of tele-health models to facilitate study activity across rural and remote locations. Regional and rural group of the Clinical Oncology Society of Australia (COSA), the peak multidisciplinary cancer clinician body in Australia, has developed the Australasian Teletrial Model in collaboration with its stakeholders to improve rural access to clinical trials. Benefits of this model are not limited to regional, rural and remote systems. This model has the potential to connect larger centres even within the same city and improve the rate of recruitment of highly specialised clinical trials, including rare cancer trials. This model has been developed in consideration of the requirements for the proper conduct of clinical trials ensuring the protection of the rights and safety of trial participants and quality data for the demonstration of safe and efficacious cancer treatments. Ethical and safe conduct of clinical trials using this model requires that the following aspects are considered and addressed by implementation plans.

**Keywords:** clinical trials, tele-medicine, rural, tele-trials, tele-oncology

### **1. Introduction**

Access to specialist cancer care services is a significant issue faced by residents of rural, remote, indigenous and some regional communities in countries with large rural and outer metropolitan populations [1]. For these communities, the lack of access to specialist services may be due to a lack of specialist oncologists locally, limited scope of practice of other rural health professionals and/or overall rural workforce shortages. Poor access to such specialised health care services could be one of the contributors to the disparity in survival and

Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 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, provided the original work is properly cited.

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons

disease-related outcomes that exist between metropolitan and non-metropolitan patients [2–5], although the authors acknowledge this issue as complex and may also relate to other factors such as behavioural or cultural factors.

It is recommended by leading authorities, such as the National Comprehensive Cancer Network (www.nccn.org) and Cancer Research UK [6], that support for the provision of clinical trials to people diagnosed with cancer is a core component of providing optimal cancer care through specialist cancer centres, hospitals and other treatment facilities. Indeed, in many cases such guidelines recommend participation in clinical trials as the best option for many cancer patients.

Clinical trials offered to people diagnosed with cancer may include new and experimental drug therapies or imaging technologies, minimally invasive diagnostic or surgical techniques, or supportive care interventions. However, as with access to specialist care, patients living outside of major metropolitan centres face many barriers in accessing clinical trials. Barriers to participation include the limited availability of trial sites closer to home and the increased cost and inconvenience of travel to major centres where the trials are taking place [7, 8].

When a patient is assessed as fit for chemotherapy or targeted therapy, medical oncologists write the care plan and send the prescriptions to rural sites where chemotherapy is given by chemotherapy-competent nurses. Where electronic systems are available, care plans are made and approved online. For oral chemotherapy, authority scripts are sent by medical oncologists to patients, rural hospitals or the local pharmacy after appropriate education by medical oncologists, nurses or pharmacists. Prior to the clinic, informed consent for participation in

**Figure 1.** A model of a rural specialist unit with specialist support via tele-medicine model of care. Sabesan et al. EJCC,

Access to Clinical Trials Closer to Home Using Tele-health

http://dx.doi.org/10.5772/intechopen.70205

159

While the models mentioned above are largely medical tele-health models, models such as the Queensland Remote Chemotherapy Supervision (QReCS) model [19] enables rural generalist nurses to administer chemotherapy at rural sites with the support of the rural generalist doctors and pharmacists, under the supervision of medical oncologists and chemotherapy-competent nurses from larger centres using tele-medicine and tele-nursing respectively (**Figure 2**) [20].

the tele-oncology clinic is obtained from the patients.

**1.2. Remote chemotherapy supervision model**

**Figure 2.** Remote chemotherapy supervision model.

2015.

While it may be reasonable to establish clinical trials units in large regional cancer treatment centres, the logistics of maintaining a suitably trained workforce and undertaking the ethical and regulatory responsibilities of clinical trials may be difficult in smaller rural and regional sites with limited resources and low patient numbers.

Tele-oncology models of care have been shown to satisfy many specialist health care needs of rural and regional patients in countries with large rural populations [1]. Using tele-oncology models, many cancer centres have been able to facilitate the administration of complex chemotherapy in rural and regional areas [9–11]. Around the world, such centres have implemented safe and successful tele-oncology models that are acceptable to patients, families and health professionals, saved money for health service provision and enhanced the capabilities of rural health systems in oncology services to provide cancer care [10, 12–17]. In addition, cancer services can be delivered to rural patients closer to home in a timely manner [18]. Teleoncology models of care may outline a system-level intervention to address issues of equity and access to clinical trials. For example, adopting this model would enable rural and regional sites with limited resources to provide access to Phase III comparative effectiveness studies and potentially trials of new and novel therapies for the local population.

This document outlines a feasible and effective tele-health strategy to increase access to clinical trials closer to home, while at the same time ensuring the proper conduct of cancer clinical trials.

#### **1.1. Overview of established clinic and treatment models of tele-oncology in Australia and globally**

Similar to most of the specialist tele-health models around the world, the Townsville teleoncology [15] model enables medical oncologists from Townsville, Australia to provide their services to rural sites, using traditional videoconferencing technology or web-based systems (**Figure 1**). At larger rural centres, rurally-based doctors, chemotherapy-competent nurses and allied health workers accompany patients during tele-consultations. At other rural sites, patients are accompanied by either a doctor or a nurse for post-treatment reviews, toxicity reviews or follow-up visit(s) tele-consultations [12].

**Figure 1.** A model of a rural specialist unit with specialist support via tele-medicine model of care. Sabesan et al. EJCC, 2015.

When a patient is assessed as fit for chemotherapy or targeted therapy, medical oncologists write the care plan and send the prescriptions to rural sites where chemotherapy is given by chemotherapy-competent nurses. Where electronic systems are available, care plans are made and approved online. For oral chemotherapy, authority scripts are sent by medical oncologists to patients, rural hospitals or the local pharmacy after appropriate education by medical oncologists, nurses or pharmacists. Prior to the clinic, informed consent for participation in the tele-oncology clinic is obtained from the patients.

#### **1.2. Remote chemotherapy supervision model**

disease-related outcomes that exist between metropolitan and non-metropolitan patients [2–5], although the authors acknowledge this issue as complex and may also relate to other

It is recommended by leading authorities, such as the National Comprehensive Cancer Network (www.nccn.org) and Cancer Research UK [6], that support for the provision of clinical trials to people diagnosed with cancer is a core component of providing optimal cancer care through specialist cancer centres, hospitals and other treatment facilities. Indeed, in many cases such guidelines recommend participation in clinical trials as the best option for

Clinical trials offered to people diagnosed with cancer may include new and experimental drug therapies or imaging technologies, minimally invasive diagnostic or surgical techniques, or supportive care interventions. However, as with access to specialist care, patients living outside of major metropolitan centres face many barriers in accessing clinical trials. Barriers to participation include the limited availability of trial sites closer to home and the increased cost

While it may be reasonable to establish clinical trials units in large regional cancer treatment centres, the logistics of maintaining a suitably trained workforce and undertaking the ethical and regulatory responsibilities of clinical trials may be difficult in smaller rural and regional

Tele-oncology models of care have been shown to satisfy many specialist health care needs of rural and regional patients in countries with large rural populations [1]. Using tele-oncology models, many cancer centres have been able to facilitate the administration of complex chemotherapy in rural and regional areas [9–11]. Around the world, such centres have implemented safe and successful tele-oncology models that are acceptable to patients, families and health professionals, saved money for health service provision and enhanced the capabilities of rural health systems in oncology services to provide cancer care [10, 12–17]. In addition, cancer services can be delivered to rural patients closer to home in a timely manner [18]. Teleoncology models of care may outline a system-level intervention to address issues of equity and access to clinical trials. For example, adopting this model would enable rural and regional sites with limited resources to provide access to Phase III comparative effectiveness studies

This document outlines a feasible and effective tele-health strategy to increase access to clinical trials closer to home, while at the same time ensuring the proper conduct of cancer clinical trials.

**1.1. Overview of established clinic and treatment models of tele-oncology in Australia**

Similar to most of the specialist tele-health models around the world, the Townsville teleoncology [15] model enables medical oncologists from Townsville, Australia to provide their services to rural sites, using traditional videoconferencing technology or web-based systems (**Figure 1**). At larger rural centres, rurally-based doctors, chemotherapy-competent nurses and allied health workers accompany patients during tele-consultations. At other rural sites, patients are accompanied by either a doctor or a nurse for post-treatment reviews, toxicity

and inconvenience of travel to major centres where the trials are taking place [7, 8].

and potentially trials of new and novel therapies for the local population.

factors such as behavioural or cultural factors.

sites with limited resources and low patient numbers.

reviews or follow-up visit(s) tele-consultations [12].

many cancer patients.

158 Clinical Trials in Vulnerable Populations

**and globally**

While the models mentioned above are largely medical tele-health models, models such as the Queensland Remote Chemotherapy Supervision (QReCS) model [19] enables rural generalist nurses to administer chemotherapy at rural sites with the support of the rural generalist doctors and pharmacists, under the supervision of medical oncologists and chemotherapy-competent nurses from larger centres using tele-medicine and tele-nursing respectively (**Figure 2**) [20].

**Figure 2.** Remote chemotherapy supervision model.