https://orcid.org/0000-0001-6001-8411
Abstract
Flow in streams and rivers typically erodes the banks, causing channel bank migration laterally, resulting in loss of nearby land, modification in channel morphology, excessive sediment transport, and water quality degradation. A spur dike is a hydraulic structure placed at the channel bank projecting outward to guide or divert the flow away from the bank, thus protecting it from erosion. The stability of the riverbed and banks is influenced by turbulent characteristics such as three-dimensional velocity distribution, turbulent kinetic energy, Reynolds shear stress, turbulent intensity, and bed shear stress. The researchers found that these turbulence parameters are instrumental in sediment movement along the channel's bed and from its banks. Spurs dikes are a significant river training structure provided along the river bank to protect from erosion. Several aspects related to spur dikes, such as their geometry, physical features, design considerations, flow and scour patterns, etc., are critically reviewed in this paper. Despite the numbers of literature in the field of turbulent characteristics and scour depth around spur dike, the role of vegetation and the effect of seepage around spur dike still remains an unexplored area. These knowledge gaps of spur dikes in field conditions are discussed for future studies.
HIGHLIGHTS
Assessment of spur performance for bank erosion control.
Details of spur types and design criteria discussed.
The gaps in current knowledge about spurs identified.
Future research direction regarding the effect of seepage and vegetation on spur performance is presented.
INTRODUCTION
Rivers flow through various landform terrains, starting from the rocky, boulder, and alluvial stage to the delta stage. In the rocky and boulder stage rivers pass through boulders and rocks, which are hard to displace. However, in the alluvial stage river comes across different sediment particles ranging from larger sand to clay and silt. These particles in alluvial stages are susceptible to erosion and get transported downstream along the river flow, causing erosion. The removal of bank soil particles by flow velocity generates shear in the bank, one of the primary mechanisms causing riverbank erosion (Gholami & Khaleghi 2013).
Riverbank erosion is one of the most common causes of bank instability. While bank erosion increases the width of the channel, deposition decreases it. However, these processes do not occur, therefore, the river width constantly fluctuates. Some structures in the stream, such as levees, guide banks, spur dikes, etc., are constructed to maintain the channel's width and protect the river bank from erosion. The preference of a structure over the other depends on the condition in which the structure will be constructed. Each has its advantages and disadvantages, generally governed by factors such as bank condition, type of soil present in the bank, slope of the bank, channel curvature, etc. When compared to other riverbank erosion prevention techniques, spur dikes provide one of the best solutions (El-Rashedy et al. 2018).
Spur dike protects a bend in the Gamka River at Calitzdorp, South Africa (King 2009).
Photos captured downstream of the spur dike before, during, and after the floods in 2008, showing the minimal damage caused by the flood (King 2009).
Photos captured downstream of the spur dike before, during, and after the floods in 2008, showing the minimal damage caused by the flood (King 2009).
It is essential to know what causes riverbank erosion in order to prevent it. Researchers studied and found that the nature of flow turbulence is the main reason for bank erosion and sediment transportation. The stability of the bed and banks is highly influenced by factors relating to turbulent flow, including the three-dimensional distribution of velocity, turbulent kinetic energy, Reynolds shear stress, turbulent intensity, and bed shear stress.
Turbulence plays a significant role in enhancing sediment transport from or around the structures, which may cause the failure of the structure. To ensure these structures’ safety and prevent bank erosion, studying the behavior of turbulent flow parameters around these structures becomes imperative. This paper is a comprehensive review of studies on several aspects associated with spur dikes and knowledge development. In this paper, we have critically reviewed the current state of the art on the influence of turbulent characteristics on the bed and bank stability of spur dikes. Based on the current knowledge, we have identified and discussed vital research areas which are still not sufficiently explored, such as the effect of seepage and vegetation in the channel.
CLASSIFICATION OF SPUR DIKES
Spur dikes can be classified based on:
construction methods;
submergence conditions
geometry;
interaction with the flow field.
Based on permeability, there are two types of spur dikes: permeable and impermeable spur dikes. Permeable spur dikes are often built of one or more rows of steel, bamboo, timber, or RCC piles. Permeable spur dikes are usually applied as temporary structures and are cheaper. Impermeable spur dikes are generally built of readily available materials such as stones, gravel, rocks, and local materials. An impermeable spur dike generally restricts and diverts the incoming flow. On the other hand, a permeable spur dike allows the flow to pass through it at a low velocity (Shampa et al. 2020; Iqbal et al. 2021; Mirzaei et al. 2021; Tripathi & Pandey 2021, 2022).
A submerged spur dike is fully immersed in water, whereas non-submerged spur dikes are partially submerged in water. Based on the shape of the head the spur dike can be classified into various categories such as straight, L-shape (for which the head of the structure turns downstream parallel to the streamflow), T-shape, or hammer-head (for which the head of the structure turns in both sides upstream and downstream), hockey, and molehead spur dikes.
Based on the alignment, spur dikes are categorized into three types: attracting, deflecting, and repelling spur dikes. An attracting spur dike inclines towards the downstream with the bank and tends to attract the flow toward the bank, but a repelling spur dike tilts the flow in the upstream direction itself, causing the flow to divert away from the bank. A deflecting spur dike or transverse dike is fixed perpendicular, extending from the bank into the river to deflect the current away from the bank as shown in Figure 3.
GENERAL GUIDELINES FOR SPUR DESIGN AND RECOMMENDATIONS
The essential elements that are frequently considered while designing spur dikes include plan view shape, length, spacing between adjacent spur dikes, orientation, channel cross-section, crest height, the material used for construction, and riprap size (Richardson et al. 1975; Brown 1985; Yossef 2002) as described in Figure 4. The design methods used to construct the spur dikes may differ, but they all serve the common purpose of providing bank protection at a specific channel section. The most significant characteristics to consider are discussed below.
Planview shape
Spur dikes can be built using various plan view shapes. Some examples include straight (rectangular) spur dike, hockey stick or curved, inverted hockey stick spur dike, L-head, straight spur dike with pier head, and T-head. Compared to other shapes of spur dikes, the rectangular shape is one of the most cost-effective constructions. It has received significant attention from researchers because its installation is more effortless in both the field and the laboratory. Thus, researchers mainly utilize rectangular shape spur dikes (summarized in Table 1) to study flow characteristics around the spur dike. Although other shapes of the spur are also explored, their implementation is limited. Kuhnle et al. (2008) used a trapezoidal spur dike to observe flow velocities in a laboratory flume around a submerged spur dike. Hashemi et al. 2008) confirmed that the scour depth formed around spurs is less in L-shaped spurs than in other shapes. El-Rashedy et al. (2016) analyzed the effect of discharge and Froude number on the scouring process around the different shapes of spur dikes, such as straight, hockey, mole head, L-shape, and T-shape. Experiments suggest that a hockey shape spur dike performs better in reducing scour depth. Kumar & Ojha (2019a, 2019b) investigated turbulent flow characteristics, and equilibrium scour depths around an un-submerged L-head spur dike using varying structure compositions along with different groyne configurations and constriction ratios. The flow patterns near in-stream rock structures were studied using single-arm rock vanes (at 20 and 30°), J-hook vane (at 30°), and bend way weirs (at 80 and 60°) with the help of large-eddy simulation along with the laboratory experiments (Kang et al. 2021a). The properties of the water surface profile and flow velocity surrounding the spur dikes of five distinct shapes, including the trapezoidal section arc straight head, the trapezoidal section arc hook head, the trapezoid section fan straight head, the trapezoidal section fan hook head, and the arc section straight head, were analyzed by Yu et al. (2020). In contrast, studies in the last decade suggest that the spur dike of T-shape has the least amount of scouring among all geometric shapes of spur dikes (Vaghefi et al. 2012, 2015, 2018, 2019; Safarzadeh et al. 2016; Vaghefi et al. 2016a, 2016b; Mehraein et al. 2017; Tripathi & Pandey 2021). Furthermore, Bahrami-Yarahmadi et al. (2020) employed the triangular spur dike to examine the scour pattern developed around it and suggested that it can reduce scouring at spur dike tips.
A summary of the geometric and hydraulic conditions of previous experiments and simulations
| S.no | Authors | Shape of spur | Single/series | Orientation | Experimental/numerical | Model/method used | Re (Reynolds Number) | Fr (Froude number) |
|---|---|---|---|---|---|---|---|---|
| 1 | Giri et al. (2004) | Rectangular | SERIES (3) | 90° | Numerical simulations were substantiated using the measured experimental data (ADV) | 2-D numerical model | 20,000 | |
| 2 | Kuhnle et al. (2008) | Trapezoidal | SINGLE | 90° | Simulated numerically & Compared with experimental data (ADV) | finite element method (k–ε turbulent model) | 0.2 | |
| 3 | Duan (2009) | Rectangular | SINGLE | 90° | Experimental (ADV) | 48,483 | ||
| 4 | Yazdi et al. (2010) | Rectangular | SINGLE | 70, 90, 110° | Numerical results verified through the experimental data (ADV) | Fluent (k–ε turbulent model) | ||
| 5 | Duan et al. (2011) | Rectangular | SINGLE | 90° | Experimental (ADV) | 84,059 and 53,157 | ||
| 6 | Koken & Gogus (2015) | Rectangular | SINGLE | 90° | Numerical simulation (DES) | DES | 45,000 | |
| 7 | Safarzadeh et al. (2016) | Rectangular and T-shape | SINGLE | 90° | Experimental (ADV) | 60,000 | 0.35 | |
| 8 | Vaghefi et al. (2016b) | T-shape | SINGLE | 60, 90, 120° | Numerical results verified through the experimental data (ADV) | SSIIM CFD software, Navier–Stokes equation, and k–ε turbulence model | ||
| 9 | Mehraein et al. (2017) | T-SHAPED | SINGLE | 90° | Experimental (ADV) | 34,000 | 0.38 | |
| 10 | Kang (2018) | Rectangular | SINGLE | 90° | LES are compared with the experiment (ADV) | LES | 3.00 × 104 | 0.1 |
| 11 | Jeon & Lee (2018) | Rectangular | SINGLE | 90° | Experimental (ADV) | LES | 3.00 × 104 and 6.59 × 104 | 0.10 and 0.90 |
| 12 | Vaghefi et al. (2018) | T-shape | SINGLE | 45° attractive and repelling | Numerical simulation of the experimental model (ADV) | CFD-RNG k-E turbulent model | ||
| 13 | Kumar & Ojha (2019a) | L-head | SINGLE | 90° | Experimental (ADV) | 25,000 − 44,000, | 0.34 − 0.39 | |
| 14 | Kumar & Ojha (2019b) | L-head | SINGLE | 90° | Experimental (ADV) | 3.9 × 104 | 0.34 | |
| 15 | Bahrami-Yarahmadi et al. (2020) | Rectangular and Triangular | SERIES (4) | 90° | Experimental (EVM) | 0.176, 0.196, 0.216, and 0.235 | ||
| 16 | Shampa et al. (2020) | Slit-type permeable spur dike | Series of slit-type spurs (5) | 60, 90, 120° | Numerical simulations (PIV) substantiated using the measured experimental data (EVM) | 3D RANS; k-ω SST | 34,430 | 0.71 |
| 17 | Kang et al. (2021a) | J-hook vanes, Rock vanes, and bendway weirs | SINGLE | rock vanes-20, 30° J-hook vane-30° bendway weirs-60,80° | Large-eddy simulation (LES) and flume experiments (ADV) | LES | 4.08 × 104 | 0.19 |
| 18 | Mirzaei et al. (2021) | SINGLE | 90° | Numerical simulation is compared with experimental results | FLOW 3D-LES turbulence model | |||
| 19 | Jafari & Sui (2021) | Rectangular | SERIES (2) | 90, 60, and 45° | Experimental (ADV) | 0.19, 0.15, 0.10 | ||
| 20 | Akbari et al. (2021) | T-shape | SINGLE | 60, 89, 91, and 150° | Experimental (ADV) | 67,857 | 0.34 | |
| 21 | Lodhi et al. (2021) | Rectangular | SINGLE | 90° | Experimental (ADV) | 87,474 | 0.65 | |
| 22 | Kang et al. (2021b) | Rectangular | SINGLE | 90° | Numerical simulation & Experimental (ADV) | LES | 3.00 × 104 | 0.1 |
| 23 | Kafle (2021) | Rectangular | SERIES | 90° | Numerical simulation | CFD– model Nays 2D | ||
| 24 | Iqbal et al. (2021) | Rectangular | SERIES | 90° | Numerical simulation (PIV) | Reynolds stress model RSM [FLUENT (ANSYS)] | 10,000 | 0.13 |
| 25 | Mulahasan et al. (2021) | Rectangular | SINGLE | 90° | Simulated numerically and compared with experimental data | k-ε, k-w, RSM CFD-VOF-ANSYS FLUENT | (6560), (9930), (10,959) | (0.409) (0.334) (0.295) |
| 26 | Indulekha et al. (2021) | Rectangular | SERIES (6) | 15, 30, 45, 90, 120, 150° | Simulated numerically and compared with experimental data | ANSYS Fluent | 0.35 | |
| 27 | Yu et al. (2020) | Five different shapes | SINGLE | 90° | Experimental (ADV) | |||
| 28 | Pourshahbaz et al. (2022) | Rectangular | SERIES (3) | 90° | Numerical simulations substantiated using the experimental data (ADV) | FLOW-3D and SSIIM 2.0 | 0.19, 0.25 |
| S.no | Authors | Shape of spur | Single/series | Orientation | Experimental/numerical | Model/method used | Re (Reynolds Number) | Fr (Froude number) |
|---|---|---|---|---|---|---|---|---|
| 1 | Giri et al. (2004) | Rectangular | SERIES (3) | 90° | Numerical simulations were substantiated using the measured experimental data (ADV) | 2-D numerical model | 20,000 | |
| 2 | Kuhnle et al. (2008) | Trapezoidal | SINGLE | 90° | Simulated numerically & Compared with experimental data (ADV) | finite element method (k–ε turbulent model) | 0.2 | |
| 3 | Duan (2009) | Rectangular | SINGLE | 90° | Experimental (ADV) | 48,483 | ||
| 4 | Yazdi et al. (2010) | Rectangular | SINGLE | 70, 90, 110° | Numerical results verified through the experimental data (ADV) | Fluent (k–ε turbulent model) | ||
| 5 | Duan et al. (2011) | Rectangular | SINGLE | 90° | Experimental (ADV) | 84,059 and 53,157 | ||
| 6 | Koken & Gogus (2015) | Rectangular | SINGLE | 90° | Numerical simulation (DES) | DES | 45,000 | |
| 7 | Safarzadeh et al. (2016) | Rectangular and T-shape | SINGLE | 90° | Experimental (ADV) | 60,000 | 0.35 | |
| 8 | Vaghefi et al. (2016b) | T-shape | SINGLE | 60, 90, 120° | Numerical results verified through the experimental data (ADV) | SSIIM CFD software, Navier–Stokes equation, and k–ε turbulence model | ||
| 9 | Mehraein et al. (2017) | T-SHAPED | SINGLE | 90° | Experimental (ADV) | 34,000 | 0.38 | |
| 10 | Kang (2018) | Rectangular | SINGLE | 90° | LES are compared with the experiment (ADV) | LES | 3.00 × 104 | 0.1 |
| 11 | Jeon & Lee (2018) | Rectangular | SINGLE | 90° | Experimental (ADV) | LES | 3.00 × 104 and 6.59 × 104 | 0.10 and 0.90 |
| 12 | Vaghefi et al. (2018) | T-shape | SINGLE | 45° attractive and repelling | Numerical simulation of the experimental model (ADV) | CFD-RNG k-E turbulent model | ||
| 13 | Kumar & Ojha (2019a) | L-head | SINGLE | 90° | Experimental (ADV) | 25,000 − 44,000, | 0.34 − 0.39 | |
| 14 | Kumar & Ojha (2019b) | L-head | SINGLE | 90° | Experimental (ADV) | 3.9 × 104 | 0.34 | |
| 15 | Bahrami-Yarahmadi et al. (2020) | Rectangular and Triangular | SERIES (4) | 90° | Experimental (EVM) | 0.176, 0.196, 0.216, and 0.235 | ||
| 16 | Shampa et al. (2020) | Slit-type permeable spur dike | Series of slit-type spurs (5) | 60, 90, 120° | Numerical simulations (PIV) substantiated using the measured experimental data (EVM) | 3D RANS; k-ω SST | 34,430 | 0.71 |
| 17 | Kang et al. (2021a) | J-hook vanes, Rock vanes, and bendway weirs | SINGLE | rock vanes-20, 30° J-hook vane-30° bendway weirs-60,80° | Large-eddy simulation (LES) and flume experiments (ADV) | LES | 4.08 × 104 | 0.19 |
| 18 | Mirzaei et al. (2021) | SINGLE | 90° | Numerical simulation is compared with experimental results | FLOW 3D-LES turbulence model | |||
| 19 | Jafari & Sui (2021) | Rectangular | SERIES (2) | 90, 60, and 45° | Experimental (ADV) | 0.19, 0.15, 0.10 | ||
| 20 | Akbari et al. (2021) | T-shape | SINGLE | 60, 89, 91, and 150° | Experimental (ADV) | 67,857 | 0.34 | |
| 21 | Lodhi et al. (2021) | Rectangular | SINGLE | 90° | Experimental (ADV) | 87,474 | 0.65 | |
| 22 | Kang et al. (2021b) | Rectangular | SINGLE | 90° | Numerical simulation & Experimental (ADV) | LES | 3.00 × 104 | 0.1 |
| 23 | Kafle (2021) | Rectangular | SERIES | 90° | Numerical simulation | CFD– model Nays 2D | ||
| 24 | Iqbal et al. (2021) | Rectangular | SERIES | 90° | Numerical simulation (PIV) | Reynolds stress model RSM [FLUENT (ANSYS)] | 10,000 | 0.13 |
| 25 | Mulahasan et al. (2021) | Rectangular | SINGLE | 90° | Simulated numerically and compared with experimental data | k-ε, k-w, RSM CFD-VOF-ANSYS FLUENT | (6560), (9930), (10,959) | (0.409) (0.334) (0.295) |
| 26 | Indulekha et al. (2021) | Rectangular | SERIES (6) | 15, 30, 45, 90, 120, 150° | Simulated numerically and compared with experimental data | ANSYS Fluent | 0.35 | |
| 27 | Yu et al. (2020) | Five different shapes | SINGLE | 90° | Experimental (ADV) | |||
| 28 | Pourshahbaz et al. (2022) | Rectangular | SERIES (3) | 90° | Numerical simulations substantiated using the experimental data (ADV) | FLOW-3D and SSIIM 2.0 | 0.19, 0.25 |
CFD, computational fluid dynamics; EVM, electromagnetic velocity meter; PIV, particle image velocimetry; DES, Detached eddy simulation; LES, Large-eddy simulation.
Spur dike length
Spur dike length is the length projected perpendicularly to the stream flow direction. It is presented as a percentage of channel width at the bank-full stage. According to the literature, the available parameters for determining spur dike length are site-specific. For straight reaches, Alvarez (1989) proposed that the spur dike length should be kept between the mean depth (h) and 0.25 times the free surface width (B) of the flow. Richardson et al. (1975) recommended a value of 15.24 m as the minimum length and a range from 10 to 15% of the bank-full channel width as the maximum length for straight reaches, large-radius bends, and braided channels. It has been noticed that the length of the spur dike is associated with more scour. Furthermore, when the length of the spur dike is increased, the maximum scour depth moves closer to the channel's outer wall (Vaghefi et al. 2009). The bed shear stress values near the spur dike's tip increased significantly as the length of the spur dike expanded (Koken & Gogus 2015).
Spur dikes spacing
Spur dikes are installed mainly in series rather than as individual structures. In the case of spur dikes installed as a series, flow around the spur dikes alters according to the spacing between the spur dikes.
In the literature, ideal ratio (or) aspect ratio (or) spacing factors (=spacing of spurs/length of spur) range from 1 to 6, where less than one spacing factor is used in retardance spurs, and six is adopted for impermeable diverter spurs. Several field spurs were constructed to study the bank protection of the river Sutlej below the Panjnad headwork. After a series of experiments, the ideal ratio is around 5 for the longest length of bank protection. The bank between the spurs may be attacked and degraded when the value is more than five, as found by Ahmad (1951). As suggested by Fenwick (1969), the spacing of the spur dikes is classified based on the purpose of its installation (for example, spacing ratio values of 2–2.5 for flow control and 3 for bank protection). Richardson et al. (1975) recommend spacing 1.5–6 times the upstream projected spur length into the flow. An aspect ratio of 1.5–2.0 is recommended for obtaining a distinct channel for navigation purposes. For bank protection purposes, the ratio of 2–6 is generally used. In addition, Garg et al. (1980) suggested that when more than one spur is built, the spacing between them is determined by the spur's angle and the flow's curvature. Also, the spurs are separated by 3–4 times their length.
For groyne installation and protection, considering the transmissivity, angle, length, and channel curvature of the groyne, Brown (1985) proposed a range of aspect ratio = 1–6. The appropriate installation spacing is proposed as a minimum of four times and a maximum of six times, considering a decrease in flow velocity according to the installation of upward groynes and river bed stability Kim et al. (2014). Bahrami-Yarahmadi et al. (2020) used a triangular shape for their study. They recommended that the spacing between them be restricted to 5.5 times the effective length of the structure. Hajibehzad et al. (2020) showed the maximum scour depth around the spur dikes as the distance between them increases. Hence, spur dike length and spacing between them are the significant design factors for bank protection.
Spur dike orientation
Hydraulic structures such as spur dikes or groynes extend from the bank of rivers or streams oriented either upstream, downstream, or perpendicular to the main flow direction. The orientation of the spur dike influences the flow pattern, scouring, and sedimentation processes in the vicinity of the spur dike. Richardson & Simons (1984) suggested that a spur dike's orientation ranges between 30 and 120° when measured downstream. For navigation purposes, spur dikes inclined downstream are more effective as they provide a greater flow depth. Spur dikes with a greater than 90° orientation angle are effective for bank protection. Because sediment materials settle more readily between these spur dikes, they provide a highly stable river bank (Brown 1985; Kuhnle et al. 2002).
According to United Nations (1953), the current norm is to build spur dikes either perpendicular to the bank or upstream. An upstream dike angle of 100–120° was proposed for bank protection. Garde et al. (1961) propounded that the maximum scour depth would be most significant for a spur perpendicular to the bank line and reduced for all other upstream and downstream orientations. Ezzeldin et al. (2007) commented that the greatest width of scour holes corresponds to the 135° spur. Still, they provide improved aquatic habitats and minimize the possibility of erosion of the channel bank. Krishna Prasad et al. (2016) suggested an angle of a 135° spur for reducing erosion and protecting the bank. As the angle of inclination of the spur dike decreases, the scour hole depth, length, and width parameters decrease (Nath & Misra 2017).
Crest elevation
The crest elevation of spurs is described based on alterations caused by flow. Spurs can be built to remain above the water level (non-submerged) or submerged during floods and emerge only after the flood has passed. The crest height of spurs should be at least as high as the bank of the channels for bank protection. Non-submerged spurs are usually made impermeable because severe erosion can occur along the spur downstream due to overtopping water in submerged spurs. On the other hand, submerged spurs can be permeable because they do not obstruct the flow as much as solid spurs. In addition, submerged spurs must attain a height between one-third and half the flow depth (Ji1a & Karmacharya 2000).
Minimum number of spurs along the stream bank
The number of spurs required is determined by the length of the stream bank to be protected and the estimated spacing between the spurs. Streamflow patterns and bed scour patterns associated with different arrangements of spur dikes are utilized to determine which arrangements for single structure and multiple structures are suitable for protecting erosion of banks and influencing scour patterns. The number of spurs to protect stream banks or to contract the stream should be a minimum of three spurs. For the protection of embankments across the stream, one or two spurs may be adequate (Richardson & Simons 1984).
FLOW PATTERN AROUND SPUR DIKE
Schematic representation of a spur dike configuration displaying significant design criteria (USACE 1980).
Schematic representation of a spur dike configuration displaying significant design criteria (USACE 1980).
Main flow zone
The flow accelerates due to a spur dike in the main flow zone. According to Molinas et al. (1998), the velocity at the spur dike head may be enhanced by up to 50% of the incoming flow velocity. In addition, Ho et al. (2007) used both experimental and computational approaches to study the flow around impermeable spur dikes and came up with similar conclusions.
Wake zone
In the wake zone, the flow can be further classified into two zones: return flow and reattachment.
Return flow zone
Two eddies of different sizes and rotating directions are generally formed in the return flow zone. A small eddy is formed in the vicinity of the spur dike, the center of which is nearly equal to the length of the spur dike (L). At the downstream end of the small eddy, a larger eddy forms, with its center about six times the length of the spur dike away from the spur dike.
Reattachment zone
The reattachment zone is downstream of the spur dike, where the divided flow re-joins with the channel bank. Yong & Ikeda (1997) propounded that the reattachment zone is present at a distance of approximately six times the length of the spur dike (L) and is located between 11 and 17 L. However, the reattachment zone is frequently reduced to a single point for easy analysis. The time-averaged velocity is zero at this point. However, it is essential to remember that the instantaneous reattachment point varies. Ouillon & Dartus (1997) found that the reattachment point for impermeable spur dikes was 11.5 L in the experiments and 10.7 L in the numerical model analysis.
SCOUR AROUND SPUR DIKE AND THEIR CLASSIFICATION
The scouring in the vicinity of the spur dike is usually categorized as:
- (1)
general scour;
- (2)
constriction scour; and
- (3)
local scour.
General scour occurs on a channel bed due to sediment movement and occurs regardless of the presence of a spur dike. The installation of the spur dike narrows the riverbed, resulting in constriction scour. The spur dike restricts flow and promotes local scouring around the structure. The primary purpose of a spur dike is to deflect the main flow away from the bank. However, like other hydraulic systems, the spur dike faces the biggest threat to its intended performance from excessive scouring. This scour, known as local scour, is frequently recognized as a vital cause of the failure of the structure. Correct estimation of the maximum local scour depth is crucial for these structures’ safe design.
Flow structure in the scour (local) area
An obstruction like spur dikes or groynes significantly affects the flow patterns in a river. It alters sediment transport, deposition, and general and local scour near the spur dike. The obstruction caused by a spur dike or groin generates a complex system of vortices. Vortices remove these sediments from the base of the structure with enhanced lateral flow flowing through the obstacle. After being propelled along the mainstream flow in the direction of the downstream deposit, the eroded sediments are subsequently conveyed by wake vortices and aggrade downstream rivers.
EFFECT ON MORPHOLOGY DUE TO SPUR INSTALLATION
The flow characteristics in the channel have a considerable impact on bed morphology. Installing a spur dike along the bank of the channel adds to the complexity of flow even further. The projection of a structure, such as a spur dike outward from the bank, alters the flow patterns and bed morphologies. Usually, these changes initiate the scouring process. The study of morphology changes in the presence and absence of a spur dike is essential to evaluate how the erosion process affects the channel bank and bed. The scouring in the channel affects spur dike strength, the primary cause of spur dike failure. The maximum expected scour depth must be considered from the structure's foundation to avoid failure. Therefore, investigations attempting to determine what causes the scouring and how to estimate the maximum depth of scouring surrounding the spur dike are critical research challenges. Several studies have already been conducted on these lines; however, there is still much uncertainty in predicting scour depth. Scour at spurs is often predicted based on experience with a specific river or by employing a case-specific physical model. Many factors that influence the scouring process include spur dike shape, projected and wing length of the spur, orientation, spacing between adjacent spur dikes, channel cross-section, crest height, the material used for construction, permeability, and sediment and riprap size. Researchers attempted to explore the influence of these factors independently and in combination to conclude which independent factors or their combinations contribute more to scouring processes.
Ezzeldin et al. (2007) studied the local scour around a single straight impermeable submerged spur installed in a channel with different angles relative to the flow direction. Scour depth was found to be more due to greater resistance to the flow made by the spurs. Scour depth increases with an increase in the Froude number and the angle of inclination of the spur with respect to the flow direction. The maximum width of the scour hole was found at the orientation, with a spur angle of 135°. Atarodi et al. (2021) performed experiments on spurs placed in a series and introduced a protective spur to reduce the scouring of the downstream spurs. The experiments investigated each spur's effect on other spurs of the series, highlighting the protective spur's influence in reducing the scour around other spurs. The introduced protective spur was shown to effectively decrease the scour around the spurs placed sequentially. Vaghefi et al. (2009) investigated scouring near a T-shaped spur dike at a 90° bend channel. The different lengths of spur dike at various aspects of scour depth characteristics such as amount, volume, and dimensions were analyzed. It was found that these parameters increased as the length of spur dike from the bank increased. The maximum scour depth was obtained at the upstream side just near the spur dike. Alauddin & Tsujimoto (2012) installed groynes in a series with different configurations. They conducted experiments to find which is more effective at high and low flow conditions. The results demonstrated that modified groynes are more effective than conventional ones for navigation channel maintenance at low-flow fields and bank protection at high-flow. Vaghefi et al. (2012) experimentally investigated the scouring near the T-shaped spur dike at 90° bends. They studied two scour holes: one developed near the nose of the spur dike at the upstream section, and the other developed at some distance from the spur at the downstream section. The scour volume upstream is much higher compared to downstream. Researchers also reported that the maximum scour depth increases as the spur dike length decreases (Ezzeldin et al. 2007). Dawood (2013) conducted laboratory experiments with three different shapes of impermeable spurs in a straight channel: straight, T-head, and L-head. They observed an indirect relationship between the effect of spur numbers and the shape of spurs on the maximum scouring depth. In their experiments, the distance considered between the spurs was 1, 1.5, and 2 times the length of the spurs. The researcher reported an increase in scour depth by nearly 20% when the spurs’ distance increased to 0.5 times the length of the spur. Pandey (2014) reported that in the case of two subsequent groins in a rectangular straight channel, the maximum scour depth always developed at the upstream side of the first groin with its location near the nose of the groin on the upstream side. The scour hole size increases as the radius of the channel bend to channel width ratio increases (Mehraein & Ghodsian 2017). The formation of scour around the spur dike projected at the bend is caused due to cross-current and vortices formed around the structure (Pandey et al. 2019). Scour patterns around triangular and rectangular spur dikes were compared at different hydraulic conditions. The result revealed that scour hole dimensions, such as maximum scour depth and volume, were smaller than rectangular spur dikes in triangular spur dikes (Bahrami-Yarahmadi et al. 2020). A study of the erosion and sedimentation patterns reveals that scour would occur at the tip and near the triangular and rectangular spur dike. Akbari et al. (2021) studied the flow patterns around T-shaped spurs to determine the most effective geometric shapes. They found that the length of the spur dike web and its wing shape affected the flow characteristics. An increase in the web length and spur dike size can increase the flow velocity by 77% at the bed, and 38% near the water surface, when the length of the spur installed is about 25% of the channel width. Tripathi & Pandey (2021) examined the local scour and general scour in the vicinity of a T-shaped spur organized at different locations on the bank of a reverse meander channel. It was noticed that with an increase in the Froude number, the flow moves towards the spur dike to form a local scour and reduces the general scour in the vicinity of the spur dike while the depth of scour hole increases. Pandey et al. (2021) investigated temporal scour depth variation in the spur dike (vertical wall) to identify the most prominent parameters affecting the performance of the spur dike with non-uniform sediment. They proposed a new temporal scour depth equation for calculating maximum scour depth around spur dikes in the presence of non-uniform sediment. It was observed that the variation of temporal scour depth increases with an increase in parameters such as the threshold velocity ratio, Froude number, flow depth-particle size ratio, and flow shallowness and reduces as the non-uniformity of the sediment increases. Flume experiments conducted by Farshad et al. (2022) revealed significant attenuation to maximum scour depth in the case of permeable spur dike, as compared to the impermeable dike. Also, minimum bank retreat in a meandering channel was observed in the case of permeable spur dikes (Esmaeli et al. 2022). Similar observations were reported by Khajavi et al. (2022) and Hakim et al. (2022), wherein permeable spurs considerably eliminated the scour at bridge abutments in both steady and unsteady flow conditions. Tripathi & Pandey (2022) reviewed previous research on flow patterns and prediction of temporal and maximum scour depth around spur dikes formed by straight, L-shaped, and T-shaped spurs placed at 90 and 180° curved channels. A detailed review of the numerical and experimental study suggests that the data and associated results are inadequate for the construction of spurs employed as river structures in curved channels.
The knowledge of how different shapes and orientations of spur dikes in the channel contribute to erosion processes was investigated to propose the most efficient and cost-effective spur dikes out of the numerous potential shapes. However, most researchers have not considered one of the primary factors present in the channel that impacts the bank and bed load transport process, even in the presence of spur dikes, which is seepage. In natural channels, along with the main flow, there is significant seepage flow from the channel bed and banks. The interaction of seepage will affect the flow structure, consequently affecting the scour patterns around the spur dikes. Future studies in this direction are needed for a more realistic prediction of hydro-morphology around spur dikes for field conditions.
TURBULENCE CHARACTERISTICS DUE TO SPUR INSTALLATION
The presence of a spur dike affects the flow, especially near the banks of the channel, and modifies the turbulent characteristics associated with the flow. The nature of turbulence in a flow is studied by measurement and analysis of instantaneous flow velocities in cartesian coordinates. The analysis provides various turbulent parameters of the flow, which include Reynolds shear stress, turbulent intensity, turbulent kinetic energy, bed shear stress, etc. The morphology around spur dikes is governed by turbulent flow parameters around the spur dikes. These characteristics are statistically estimated using the root-mean-square (RMS) of the turbulent velocity fluctuation and covariances for all three velocity combinations. Researchers have analyzed the flow pattern around spur dikes and determined mean velocity and turbulent flow characteristics, local scour, riverbank stabilization, and scour reduction by conducting laboratory tests and numerical simulations. The process understanding gained from these studies and our current knowledge about flow structure and morphological interactions around spur dikes is explicated in the following section.
Based on experimental results
Physical-model experiments are an effective way to learn about critical flow characteristics. Researchers experimentally studied how bed and bank stability is affected due to the influence of turbulent characteristics in the vicinity of spur dikes. As a research objective, different shapes of spur dikes are employed in various locations, with varying orientations and spur lengths, to provide suitable arrangements. An experimental flume with a fixed bed was used by Duan (2009) to analyze the three-dimensional turbulent flow zone near a spur dike. Results show that the maximum bed-shear stress was estimated at around 2–3 times the approaching flow of the mean bed-shear stress, which is located just upstream of the tip of the spur.
Furthermore, turbulence intensities were high as the flow moved downstream, the mean downstream velocity was nearly zero, and the mean kinetic energy declined, whereas the turbulent kinetic energy increased. Duan et al. (2011) investigated the mean flow and turbulence patterns with scoured and flatbed surfaces around a spur dike. They concluded that the turbulence intensities in the longitudinal (u′) and transverse (v′) components are significantly higher, while the vertical component (w′) is significantly smaller than the flatbed. Furthermore, the estimated maximum bed shear stress is approximately 6–8 times the incoming flow for non-erodible and erodible bed surfaces. Safarzadeh et al. (2016) investigated the 3D turbulent flow field near straight and T-shape spurs under a smooth flatbed. According to the experiment results, the presence of the spurs enhanced the turbulent kinetic energy (TKE) by 10 times. In addition, TKE was observed to be higher and more extended in the upstream region of the T-shape spur than in the straight spur. Circular 3D flow structures just upstream of the T-shape spur dike are considered responsible for this phenomenon. Mehraein et al. (2017) studied the mean and turbulent flow fields experimentally and measured scour holes around a submerged and emerged spur dike in a 90° bend. They found that TKE reaches its highest value near the spur dikes at the upstream tip and elongates as it approaches the downstream border between the approach and recirculating flow. They also showed that TKE-predicted bed shear stress shows a good association between scour and bed shear stress. Kumar & Ojha (2019) used an unsubmerged L-head spur dike to investigate mean and turbulent flow characteristics. They observed that the magnitude of the bed shear stress, vertical Reynolds stress, and turbulent kinetic energy decreases in the wake zone as groyne's configuration and constriction ratio increases. In another study, they found that as the flow approaches the spur dike, the magnitude of turbulent kinetic energy increases; however, this decreases significantly in the confined region of the groyne faces inside the wake zone. They also found that bed shear stress increases considerably (by 4.78 times the approaching bed shear stress) within the inner wake zone at the groyne faces and near the submerged dike. The effects of the spur dike on turbulent properties under ice cover circumstances were evaluated by Jafari & Sui (2021). The most significant velocity fluctuations were observed above the scour hole and near the spur wing. In addition, ice on the water surface alters the bed shear stress and increases turbulence intensities inside the scour holes, which can substantially impact sediment movement. They also observed Reynolds shear stress and found it is negative inside the scour holes, but it becomes positive as it approaches the flow surface and reaches its maximum just above the scour holes. Lodhi et al. (2021) explored turbulent characteristics near spur dikes. According to their findings, higher longitudinal velocity values were going beyond the scour hole zone and were lower within the scour hole region. The Reynolds stresses and turbulence intensities were greater in the scour hole in the spur dike's wake zone, and the wake zone had the greatest TKE value. Due to an increase in the degree of submergence, the TKE increases in front of the spur dike and decreases at the axis as well as at the rear side of the dike (Yu et al. 2022). Physical model studies were conducted by Wang et al. (2022) on the spur dikes in the Three Gorges Reservoir area of the Yangtze River due to the action of landslide surge. The results show significant effects on the circumferential wave pressure upstream and downstream of the spur dike due to landslide surge.
Based on numerical simulations
mean velocity; 
fluctuation of turbulent velocity; 
time; 
production (turbulent kinetic energy); 
mean total dynamic pressure; 
turbulent kinetic energy; 
rate of dissipation of turbulent kinetic energy; 
turbulent eddy viscosity 
; 
forcing term and 
density of water. Constants of 
model were assigned from standard values recommended by Launder & Sharma (1974).
, to predict flow patterns in the zone of spur dike. In this research, the objective was to determine 
and following transport equations (Launder & Spalding 1983) were used to obtained 
and 
:
is an empirical constant; 
where 
is viscosity of fluid, 
is the turbulence viscosity; 
represents the generation of turbulent kinetic energy due to the mean velocity gradients, 
and 
are constants, 
and 
are the turbulent Prandtl numbers and other standard constant used in this model recommended by Launder & Spalding (1983).The impacts of flow discharge, spur dike length, and orientation on the bed shear stress distribution were also investigated. They concluded that the vertical spur experiences higher bed-shear stress than the stream's spur dikes-oriented upside or downside. Also, the shear stress increases for longer spur dikes as the higher velocities flow through, the narrower the flow cross-section. Koken & Gogus (2015) studied the turbulent flow pattern by using DES (detached eddy simulation) model around isolated spur dikes of three different lengths. The investigations revealed that as the spur dike length increased, the substantial bed shear stress values near the tip of the spur dike increased. Additionally, the upstream sections of the separated shear layers and the upstream regions of the primary horseshoe vortex increased. To determine the modified eddy viscosity following transport equation is solved:
(7)
is the kinematic viscosity, 
is the contravariant resolved velocity, t is time, 
is the turbulence length scale, and 
is the curvilinear coordinate in the j direction. The other variables and parameters are:
is the Von Karman constant, which is 0.41 and:
is obtained from:
The model constants in the above equations are: 
= 0.135, 
= 0.622, σ = 0.67, 
= 0.71, 
= 0.3, 
= 2.0 and 
.
model was employed for this modelling. Equations are expressed as:
is the velocity, P is pressure and 
is body force, 
and 
represent the effective diffusivity of k and ω, respectively. 
and 
are the dissipation of k and ω due to turbulence. 
and 
are the user-defined source terms.Mulahasan et al. (2021) employed (k–ε) and (k–ω), Reynolds Stress Model (RSM) turbulence models to study the flow properties around a vertical emergent sidewall abutment and compared the results with the experimental data. The result showed that the highest turbulent kinetic energy was observed at high velocity in the separation zone, and the bed shear stress was reduced in the recirculation zone. This study also observed that bed shear stresses are 2–3 times the approaching flow of the mean bed shear stress. Iqbal et al. (2021) used the Reynolds stress turbulence model built using the three-dimensional numerical code FLUENT (ANSYS) to investigate the flow and turbulence characteristics of rectangular spur dikes with varying permeability. They found that the turbulent intensity and turbulent kinetic energy were significantly lower in the permeable spur dike than in the impermeable spur dike. As a result, they recommended that a permeable spur dike be used to prevent the spur dike head from strong turbulent flow during floods and to minimize the recirculation zone of the spur dike field. Reynolds averaged equations (governing equations) for continuity and momentum are given below:
are the Reynolds stresses.
represent the rate of change of Reynolds stresses, 
is the convection transport, 
represents the rate of generation of Reynolds stresses due to diffusion, 
represents dissipation rate of stresses, 
represents the distribution of stresses to turbulent pressure-strain interactions, and 
is the distribution of stresses due to rotation.Kang et al. (2021b) studied the mean flow and turbulence characteristics under a low length-to-depth ratio near a non-submerged rectangular spur. A large-eddy simulation model was employed for the studies, and the results were compared with experimental data (ADV). A numerical model developed by Kang & Sotiropoulos (2011) was employed to carry out LES. They noticed that the horseshoe vortex significantly increases bed shear stress under its trajectory and around the spur dike of its upstream corner. They also found that the maximum bed shear stress was almost 17 times the entering flow's mean bed shear stress. Permeable spur dikes placed in spillway bends were found effective in reducing velocities, as well as increasing the energy dissipation rate up to 21% (Yang et al. 2021). Haider et al. (2022) studied the flow turbulence around two spur dike patterns (L and T) using computational fluid dynamics (CFD) with a standard k − ε model. Both the dike patterns were found effective in damping velocities and turbulence intensities in the riverbank flow, as compared to the conventional spur dike. Chen et al. (2022) studied the turbulence statistics in the detached shear layer behind a spur dike using Large-Eddy Simulations.
Several investigations conducted to disclose the three-dimensional flow characteristics surrounding a spur dike are summarized in Tables 1 and 2.
A summary of the previous work related to turbulent characteristics
| S.no | Authors | 3D velocity | BSS | TKE | RSS | TI |
|---|---|---|---|---|---|---|
| 1 | Giri et al. (2004) | ✓ | ✓ | ✓ | ✓ | ✓ |
| 2 | Kuhnle et al. (2008) | ✓ | ✓ | · | · | · |
| 3 | Duan (2009) | ✓ | ✓ | ✓ | ✓ | ✓ |
| 4 | Yazdi et al. (2010) | ✓ | ✓ | · | · | · |
| 5 | Duan et al. (2011) | ✓ | ✓ | ✓ | ✓ | ✓ |
| 6 | Koken & Gogus (2015) | ✓ | ✓ | ✓ | · | · |
| 7 | Safarzadeh et al. (2016) | ✓ | · | ✓ | · | · |
| 8 | Mehraein et al. (2017) | ✓ | ✓ | ✓ | · | · |
| 9 | Jeon & Lee (2018) | ✓ | · | ✓ | ✓ | ✓ |
| 10 | Kumar & Ojha (2019a) | ✓ | ✓ | ✓ | ✓ | ✓ |
| 11 | Kumar & Ojha (2019b) | ✓ | ✓ | ✓ | ✓ | · |
| 12 | Kang et al. (2021a) | ✓ | · | ✓ | ✓ | ✓ |
| 13 | Indulekha et al. (2021) | ✓ | · | ✓ | · | · |
| 14 | Mulahasan et al. (2021) | ✓ | ✓ | ✓ | · | · |
| 15 | Iqbal et al. (2021) | ✓ | · | ✓ | · | ✓ |
| 16 | Kang et al. (2021b) | ✓ | ✓ | ✓ | ✓ | · |
| 17 | Lodhi et al. (2021) | ✓ | · | ✓ | ✓ | ✓ |
| 18 | Jafari & Sui (2021) | ✓ | ✓ | ✓ | ✓ | ✓ |
| S.no | Authors | 3D velocity | BSS | TKE | RSS | TI |
|---|---|---|---|---|---|---|
| 1 | Giri et al. (2004) | ✓ | ✓ | ✓ | ✓ | ✓ |
| 2 | Kuhnle et al. (2008) | ✓ | ✓ | · | · | · |
| 3 | Duan (2009) | ✓ | ✓ | ✓ | ✓ | ✓ |
| 4 | Yazdi et al. (2010) | ✓ | ✓ | · | · | · |
| 5 | Duan et al. (2011) | ✓ | ✓ | ✓ | ✓ | ✓ |
| 6 | Koken & Gogus (2015) | ✓ | ✓ | ✓ | · | · |
| 7 | Safarzadeh et al. (2016) | ✓ | · | ✓ | · | · |
| 8 | Mehraein et al. (2017) | ✓ | ✓ | ✓ | · | · |
| 9 | Jeon & Lee (2018) | ✓ | · | ✓ | ✓ | ✓ |
| 10 | Kumar & Ojha (2019a) | ✓ | ✓ | ✓ | ✓ | ✓ |
| 11 | Kumar & Ojha (2019b) | ✓ | ✓ | ✓ | ✓ | · |
| 12 | Kang et al. (2021a) | ✓ | · | ✓ | ✓ | ✓ |
| 13 | Indulekha et al. (2021) | ✓ | · | ✓ | · | · |
| 14 | Mulahasan et al. (2021) | ✓ | ✓ | ✓ | · | · |
| 15 | Iqbal et al. (2021) | ✓ | · | ✓ | · | ✓ |
| 16 | Kang et al. (2021b) | ✓ | ✓ | ✓ | ✓ | · |
| 17 | Lodhi et al. (2021) | ✓ | · | ✓ | ✓ | ✓ |
| 18 | Jafari & Sui (2021) | ✓ | ✓ | ✓ | ✓ | ✓ |
BSS, Bed shear stress; TKE, Turbulent kinetic energy; RSS, Reynolds Shear Stress; MTI, Turbulent Intensity.
RESEARCH QUESTIONS AND FUTURE DIRECTION
Despite several research studies that have been conducted to understand the 3D flow characteristics around a spur dike, many challenges remain for future research. Some of them were attempted experimentally to contribute to the literature (Duan 2009; Duan et al. 2011; Safarzadeh et al. 2016; Mehraein et al. 2017; Kumar & Ojha 2019; Jafari & Sui 2021; Lodhi et al. 2021), while others were conducted using a numerical simulation model and compared to existing experimental work such as Giri et al. (2004); Kuhnle et al. (2008); Yazdi et al. (2010); Koken & Gogus (2015); Indulekha et al. (2021); Iqbal et al. (2021); Kang et al. (2021a, 2021b) and Mulahasan et al. (2021).
Two of the most critical factors affecting the flow in the alluvial channel in the field scenarios are vegetation and seepage. While vegetation provides natural protection against bank erosion, seepage can alter the flow field near the bed and bank of the channel. The study of flow modification in the presence of spur dike under the influence of seepage and vegetation is still unexplored. The effect of these two factors on the hydro-morphology around spur dikes needs to be studied to achieve better stability and performance of spur dikes in the field.
Soil erosion is more probable when there is little or no vegetation cover on the soil (plants, grasses, crop residue, or trees). Nabaei et al. (2021) found that vegetation at the channel bed reduces the scour depth by 34.8%. Therefore, studying flow hydraulics on vegetation is essential for river process management. The vegetation in the channel bed or bank can affect the flow behavior and change the movement of sediment and flow characteristics. Understanding these flow characteristics is necessary for the safety of dikes and for preventing bank erosion. Despite the availability of literature on turbulent characteristics and scour depth around spur dikes, the effect of vegetation around spur dikes is still to be addressed in earlier research.
A spur dike or groyne is one of the most commonly used river training structures that stabilize the river bank by protecting it from erosion. Turbulent characteristics influence the stability of the bed and banks. The researchers found that turbulence significantly enhanced sediment movement along the channel's bed and from its banks. The problem gets even more challenging when seepage occurs over the permeable boundaries of alluvial channels. For example, the presence of downward seepage aids in the enhancement of sediment movement and bed shear stress, which may alter the channel's hydrodynamic properties (Rao & Sitaram 1999; Rao et al. 2011; Sreenivasulu et al. 2011; Liu & Chiew 2012; Deshpande & Kumar 2017). Furthermore, Sharma & Kumar (2017) showed that turbulence properties such as velocity, Reynolds shear stresses, shear velocities, and roughness sublayer thickness enhances due to downward seepage. However, studies on how seepage affects turbulent characteristics surrounding the spur dike are not yet available, which needs to be quantified.
Many numerical simulations and experimental studies have been done in the straight channels to observe the turbulence and mean flow characteristics around spur dike; only a few examined the same under the sinuous stream, which needs to be studied. As a result of various studies focusing on turbulent characteristics around the spur dike, only rectangular channel cross-sections are utilized. Other channel cross-sections that are more efficient, such as trapezoidal, semi-circular, and circular, are not employed.
River banks are susceptible to the displacement of soil particles, resulting in bank erosion. The eroded sediments get deposited along the river as they flow downstream, causing a change in the bed level of the rivers. This deterioration of river banks and deposition along the river course can affect the natural equilibrium of rivers, lands, and control structures constructed over the river. Therefore, river bank stabilization is one of the major concerns in open channel flow for the reclamation of the environment and to secure important structures. A spur dike is one of the best solutions to this challenging scenario.
More precise knowledge of scouring around a spur dike and its impact on river bank stability is required to analyze river bank stabilization. Furthermore, observation of maximum scour depth and scour development around the spur dike is necessary for its foundation design. Many researchers studied and explored different factors influencing the flow behavior around a spur dike. Discussion about various aspects during the implementation of this structure, such as spur dike alignment, length, spacing between the spurs, orientation, contraction ratio, permeability, appearances as a single spur dike or series of spur dikes, etc., are evaluated.
Although enough research has been conducted on scour and flow patterns developed near the spurs, many researchers have not included river bank susceptibility due to the installation of spurs. The impact of scouring patterns developed near the spur on bank stability remains an unexplored area in the field of fluvial hydrodynamics. Thus, it is crucial to consider these factors to analyze the impact of spurs on both river banks and beds.
CONCLUSION
Many studies have been carried out in the available literature to determine the causes of erosion, and alternative techniques are proposed for managing it. Studies found that the spur dike is the most suitable structure, which provides stability to the channel bank by diverting the flow away from it. Based on the critical review of these studies on spur dikes, the following conclusions and recommendations can be made concerning spur dikes:
- (1)
Spur dikes significantly prevent sediment erosion from the bank. The degree of bank protection provided by spur dikes is dependent on various parameters such as spur dike orientation angle, length, spacing, and permeability.
- (2)
The available factors for estimating spur dike length are site-specific. As the length of the spur increases, the protected distance downstream increases, but not proportionally; the model dikes could protect a bank 2–5 times their length.
- (3)
In a series, the spacing of spur dikes should be fixed considering all related factors, including both high and low flow conditions. If the water level changes, the working length of the spur dike may vary, and hence the spur ratio can differ significantly. If the spur dikes are placed with long distances between them, a meander loop may form between spur dikes. However, the system will not be cost-effective if the spur dikes are placed too close to each other. Therefore, spur dike spacing is the most crucial factor in spur dike design.
- (4)
Spur dikes oriented upstream provide even more bank protection, followed by spur dikes oriented perpendicular to the flow. However, downstream-oriented spur dikes provide minimum protection compared to upstream and perpendicular-oriented ones.
- (5)
The flow turbulence is significantly lower in the permeable spur dike than in the impermeable spur dike. As a result, a permeable spur dike is preferable in order to protect the spur dike head from the intense turbulence of the flow and to restrict the recirculation zone of the spur dike field.
- (6)
Upstream spur dikes manage most of the erosive power of the streamflow compared to downstream spur dikes. As a result, deeper local scour and greater settlement of the spur dike tip into the scour hole. Therefore, special design attention must be given to them to ensure the stability of upstream spur dikes in a spur dike field. To avoid collapse, the foundation of the upstream spur dike must be deeper.
- (7)
The scour hole in the spur dike's wake zone and near the spur wing experience the highest velocity fluctuations, pressure, Reynolds stresses, turbulence intensities, and turbulent kinetic energy and elongates as it approaches the downstream.
- (8)
Fluvial factors in the channel, such as seepage, vegetation, etc., can significantly affect the hydro-morphology around spur dikes. Sufficient literature is unavailable on these lines, and studies should be conducted in the future to answer these research questions.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.
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