Riverbank Stability Research Articles

Assessing Genetic Variability and Population Structure of Alnus glutinosa (Black Alder) in Kazakhstan Using SSR Markers

Alnus glutinosa plays a crucial role in flood control, riverbank stabilization, and water purification. Recognized for its ecological significance, it is listed in the Red Book of Kazakhstan. This study investigated the genetic variability of A. glutinosa populations in Kazakhstan, analyzing 78 trees from seven populations in the Bayanaul mountain forest massif and the northern Turgay regions using 12 SSR markers. The study identified an average of 6.3 alleles and 2.783 effective alleles, as well as observed and expected heterozygosities of 0.570 and 0.562, respectively, reflecting genetic diversity. Among the populations, KS1 (northern Turgay) and PVL3 (Bayanaul) displayed the highest diversity, while PVL5 (Bayanaul) showed slightly lower diversity. The analysis of molecular variance results indicated that 86% of the genetic diversity occurred within populations, with 14% attributed to differences between populations. A UPGMA tree based on Nei’s genetic distance revealed three distinct clusters, suggesting geographically structured genetic variability in A. glutinosa populations.

Evaluating the suitability of Brazilian native species for riverbank stabilization and protection

In Brazil, soil and water bioengineering techniques have mainly been used for hydraulic stabilization, water course management and to re-establish the vegetation in fluvial environments. In these techniques plants are considered as an important structural component and their use requires adequate selection. The present study aimed to evaluate the root system and shoot development traits of the Allamanda cathartica L., Ludwigia elegans (Camb.) H. Hara and Sesbania virgata (Cav.) Pers species. The experiment was conducted in a greenhouse at the Laboratory of Soil Bioengineering at the Federal University of Santa Maria. The following variables were evaluated after 120 days: the survival rate, average height, average root collar diameter, average number and sum of shoot length per plant, average number of primary roots and the sum of primary root length, length of the largest root and root dry mass per plant. The percentage of fine roots and coarse roots and distribution of root dry mass percentage in soil depth were also evaluated. The results confirm the suitability of the L. elegans, S. virgata and A. cathartica species for riverbank stabilization and protection in soil and water bioengineering works.

Assessing river bank erosion on Majuli Island for strength and stability in resilient protection

ABSTRACT The present study addresses the issues and challenges of Brahmaputra river bank erosion near Majuli Island, Assam. For field study, the most vulnerable locations, namely (i) Ahatguri area, (ii) Okhala Chuk, (iii) Kamalabari ferry ghat, (iv) Cinnatoli Chapori and (v) Kandhulimari area are taken into consideration. Geometrical as well as geotechnical investigations were carried out to obtain detailed information for the stability analysis of river bank slopes of selected sites. Through 2-D finite element-based numerical tool PLAXIS2D, results indicated low stability of river bank due to low shear strength and ingress of moisture. To improve the strength and stiffness of the river bank soil, authors suggest a soil stabilisation technique using a Cement-Soil mixture with a 1:25 ratio (4%). The influence of improvement in the geotechnical properties was noted with the improvement in the stability of the river bank soil when assessed numerically. Results depicted that under ‘saturated and stabilized condition’, approximately 99% reduction in maximum total displacement and 55–85% reduction in maximum total strain was observed at all the five critical locations studied. Factor of safety values of stabilised bank was increased by 4.5 to 12 times, compared to the corresponding results obtained for ‘saturated and unstabilized’ condition.

Investigating Flow around Submerged I, L and T Head Groynes in Gravel Bed

Riverbank erosion poses a significant threat to the stability and integrity of river training structures. River training structures such as groynes are important components of sustainable development as they play a crucial role in mitigating flood risks, controlling erosion, and supporting the habitat for aquatic organisms. The habitats vary largely according to the groyne type. A comprehensive comparative analysis of the flow field around the I, L, and T head groynes in the gravel bed is drawn. This study will be of immense use for riverbank protection in hilly terrain where streams are mostly dominated by the gravel bed. Laboratory experiments were conducted in a channel with a sediment bed as gravel of size 9.36 mm. Consistent flow conditions were maintained, with a flow depth (D) of 0.136 m and Froude no (Fr) of 0.61. The performance of these groynes, quantified using Lp (length of bank protection), was investigated. LHG and THG, notably, instigate more profound scour depths, recording values of 0.295 D and 0.29 D, respectively, while IHG trails with the value of 0.21 D. The complex flow field involving velocity peaks, decelerated, and negative flow is discussed and is attributed to flow separation at the groyne tip and the horseshoe vortex. The Lp for each groyne was estimated, with the IHG providing the maximum bank protection of 1.2 L1, L1 being the transverse length of the groyne. The cost–benefit analysis revealed IHG as the most cost-effective structure. These findings contribute to optimization of riverbank stabilization efforts, enhancing the resilience of hydraulic infrastructure and ensuring the safety and wellbeing of affected communities and ecosystems. The results also provide valuable insight into bank protection by various groynes and highlight their contribution to enhancing the resilience of river systems.

Bank erosion under the impacts of fluvial erosion, frost heaving/freeze-thaw process of rivers in seasonal frozen regions

Bank erosion is a key feature of channel evolution in alluvial rivers, and will occur under the combined effect of hydraulic erosion and frost heave/freeze-thaw process of rivers in seasonal frozen regions. However, most research on bank erosion modeling has seldom considered the impact of the frost heave/freeze-thaw process. Therefore, the variation in the mechanical characteristics of riverbank soil under the freeze-thaw cycle was investigated firstly in the current research and then used in the modeling of bank erosion processes at typical sections of the Songhua River. Additionally, a sensitivity analysis of riverbank stability was conducted using orthogonal experiments. The results indicate that after 7 freeze-thaw cycles, the soil cohesion and internal friction angle of bank soil decreased by about 10%–47 % and 9%–19 %, respectively. Unlike lowland rivers, bank erosion of rivers in seasonal frozen regions is more likely to occur during the rising water period. The frost heaving/freeze-thaw process will make the bank stability safety coefficient Fs more quickly decrease to the unstable critical value. As compared with the case without considering the frost heaving/freeze-thaw process, the mass failure occurred in advance when the frost heaving/freeze-thaw process was considered, and the calculated bank erosion volume was increased by 11%–51 %, agreeing better with the measured value. The sensitivity ranking of the four influencing factors on riverbank stability under freezing-thawing conditions is as follows: river stage > groundwater level > cohesion > internal friction angle. The current study can provide a reference for research on bank erosion and channel evolution of rivers in seasonal frozen regions.

Effects of Vibration on Buried Structures from the Removal of Steel Casings during the Installation of Rockfill Columns for Riverbank Stabilization: A Case Study

Effects of Vibration on Buried Structures from the Removal of Steel Casings during the Installation of Rockfill Columns for Riverbank Stabilization: A Case Study

Understanding geomorphodynamics in the Pergamon micro-region from a socio-ecological perspective

A systematic interdisciplinary approach based on the socio-ecological model of the Vienna school has been adopted to achieve a more nuanced and multifaceted understanding of the ancient metropolis of Pergamon (western Anatolia) and its micro-region. The city of Pergamon ranks among the ‘guiding fossils’ of urban culture in antiquity. We describe how the socio-ecological model is subject to adaptation and discussion to fit the needs and circumstances of archaeology. In focussing on geomorphodynamics, we use several approaches to conceptualise and model selected aspects of human-environment interactions, integrating data from physical geography, archaeology, building archaeology (Bauforschung) and ancient history. The model includes several dimensions of the social metabolism of Pergamon, first and foremost the carrying capacity of the environment and demographics, comprising population increase and labour as an active investment in nature. Geomorphodynamics are regarded as major ‘events’ in the model, related to the social metabolism (e.g. increased erosion/deposition in the micro-region in relation to urban sprawl). With the social-ecological model, it is possible – and becomes imperative – to include the perception and representation of human-environment interactions manifested in, for example, administrative patterns and religious practices or architecture and built infrastructure (such as terraces, riverbank stabilisation, substraction terraces and substraction bridges). Geomorphodynamics also involve various aspects of the perception of the environment, though these are not recorded in ancient texts on Pergamon known to date. Concurrently, the importance of the model in organising, structuring, and communicating interdisciplinary collaboration and discourse is highlighted.

Enhancing riverbank stability: A case study on soil improvement through Jet grouting along Can Tho riverbank

Soil cement mixing (SCM) using a high-pressure grouting method (Jet grouting), considered an improvement solution for soft soil has been popular in countries, especially in Japan and other countries in Northern Europe. However, the implementation of Jet grouting is still quite modest in the Mekong Delta. In this study, the depth effect on the compressive strength of soil-cement mixing is conducted at the Can Tho River embankment project. The results show that the uniformity of SCM depends on the cement content. The higher cement content gives a better distribution of compressive strength from the bottom to the top of SCM. In this study, the cement content of 400 kg/m3, considered the suitable content for the Jet-grouting method in Can Tho, is much higher than in (TCVN 9906:2014).

Clear Water Scour Depth Prediction using Gradient Boosting Machine and Deep Learning

The scouring process in adjacent to spur dikes has the potential for compromising the stability of riverbanks. Hence, it is necessary for river engineering to conduct precise measurement of maximum scour depth in the vicinity of spur dikes. Nevertheless, the determination of the maximum scour depth has proven to be a challenging task, primarily due to the complex nature of the scour phenomena associated with these structures. In this study, two data-driven models, namely the Gradient Boost Machine (GBM) and Deep Learning (DL), were developed to predict the clear water scour depth near to a spur dike. A total of 154 distinct observations have been collected from previous literatures. A total of 103 observations were utilized for training the model, while 53 observation were allocated for validation purposes. Several performance assessment measures were employed to evaluate the performance of the models, including the correlation coefficient (CC), root-coefficient of determination (R2), scattered plot, variation plot, and box plot. GBM outperformed the DL on the basis of above-mentioned assessment measures. Sensitivity analysis suggests that l/d50 is the most influences input parameter. Thus, the conclusion suggested that both the data-driven model can be used in the prediction of the clear water scour depth around spur dikes but GBM have highest accuracy.

Study on the Morphology and Mechanical Properties of Cynodon dactylon in the Riparian Zone Slopes of a Large Reservoir

The stability of riverbank slopes is crucial in watershed ecology. The morphology and tensile strength properties of plant roots play a significant role in slope stability, which is of great importance for the ecological stability of riverbanks. The Jinsha and Yalong River basins are the largest hydropower bases in China and are in the ecologically fragile areas of the dry and hot river valleys, yet fewer studies are available on these basins. Further studies on the growth morphology and root mechanical properties of plant roots in the riparian zone at different elevations have not been reported. Therefore, we selected the dominant species of Cynodon dactylon root as the research subject, analyzed the root morphology, and conducted indoor single-root tensile tests to study its root structure and mechanical properties at various elevations. The results showed that the root morphology of Cynodon dactylon was positively correlated with elevation. Compared to low elevations (L and M), the root length increased by 57.3% and 21.47%, the root diameter increased by 24.85% and 13.92%, the root surface area increased by 93.5% and 67.37%, and the total root volume increased by 119.91% and 107.36%. As the elevation gradient increased, the flooding time decreased, leading to more developed plant roots for Cynodon dactylon. The Young’s modulus ranged from 148.43 to 454.18 MPa for Ertan Cynodon dactylon roots and 131.31 to 355.53 MPa for Guanyingyan Cynodon dactylon roots. The maximum tensile strength, ultimate tensile strength, ultimate elongation, and Young’s modulus of the plant root of the Cynodon dactylon showed a power function relationship with the diameter. The maximum tensile strength increased as the diameter increased, while the remaining properties decreased following a power function relationship. The maximum tensile strength, ultimate tensile strength, and Young’s modulus of Cynodon dactylon were positively correlated with elevation, while the ultimate elongation was negatively correlated with elevation. The results elucidate the influence of elevation on the root morphology and mechanical properties of dominant riparian species. This provides a theoretical basis for managing and protecting riparian slopes in ecologically fragile areas.

Vegetation enhances curvature-driven dynamics in meandering rivers

Stabilization of riverbanks by vegetation has long been considered necessary to sustain single-thread meandering rivers. However, observation of active meandering in modern barren landscapes challenges this assumption. Here, we investigate a globally distributed set of modern meandering rivers with varying riparian vegetation densities, using satellite imagery and statistical analyses of meander-form descriptors and migration rates. We show that vegetation enhances the coefficient of proportionality between channel curvature and migration rates at low curvatures, and that this effect wanes in curvier channels irrespective of vegetation density. By stabilizing low-curvature reaches and allowing meanders to gain sinuosity as channels migrate laterally, vegetation quantifiably affects river morphodynamics. Any causality between denser vegetation and higher meander sinuosity, however, cannot be inferred owing to more frequent avulsions in modern non-vegetated environments. By illustrating how vegetation affects channel mobility and floodplain reworking, our findings have implications for assessing carbon stocks and fluxes in river floodplains.

Experimental study on the optimal spur dike shape under downward seepage

ABSTRACT The successful stabilization of riverbanks and the construction of sustainable foundations, extensive knowledge of the scour process and accurate assessment of scour depth around spur dikes are required. This study focuses on optimizing the spur dike shape to manage flow turbulence effectively and minimize local scour while considering the impact of downward seepage. The investigation was conducted within an experimental flume featuring a mobile bed under a clear water regime and the provision for downward seepage. The investigation concentrated on three distinct spur dike shapes (T, L, and rectangular) under different seepage velocities (V S1 and V S2) and a no-seepage condition. The current study also illustrates changes in bed morphology, temporal evolution and longitudinal profile of scour depth with and without downward seepage. The results reveal that the downward seepage intensifies the motion of sediment particles, and more seepage leads to an escalated particle detachment, resulting in deeper scour depressions. The T-shaped spur dikes exhibited the lowest scour depths compared to the other shapes, both with and without seepage. The negative impact on velocity and RSS magnitude was observed at the near channels bed where maximum scour depth was achieved. This phenomenon is closely linked to horseshoe vortices’ formation and current generation. These factors play a pivotal role in the detachment of particles from the base of the structure.

A framework model to integrate sources and pathways in the assessment of river water pollution

Metal and nutrient pollution, soil erosion, and alterations in climate and hydrology are prevalent issues that impact the water quality of riverine systems. However, integrated approaches to assess and isolate causes and paths of river water pollution are scarce, especially in the case of watersheds impacted by multiple hazardous activities. Therefore, a framework model for investigating the multiple sources of river water pollution was developed. The chosen study area was the Paraopeba River basin located in the Minas Gerais, Brazil. Besides multiple agriculture, industrial, and urban pollution sources, this region was profoundly affected by the rupture of the B1 tailings dam (in January 2019) at the Córrego do Feijão mine, resulting in the release of metal-rich waste. Considering this situation, thirty-nine physicochemical and hydromorphological parameters were examined in the Paraopeba River basin, in the 2019–2023 period. The analysis involved various statistical techniques, including bivariate and multivariate methods such as correlation analysis, principal component analysis, and clustering. The Paraopeba River was mainly impacted by metal contamination resulting from the dam collapse, whereas nutrient contamination, mainly from urban and industrial discharges, predominantly affected its tributaries. Additionally, the elevated concentrations of aluminum, iron, nitrate, and sulfate in both main river and tributaries can be attributed to diffuse and point source pollution. In terms of hydromorphology and soil type, the interaction between woody vegetation and erosion-resistant soils, especially latosols, contributes to the stability of riverbanks in the main river. Meanwhile, in the tributaries, the presence of neosols and sparse vegetation in urbanized areas promoted riverbank erosion potentially amplifying pollution. While the study was conducted in a particular watershed, the findings are based on a methodology that can be applied universally. Hence, the insights on surface water quality from this research can be a valuable resource for researchers studying watersheds with diverse pollution sources.

Recent changes in riparian and floodplain vegetation in England and Wales and its geomorphic implications

AbstractRecent river studies in the United Kingdom have observed an increase in riparian vegetation and its potential impact on river channel change and sedimentation. Here, we quantify changes in floodplain and riparian vegetation during the first two decades of the 21st century along reaches of eight gravel‐bed rivers in England and Wales that exhibit varied active and stable, single and multi‐thread planforms. The analysis employs information drawn from open‐access sources including national LiDAR surveys and the photographic analysis of repeat aerial and satellite imagery. Most reaches show an increase in woody vegetation across their floodplains reflecting both natural colonisation and deliberate planting, and all but one of the reaches show an increase in woody riparian vegetation cover along their riverbanks. Of the six reaches that have exposed riverine sediments, five show a reduction in exposed sediment area as a result of vegetation encroachment. Contrasts in the rate, extent and location of riparian change were associated with the stability of the channel planform, with differences seen between stable and more active reaches. The significance of riparian woodland in promoting riverbank stability is demonstrated. Riparian vegetation development varies between river reaches, largely in response to differing rates of channel movement but also because of multiple and diverse local decisions regarding the management of in‐channel and channel‐adjacent vegetation by landowners rather than a single national policy. We consider the relevance of our findings and the value of remote monitoring for future river management interventions.

Approximation in scour depth around spur dikes using novel hybrid ensemble data-driven model.

The scouring process near spur dikes poses a threat to riverbank stability, making it crucial for river engineering to accurately calculate the maximum scour depth. However, determining the maximum scour depth has been challenging due to the intricacy of scour phenomena surrounding these structures. This research introduces a reliable ensemble data-driven model by hybridizing random tree (RT) using additive regression (AR), bagging (B), and random subspace (RSS) for predicting scour depths around spur dikes. A database of 154 experimental observations was collected from literature, with 103 and 51 observations used for training and testing subsets, respectively. A dimensionless analysis was performed on the collected dataset, selecting four variables as input variables (v/vs, y/l, l/d50, and Fd50) and ds/l as response variables. The performance comparison demonstrates that B_AR_RT has a better coefficient of determination (R2) of 0.9693, root mean square error (RMSE) of 0.1305, and Nash-Sutcliffe efficiency (NSE) of 0.9692. Finally, a comparison of the best hybrid model has been done with previous studies, and sensitivity analysis is performed to determine the most influential parameter for predicting the scour depth around spur dikes.

Review on different shapes of spurs and their effects on channel morphology

Abstract In this paper, the significance of the shape of spurs on flow and bed morphology is understood, accompanied by an appeal to investigate alternative shapes like L-head, T-head spurs, and hockey-shaped spurs, which could offer considerable benefits for river management. The spurs with T-head shape are found to be more efficient in reducing the bed scouring of the channel relatively, although it depends on the orientation of the spur, location of installation, and shape of the channel. Furthermore, development of horseshoe vortex is found insignificant near the base of the T-head spur dike. T-head spurs could more effectively redirect flow and prevent erosion while L-head spurs may enhance riverbank stability. This highlights the need for more investigation into how different spur shapes collectively affect river morphology, flow velocity, and sediment transport patterns. Temporal variations in bed morphology, especially the scour depth and sediment transport dynamics near spur dikes, should also be investigated to understand their changing impact better. Finally, this study provides a complete summary of existing knowledge gaps and future research initiatives relevant to various shapes of spur dikes and their role in riverbank erosion management.

Mathematical Treatment of Bimodality for the Safety Factor in Riverbank Stability Analysis Using Cusp Catastrophe

Mathematical Treatment of Bimodality for the Safety Factor in Riverbank Stability Analysis Using Cusp Catastrophe

Uncovering the lack of awareness of sand mining impacts on riverbank erosion among Mekong Delta residents: insights from a comprehensive survey

Global sand demand due to infrastructure construction has intensified sand mining activities in many rivers, with current rates of sand extraction exceeding natural replenishment. This has created many environmental problems, particularly concerning riverbank stability, which adversely affects the livelihoods of people in the Vietnamese Mekong Delta (VMD). However, sand mining’s social impacts in the region remain inadequately understood. Here we assess locals’ perception of sand mining activities in the VMD and its impacts on riverbank erosion. Residents living along the Bassac River, a hotspot of sand mining, were interviewed. Our results showed that while sand mining is perceived as destructive to the environment, few were aware of its role in worsening riverbank erosion. Only residents directly affected by riverbank collapse were aware of the implications of sand mining and its negative effect on bank stability, as they seem to have actively sought clarification. Our findings highlight the need for greater awareness and understanding among the locals regarding sand mining’s impact on riverbank stability.

Stability analysis of riverbanks with a dual structure under water-root-soil coupling.

The collapse mechanism of dual-structure vegetation riverbanks at different water levels is unclear. A method for calculating the critical collapse width of a dual-structure vegetation bank under different failure modes that consider the variations in river and groundwater levels and the influence of vegetation roots is proposed. Combined with the influence of flow lateral erosion and slope toe accumulation, a calculation model of riverbank stability was established. The results show that shear failure is the main failure mode when the cohesive soil layer on a dual-structure bank is thick, and the critical collapse width of the bank with root soil is higher than that of the soil bank. The critical collapse width of the bank varied with the water level during different water level periods. Compared with a soil riverbank, a rooted soil riverbank can significantly prolong the bank collapse time. The collapse width of a soil bank without vegetation roots is smaller than that of a rooted soil bank, and the cumulative collapse width is related to calculation time. The greater the thickness of rooted soil, the slower the decay rate of bank stability under water flow erosion.

Application of Machine Learning Models to Bridge Afflux Estimation

Bridges are essential structures that connect riverbanks and facilitate transportation. However, bridge piers and abutments can disrupt the natural flow of rivers, causing a rise in water levels upstream of the bridge. The rise in water levels, known as bridge backwater or afflux, can threaten the stability or service of bridges and riverbanks. It is postulated that applications of estimation models with more precise afflux predictions can enhance the safety of bridges in flood-prone areas. In this study, eight machine learning (ML) models were developed to estimate bridge afflux utilizing 202 laboratory and 66 field data. The ML models consist of Support Vector Regression (SVR), Decision Tree Regressor (DTR), Random Forest Regressor (RFR), AdaBoost Regressor (ABR), Gradient Boost Regressor (GBR), eXtreme Gradient Boosting (XGBoost) for Regression (XGBR), Gaussian Process Regression (GPR), and K-Nearest Neighbors (KNN). To the best of the authors’ knowledge, this is the first time that these ML models have been applied to estimate bridge afflux. The performance of ML-based models was compared with those of artificial neural networks (ANN), genetic programming (GP), and explicit equations adopted from previous studies. The results show that most of the ML models utilized in this study can significantly enhance the accuracy of bridge afflux estimations. Nevertheless, a few ML models, like SVR and ABR, did not show a good overall performance, suggesting that the right choice of an ML model is important.