In this research, an assessment of scour depth prediction in meandering channels with spur dikes is made employing machine learning approaches. Efficient determination of the scour depth is therefore vital in the prediction of morphologic aspects and structural stability. The input parameters include sinuosity (S), spur dike locations (Ld), and porosity (P) with experimental data from sinusoidal flumes. Four machine learning models; Extreme Gradient Boosting (XGBoost) with Particle Swarm Optimization (PSO) XGBoost-PSO, Random Forest (RF), k-Nearest Neighbors (k-NN), and Decision Tree-Neural Network (DT-NN) were used and compared. The findings demonstrate an R-value of 0.995 in the case of RF model while XGBoost-PSO gave second-best accuracy with R = 0.988. The results of the SHAP analysis illustrated that porosity and sinuosity are significant factors affecting scour depth (Ds/Yn, Ds: scour depth, Yn: water depth) and had moderate importance assigned to spur dike location. Kernel density plots further supported the RF model regarding error distribution consistency. Even though, both XGBoost-PSO yielded better results because of hyperparameter tuning, k-NN and DT-NN had less precise outcomes specifically predicted for progressive hydraulic procedures. Taylor's diagram even revealed greater accuracy of prediction by RF. Hence, a proper selection of appropriate machine learning models remains the first step in estimating scour depth sufficiently for flood and erosion control.

This study investigates the role of emerged vegetation in enhancing the performance of submerged spur dikes for better flow control and bank protection in river systems. The research utilizes a numerical model based on Computational Fluid Dynamics (CFD), validated with experimental data. After validation, the study explores various configurations of vegetated spur dike, adjusting the submergence heights of the impermeable spur dike to achieve porosity ranging from fully impermeable to highly porous. Porosity levels of 24%, 48%, and 72% were chosen based on the spur dike height and the effectiveness of staggered vegetation arrangements in maximizing drag and reducing velocity. This approach aims to determine their impact on flow structure, velocity, and turbulence characteristics. The results reveal that impermeable dikes create strong recirculation zones downstream, increasing the potential for bank erosion. Introducing vegetation on the dike, particularly at moderate porosities (24% and 48%), effectively disrupts this behavior by reducing downstream velocity and mitigating mass and momentum exchange concentration between the spur dike field and the mainstream. However, the highest porosity case (72%) offered reduced flow resistance, limiting its protective effectiveness. Analysis of velocity and stress distributions showed that vegetation porosity significantly impacts normal and shear stresses, influencing flow stability at critical points around the spur dike. The findings signify the potential of integrating vegetation into spur dike designs to achieve a balance between effective flow conveyance and erosion control even in the spur dike submergence condition. This approach can outperform conventional emerged impermeable spur dikes, as supported by previous studies that demonstrate the effectiveness of porous and vegetated structures in reducing flow resistance, minimizing stagnation zones, and improving sediment deposition compared to impermeable designs.

A flood protection dike blends seamlessly with natural surroundings. These dikes stand as vital shields, mitigating the catastrophic effects of floods and preserving both communities and ecosystems. Their design not only aids in controlling water flow but also ensures minimal disruption to the local environment and its biodiversity. The present study used a uniform cohesionless sand with d₅₀ = 0.9 mm to investigate the local scour process near a single combined dike (permeable and impermeable), replicating a flooding scenario. The experiments revealed that the maximum scour depth is likely to occur at the upstream edge of the dike, resembling a local scour observed around a scaled-down emerged dike in an open channel. The scour hole downstream of the dike gets shallower as it gets smaller, as do the horseshoe vortices that surround it. Additionally, by combining different pile shapes, the flow surrounding the dike was changed to reduce horseshoe vortices, resulting in scour length and depth reductions of 48% at the nose and 45% and 65% at the upstream and downstream dike–wall junction, respectively. Contrarily, the deposition height downstream of the dike had a reciprocal effect on permeability, which can severely harm the riverbank defense system. The combined dike demonstrates their ability to mitigate scour by reducing the flow swirls formed around the dike. The suggested solutions can slow down the rapid deterioration and shield the dike and other river training infrastructure from scour-caused failures.