Predicting suspended sediment load (SSL) in water resource management requires efficient and reliable predicted models. This study considers the support vector regression (SVR) method to predict daily suspended sediment load. Since the SVR has unknown parameters, the observer‐teacher‐learner‐based Optimization (OTLBO) method is integrated with the SVR model to provide a novel hybrid predictive model. The SVR combined with the genetic algorithm (SVR‐GA) is used as an alternative model. To explore the performance and application of the proposed models, five input combinations of rainfall and discharge data of Cham Siah River catchment are provided. The predictive models are assessed using various numerical and visual indicators. The results indicate that the SVR‐OTLBO model offers a higher prediction performance than other models employed in the current study. Specifically, SVR‐OTLBO model offers highest Pearson correlation coefficient (R = 0.9768), Willmott’s Index (WI = 0.9812), ratio of performance to IQ (RPIQ = 0.9201), and modified index of agreement (md = 0.7411) and the lowest relative root mean square error (RRMSE = 0.5371) in comparison with SVR‐GA (R = 0.9704, WI = 0.9794, RPIQ = 0.8521, and md = 0.7323, 0.5617) and SVR (R = 0.9501, WI = 0.9734, RPIQ = 0.3229, md = 0.4338, and RRMSE = 1.0829) models, respectively.

In this study, the hydrodynamics of rectangular broad-crested porous weirs were numerically simulated using a nonlinear model between the pressure gradient and flow velocity through the porous medium. Computational fluid dynamics (CFD) analysis has been performed and renormalized group (RNG) $\mathrm{k}\text{-}ϵ$ model is used as the turbulence closure for Reynolds-averaged Navier-Stokes (RANS) equations. Solid and porous weirs with various properties were examined, and the drag coefficients of the porous weirs in the nonlinear flow resistance model were determined using sensitivity analysis. A logarithmic equation to determine the drag coefficient directly as a function of the hydraulic permeability is presented. By performing three-dimensional (3D) numerical simulations for a wide range of the approach discharge for different porous weir models, the discharge coefficient is described as a piecewise function of related parameters, such as head over the weir, porosity, and the grain diameter of the porous weir. Moreover, for the simulated scenarios, ratios of water passing through and over the weir are determined; consequently, new equations for the discharge ratio are developed. Finally, complex flow features over and through the different porous weirs have been expounded using developed discharge ratio curves.