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Nowadays, the porous screens have been used extensively in open channels to prevent erosion in ditches as the water in supercritical state flows past the screen which forces the formation of a hydraulic jump upstream of the screen and produces significant energy loss. In this investigation, the operation of screens has been studied for supercritical flow and the Froude number in the range of 4.5 to 10.6 on two reverse slopes experimentally. In this study, the parameters included arrangements of screens in both the single and double types, and the angle and distance of screens from the hydraulic jump toe. The screens were studied with a porosity of about 50% with square holes. The study results showed that using of screens on the reverse slope of − 0.025 dissipates more energy compared to reverse slope of − 0.015. The screens with double arrangement have better performance and dissipate more energy than the screens with single arrangement, while the distance of screens from the toe of the hydraulic jump does not have a significant effect on the energy dissipation.

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Various shapes of weirs, such as rectangular, trapezoidal, circular, and triangular plan forms, are used to adjust and measure the flow rate in irrigation networks. The discharge coefficient (Cd) of weirs, as the key hydraulic parameter, involves the combined effects of the geometric and hydraulic parameters. It is used to compute the flow rate over the weirs. For this purpose, a hybrid ISADE-SVR method is proposed as a hybrid model to estimate the Cd of sharp-crested W-planform weirs. ISaDE is a high-performance algorithm among other optimization algorithms in estimating the nonlinear parameters in different phenomena. ISaDE algorithm is used to improve the performance of SVR by finding optimal values for SVR's parameters. To test and validate the proposed model, the experimental dataset of Kumar et al. and Ghodsian were utilized. Six different input scenarios are presented to estimate the Cd. Based on the modeling results, the proposed hybrid method estimates the Cd in terms of the H/P, Lw/Wmc, and Lc/Wc. For the superior method, R2, RMSE, MAPE, and δ are obtained as 0.982, 0.006, 0.612, and 0.843, respectively. The amount of improvement in compared with GMDH, ANFIS and SVR is 3.6%, 1.2%, 1.5% in terms of R2.

The present research describes a laboratory study of hydraulic jump in the abrupt asymmetric expansion stilling basin as an energy dissipator by changing the geometry of walls and bed roughness elements. The experiments were carried out in a horizontal flume with 10 m length, 0.5 m width, and 0.5 m depth for a range of the upstream Froude numbers ( F r 1 ) from 5 to 11. Four physical models with expansion ratio of α   = 0.33, 0.5, 0.67, and 1 and asymmetry ratio of Δ = 0.16 were installed in the flume and two different heights of roughness elements ( h   = 1.4 and 2.8 cm) were also considered. The results indicated that the sequent depth and the jump length as well as the roller length below abrupt asymmetric expansion on the rough bed were decreased in comparison to the same parameters of the jump in a prismatic channel with smooth bed. It was revealed that the roughness elements have the effective role on stabilization of the hydraulic jump location. The analysis of energy dissipation efficiency confirmed that the spatial jump in the abruptly expanded basin with roughened bed was more efficient than classical jump. In order to estimate the hydraulic jump characteristics, empirical relationships associated with expansion ratio of basin walls, relative height of roughness elements and upstream Froude number were proposed based on the experimental data that resulted in preliminary design of an abrupt asymmetric enlarged basin.

Owing to the nonlinear and non-stationary nature of the suspended sediment transport in rivers, suspended sediment concentration (SSC) modeling is a challenging task in environmental engineering. Investigation of SSC is of paramount importance in river morphology and hydraulic structures operation. To this end, for SSC modeling, first random forest (RF) and multi-layer perceptron (MLP) standalone models were developed, and then, they were optimized with genetic algorithm (GA) and stochastic gradient descent (SGD) to develop GA-MLP, GA-RF, SGD-MLP, and SGD-RF hybrid models. Variety of input scenarios are implemented for SSC prediction to find the best input combination. The streamflow and SSC data collected from two stations of Minnesota and San Joaquin rivers, respectively, located at South Dakota and California are utilized in the current study. Accuracies of the developed models are examined by means of three performance criteria of correlation coefficient (CC), scattered index (SI), and Willmott's index of agreement (WI). A significant promotion in accuracy of hybrid models has been seen in contrast to their standalone counterparts. As can be deduced from the results, GA-MLP-5 and GA-RF-5 models with CC of 0.950 and 0.944, SI of 0.290 and 0.308, and WI of 0.974 and 0.971, respectively, were found as best models for prediction of SSC at Minnesota river. The developed SGD-MLP-5 and SGD-RF-5 models with CC of 0.900 and 0.901, SI of 0.339 and 0.339, and WI of 0.945 and 0.946, respectively, gave accurate results at San Joaquin river. Through the application of SGD algorithm, the adaptive learning rate, epochs, rho, L1 and L2 were activated and presumed as 0.004, 10, 1, 0.000009 and 0, respectively. The ExpRectifier was considered as san activation operation due to its better efficiency in comparison with its alternatives for predicting SSC in SGD-MLP model. According to the results, the fifth scenario that incorporates SSC t-1 , SSC t-2 , Q t , Q t-1 , and Q t-2 were found superior for SSC modeling in the studied rivers. The recommended hybrid algorithms based on GA and SGD optimization algorithms are proposed as practical tools for solving complex environmental problems.