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2 Acta Geophysica

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Daily streamfow prediction using support vector machine artifcial fora (SVM AF) hybrid model

100%

Dehghani R. , Torabi Poudeh H. , Younesi H. , Shahinejad B.

Acta Geophysica

2020

tom Vol. 68, no. 6

1763--1778

Precise estimation of river fow in catchment areas has a signifcant role in managing water resources and, particularly, mak ing frm decisions during food and drought crises. In recent years, diferent procedures have been proposed for estimating river fow, among which hybrid artifcial intelligence models have garnered notable attention. This study proposes a hybrid method, so-called support vector machine–artifcial fora (SVM-AF), and compares the obtained results with outcomes of wavelet support vector machine models and Bayesian support vector machine. To estimate discharge value of the Dez river basin in the southwest of Iran, the statistical daily watering data recorded by hydrometric stations located at upstream of the dam over the years 2008–2018 were investigated. Four performance criteria of coefcient of determination (R2 ), rootmean-square error, mean absolute error, and Nash–Sutclife efciency were employed to evaluate and compare performances of the models. Comparison of the models based on the evaluation criteria and Taylor’s diagram showed that the proposed hybrid SVM-AF with the correlation coefcient R2 = 0.933–0.985, root-mean-square error RMSE = 0.008–0.088 m3 /s, mean absolute error MAE = 0.004–0.040 m3 /s, and Nash-Sutclife coefcient NS = 0.951–0.995 had the best performance in estimating daily fow of the river. The estimation results showed that the proposed hybrid SVM-AF model outperformed other models in efciently predicting fow and daily discharge.

Flow structures in asymmetric compound channels with emergent vegetation on divergent floodplain

88%

Rahim A. S. , Yonesi H. A. , Shahinejad B. , Podeh H. T. , Azamattulla H. M.

Acta Geophysica

2022

tom Vol. 70, no 5

2403--2421

Knowledge and management of hydraulic processes including flow pattern, sediment transport, and food level prediction in natural rivers require proper understanding of interactions between food flow and vegetation in floodplains. This study examined the flow structures and turbulence parameters in an asymmetric non-prismatic compound channel with different vegetation densities in divergent floodplain. Due to existence of vegetation, the bed shear stresses in the middle and end of the divergence floodplain decrease 78.5% and 86%, respectively. Also, the depth-averaged velocity in vegetated floodplain diminishing by about 60% and 69%. The results revealed that the production and dissipation of Reynolds shear stresses and the formed shear layer depend on the vortex shedding frequency formed behind each single rod and is very unstable. Finally, some equations were presented to estimate friction factor based on rod Reynolds number, calculate the frequency of the vortices generated behind the elements and the local drag coefficient.