Hydraulic features of flow through grassed canal

Vegetation is an important feature of many canals as it produces high resistance to flow and has a large impact on water levels and flow velocity. Majority of the research work on the subject was established based on terrestrial plants and plastic molds as laboratorial factors, whereas there are only a few studies done with natural aquatic vegetation. Hence, in this study, the most common type of vegetation was Polygonum Serrulatum, applied mainly to estimate the Manning coefficient and specific energy. The effect of vegetation and their densities on flow characteristics in the field, such as velocity ratio, Froude number, the Manning coefficient, energy coefficient, and momentum coefficient, was also studied. Field works were carried out on Ganabia 9B southeast of El-Mahalla El Kubra, El-Garbia, Egypt from July 2017 to December 2018. The different average heights ratio of vegetation in the grassed canal from the maximum vegetation height, which equals to 115 cm, were 0.24, 0.40, 0.58, 0.79, and 1.0. The velocities and water depths were measured exactly every 100 m in the longitudinal direction and every 0.5 m in the cross-sectional direction, using a Flow Tracker device. Analysis of the hydraulic parameters indicated the existence of strong correlations between the Manning coefficient and the Froude number. The Manning coefficient in partially submerged vegetation was higher than in submerged vegetation. Energy coefficient in the grassed canal was higher than in the un-grassed canal, at a ratio ranging from 0.54% to 4.37%. To verify the results, the data obtained in the present work were compared to those collected from previous studies, where a sound agreement was confirmed. Two programs, namely Statistical Package for the Social Sciences (SPSS) and Gene Expression Programming, were employed to create empirical formulas modeling the Manning coefficient and relative specific energy through the grassed and un-grassed canals. The statistical analysis favored SPSS as the better modeling program.