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Assessment of flow characteristics through a grassed canal

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Abstract

Vegetation is defined as a kind of surface roughness, which reduces the capacity of the channel and retards the flow by causing loss of energy through turbulence and drag forces of moving water. In water channels, vegetation maybe used to stabilize the water surface and prevent erosion caused by concentrated water flow. In terms of channel lining, grass offers the least expensive option and is the most esthetically pleasing. Most previous studies on this subject were conducted using artificial vegetation in laboratory experiments; research conducted in canals with natural vegetation is lacking. In this study, flow characteristics through a natural grassed canal are studied. In addition, the Manning coefficient and specific energy were determined based on field measurements for both grassed and un-grassed canals. The fieldwork was conducted on Ganabia 9B, southeast of El-Mahalla El Kubra, El-Gharbia, Egypt. The average heights of vegetation in the grassed canal ranged from (28 to 100) cm and the values of flow rate range from (0.0504 to 0.1127) m3/s. The number of tests is 42 tests for the un-grassed canal and 205 tests for the grassed canal. This study indicated that the Manning coefficient increased with an increase in energy and momentum coefficients. The energy coefficient increased with a decrease in relative specific energy and an increase in grass height. The un-grassed canal exhibited a smaller relative specific energy than the grassed canal. The momentum coefficients for the non-grassed and grassed canals were 1.015–1.517 and 1.003–1.655, respectively. Therefore, the un-grassed canal showed a higher momentum coefficient than the grassed canal at a ratio of 0.264–1.196%. The relative specific energy was calculated in two ways: (i) using the actual energy coefficient values and (ii) setting it equal to one. As such, the error percentages of the specific energy for the grassed and un-grassed canals were 0.000105–0.1652% and 0.0048–0.2194%, respectively. The results obtained herein were compared with those obtained in previous studies, showing good agreement, but differ in the accuracy of predicting values. Three programs, i.e., gene expression programming, Statistical Package for the Social Sciences, and artificial neural network, were employed to create empirical formulas for modeling the Manning coefficient and relative specific energy for the grassed and un-grassed canals. Gene expression programming was found to be the best modeling program.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Some data generated or analyzed during this study are included in this published article.

Abbreviations

A :

Cross-sectional area (m2)

dA :

Elementary area in the whole water area (m2)

E :

Specific energy (m)

E r :

Relative specific energy (m)

E rc :

Calculated relative specific energy (m)

E rp :

Predicted relative specific energy (m)

F r :

Froude number

g :

Acceleration due to gravity (m/s2)

h :

Water depth (m)

h gr :

Grass height (m)

K gr :

Grass density

L :

Canal length (m)

n :

Manning coefficient

P :

Wetted perimeter (m)

Q :

Discharge of flow (m3/s)

R :

Hydraulic radius (m)

S :

Bed slope

T :

Top width (m)

V :

Mean velocity (m/s)

V max :

Maximum velocity (m/s)

V r :

Velocity ratio

V 1 :

The upstream velocity (m/s)

V 2 :

The downstream velocity (m/s)

V i :

Point velocity at each point in the cross section (m/s)

y c :

Critical water depth (m)

α :

Energy coefficient

β :

Momentum coefficient

ρ :

The water density (kg/m3

References

  1. Moriasi D, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Am Soc Agric Biol Eng 50(3):885–900. https://doi.org/10.13031/2013.23153

    Article  Google Scholar 

  2. Yoon KS, Koh JH, Chu HJ (2008) 'Overflow characteristics on the grassed inner slope due to levee overtop**. In: 16th IAHR-APD congress, and 3rd symposium of IAHR-ISHS

  3. Arshad M, Ahmad N, Usman M, Shabbir A (2009) Comparison of water losses between unlined and lined watercourses in Indus basin of Pakistan. Pak J Agri Sci 46(4):2076–2906

    Google Scholar 

  4. Souliotis D, Prinos P (2010) '3D numerical computations of turbulence in partially vegetated shallow channel. River Flow 2010-Dittrich, Koll, Aberle, and Geisenhainer (eds), ISBN 978-3-939230-00-7.

  5. Chen Y, Kao SP, Lin JY, Yang HG (2009) Retardance coefficient of vegetated channels estimated by the Froude number. Ecol Eng 35:1027–1035

    Article  Google Scholar 

  6. Chen Y, Kao S (2011) Velocity distribution in open channels with submerged aquatic plants. Hydrol Process 25(13):1269

    Article  Google Scholar 

  7. Nehal L, Yan ZM, **a JH, Khaldi A (2012) 'Flow-through non-submerged vegetation: a flume experiment with artificial vegetation. In: Sixteenth international water technology conference, Istanbul, Turkey

  8. Chen JM, Chen X, Ju W (2013) Effects of vegetation heterogeneity and surface topography on spatial scaling of net primary productivity. Biogeosciences 4879:4896. https://doi.org/10.5194/bg-10-4879-2013

    Article  Google Scholar 

  9. Curran JC, Hession WC (2013) Vegetative impacts on hydraulics and sediment processes across the fluvial system. J Hydrol. https://doi.org/10.1016/j.jhydrol.2013.10.013

    Article  Google Scholar 

  10. Hamimed A, Nehal L, Benslimane M, Khaldi A (2013) Contribution to the study of the flow resistance in a flume with artificial emergent vegetation. Larhyss J 1112–3680:55–63

    Google Scholar 

  11. Huthoff F, Straatsma MW, Augustijn DC, Hulscher SJ (2013) Evaluation of a simple hydraulic resistance model using flow measurements collected in vegetated waterways. Open J Modern Hydrol 3:28–37

    Article  Google Scholar 

  12. Zhu C, Hao W, Chang X (2014) Vertical velocity distribution in open channel flow with rigid vegetation. Sci World J 2014:6

    Google Scholar 

  13. Devi TB, Kumar B (2015) Flow analysis around submerged vegetation. In: E-proceedings of the 36th IAHR World Congress

  14. Folorunso OP (2015) Evaluating the roughness and hydraulic resistance of partly vegetated heterogeneous open channel. J Sci Res Essays 2311–6188:593–597

    Google Scholar 

  15. Jiang B, Yang K, Cao S (2015) An analytical model for the distributions velocity and discharge in compound channels with submerged vegetation. PLOS ONE 1:10. https://doi.org/10.1371/Journal.pone.0130841

    Article  Google Scholar 

  16. Kubrak E, Kubrak J, Kiczko A (2015) Experimental investigation of kinetic energy and momentum coefficients in regular channel with stiff and flexible elements simulating submerged vegetation. Inst Geophys Polish Acad Sci 63(5):1405–1422

    Google Scholar 

  17. Koftis T, Prinos P (2015) Reynolds stress modeling of open channel flow with suspended vegetation. In: E-proceedings of the 36th IAHR world congress

  18. Keramaris E, Pechlivanidis G, Kasiteropoulou D, Michalolias N, Liakopoulos A (2016) Experimental and numerical study of turbulent flow in open channels with impermeable and porous bed. In: International conference on efficient and sustainable water systems management toward worth living development, 2nd EwaS, pp 381–387

  19. Mitra L, Saikia MD (2016) Experimental study of the effect of bed resistance on velocity profiles in rectangular channel. Int Res J Eng Technol 3:1039

    Google Scholar 

  20. Muhammad MM, Yusof KW, Mustafa MR, Ghani AA (2016) Velocity distributions in grassed channel. In: 4th annual international conference on architecture and civil engineering, ISSN 2301-394X, Grant No. 311

  21. Han L, Zeng Y, Chen L, Li M (2017) ’ Modeling streamwise velocity and boundary shear stress of vegetation covered flow. J Ecol Ind 92:378–387. https://doi.org/10.1016/j.ecolind.2017.04.012

    Article  Google Scholar 

  22. Bora P, Misra K (2018) An experimental study on the effect of flexibility of vegetation on resistance to flow. Int Res J Eng Technol 5:102369

    Google Scholar 

  23. Muhammad MM, Yusof WK, Mustafa MR, Zakaria NA, Ghani AA (2018) Prediction models for flow resistance in flexible vegetated channels. Int J River Basin Manag 7:1571–5124

    Google Scholar 

  24. Rizalihadi M, Ziana SN, Ashar H (2018) The effect of ratio between rigid plant height and water depth on the manning’s coefficient in an open channel. IOP Conf Ser Mater Sci Eng 352:012039. https://doi.org/10.1088/1757-899X/352/1/012039

    Article  Google Scholar 

  25. Zhang J, Zhong Y, Huai W (2018) Transverse distribution of streamwise velocity in open channel flow with artificial emergent vegetation. Ecol Eng 78:110

    Google Scholar 

  26. Li W, Wang D, Jiao J, Yang K (2019) Effects of vegetation patch density on flow velocity characteristics in an open channel. J Hydrodyn 31(5):1052–1059

    Article  Google Scholar 

  27. Devi TB, Sharma A, Kumar B (2019) Flow characteristics in a partly vegetated channel with emergent vegetation and seepage. J Ecohydrol Hydrobiol 20:1642–3593

    Google Scholar 

  28. MohammadPour R, Zainalfikry MK, Zakaria NA, Ab. Ghani, A., and Chan, N.W. (2019) Manning’s roughness coefficient for the ecological subsurface channel with modules. Int J River Basin Manag 18(3):349–361. https://doi.org/10.1080/15715124.2019.1672704

    Article  Google Scholar 

  29. Rizalihadi M (2019) The effect of density and height of vegetation in an open channel on the Manning's coefficient. In: MATEC web of conferences vol 258, pp 01002

  30. Shafaei H, Amini A, Shirdeli A (2019) Assessing submerged vegetation roughness in streambed under clear water condition using physical modeling. J Water Res 46(3):0097–8078

    Google Scholar 

  31. Tong X, Liu X, Yang T, HuaM Z, Wang Z, Liu J, Lim R (2019) Hydraulic features of flow-through local non-submerged rigid in the Y-shaped confluence channel. J Water 11:146

    Article  Google Scholar 

  32. Li Y, **e L, Su TC (2019) Vertical distribution of suspended sediments above dense plants in water flow. Water 12(1):102. https://doi.org/10.3390/w12010012

    Article  Google Scholar 

  33. Abd Elmoaty MS, El-samman TA (2020) Manning roughness coefficient in vegetated open channels. J Water Sci 34(1):121–128. https://doi.org/10.1080/11104929.2020.1794706

    Article  Google Scholar 

  34. Majedi MR, Afrazi M, Fakhimi A (2020) A Micromechanical model for simulation of rock failure under high strain rate loading. Int J Civil Eng. https://doi.org/10.1007/s40999-020-00551-2

    Article  Google Scholar 

  35. Manal G, Mohamed F, Sobeih I, Rashwan MH, Helal E (2020) Hydraulic features of flow through the grassed canal. Innov Infrastruct Solut 5:59. https://doi.org/10.1007/s41062-020-00308-9

    Article  Google Scholar 

  36. Mohamed H, Abd-Elaal A, Mahmoud MA (2020) Flow characteristics of open channels with floating vegetation. J Eng Res 2:10. https://doi.org/10.21608/jesaun.2020.108332

    Article  Google Scholar 

  37. Rahimi HR, Tang X, Singh P (2020) Experimental and numerical study on the impact of double-layer vegetation in open-channel flows. J Hydrol Eng 25(2):1084–699. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001865

    Article  Google Scholar 

  38. Zhang S, Liu Y, Wang Z, Li G, Chen S, Liu M (2020) Effect of slope and flow depth on roughness coefficient of lodged vegetation. J Environ Earth Sci. https://doi.org/10.1007/s12665-020-8893-9

    Article  Google Scholar 

  39. Abdelmatalib HM, Dafsari RA, Seung-Hwa Yu, Lee J (2021) Computational study of internal flow characteristics of the air induction nozzle. Int J Mech Sci. https://doi.org/10.1016/j.ijmecsci.2021.106578

    Article  Google Scholar 

  40. Caroppi G, Vastila K, Gualtieri P, Jarvela J, Giugni M, Rowinski P (2021) Comparison of flexible and rigid vegetation induced shear layers in partly vegetated channels. Water Resour Res. https://doi.org/10.1029/2020WR028243

    Article  Google Scholar 

  41. Dubitsky L, Menesses M, Belden J, Bird J (2021) Using aeration to probe the flow characteristics associated with long-term marine macrofouling growth and suppression. J Bioadhesion Biofilm Res. https://doi.org/10.1080/08927014.2021.1900131

    Article  Google Scholar 

  42. Hishikar P, Dhiman SK, Tiwari AK, Gaba VK (2021) Analysis of flow characteristics of two circular cylinders in cross flow with varying Reynolds number: a review. J Thermal Anal Calorim. https://doi.org/10.1007/s10973-021-10933-w

    Article  Google Scholar 

  43. Lama G, Errico A, Pasquino V, Mirzaei S, Preti F, Chirico G (2021) Velocity uncertainty quantification based on Riparian vegetation indices in open channels colonized by Phragmites australis. J Ecohydraul. https://doi.org/10.1080/24705357.2021.1938255

    Article  Google Scholar 

  44. Wang D, Shi S, Fu Y, Song K, Sun X, Tentner A, Liu Y (2021) Investigation of air-water two-phase flow characteristics in a 25.4 mm diameter circular pipe. Prog Nucl Energy. https://doi.org/10.1016/j.pnucene.2021.103813

    Article  Google Scholar 

  45. Yadav D, Naruka DS, Singh PK (2021) The insight flow characteristics of concentrated MWCNT in water base fluid: experimental study and ANN modeling. Heat Mass Transf. https://doi.org/10.1007/s00231-021-03086-x

    Article  Google Scholar 

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Acknowledgements

This study is based on a Ph.D. thesis being prepared by a first author, under the supervision of the other authors.

Funding

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Author information

Authors and Affiliations

  1. Civil Engineering Department, Delta Higher Institute for Engineering and Technology, Mansoura, Egypt

    Manal Gad

  2. Hydraulics, Civil Engineering Department, Faculty of Engineering, Menoufiya University, Mansoura, Egypt

    Mohamed F. Sobeih

  3. Hydraulics, Irrigation, and Hydraulic Engineering Department, Faculty of Engineering, Tanta University, Tanta, Egypt

    I. M. H. Rashwan

  4. Civil Engineering Department, Faculty of Engineering, El-Menoufiya University, Al Minufiyah, Egypt

    Esam Helal

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  1. Manal Gad
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  2. Mohamed F. Sobeih
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  3. I. M. H. Rashwan
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Contributions

All authors contributed to the study's conception and design. Material preparation, data collection, and analysis were performed by the corresponding author. The first draft of the manuscript was written by the corresponding author and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Manal Gad.

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Gad, M., Sobeih, M.F., Rashwan, I.M.H. et al. Assessment of flow characteristics through a grassed canal. Innov. Infrastruct. Solut. 7, 118 (2022). https://doi.org/10.1007/s41062-021-00716-5

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