Skip to main content
SpringerLink
Log in

Estimation of riverbank soil erodibility parameters using genetic algorithm

  • Published:
Sādhanā Aims and scope Submit manuscript

Abstract

Determination of the erodibility parameters, such as critical shear stress and erodibility coefficient, are necessary before estimating the annual bank erosion (or bank retreat) at river reaches. However, in many cases, the river site is inaccessible making it difficult to assess the soil parameters either by in situ tests or by laboratory experiments. In this study, Genetic Algorithm (GA)-based optimisation technique was used to estimate the erodibility parameters of middle reaches of the Brahmaputra River in India. Two approaches were followed. At first, erodibility parameters were estimated using daily stage records at a selected site. Secondly, based on the annual observed bank erosions (bank retreat) from satellite images, erodibility parameters were estimated in three different river reaches. All these results were compared with that from a previous study using in situ jet tests. Annual bank erosions (bank retreat) were estimated using the median values of the erodibility parameters. The results agree well with the average observed annual bank erosion of these river reaches. In addition, the effects of measurement errors and optimisation algorithms on the parameter estimation were analysed. Sensitivity analysis of the parameters in GA was evaluated and it was found that GA can be utilised in the data-scarce regions to estimate the average erodibility parameters.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8

Similar content being viewed by others

References

  1. Hanson G J and Cook K R 1997 Development of excess shear stress parameters for circular jet testing: ASAE. Paper No. 972227. St. Joseph, Mich.: ASAE, doi: 10.1002/esp.1657

  2. Hanson G J 1990a Surface erodibility of earthen channels at high stresses: Part I. Open channel testing. Trans. Am. Soc. Agric. Eng. 33(1): 127–131

    Article  MathSciNet  Google Scholar 

  3. Hanson G J 1990b Surface erodibility of earthen channels at high stresses: Part II. Developing an in-situ testing device. Trans. Am. Soc. Agric. Eng. 33(1): 132–137

    Article  MathSciNet  Google Scholar 

  4. Hanson G J and Cook K R 2004 Apparatus, test procedures, and analytical methods to measure soil erodibility in situ. Appl. Eng. Agric. 20(4): 455–462

    Article  Google Scholar 

  5. Clark L A and Wynn T M 2007 Methods for determining streambank critical shear stress and soil erodibility: implications for erosion rate predictions. Trans. Am. Soc. Agric. Biol. Eng. 50(1): 95–106

    Google Scholar 

  6. Wilcock P R 1996 Estimating local bed shear stress from velocity observations. Water Res. Res. 32(11): 3361–3366

    Article  Google Scholar 

  7. Leutheusser H J 1963 Turbulent flow in rectangular ducts. J. Hydraul. Divis. ASCE 89: 1–19

    Google Scholar 

  8. Grissinger E H 1982 Bank erosion in cohesive materials. In: Hey R D, Bathurst J C and Thorne C R (eds) Gravel-bed rivers. John Wiley & Sons: New York, NY; 273–287

    Google Scholar 

  9. Smerdon E T and Beasley R T 1961 Critical tractive forces in cohesive soils. Agric. Eng. 42(1): 26–29

    Google Scholar 

  10. Julian J P and Torres R 2006 Hydraulic erosion of cohesive riverbanks. Geomorphology 76(1–2): 193–206

    Article  Google Scholar 

  11. Karmaker T and Dutta S 2011 Erodibility of fine soil from the composite river bank of Brahmaputra in India. Hydrol. Process. 25: 104–111

    Article  Google Scholar 

  12. Hanson G J and Simon A 2001 Erodibility of cohesive streambeds in the loess area of the Midwestern USA. Hydrol. Process. 15(1): 23–38

    Article  Google Scholar 

  13. Shields A 1936 Application of similarity principles and turbulence research to bed-load movement. Translated by Ott W P and van Uchelen J C (eds) California Institute of Technology, SCS Co-operative Laboratory: Pasadena, CA. 1–44

  14. Temple D M and Hanson G J 1994 Headcut development in vegetated earth spillways. Appl. Eng. Agric. 10(5): 677–682

    Article  Google Scholar 

  15. Grabowski R C, Droppo I G and Wharton G 2011 Erodibility of cohesive sediment: the importance of sediment properties. Earth-Sci. Rev. 105(1): 101–120

    Article  Google Scholar 

  16. Daly E R, Fox G A, Enlow H K, Storm D E and Hunt S L 2015 Site–scale variability of streambank fluvial erodibility parameters as measured with a jet erosion test. Hydrol. Process. 29: 5451–5464

    Article  Google Scholar 

  17. Karmaker T and Dutta S 2016 Prediction of short-term morphological change in large braided river using 2D numerical model. J. Hydraul. Eng. DOI: 10.1061/(ASCE)HY.1943-7900.0001167

    Google Scholar 

  18. Dutta B and Singh V P 2004 Hydrology. In: Singh V P, Sharma N and Ojha, C S P (Eds.), The Brahmaputra basin water resources. Kluwer Academic, the Netherlands, pp. 139–195

  19. Karmaker T and Dutta S 2010 Generation of synthetic flood hydrograph in a large river basin. J. Hydrol. 381(3–4): 287–296

    Article  Google Scholar 

  20. Karmaker T 2010 Modeling of bank erosion in a composite riverbank in alluvial river bend. Unpublished Ph.D. thesis, Indian Institute of Technology Guwahati, Assam, India. pp 200

  21. Karmaker T and Dutta S 2015 Stochastic erosion of composite banks in alluvial river bends. Hydrol. Process. 29(6): 1324–1339

    Article  Google Scholar 

  22. Lillesand M T, Kiefer R W and Chipman J W 2008 Digital image interpretation and analysis. Remote sensing and image interpretation. 6th edn, India, Wiley, 487

  23. Whitley D 1994 A genetic algorithm tutorial. Statist. Comput. 4(2): 65–85

    Article  Google Scholar 

  24. Deb K 1995 Optimization for engineering design, algorithms and examples, Prentice-Hall India Pvt. Ltd, New Delhi, India

  25. Houck C R, Joines J A and Kay M G 1995 A genetic algorithm for function optimization: a Matlab implementation. NCSU-IE TR, 95(09)

  26. Weile D S and Eric M 1997 Genetic algorithm optimization applied to electromagnetics: a review. IEEE Trans. Antennas Propag. 45(3): 343–353

    Article  Google Scholar 

  27. Das R 2012 Application of genetic algorithm for unknown parameter estimations in cylindrical fin. Appl. Soft Comput. 12(1): 3369–3378

    Article  Google Scholar 

  28. Kirkpatrick S, Gelatt Jr C D and Vecchi M P 1983 Optimization by simulated annealing. Science 220: 671–680

    Article  MATH  MathSciNet  Google Scholar 

  29. Das R and Ooi K T 2013 Application of simulated annealing in a rectangular fin with variable heat transfer coefficient. Inverse Probl. Sci. Eng. 21(8): 1352–1367

    Article  MathSciNet  Google Scholar 

  30. Coleman T F and Li Y 1996 An interior, trust region approach for nonlinear minimization subject to bounds. SIAM J. Optimiz. 6: 418–445

    Article  MATH  MathSciNet  Google Scholar 

  31. Byrd R H, Hribar M E and Nocedal J 1999 An interior point algorithm for large-scale nonlinear programming. SIAM J. Optimiz. 9: 877–900

    Article  MATH  MathSciNet  Google Scholar 

  32. Nocedal J and Wright S J 2006 Numerical optimization, 2nd edn, Springer Series in Operations Research, Heidelberg: Springer Verlag

  33. Das R and Ooi K T 2013 Predicting multiple combination of parameters for designing a porous fin subjected to a given temperature requirement. Energy Conserv. Manag. 66: 211–219

    Article  Google Scholar 

  34. Lawler D M 1993 The measurement of river bank erosion and lateral channel change: a review. Earth Surface Process. Landforms 18(9): 777–821

    Article  Google Scholar 

  35. Lawler D M 1991 A new technique for the automatic monitoring of erosion and deposition rates. Water Resour. Res. 27: 2125–2128

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Civil Engineering, Thapar University, Patiala, 147004, India

    Tapas Karmaker

  2. School of Mechanical, Materials, and Energy Engineering, Indian Institute of Technology Ropar, Rupnagar, 140001, India

    Ranjan Das

Authors
  1. Tapas Karmaker
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ranjan Das
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tapas Karmaker.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Karmaker, T., Das, R. Estimation of riverbank soil erodibility parameters using genetic algorithm. Sādhanā 42, 1953–1963 (2017). https://doi.org/10.1007/s12046-017-0733-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12046-017-0733-6

Keywords

Search

Navigation