Estimating remaining concentration-percentages of resuspended sediments via a non-local particle model for flocculation

Authors

  • A. Abdallah DISIM, University of L'Aquila, L'Aquila, Italy
  • D. Pasquali DICEAA-Liam, University of L'Aquila, L'Aquila, Italy
  • I. Lisi ISPRA, Roma, Italy
  • M. Di Risio DICEAA-Liam, University of L'Aquila, L'Aquila, Italy

Keywords:

sediment transport model, floccule-settling velocity, deterministic particle method, non-local interaction, settling-column tests

Abstract

Maritime works often require sediment handling activities such as dredging and disposal, to maintain harbors and channels, nourish sandy beaches as well as to carefully remove and relocate contaminated materials from the bottom of estuarine and coastal areas. Such operations often lead to an increase in the concentration of suspended sediments in water columns, which in turn causes adverse effects on water quality and aquatic lives. Minimizing these detrimental impacts require designing such maritime works with care, by paying attention to the geometry of areas affected by the sediment resuspension. Numerical modeling has been recognized as a valuable tool to help designers and contractors to optimize such sediment handling works. In obtaining such, one of the most challenging aspects to be tackled is the estimation of the settling velocity of the fine-grained mixture that results from sediment resuspension. These settling velocities are affected by a phenomenon known as flocculation. In this paper, the concept of non-local interacting particles was used to formulate a one-dimensional model for the flocculation phenomenon. Also, a (deterministic) particle transport equation was formulated to reproduce the settling behavior of suspended sediments in a settling column. The proposed model was solved numerically. The simulation results provide an understanding of the mechanisms of flocculation and highlight how flocculation influences floccule-settling velocities and concentration percentages of sediments that remain in suspension.

References

Bridges, T., Ells, S., Hayes, D., Nadeau, S., Palermo, M., Patmont, C., and Schroeder, P., 2008. The four R’s of environmental dredging: Resuspension, release, remaining, and risk. US Army Corps of Engineers.

Chertock, A., 2017. A Practical Guide to Deterministic Particle Methods. In: Handbook of Numerical Analysis 18, 177–197.

Collins M.,1995. Dredging Induced Near Field Resuspended Sediment Concentration and Source Strengths. US Army Corps of Engineers, Waterways Experiment Station.

Di Francesco, M., and Rosini, M.D., 2015. Rigorous derivation of nonlinear scalar conservation laws from follow-the-leader type models via many-particle limit - Archive for rational mechanics and analysis, 217 (3), 831–871. doi:10.1007/s00205-015-0843-4

Di Risio, M., Lisi, I., Beltrami, G., and De Girolamo, P., 2010. Physical modeling of cross-shore short-term evolution of protected and unprotected beach nourishments. Ocean. Eng. 37(89), 777–789. doi:10.1016/j.oceaneng.2010.02.008

Di Risio, M., Pasquali, D., Lisi, I., Romano, A., Gabellini, M., and Paolo, D.G., 2017. An analytical model for preliminary assessment of dredging-induced sediment plume of far-field evolution for spatial non-homogeneous and time-varying resuspension sources. Coastal. Eng. 127, 106–118. doi:10.1016/j.coastaleng.2017.06.003

Je, C.H., Chang, S.W., 2004. Simple approach to estimate flocculent settling velocity in a dilute suspension. Environ. Geol. 45 (7), 1002–1009. doi:10.1007/s00254-004-0959-6

Je, C., Hayes, D., and Kim, K., 2007. Simulation of resuspended sediments resulting from dredging operations by a numerical flocculent transport model. Chemosphere. 70, 187–195. doi:10.1016/j.chemosphere.2007.06.033

José, A.J., Ole, S.M., and M. ASCE (2003). A simple formula to estimate settling velocity of naturalsediments. J. of Waterways, Port, and Coast. Engin. 129(2), 70–78.

Lions, P.-L. and Mas-Gallic S., 2001. Une méthode particulaire déterministe pour des équations diffusives nonlinéaires. (A deterministic particle method for nonlinear diffusive equations. In French). Comptes Rendus De L’Academie Des Sciences Serie I-mathematique. 332(4), 369–376. doi:10.1016/S0764-4442(00)01795-X

Lisi, I., Di Risio, M., and De Girolamo, M., 2016. Engineering tools for the estimation of dredging- induced sediment resuspension and coastal environmental management. In: Intech (Ed.), Applied Studies of Coastal and Marine Environment, 55–83.

Morale, D., Capasso, V.O., and Oeschläger, K., 2005. An interacting particle system modeling aggregation behavior: from individuals to populations. J. Math. Biol. 50, 49–66. doi:10.1007/s00285-004-0279-1

Nichols, M., and Howard-Strobel, M., 1991. Evolution of an urban estuarine harbor: Norfolk, Virginia. J. Coast Res. 7(3), 745–757.

Özer, A., 1994. Simple equations to express settling column data. J. Environ. Eng. 120(3), 677–682. doi:10.1061/(ASCE)0733-9372(1994)120:3(677)

Published

2020-10-01