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DSD-INT 2019 Modeling vegetation controls on gravel bed river morphodynamics - Silviglia

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Presentation by Dr. Annunziato Siviglia, ETH Zürich, Switzerland, at the Delft3D - User Days (Day 3a: River morphodynamics), during Delft Software Days - Edition 2019. Wednesday, 13 November 2019, Delft.

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DSD-INT 2019 Modeling vegetation controls on gravel bed river morphodynamics - Silviglia

  1. 1. Laboratory of Hydraulics, Hydrology and Glaciology DICAM as Siviglia Annunziato* 1 *Laboratory of Hydraulics, Hydrology and Glaciology, ETH Zürich, Switzerland 1 Now at the Department of Civil, Environmental and Mechanical Engineering (DICAM), University of Trento, Italy Modeling vegetation controls on gravel bed river morphodynamics Symposium on Advances in Mathematical Modelling of Hydraulic and Morphodynamic Problems Delft 13.11.2019
  2. 2. 2 ▪ River bars and vegetation: the case of the Alpine Rhine river ▪ Modeling framework I: vegetation as a single biomass and biogeomporphic feedbacks ▪ Modeling framework II: the role of plant roots ▪ Conclusion & Outlook Outline DICAM as
  3. 3. • Alternate bar morphology (42 km) • Reach A: steady bars, Reach B: migrating bars (Adami et al. WRR 2016) 3 River bars and vegetation: the case of the Alpine Rhine river DICAM as
  4. 4. 4 4. Vegetation patternRiver bars and vegetation: the case of the Alpine Rhine river Vegetation establishment on steady bars (Reach A) DICAM as
  5. 5. 5 4. Vegetation patternRiver bars and vegetation: the case of the Alpine Rhine river Vegetation removal on migrating bars DICAM as
  6. 6. 6 River bars and vegetation: the case of the Alpine Rhine river DICAM as
  7. 7. 7 Magra River (Italy) 2007 2011 (before the big flood ) Can we predict how the shift from a vegetated system to a bare soil configuration, occur? DICAM as
  8. 8. Our goal was to advance in the mechanistic understanding and quantification of some important ecomorphodynamic processes, that so far have been described only qualitatively. Our approaches grounded on the deploy, and the development, of models able to shed light on basic processes functioning, highlighting the importance of including a sufficient level of details to study ecomorphodynamic processes, which at the same time allow for a clear identification of cause-effect relationships. These results may form a more solid basis for further studies and focus efforts in experiments and models that seek quantification. 8 4. Vegetation patternModeling goal: DICAM as
  9. 9. 9 3. Basics BASEMENT has a 1D and 2D sub module Hydrodynamics • depth-averaged equations for fluid flow • finite volume discretization using Riemann solvers • unstructured grid (2D) Morphodynamics • Exner equation • Uniform sediments • Bedload DICAM as
  10. 10. 10 Model framework I: Vegetation description Vegetation description Plant DICAM as ζ 𝑢𝑝𝑟 ζ 𝑢𝑝𝑟 = roots length The vegetation is described by a biomass, B. Vegetation description Main biogeomorphic feedbacks Biomass B Flow resistance Shear stresses Sediment cohesion Vegetation removal
  11. 11. • Vegetation dynamics is described by a logistic function: 11 𝑑𝐵 𝑑𝑡 = 𝜎 𝐵 𝐵(𝑡) 1 − 𝐵(𝑡) 𝐾(𝑧 𝐵) 𝜎 𝐵 represents the timescale of vegetation growth; 𝐾(𝑧 𝐵) is the carrying capacity, i.e. the maximum vegetation biomass that can grow at a given bed level. DICAM as Implementation of vegetation dynamics vegetation growth
  12. 12. 12 Implementation of vegetation dynamics Vegetation: distribution on elevation gradient and carrying capacity (Riparia, 2005) We assume that the carrying capacity distribution is a bell-shaped function of the bed elevation 𝑧B. Parameters 𝜆1 and 𝜆2 control the rate at which fitness diminishes away from its maximum, while 𝑧0 is related to the optimal elevation. 𝜙 is a parameter normalizing the maximum value of 𝐾 𝑧 𝐵 to 1 (𝜙 = 2 𝑖𝑓 λ1 = λ2). 𝑧0 is the elevation with respect to the mean water level 𝑧 𝑤. 𝑧 𝑤 is computed assuming a high value of the soil permeability, i.e. it always matches the water stage in the main channel. This is numerically computed using an Inverse Distance Weighted (IDW) algorithm. 𝐾 𝑧 𝐵 = 𝜙 exp 𝜆1 𝑧B − 𝑧W − 𝑧0 + exp −𝜆2 𝑧B − 𝑧W − 𝑧0 DICAM as
  13. 13. λ1 ≠ λ2 𝑧0=5 m 13 Implementation of vegetation dynamics Vegetation: distribution on elevation gradient and carrying capacity λ1 = λ2 𝑧0 𝐾 𝑧 𝐵 𝐾 𝑧 𝐵 𝐾 𝑧 𝐵 Parameters 𝜆1 and 𝜆2 control the rate at which fitness diminishes away from its maximum, while 𝑧0 is related to the optimal 𝜙 = 2 𝑖𝑓 λ1 = λ2 𝑧0=5 m λ1 = λ2 𝑧𝐵 𝜆 ↑ 𝑧w=0 𝑧w=0 𝑧w=0 (Riparia, 2005) 𝐾 𝑧 𝐵 = 𝜙 exp 𝜆1 𝑧B − 𝑧W − 𝑧0 + exp −𝜆2 𝑧B − 𝑧W − 𝑧0 DICAM as
  14. 14. 14 Implementation of vegetation dynamics Vegetation mortality mechanism (uprooting modeling) The plant removal by uprooting, within a cell domain (given location (x,y)) , is modeled assuming that the biomass disappears as soon as the total erosion during a flood event reaches a given value ζ 𝑢𝑝𝑟. In this way we take into account the presence of roots assuming that type II uprooting occurs. (Edmaier et al., 2011) In gravel bed rivers, uprooting occurs as a consequence of riverbed erosion that gradually exposes part of the roots to the flow thus reducing the anchoring resistance of the plant (Type II uprooting as defined by Edmaier et al., 2011). DICAM as Uprooting → 𝐵 → 0 if erosion > ζ 𝑢𝑝𝑟 = roots length
  15. 15. It is evaluated as: 15 Modelling framework Eco-morphodynamics (Corenblit, 2007) 𝑺 𝒇 = 𝑓 𝑡𝑜𝑡𝑎𝑙 𝑠ℎ𝑒𝑎𝑟 𝑠𝑡𝑟𝑒𝑠𝑠 = 𝑓(𝜏) Flow resistance is a function of the total shear stress : 𝜏 = 𝒖 𝒖 𝑲 𝒔 𝟐 ℎ Τ1 3 𝑲 𝒔 = 𝐾𝑠,𝑔 − 𝐾𝑠,𝑔 − 𝐾𝑠,𝑣 𝐵 𝐾 Where 𝐾𝑠,𝑔 is the roughness associated to the bare soil (no vegetation, only sediments!!!) 𝐾𝑠,𝑣 is the Strickler coefficient associated to the vegetation (can be quantified through image analysis e.g. the Jarvela’s approach) 𝐾 𝑖𝑠 𝑡ℎ𝑒 𝑐𝑎𝑟𝑟𝑦𝑖𝑛𝑔 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 DICAM as
  16. 16. 16 (1 − 𝑝) 𝜕𝑧 𝐵 𝜕𝑡 + 𝜕𝑞 𝐵𝑥 𝜕𝑥 + 𝜕𝑞 𝐵𝑦 𝜕𝑦 = 0 Exner eqn. 𝛥𝑥 𝛥𝑦 ℎ 𝑧 𝐵 Evaluation of the sediment discharge ByBx qq , 𝒒 𝐵 = 8(θ − θ 𝑐𝑟) Τ3 2 The modification of the flow field have profound effects on sediment transport. where θ = τ (𝑡𝑜𝑡𝑎𝑙 𝑠ℎ𝑒𝑎𝑟 𝑠𝑡𝑟𝑒𝑠𝑠) (ρ 𝑠 − ρ)𝑔𝑑 𝑠 and  = 𝐾𝑠,𝑔 𝐾𝑠,𝑣 2 < 1 DICAM as 𝜽 𝒄𝒓 = 𝜃𝑐𝑟,𝑔 − 𝜃𝑐𝑟,𝑔 − 𝜃𝑐𝑟,𝑣 𝐵 𝐾 Vegetation roots increase soil cohesion (increase of 𝜽 𝒄𝒓):
  17. 17. 17 17 17 17 Simulations Lenght Width Slope Unique grain size 20 km 125 m 0,38 % 34 mm River bed elevation: Initial configuration for all simulations Magra, 2014 [m] Computational mesh + River bed elevation[m] 1500 m3/s for 30 days DICAM as
  18. 18. 18 18 18 18 Vegetation parameters Changing 𝑧0 DICAM as [Camporeale, 2006]
  19. 19. Eco-morphological interactions River bed elevation [m] Biomass distribution 0 500 1000 1500 2000 0 20 40 60 80 100 Q m3/s Time (h) Hydrograph Initial river bed elevation [m] 19 [m] [m]
  20. 20. 20 20 2020 20 20 20 Results interactions between vegetation and morphology Surviving vegetated patches actively modify the bed topography Stream power→ ω= 𝑄 𝑝 𝑠 𝑊 DICAM as
  21. 21. 21 21 21 2121 21 21 21 Results interactions between vegetation and morphology Vegetation abundance and roots Ground-water level Specialized vs Non-specialized vegetation Growth rate: different plant species or different hydrological regimes (e.g. time span between floods) For the quantitative identification of the threshold between vegetated and un-vegetated configurations we use the asymmetry of the frequency distribution of bed elevation (skweness<0→bare soil, skweness>0→vegetated soil) DICAM as
  22. 22. 22 22 22 2222 22 22 22 Results effect of vegetation spatial distribution Reduced water availability (lower 𝑧0 ) Reduced water availability (lower 𝑧0 ) results in vegetation growing at lower bed elevation (panel A) and consequently in increased erosion and vegetation removal during the flood (Panel B). 𝑧0 𝑧0 DICAM as
  23. 23. • …what we found: • The inclusion of a simple model for vegetation can reproduce the major effects of vegetation on river morphology • Flood intensity, groundwater level and the time lag between floods are crucial parameters for the stabilization of species in a river environment; • …still a lot is needed: • The uprooting mechanism was oversimplified • Taking into account the time lag between floods 23 DICAM as
  24. 24. 24 Vegetation description Main biogeomorphic feedbacks Above-ground Flow resistance Shear stresses Sediment cohesion Vegetation removal Plant Below-ground SEDIMENT Biomass allocation DICAM as Biogeomorphic feedbacks: what is the role of plant roots? This work is part of the Francesco Caponi’s, PhD thesis Laboratory of Hydraulics, Hydrology and Glaciology, ETH Zurich
  25. 25. 25 Plant root description: a stochastic (mean) representation Optimalroot-growzone Rootingdepth Groundwater Rangeofwatertableoscillations Vertical root density distribution Ratio between root grow and decay Function accounting for the stochasticity Tron et al., 2014, 2015 DICAM as
  26. 26. CAPONIFRANCESCO-ISE2018 26 ▪ Below-ground biomass changes the critical Shields parameter: 𝜃𝑐𝑟(ζ) = 𝜃𝑐𝑟,𝑔 − 𝜃𝑐𝑟,𝑔 − 𝜽 𝒄𝒓,𝒗 𝑏 𝑟(ζ) ▪ Uprooting (Type II): 𝛽 = 𝑩 𝒄𝒓 𝐵𝑟 = ‫׬‬0 ζ 𝑢𝑝𝑟 𝑏 𝑟 𝑧 𝑑𝑧 ‫׬‬0 ζ 𝑟 𝑏 𝑟 𝑧 𝑑𝑧 Plant-root feedback: uprooting and root- enhanced soil cohesion DICAM as Experimental evidence suggests that exposure of only part of the entire root biomass might be sufficient to uproot plants (Edmaier et al., 2015).
  27. 27. 27 flow Vegetated patch Erosion Potential: maximum scour at equilibrium in the downstream part ot the patch presence of only above-ground vegetation, 𝐸𝑒𝑞 NO roots Top view of the channel Erosion Riverbed equilibrium Disturbance Numerical runs: quantifying morphological disturbance DICAM as
  28. 28. 28 flow Vegetated patch Uprooting depth: erosion that vegetation withstands before uprooting occurs, ζ 𝑢𝑝𝑟 NO roots Top view of the channel Resistance Eroded vegetation Deep or Numerical runs: including plant roots Shallow DICAM as
  29. 29. 29 Results: vegetated patch at equilibrium Bare riverbed Vegetated riverbed Erosion potential Uprootingdepth Low disturbanceHigh disturbance DICAM as
  30. 30. 30 Bare riverbed Vegetated riverbed Plant root effects are mediated by competition between erosion and resistance DICAM as
  31. 31. • …what we found: • Prediction of the co-evolution of riverbed and vegetation must account for vegetation removal by uprooting • The balance between riverbed erosion and root resistance mediates the potential effects of plant-root biogeomorphic feedbacks • …still a lot is needed: • This modeling study may help to focus experimental and field studies • Application on more complex morphologies and environmental conditions can help to understand the co-evolution of vegetation and morphology of riparian areas 31 Conclusion and outlook DICAM as
  32. 32. 32 Plant mortality mechanisms: uprooting and burial DICAM as Biogeomorphic feedbacks: what is the role of plant roots?
  33. 33. 33 More on this model…. DICAM as
  34. 34. • Find out more: 34 Thank you! DICAM as

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