LanniC_EGU2010

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LanniC_EGU2010

  1. 1. Understanding hydrological processes to improve the landslide model prediction Cristiano Lanni University of Trento Jeff McDonnell, OSU Riccardo Rigon, UoT
  2. 2. Outline 1 HS11.7 1.  Mapping shallow landslide using hydrological model: the state of the art 2.  The role of bedrock surface on subsurface water-flow dynamics: the PANOLA TRENCH HILLSLOPE 3.  Is DWI able to follow surface topography ? 4.  Looking to improve the performance of the simpler hydrological models © Oregon State Trento University of University
  3. 3. 2 HS11.7 SIMPLE HYDROLOGICAL MODELS COMPLEX HYDROLOGICAL MODELS 1D – i.e. TRIGRS (Baum et al.,2002) a)  C o n s i d e r s t h e s t e a d y - s t a t e ∂ψ ∂θ ∂   ∂ψ  = K (ψ ) −1 hydrological condition ∂t ∂ψ ∂z   ∂z  b)  Does not take into account the 3D – i.e. GEOtop (Rigon et al.,2006), shear-strength in unsaturated soil HYDRUS-3D € ∂ψ ∂θ ∂   ∂ψ ∂x 3  = K x (ψ ) +  ∂t ∂ψ ∂x i  i  ∂x i ∂x i  € INFINITE SLOPE STABILITY MODEL (accounting for unsaturated zone) © Oregon State Trento University of University
  4. 4. The role of bedrock shape: Panola Trench Hillsope 3 HS11.7 Bedrock   High soil-depth variability Ground Flow direction Bedrock © Oregon State Trento University of University depression
  5. 5. 4 HS11.7 Geometry  α = 13° α = 20° α = 30° PANOLA13 PANOLA20 PANOLA30 Soil (sandy-silt)  Ksat = 10-4 m/s Bedrock  Ksat = 10-7 m/s Triggering Factor  Intensity = 6.5 mm/h Duration = 9 hours © Oregon State Trento University of University
  6. 6. 5 HS11.7 Panola13 t=6h sat=3% t=7h sat=18% t=9h sat=43%   Saturated area at the soil- bedrock interface increases very rapidly © Oregon State Trento University of University t=14h
  7. 7. 6 HS11.7 time t=1h t=4h t=12h .. ….… Downslope Drainage efficiency α = 13° .. ….… α = 20° .. ….… α = 30° © Oregon State Trento University of University
  8. 8. before proceeding further…. HS11.7 Lanni et al. 2010 (submitted to WRR) 1D   No role played by hillslope gradient 3D   Significantly affected by hillslope gradient © Oregon State Trento University of University
  9. 9. Moving to hillslope stability…. HS11.7 FACTOR OF SAFETY MECHANICAL PROPERTIES Panola30 c’ = 0 kPa φ’ = 30° (FS=1) (1<FS<1.05) © Oregon State Trento University of University t=10h
  10. 10. +5.0% +12.0% 9 HS11.7 +1.4% +11.0% t=0h t=6h t=7h t=8h +6.2% +14.2% +11.2% +26.2% t=9h   Bedrock depression determines the threshold effect © Oregon State Trento University of University t=10h
  11. 11. 10 HS11.7 Hjerdt et al., 2004 WRR € © Oregon State Trento University of University
  12. 12. 11 HS11.7   Maximum pore pressure © Oregon State Trento University of University
  13. 13. 12 HS11.7 © Oregon State Trento University of University
  14. 14. 12 HS11.7 N 1 N ∑( ( ) )( ψ i − ψ ⋅ DWI ( i) − DWI ) cor(ψ ,DWI ) = i=1 var(ψ )⋅ var(DWI ) €   INVERSE correlation   DIRECT cor(ψ (t = 3h),Z) = −0.9 between SOIL-THICK correlation and PRESSURE HEAD in between DWI € the I stage of rain- and PRESSURE infiltration HEAD in the II stage of rain- cor(ψ (t = 11h),DWI ) = +0.83 infiltration © Oregon State Trento University of University €
  15. 15. 13 HS11.7   Unsaturated soil (vertical recharge) p p h t +1 = h t + Δt i, j i, j θ sat − θ ht ht+1   Saturated soil (vertical recharge + € lateral flow + DWI effect) ΔV = qin – qout + p*[A W(t) = k * qout(t) ΔVi,j = qin – qout + p*[A(i,j)+1-Ai,j] Basin Δt γ ⋅ A 0.5 i, j ki, j = K sat⋅ DWI β −t / ki, j  αi, j ( t) = 1− e t ≤ Tp     p p h t +1 = h t +  + Ai, j⋅ α (t) − A Δt i, j i, j  θ sat − θ ai, j⋅ φ   i, j ( ) i, j +1 ⋅ α (i, j ) (t) +1   T /k  −t / k αi, j ( t) =  e p i, j − 1 e i, j t > T p  €   € € © Oregon State Trento University of University €
  16. 16. 14 HS11.7   Unsaturated soil   Saturated soil    p   h t +1 = h t + p p i, j θ sat − θ Δt h t +1 = h t +  + Ai, j⋅ α (t) − A Δt i, j i, j i, j  θ sat − θ ai, j⋅ φ   i, j ( ) i, j +1 ⋅ α (i, j ) (t) +1    €   Irregular shape € © Oregon State Trento University of University
  17. 17. 14 HS11.7   Unsaturated soil   Saturated soil    p   h t +1 = h t + p p i, j θ sat − θ Δt h t +1 = h t +  + Ai, j⋅ α (t) − A Δt i, j i, j i, j  θ sat − θ ai, j⋅ φ   i, j ( ) i, j +1 ⋅ α (i, j ) (t) +1    € SHALSTAB € NEW SIMPLE MODEL © Oregon State Trento University of University
  18. 18. TAKE HOME MESSAGGES 15 HS11.7 1.a First, vertical rain-infiltration induces the infiltration-front propagation 1.b Then, lateral-flow could “turn on” because of the built-up pore-water pressures at the soil-bedrock interface 1.c Finally, bedrock shape (i.e., spatial soil thickness variability) could affect the flow dynamics, inducing a fast decrease of FS 2.  Putting DWI concept in modelling approach and removing S-S assumption it seems possible to improve the prediction performance of the simpler hydrological models 3. Please, take care in the use of SHALSTAB: The hydrological ratio p/T represents a calibration parameter rather than real physical properties …but Montgomery and Dietrich also wrote this in their original paper © Oregon State Trento University of University
  19. 19. Thank you for your attention! cristiano.lanni@gmail.com
  20. 20. HS11.7 EXTRA SLIDES © Oregon State Trento University of University
  21. 21. Threshold for initiation of 3 HS11.7 Subsurface water-flow   The precipitation threshold for initiation of Subsurface Stormflow seems related to the micro-topography in the bedrock   Saturated patched recorded at the soil-bedrock interface are usually a balance between upslope accumulated water and downslope drainage efficiency © Oregon State Trento University of University by Jeff McDonnell and his research team
  22. 22. 6 HS11.7   Max pressure head at the SOIL-BEDROCK INTERFACE Unsat Sat α = 13° α = 20° α = 30° © Oregon State Trento University of University Downslope Drainage efficiency
  23. 23. 7 HS11.7 Panola13 t=6h sat=3% t=7h sat=18% t=9h sat=43%   …..and than the average value of positive pore-water pressure continues to grow © Oregon State Trento University of University t=14h
  24. 24. 7 HS11.7 time   1D & 3D mechanism t=1h t=4h t=12h 1.  Vertical flow 2.  Lateral flow & bedrock obstructions panola13 .. ….… panola20 .. ….… N 2 var(ψ ) = 1 N ∑( ψ ( i) − ψ ) panola30 i=1 .. ….… € © Oregon State Trento University of University
  25. 25. 12 HS11.7 Rain 1: Rain 2: Intensity = 6.5 mm/h Intensity = 12 mm/h Duration = 9 hours Duration = 5 hours Rain = 58.5 mm Rain = 60 mm t=10h t=5h FS<1  12.6% FS<1  48.9% © Oregon State Trento University of University
  26. 26. 12 HS11.7 SHALSTAB Maximum pore pressure p= 5% I h p A = Z T b sin β © Oregon State University University of Trento
  27. 27. 14 HS11.7 SHALSTAB model   Water-mass balance in steady state condition Qsup + Qsub = I ⋅ A h ν ⋅ A+K b Z cos β sin β =I⋅A € sat Z h p A € = Z T b sin β T = hydraulic trasmisivity Z = soil-thick €  γ h  tanφ ' h = water-table thick in steady-state condition FS = 1− w  € β = local slope  γ Z  tan β € A = Upslope contributing area € q = effective rainfall © Oregon State Trento University of University € €
  28. 28. 15 HS11.7 € SHALSTAB COMPLEX HYDROLOGICAL MODEL p= 5% I   The limitation of water-table grows everywhere steady-state condition   “A” determines the Unable to account for water-table thick distribution “topography obstructions” © Oregon State Trento University of University
  29. 29. 17 HS11.7   Unsaturated soil   Saturated soil    p   h t +1 = h t + p p i, j θ sat − θ Δt h t +1 = h t +  + Ai, j⋅ α (t) − A Δt i, j i, j i, j  θ sat − θ ai, j⋅ φ   i, j ( ) i, j +1 ⋅ α (i, j ) (t) +1    €   Planar shape € © Oregon State Trento University of University
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