Development of a DHSVM
Erosion and Sediment
Transport Model
Presented by Jordan S. Lanini, University of Washington
Colleen O. Doten, University of Washington
Laura C. Bowling, Purdue University
Edwin D. Mauer, Santa Clara University
Jordan S. Lanini, University of Washington
Nathalie Voisin, University of Washington
Dennis P. Lettenmaier, University of Washington
Presentation outline
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•
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Motivation for erosion model
Mass wasting component
Surface erosion component
Channel erosion and routing component
Testing and evaluation
Future research directions
Motivation for erosion model
Forest
Roads
www.homefirefightingsystems.com
Forest Fire
Timber Harvest
Sediment Model
DHSVM
SURFACE EROSION
Qsed
CHANNEL EROSION
& ROUTING
Provides Inputs
for all Three
Components
MASS WASTING
Watershed Sediment Module
Q
OUTPUT
DHSVM Inputs to Sediment Model
DHSVM
Soil Moisture Content
Precipitation
Leaf Drip
Infiltration and Saturation
MASS WASTING
Excess Runoff
SURFACE EROSION
Channel Flow
CHANNEL EROSION &
ROUTING
Mass Wasting
http://www.for.gov.bc.ca/research/becweb/zone-MH/mh-photos/
• Dynamic soil
saturation predicted
by DHSVM
• Finer resolution grid
(10 m) for failure
computation
L. Bowling, C. Doten
Icicle Creek, WA
Mass Wasting Module (MWM)
• Slope stability is a function of soil moisture,
slope, and soil and vegetation characteristics.
• Failure is determined by the infinite slope
stability model, using a factor of safety (FS)
FS =
resisting forces
driving forces
• Slope instability is indicated by a FS < 1.
L. Bowling, C. Doten
MWM - Stochastic Nature
• Four soil and vegetation characteristics:
–
–
–
–
soil cohesion,
angle of internal friction,
root cohesion, and
vegetation surcharge
are input as probability distributions.
• They can be assigned to one of three
distributions:
– uniform,
– normal or
– triangular.
L. Bowling
Results of a Stochastic Run
Probability of failure
Pixels in black failed at least once in 1000 iterations of MWM
L. Bowling
MWM - Mass Redistribution
L. Bowling
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Pixels are considered to fail to
bedrock.
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Failed material travels down the slope
of steepest descent.
•
Downslope pixels can fail in response
to the initial failure.
•
Landslide stops at a critical slope
angle. The failed volume is evenly
distributed among all downslope
pixels.
•
Landslides entering channels system
continue as debris flows depending
on the junction angle.
Surface Erosion & Routing
http:www.geo.uni-bonn.de/cgi-bin/geodynamik_main?Rubrik=research&Punkt=geomorphology
Current DHSVM Runoff Generation and Routing
Runoff is produced via:
•
Saturation excess (pixels 6 and 7)
•
Infiltration excess based on a user-specified
static maximum infiltration capacity (pixel 3)
Runoff is routed to the downslope neighbors one
pixel/time step
Runoff Generation – Dynamic
Infiltration Excess
• Calculation of maximum infiltration capacity:
– The first timestep there is surface water on the
pixel, all surface water infiltrates.
– If there is surface water in the next timestep, the
maximum infiltration capacity is calculated based on
the amount previously infiltrated.
• Dominant form of runoff generation on
unpaved roads and post burn land surfaces
N. Voisin
Kinematic Runoff Routing
• Pixel to pixel overland flow routed using an explicit
finite difference solution of the kinematic wave
approximation to the Saint-Venant equations
• Manning’s equation is used to solve for flow area in
terms of discharge
• Per DHSVM timestep, a new solution sub-timestep is
calculated satisfying the Courant condition, which is
necessary for solution stability.
L. Bowling
Surface Erosion
raindrop
impact
leaf drip
impact
• Transportable
sediment is the sum
of particles detached
by three
mechanisms
• Erosion is limited by
overland flow
transport capacity
shearing by overland flow
Mechanisms of Soil Particle Detachment
L. Bowling, J. Lanini,
Hillslope Sediment Routing
• Sediment is routed using a four-point finite
difference solution of the two-dimensional
conservation of mass equation.
• If the pixel contains a
channel (including road side
ditches), all sediment and
water enters the channel
segment.
L. Bowling
sediment
and water
Forest Road Erosion
raindrop
impact
shearing by
overland flow
surface
erosion
• Transportable
sediment consists of
particles detached by
two mechanisms
• Overland flow will be
infiltration excess
generated.
• Routing to include
road crown type
– insloped
– outsloped
– crowned
C. Doten
Channel Erosion & Routing
www.eas.purdue.edu/geomorph/ envben.html
Channel Routing
• Sediment Supply
– channel sediment storage from the MWM
– lateral inflow from hillslope and roads
– upstream channel segment
• Sediment particles
– have a constant lognormally distributed grain size
which is a function of the user-specified median grain
size diameter (d50) and d90
– are binned into a user-specified number of grain size
classes
E. Maurer
Channel Routing
• Sediment is routed using a four-point finite
difference solution of the two-dimensional
conservation of mass equation.
• Instantaneous upstream and downstream
flow rates are used in the routing.
• Transport depends on
– available sediment in each grain size class, and
– capacity of flow for each grain size calculated using
Bagnold’s approach for total sediment load.
E. Maurer
Testing and Evaluation
Little Wenatchee
Sensitivity Analysis - Rainy Creek
Input Parameter
Baseline
Min
Max
Sensitivity
References)
effective soil cohesion, kPa
3
0.25
100
high
Hammond et al. (1992)
Lindeburg (2001)
effective angle of internal
friction, degrees
31
28
34
high
Hammond et al. (1992)
Holtz and Kovacs (1981)
Lindeburg (2001)
root cohesion, kPa
(5% of basin)
(90% of basin)
Hammond et al. (1992)
3
15
2
12
6
23
high
low
vegetation surcharge, kg/m2
(5% of basin)
(90% of basin)
12.5
122
0
49
25
1995
low
low
Sidle (1992)a
Hammond et al. (1992)
soil bulk density (kg/m3)
1569
1400
1600
medium
STATSGO (USDA, 1994)
soil depth (m)
0.761.278
Baseline
1.762.278
high
b
MWM Application Challenges
• Soil depth
– typically a hydrologic calibration parameter
– changes in soil depth will impact mass wasting
• Soil moisture
– mass wasting model uses soil moisture in each pixel
at a daily time step
– unrealistic degrees of saturation are going to effect
mass wasting
C. Doten
Surface Erosion Application
Challenges
• Model resolution
– smaller resolutions will result in smaller sub-time step,
increasing run time
• Runoff (Infiltration Excess)
– Sub-timestep calculated from largest infiltration excess
observed for time step
– unrealistic values will result in smaller sub-time step,
increasing run time
• Surface erosion run time
– since mass wasting is the predominant form of sediment
transport in PNW basin, surface erosion can be limited to userspecified time periods decreasing run time
C. Doten, J. Lanini
Testing and Evaluation
• Mass wasting
– Land slide mapping of Rainy Creek derived from
aerial photography
• Surface erosion
– Observed local and regional land and road surface
erosion rates
• Channel routing
– Observed stream sediment concentrations
C. Doten
Scenario Analyses I: Forest Roads
Forest Road Erosion
Road Location in the Hillslope
& Hillslope Curvature
C. Doten
Scenario Analyses II: Timber Harvest and
Forest Fire
Enhanced Transport Capacity
• Decrease in annual evaporation
• Increased snow accumulation
• Enhanced snow melt
– Greater radiation exposure
– Increased turbulent energy
transfer
Enhanced Sediment Supply
• Mass wasting (landslides)
– Decreased root strength
– Enhanced soil moisture
• Surface erosion
http://www.for.gov.bc.ca/research/becweb/zone-MH/12_Res_Man.htm
C. Doten
Questions/Comments
We would like to acknowledge financial
support from the USFS PNW Research
Station and Wenatchee Lab for the
development of this model
Data Input Needed for
Sediment Model
• Smaller resolution (10m) DEM
• Debris Flow Material d50 and d90
• Soils: Bulk Density, Manning n, K index, d50,
distributions (mean, stand deviation, minimum
value, maximum value) of Cohesion and Angle
of Internal Friction
• Vegetation: Vegetation Surcharge distribution
(minimum value and maximum value) and Root
Cohesion distribution (mode, minimum value
and maximum value)
References
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Bagnold, R.A., 1966, An approach of sediment transport model from general physics. US Geol. Survey
Prof. Paper 422-J.
Benda, L. and T. Dunne, 1997, Stochastic forcing of sediment supply to channel networks from
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Beven, K.J. and M.J. Kirkby, 1979, A physically based, variable contributing area model of basin
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Burton, A. and J.C. Bathurst, 1998, Physically based modeling of shallow landslide sediment yield at a
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Chow V.T., D.R. Maidment, L.W.Mays 1988: Applied Hydrology. McGraw-Hill Book Company pp572.
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References (con’t)
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Rubey, W.W., 1933, Settling velocities of gravels, sands, and silt particles, Am. Journal of Science, 5th
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Smith R.E., D.C. Goodrich, D.A. Woolhiser, and C.L. Unkrich 1995: KINEROS – a kinematic runoff and
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