Mass Wasting

Mass Wasting

Colleen O. Doten

August 18, 2004

http://www.for.gov.bc.ca/research/becweb/zone-MH/mh-photos/

Outline

• Subsurface Moisture Redistribution in DHSVM

• Erosion and Sediment Transport Module

• Implementation

• Output

Subsurface Moisture Redistributionin DHSVM

• Soil depth effects dynamics of:– Subsurface moisture storage– Vertical and lateral movement– Predicted saturation thickness (saturated

depth/total soil depth)

• Soil saturation is determined using the subsurface routing scheme of Wigmosta and Lettenmaier (1999)

Outline



• Implementation

• Output

Erosion and Sediment Transport Module

HILLSLOPE EROSION

Soil Moisture Content

CHANNEL ROUTINGPrecipitationLeaf Drip

Infiltration and Saturation Excess Runoff

DHSVM

Q

Qsed

Sediment

MASS WASTING

Erosion

Deposition

ROADEROSION

Sediment

Channel Flow

Failure Prediction

• Mass wasting algorithm performed at a finer resolution

• TOPMODEL topographic wetness index used to redistribute soil saturation (Beven and Kirkby, 1979; Burton and Bathurst, 1998)

• Run for critical times

Failure Prediction

• Slope stability is a function of– Soil moisture– Slope– Soil properties– Vegetation properties

• Failure is determined using the infinite slope model with a factor of safety (FS):

L

S

mL

Sd

CC

forces

forces

driving

resistingFS w

rs

)tan(

tan)(

)2sin(

)(2

Failure Prediction

• Soil and vegetation characteristics described by probability distributions– Soil cohesion– Angle of internal friction– Root cohesion– Vegetation surcharge

Mass Redistribution

• Failures occur one pixel at a time.

• Failure travels down slope of steepest descent.

• Failed area can increase due to the initial failure.

• Failure runs out an empirically determined distance. The failed volume is evenly distributed along the runout distance.

• Failures entering the channel system continue as debris flows depending on the junction angle.

Change in Soil Depth

Probability of Failure

Easting, mN

orth

ing,

m

Nor

thin

g, m

Nor

thin

g, m

Easting, m Easting, m

Outline



• Implementation

• Output

Test Catchment – Rainy Creek

NN

Easting, m

Nor

thin

g, m

• Drainage area of 44 km2

• Snowmelt dominated basin

• Mean annual inferred precipitation of 150 to 230 cm (PRISM)

• Elevation range 630 to 2150 m

Rainy Creek Spatial DataLoamy sand

Sandy Loam

Fine Sandy Loam

Loam

Organic

Bedrock

Water

Fragmented Rock

COLD_int1,3

COOL_int1,2,3

DRY_int1,2,3

DRY_ofms2,3

Forest_si1,2,3

MOIST_int1,2,3

Grassland

Shrubland

Water

Rock

Barren

Soil Types

Vegetation Types

Soil Depth

Depth, m

Slope

degrees

Mean slope: 26

Provided by USDA Forest Service Pacific Northwest Research Station and Wenatchee Forestry Sciences Laboratory

Sediment Module Implementation• Fine resolution DEM (10-m) (USDA Forest Service)

• Fine resolution mask (10-m) (UW)

• Spatially variable parameters – Soil Parameters

• Cohesion distribution: 4.5 – 22 kPa (Hammond et al. ,1992, and others)

• Angle of internal friction distribution: 29 – 42 degrees (Hammond et al. ,1992)

– Vegetation Parameters• Cohesion distribution: 2 - 23 kPa (Hammond et al. (1992), Burroughs and Thomas

(1977), Montgomery et al. (1998), Dietrich et al. (1995), Wu et al. (1979), Wu (1984), Ziemer (1981))

• Vegetation Surcharge distribution: 0 – 195.4 kg/m2 (Hammond et al. ,1992)

• Run for a six year period: 10/1/1991 to 9/30/1997• Mass wasting algorithm was run for six events:

– 05/08/1992– 05/18/1993– 05/30/1995– 06/08/1996– 05/17/1997– 06/15/1997

Modeled Saturated Fraction

05.08.1992 05.18.1993 05.30.1995

06.08.1996 05.17.1997 06.15.1997

Saturated depth/ Soil depth

Outline



• Implementation

• Output

Default Output• AggregatedSediment.Values

– Saturated thickness (basin average, 0-1) – Delta soil depth (basin average in m) – Failure probability (basin average, 0-1) – Total Mass wasting (m3)– Total Mass Deposition (m3)– Total Sediment to Channel (m3)

• MassSediment.Balance– Total Mass wasting (m3)– Total Mass Deposition (m3)– Total Sediment to Channel (m3)– Total Mass Wasting

Final Sediment Mass BalanceMassWasted (m3): 8.88e+04SedimentToChannel (m3): 3.25e+04MassDepostion (m3): 5.63e+04Mass Error (m3): -3.679688e+00

Default Output

• failure_summary.txt– Average number of failures– Average number of pixels per failure– Total number of failed pixels with a probability >

prescribed threshold

• saturation_extent.txt– Total number of pixels with saturated fraction >

MTHRESH

Optional Output

Model Maps (binary file) and Graphic Images (real-time):

• Fine Map DEM, m• Fine Map Saturated Thickness, 0-1• Fine Map Delta Depth, m• Fine Map Failure Probability, 0-1• Sediment to Channel, m3

Modeled Maximum Probability of Failure

Easting, m

Nor

thin

g, m

• 82% soil depth > 1.5 m (12% of areas with soil depth > 1.5 m)

• 26% had soil type of loam or organic (40% of areas with these soil types)

• 40% had vegetation type of shrubland or barren (39% of areas with this vegetation type)

• Mean slope 30.7º

Aerial Photograph Survey• 5 stereo pairs spanning

22 years (1970-1992) • Mapped 62 slides using

a confidence level scheme

Modeled Change in Soil Depth

Annual sliding rate (kg/ha)Vegetation Category 1: 4,300 Vegetation Category 2: 1,390Vegetation Category 3: < 1Vegetation Category 4: 0

Easting, m

Nor

thin

g, m

Vegetation Category

Rock, Water

DRY_ofms2,3

COOL_int1,3, COLD_int1,2,3, DRY_int1,2,3, MOIST_int1,2,3

Forest_si1,2,3, Grassland, Shrubland, Barren

Annual sliding rate (kg/ha)Estimated rate: 3,317Simulated rate: 5,700Adjusted simulated rate: 4,450 (0.26 mm/yr)

Modeled Channel Routing Results

Simulated Rates, kg/ha/yrHillslope erosion: 634

Road surface erosion: 17 – 41(164 – 394 kg/km road)(3,247–7,842 kg/ha of road)

Sediment Yield: 1,000 – 1,020

Published Rates, kg/ha/yrHillslope erosion: 8 – 100 (north central WA)

Road surface erosion: – 3,800 to 500,000 kg/km of road (Olympic

Peninsula, WA)

– 12,000 to 55,000 kg/ha of road (central ID)

Sediment Yield: 813 – 13,500 (coastal OR and CA, western WA)

Sensitivity Analysis

• Many have performed sensitivity analysis on the infinite slope model:– Gray and Megahan, 1981– Hammond et al. 1992– Wu and Sidle, 1995– Borga et al., 2002

• For parameters tested, we had similar results:– most sensitive to soil cohesion, root cohesion and soil

depth– less sensitive to angle of internal friction– insensitive to saturated density and vegetation

surcharge

Sensitivity Analysis – Soil Depth

Existing

Change in Soil Depth:-0.72 to 1.4 m

Annual Rate: 6,745 kg/ha

Existing + 0.5m



Exisiting - 0.5m

Change in Soil Depth:-0.28 to 0.81m


Sensitivity Analysis – Soil Depth

Existing

Maximum Failure Probability: 0 to 0.28

Existing + 0.5m


Exisiting - 0.5m


Sensitivity Analysis – Event Criteria

Greatest Saturation Extent



Days (15) with precipitation > 4 cm


Annual Rate: 875 kg/ha

Six Largest Storms


Annual Rate: 610 kg/ha

Sensitivity Analysis – Event Criteria

Greatest Saturation Extent


Days (15) with precipitation > 4 cm


Six Largest Storms


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Dietrich, R.V., J.J.T. Dutro, and R.M. Foose, 1982: AGI Data Sheets for geology in the field, laboratory, and office, 2nd ed., American Geological Institute, Falls Church, VA.

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Gray, W.H. and W.F. Megahan, 1981, Forest vegetation removal and slope stability in the Idaho batholith, Res. Pap. INT-271, USDA For. Serv., Ogden, Utah.

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American Geophysical Union, Washington D.C.Ward, T.J., R. Li, and D.B. Simons, 1981: Use of a mathematical model for estimating potential landslide sites in steep forested

drainage basins, In: Erosion and sediment transport in Pacific Rim steeplands, T.R.H. Davies ad A.J. Pearce (eds), IAHS Publ. No. 132, Institute of Hydrology, Wallingford, Oxfordshire, UK

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Wu, W., and R.C. Sidle, 1995: A distributed slope stability model for steep forested basins, Water Resour. Res., 31, 1097-2110.Borga, M., G. Dalla Fontana, C. Gregoretti, and L. Marchi, 2002: Assessment of shallow landsliding by using physically based model of hillslope stability, Hydrol. Process., 16, 2833-2851.

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Mass Wasting