Lab

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Factors Controlling the Spatial and Temporal
Variability of Dust Emissions the need for
suitable surrogate measures at large spatial
scales.
W.G. Nickling Wind Erosion Laboratory Department
of Geography University of Guelph Canada and J.A.
Gillies Division of Atmospheric Sciences Desert
Research Institute Reno Nevada
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Outline

• Background driving and resisting forces for dust
  emissions.
• Scaling Issues
• Temporal Issues (natural variability)
• Suitable surrogate measures - discussion

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Driving and Resisting Forces

• Driving
• Wind stress
• Saltation
• Mechanical

• Resisting
• Texture/Aggregate
  I Size Distribution
• Crusting
• Lags
• Moisture/precipitation
• Vegetation

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The Wind Profile
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The Wind Profile
?o ? u2
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Saltation Ejection-Abrasion

• based on Owen (1964) and Gillette Passi (1988),
  Shao et al. (1993) argued in that
• q a u3
• and thus
• F a u3
• F a q?

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(No Transcript)
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Driving and Resisting Forces

• Driving
• Wind stress
• Saltation
• Mechanical

• Resisting
• Texture/Aggregate
  I Size Distribution
• Crusting
• Lags
• Moisture/Precipitation
• Vegetation

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Texture/Aggregate Size Distribution
(after Chatenet et al. 1996)
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Crusts
Salt Crusts
Biological Crusts
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Saltation Impact Energy and Crust Strength

(Rice et al. 1999)
Energy of Impacting Grains
Strength/Binding Energy of the Surface Crust
Probability
Potential Erosion
The Guelph Field Penetrometer
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Surface Lag Deposits
Developing deflation lag
High concentration of fines below surface
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Dust Emission Concepts

• dust emission is an indirect process most
  particulates are emitted by a sand blasting
  process due to saltation (Gillette and Passi
  1988 Shao et al. 1993)
• Saltating particles must overcome binding energy
  between surface grains (Shao et al. 1993 Alfaro
  et al. 1997)
• The vertical dust flux (F) is proportional to the
  horizontal sand flux (q) for a given site
  (Gillette and Passi 1988 Alfaro et al. 2000)

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Dust Emission

• Gillette (1977), Gillette and Passi (1988),
  Alfaro et al. (1997, 2000), based on theoretical
  arguments and wind tunnel testing, argued that
  for idealized soils
• should be independent of u (shear velocity)

Vertical dust flux
F

q
Mass flux
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The Binding Energy Concept (Shao, 2000 Alfaro
et al. 1997, 2000)
Sandy Loam FS
F/q (m-1)
Clayey Silt Loam FSS
0
0.5
1
1.5
2
u (m/s)
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Ratio of Vertical Dust Flux to Horizontal Mass
Transport Rate vs Shear Velocity(all sites)
On Lake
Off Lake
Silty
Sandy
F/q (m-1)
1.
without feed
without feed
with feed
with feed
0
0.4
0.6
0.8
1.0
1.2
1.4
0.2
u (m/s)
(Nickling et al. 2000)
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Ratio of Vertical Dust Flux to Horizontal Mass
Transport Rate vs Shear Velocity(at a site)
Off Lake
On Lake
F/q (m-1)
without feed
without feed
with feed
with feed
0
0.4
0.6
0.8
1.0
1.2
1.4
0.2
u (m/s)
(Nickling et al. 2000)
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Precipitation

• In most deserts effect of precipitation is
  indirect
• Rapid surface drying reduces short term effect
• Longer term effects
• Development of surface crusts
• Enhancement of vegetation cover (can be a
  considerable lag time)
• Supply of fresh fine-grained sediment to alluvial
  channels and basins (playas)

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The Stabilizing Role of Vegetation
(after Wolfe and Nickling 1993))
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Owens Lake/Shear Stress Partitioning
The Shear Stress Partitioning Concept (Schlichting
1936)
Owens Lake CA
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Roughness/Non-erodible Elements

• Second only in importance to the ability of the
  soil surface to erode (Tegen et al., 2002).

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Roughness Effects threshold ratio scales with l.
l nbh/S
(after King et al 2004)
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Roughness Effects sand transport efficiency
scales with l.
flux with no roughness
leading edge of roughness
(JER data, May 2004)
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Temporal and Spatial Variability

• Driving and resisting forces are spatially and
  temporally variable at widely different scales
  (e.g., vegetation cover, moisture content,
  crusts, etc.)
• Some changes will result in decreased emissions,
  others in increased emissions
• Some scales will be well below that currently
  available from
• - remotely sensed data
• - other data bases

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Scaling Issues

• Can we scale up our understanding developed from
  field and wind tunnel tests?

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Surface Roughness

• There are problems. King et al. (2004) found MB
  (1995) partitioning scheme fails for field scale
  (i.e., vegetation) roughness.
• Raupach et al. (1993) captures larger scale
  roughness effects.

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(after King et al 2004)
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(after King et al 2004)
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Scaling Issues

• Are scales of measurement (i.e., remote
  measurement resolution or surrogate) compatible
  with the scale of the process?

Wind Shear GCMs, 60-80 km (1?x1?) meso-scale,
1-5 km Texture/Aggregate Size Distribution IGPB
soil texture database (global), NRCS (specific to
U.S., CD, Mex.)
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Roughness roughness proxies (e.g., radar
roughness, radiance-derived) are typically
measured at scales of 2-30 m (what are links to
aerodynamic roughness?)
Vegetation monthly leaf area index at 1 km
resolution (satellite), AVIRIS (4 m resolution
(aircraft) (l obtainable?)
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Suitable Surrogates?

• Are data sets with suitable parameters available
• If they dont exist can we develop them
• Do we need to use surrogates

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Suitable Surrogates?

• Soil texture
• Roughness
• Moisture
• Degree of disturbance