AirWare On-line Reference Manual
| ||Release Level || 6.2 |
| ||Release Date ||2013 09 |
| ||Revision Level ||1.0|
Last modified on:
Monday, 9-Sep-13 21:17 CEST
Dust entrainment: model basics
The dust entrainment model is a distributed, (arbitrary resolution) dynamic (hourly
time step) model to predict the wind erosion and (re-)entrainment of particles
from natural surfaces, primarily unvegetated or sparsely vegetated soils.
The DUST model produces dynamic (hourly) emission matrices (g/s/km2), that together with any
anthropogenic emission data for point, line and area sources, provide input to the
respective transport, dispersion, and deposition model used. In addition to the
threshold friction velocity approach (e.g., Draxler et al. 2001) that uses
geomorphology and soil properties, is also considers vegetation coverage and soil
moisture as estimated by the MM5 prognostic meteorological model. MM5 is also used
to forecast wind velocities, and a Weibull function to generate distributed wind
speeds around the predicted hourly mean wind speed.
For specific form of landuse, special "sub-models" are used:
The dust entrainment model estimates non-pyrogenic dust
emission from natural surfaces as a function of primarily wind speed, land
cover/vegetation, soil characteristics, and soil moisture,
The total Dust PM10 emission [g/s/km2] is calculated as the product of
- Area sources (cities, industrial areas)
- Area sources (surface mining)
- Line sources (unpaved roads)
- WindFactor, (a non-linear threshold function)
- soil type (the wind thresholds oare soil type dependent)
- ErosionFactor (erodibility), combining vegetation index (bare soil fraction),
- a calibration factor (multiplier)
The wind factor is computed from average hourly (monitored or generated by MM5) ground level
wind speed (m/s) using a Weibull function to generate a distribution of wind speeds
and their relative frequency around that mean, as follows:
for v>TR: f(v) = (v - TR) **EXP
for v<TR: f(v) = 0
- TR is the (user-defined) Wind Threshold,
- EXP is the (user-defined) Exponent
windFactor = sum over all frequency classes of ( f(v)*frequency(v) )
frequency(v) = (k/c) * pow( (v/c), (k-1) ) * exp( -pow( (v/c), k) )
The Weibull distribution is a continuous probability distribution, named after Waloddi Weibull,
who described it in detail in 1951. The shape parameter k is used defined s part of the model
calibration. A user defined multiplier can be used to scale the original,
hourly average wind speed. to account for the open-ended nature and improve computational efficiency,
a maximum wind speed cutoff value defined in multiples of the average wind speed.
Erosion is based on a minimum wind speed threhold, that depends on the soil
type distribution within each grid cell, see below.
- v is the wind speed,
- k is the shape parameter,
- c is the scale parameter of the
Soil distribution in each model grid cell (percentage of coarse, medium, and heavy soil)
is based on FAO soil map .
The soil type defines the minimum wind speed for erosion.
The erosion factor is a multiplier that limits the maximum possible erosion
defined by wind speed and the exponential threshold functions of the wind
speed (with individual thresholds for three soil fractions).
The elements of the erodibility factor include:
- Soil moisture: using a linear threshold function:
the soil moisture dependent scaling factor of erodibility is
zero above the soil moisture threshold value (expressed as a percentage of
water in the uppermost 20 cm soil layer as estimated by MM5).
- between the threshold and zero soil moisture erodibility increases
linearly with a user defined slope.
soil moisture > SMT % => sm_factor = 0
soil moisture < SMT % => sm_factor = (SMT - soil_moisture) * SMM
where SMT is the soil moisture threshold and SMM is the soil moisture multiplier
- Vegetation index: depending on data availability this can be derived from land use data,
NDVI (e.g., from the MODIS satellite platform), or VCF:
For the vegetation index, the DUST model uses Vegetation Continuous Fields,
The Vegetation Continuous Fields collection contains
proportional estimates for vegetative cover types: woody vegetation, herbaceous
vegetation, and bare ground.
- Terrain roughness: this is defined as the normalized difference in
elevations (based on the 30m DEM) within any 1 km2 grid cells; with minimum of 1 (completely flat),
the maximum elevation difference within a grid cell has a user defined value,
that acts as a divider on the erosion factor: e.g., a value of 1.25 would reduce erosion in the
roughest cell by 20% compared to any flat one.
Terrain roughness and soil moisture are optional, the default (if no data are available) ignores their possible impacts.