Ss = [u_z - U_z]/U_z

-Where u_z is the wnd speed at heigh z, and U_z i the wind speed at height z on the reference anemometer.

z_o (aerodynamic roughess length) decreases as surface becomes smoother. It is around 0.5m in a town, around 0.05m in a field, and around 0.0001m over water.

--how quickly wind speed increases with height (lower value means quicker increase)

Different roughnesses have different effects on roughness at surface (where effect is greatest), but all lines meet and equal at the PBL (plenetary boundary layer)

Hill

Flow passing over a hill, stream lines come closer together above the hill (speed up flow)

-compressed into this space.

Relative speed up graph (of wind going over a hill) looks like a hill, with disance on x-axis, and the top of the relative speed hill being at 0m from distance of hill crest.

Therefore, ideal spot for a turbine is at the hill crest.

Turbulence levels in the lee of the hill would have disastrous consequences for turbines, as relative speed is significantly reduces (shooting wind over crest)

Altering shape of hill/obstruction changes lee and before hill effect. (Taller the hill, longer recovery time).

vertical velocity is greatest directly in lee, and lowest at the crest.

Valley

-relative velocity greatest in immediate lee of valley

-lowest in middle of depression

-upwind edge has fractional speed-up ratio of slightly higher than 0 (0.2), though downwind is significantly higher (0.6-0.8).

-Centre is around -0.4

-Greatest erosion occurs at upwind edge

-greatest deposition occurs in lee of downwind edge and on the upwind valley slope.

WP = u³

OR

WP= (0.5)*(p_a)*(u³)

Often the cube of wind speed is used as a simple estimate of wind power.

Inclusion of air density(kg/m3, varies with temperature and time) and a constant provides a  better estimation

Relation between the wind speed and power.

Wind power rises as a power function (no pun) relative to wind speed.

I.E. as wind speed increases, wind power increases faster.

WP = (0.5)*(pa)*(A)*(u³)

Where A is the swept area of the turbine (m²)

A is given by (pi)(r²)

The world's largest wind turbine generator has a rotor blade radius of 63m and so the rotors sweep an area of about 12470m2. If we use an air density value of 1.23kg/m3 and a wind speed of 14 m/s we get:

WP= 0.5*1.23*12,470*(14³)=21,000,000 watts (21 MW)

**As temperature increases, density decreases in an approximately linear manner

****Wind power on a really hot day is way less than on a really cold day!!!! (+35C vs -30C = 5MW difference in above turbine)

**What is the Betz Limit??

-Turbulence and gusts

-Shear stress and shear velocity

-Drag coefficient

-Wind Direction (wind rose)

The turbulent variations of the wind speed are typically expressed in terms of teh standard deviation, (σu), of velocity fluctuations measured over 10 to 60 minutes, normalized by the wind speed.

The Tubulence Intensity, I_u, is a widely used measure when neutral conditions persis with a logarithmic wind profile over at terain. Turbulence intensity may be derived from:

I_u= (σu)/U   (Dynamic TI)

I_u= 1/ln(z/z_o) (z-dependent TI)

Typical values of Iu for neutral conditions in different terrains are:

Flat/Open grassland: 13%

Sea: 8%

Complex terrain: 20% or more

So.... increasing terrain complexity results in greater turbulence intensity

stress= force per unit area

Wind shear stress is the force (per unit area) exerted by the moving fluid (air) on an object or surface. The equation for shear stress is given by:

τ= p_au_*²

Where pz is the density of the fluid (air) in kg/m3, and u_* is the shear velocity of the moving fluid, usually measured in m/s

We cannot measure the fluid shear stress directly so we must use surrogate measurements to resolve it.

Why does shear stress matter in wind science??

-Resolves stresses acting on structures

-Determines sediment/snow transport

-Stresses acting on turbines

**THINGS MOVE AND DEFORM IN RESPONSE TO STRESS

pa= -0.0047(temp.) +1.2976

u_* (aka friction velocity)

Shear velocity relates the difference of wind velocity at two heights

shear velocity = k(Uz2-Uz1)/ln(Z2-Z1)

Were Z1 is below Z2, so that Uz1 is less than Uz2

When calculating shear stress, assume density is 1.22kg/m3

Shear velocity tends to fluctuate between 0 and 1

The drag coefficient is a dimensionless quantity which is used to quantify the drag or resistance of an object in a fluid environment such as air or water.

C_z = (u_*/U_z)²

Where Cz - the drag coefficient at height Z

Values usually around 0.002-0.010 ish

-not much variation at a given height (shear velocity varies more)

All sources approx 94 quadrillion BTU

-One British Thermal Unit is the heat that will raise the temp of one pound of water by one degree F. Approximately the amount of heat generated by burning one kitchen match.

One BTU = 1054 Joules = 0.000293 kWh

39% Petroeum

23% Natural Gas

23% Coal

8% Nuclear Electric

8% Renewable

-50% hydro

-43% biomass

-5% geothermal

-1% solar

Oil discovery is on a trend of decrease, while production is on a trend of increase.

Conventional Oil reserves are mostly in middle east gulf, then in Eurasia.

What to do after the end of cheap energy?

-last one standing: the way of war and competition

-powerdown: the path of self-limitation

-waiting for the magic elixir: false hopes, wishful thinking, and denial

-building lifeboats: the path of community

What's the hold-up with renewable energy sources like wind?

-electricity in North America is extremely cheap (no incentive)

-the grid cannot take it

-storage

As for wind energy, Can is 11th in world, with installed capacity of 2,369MW. America is first

The most comprehensive study to date found the potential of wind power on land and near-shore to be 72TW, equivalent to 54000 Million tons of oil equivalent (MToE) per year, or over five times the world's current energy use in all forms.

The potential takes into account only locations with mean annual wind speeds greater than 6.9m/s at 80m. It assumes 6 turbines per square km for 77m diameter, 1.5 MW turbines on roughly 12% of the total global land area.

Renewable energy sources in Canada consist mainly of wind and hydroelectric.

Interestingly enough, electricity production of these two sources alternate according to seasons:

-hydro usefullness peaks in summer, while wind peaks in winter, and the yearly average is pretty much right in between.

1600s - Windmills in the Neterlands, pumping water and grinding grains

1888 - Charles Brush develops first large wind generator producing 12kW

Early 1900s - Windmills drive pumps and generators across rural North America

1941 - first prototype turbine (Putnam's 1.25 MW turbine) - also demonstrates need for lighter materials

1)Blade

2)Rotor Hub

3)Pitch Cylinder (in front of rotor hub)

4)Main shaft

5)Gear Box

6)Generator

7)Transformer

The torque shaft integrates with gears in some turbines. The gears connect to another shaft that turns a coil within the generator.

Most generators have a long, coiled wire on their shafs surrounded by a giant magnet.

When the turbine turns, the shaft and rotor is turned. As the shaft inside the generator turns, an electric current is produced in the wire. The electric generator is converting mechanical, moving energy into electrical energy.

The generator is based on the principle of "electromagnetic induction" discovered in 1831 by Michael Faraday, a British scientist. Faraday discovered that if an electric conductor, like a copper wire, is moved through a magnetic field, electric current wil flow of "be induced" in the conductor. So the mechanical energy of the moving wire is converted into the elecric energy of the current that flows in the wire.

1)Land acquisition

2)Resource analysis

3)Envioronmental work (EIA)

4)Interconnection

5)Permiting & Public Consultation

6)Secure Equipment

7)Construction

8)Commissioning

Steps 2, 3, 5, 7 typically take the longest.

The Cowley Ridge Wind Plant is the first commercial wind plant in Canada. Phase One was commissioned in 1993 and Phase Two in 1994.

Easily seen off Highway 3 from the town of Cowley, the wind plant features 57 Kenetech turbines, with a total capacity of 21.4 MW. Average production from this wind plant is more than 60 million kWh of electricity per year, which is enough to power 8,400 typical Canadian households.

The wind turbines at Cowley Ridge are mounted on 24.5 metre lattice towers and operate at wind speeds of up to 97 kilometres per hour. Each turbine has three blades and rotors that are 33 metres in diameter.

Rotor diameter started at around 20m, is currently around 100 meters, and is projected to reach nearly 140 meters in offshore plants by 2015

Albert Betz was a german physicist who concluded that no wind turbine can convert more than 59.3% of the kinetic energy of the wind into mechanical energy turning a rotor.

Wind turbines extract energy by slowing down the wind. For a wind turbine to be 100% efficient it would need to stop 100% of the wind – a theoretical impossibility

The theoretical maximum power efficiency of any wind turbine is 0.59 (i.e. no more than 59% of the energy carried by the wind can be extracted by a wind turbine).

Once you also factor in other aerodynamic inefficiencies the limit is well below the theoretical Betz Limit with values of 30% common even in the best designed wind turbines. Even less power is available when gearing, controls and other components of turbines are considered. Thus, in most cases only 10-30% of the power of the wind is ever actually converted into usable electricity.

Conversion to electricity is 70% of the 60% that is not spilled.

Theoretically, power increases exponentially with wind speed, yet in reality power levels out at a certain windspeed much sooner.

The energy potential per second (the power) varies in proportion to the cube (the third power) of the wind speed, and in proportion to the density of the air.

Turbine output effectively increases with the length of rotors (swept area)

Large rotor radius (63m)

WP= 0.5*1.23*12,470*(14^3) = 21,000,000W

Small radius (20m)

WP = 0.5*1.23*1256*(14^3) = 2,100,000W (10x less)

Rotor Radius vs Power is a (power/log/exp?) curve

-Lec13/sl30

-now power vs windspeed for a while until "cut-in" speed is reached

-gradual incline to (carrying capacity graph) peak output

-steady here until cut-out of furling speed

furling: the process of forcing, either manually or automatically, the blades of a wind turbine out of the direction of the wind in order to stop the blades from turning. Furling works by decreasing the angle of attack, which reduces the induced drag from the lift of the rotor, as well as the cross-section. A fully furled turbine blade, when stopped, has the edge of the blade facing into the wind.

 cut-in speed: the lowest wind speed at which a wind turbine begins producing useable power.

cut-out speed: the highest wind speed at which a wind turbine stops producing power

The most important reason is the stability of the turbine. A rotor with an odd number of rotor blades (and at least three blades) can be considered to be similar to a disc when calculating the dynamic properties of the machine.

A rotor with an even number of blades will give stability problems for a machine with a stiff structure. The reason is that at the very moment when the uppermost blade bends backwards, because it gets the maximum power from the wind, the lowermost blade passes into the wind shade in front of the tower.

Horizontal Axis (HAWT)

-propeller-style (blades-canada)

Vertical axis (VAHT)

-savonius-type

-darrieus-type

1)Climatology and Meteorology

2)Quality site plan

3)Energy estimates

4)Economic feasibility

*A change in speed from 12mph to 11mph can lead to a 33% decrease in the energy available in the wind!

CRITICAL TO MONITOR!

technical reasons:

-wind shear

-turbulence

-inflow winds

-extreme winds/gusts

-site design

-wake effects

Needed for:

-turbine manufacturers and foundation design

Wind is Site Specific!

Met Tower

-Wind speed (2 per level on tower)

-Wind Direction

-Different heights

-temperature, pressure

-data linked via data logger and cellular to internet connection

Goal: Estimate the energy at the hub height of the wind turbine!

-50-60m tall

-5x4 steel guy wires

-lifted using 'gin pole'

-when evaluating... must have data management

-check for errors (sensor failure, missing data, icing, etc)

-want to have it up for a year

-inter-annual variation

-annual average wind speed

-other averages

*Seasonal changes in wind speed are not spatially uniform! (increases in some areas, decreases in others)

Describe wind with a wind speed distribution histogram

-wind tends to be around 6-8m/s most of the time.

-graph is %time vs wind speed categories

Look at inter-annual variation if possible

To determine range of conditions (at different temporal scales) that occur at the site (how much variation around the mean?)

To determine worst case scenarios (is the site prone to frequent episodes of extremely high winds that might damage the turbine?)

To determine how variable the wind is at different scales (is it more variable during peak demand periods than outside these periods?)

* need lots of recording sites! Data does not correlate if far away

WHAT IS ROUGHNESS?

-Roughness is considered to be any element that alters wind from its original flow

-exists at many scales from micro topographic features (ripples on sand dunes), to land form scale (entire dune)

WHAT DOES ROUGHNESS DO?

-extracts momentum

-producing turbulence in the form of wakes behind obstacles

-breaking down large-cale turbulent eddies into smaller scale motions

FACTORS AFFECTING ROUGHNESS

The gradient of the velocity profile within the roughness sub-layer is related to several roughness element length scales:

-height

-width

-spacing

-density

-geometry

WHY EVEN CARE ABOUT ROUGHNESS?

WIND EROSION
Shear stress partitioning

-when the soil surface is obstructed by roughness elements the total force (Fo) of the wind is partitioned b/w the roughness elements (Fr) and the intervening bare soil (Fg):

F_o=F_r+F_g

-relevant for the fact we must know how much force is extracted by the roughness elements in order to determine how much force is still available to entrain particles.

WIND DEPOSITION

Blowing snow/drifting

Moisture Capture

WIND POWER
Affect on wind speed

Roughness elements cause turbulent unstable flow

-turbine location selection

MODELLING

Atmospheric modelling

Pollution modelling

Roughness density has a large affect on how wind articulates over the surface. Different densities create different flow regimes, affecting dependants such as wind erosion and particle movement.

-isolated roughness flow

-wake interference flow

-skimming flow

Many ways to characterize roughness..

Field measurements

-wind profiles

-physical measurements

Remote Sensing

-laser scanning

-LiDAR/Laser Altimetry

-Radar

The use of anemometers setup at specified intervals demonstrate the roughness length of the roughenss features in the derived wind profile from the gathered data.

Frontal Area Index

Defined as L_c=L_a/SA

La is the silhouette area (breadth*height), SA is defined as the number of roughness elements divided by the sample area.

With the frontal area index calculated, roughness for sparse array of vegetation can then be calculated through the use of the formula:

z_o= 0.5hL_c

Where h is the mean height of the roughness elements.

PROBLEMS associated with field measurements:

-How accurate of a representation was obtained through sampling?

-Time consuming, field work is expensive to conduct

-Measurements often generalize the roughness element.

The LIDAR instrument consists of a system controller and a transmitter and receiver

Scanning Mirror sweeps laser beam across the ground.

Range to target is determined by measuring the time interval b/w transmission and return of reflected laser pulse.

Aircraft position is determined using GPS phase differencing techniques.

LIDAR systems can emit pulses at rates greater than 100k pulses per second referred to as pulse repetition frequency. A pulse of laser light travels at c, the speed of light (3x 10⁸ m/s). LIDAR technology is based on the accurate measurement of the laser pulse travel time from the transmitter to the target and back to the receiver. The traveling time of a pulse of light, t, is:

R=0.5tc

Where R is the range (distance) b/w the LIDAR sensor and the object.

LIDAR/Laser Altimetry

-Holland et al. using LiDAR to characterise roughness of urban areas

-extract parameters from the LiDAR data required to calculate roughness. z_o = 0.5hL_c

-Filters, creation of raster datasets, feature extraction.

Good for large roughness elements, ineffective for smaller vegetation types (resolution isn't great enough)

Optical Techniques

Jansinki and Crago 1999 use canopy area density (total single sided area of all the canoy elements per unit ground area) as a surrogate for the frontal area index in order to determine roughness

-generalizations start to be made about stand characteristics

-used assumed stand averages and assuming stand homogeneity

Radar

-determined relationships between z_o and backscatter

LASER SCANNING

Same principls as LiDAR

Data similar to LiDAR pint cloud data (X,Y,Z)

Currently being used for soil surface roughness (physical roughness not aerodynamic roughness)

-characterizng surface roughness using RMSH

-quantifies the deviation from the mean

-Higher RMSH the rougher the surface

(look at formula for this)

Have not came across a study using laser scanning to quantify aerodynamic roughness

Benefits of laser scanning:

-very high quality data (point cloud resolutions in the order of mm scale)

-relatively inexpensive as compared to LiDAR data

-no generalization of features

-ability to capture very fine features

Drawbacks:

-robust datasets

-area coverage is somewhat limited

-no first and last return data (unlike LiDAR)

Conduct analysis on separated point clouds.

Investigate the relationship between RMSH and Zo

CanWEA is the national association for Canada's wind energy industry (advocacy, communication, education)

Represent 340 corporate members

-Turbine Manufacturers (GE)

-Component Manufacturers (Hitachi)

-Project Owners/Developers (Suncor, TransAlta)

-Utilities (Hydro Quebec)

-Service Providers (Jacques Whitford)

-installed wind capacity is increasing on a yearly basis in Canada

1,856MW of installed capacity in Canada

Close to 3000MW of signed power purchase agreements in place with construction immanent

More than 3000MW of additional power purchase agreements to be signed in 2008

*Quebec is leading the way*

Provincials objectives now represent a minimum of 12000MW by 2016

-Ontario 4600 by 2020

-Quebec 4,500 by 2016

-Alberta examining transmision options for 2000-3000MW

-Manitoba 1000MW by 2017

-BC and Labrador have large untapped potential

12,000MW of wind energy in 2016 would:

-serve 3.6 million Canadian homes annually

-meet 5% of Canada's total electricity demand

-represent 30+% of electricity produced from new facilities constructed in 2005-2015

-represent a $20+ billion investment (2005-2015)

-reduce GHG emissions by 9million tonnes/yr

But.. this only scratches the surface of Canada's wind energy potential

*****

Alberta has most installed potential, with Ontario right behind, and Quebec very close in third

-AB is frozen... Quebec making HUGE advances

Canadian current installed capacity is 1856MW

AB leading windfarms are Pincher Creek (43%), Willow Creek (29%), Taber (21%)

Electricity Output

-Example: a 100MW windfarm averaging 35% capacity

-Output = Generation MW x 8760 hours x  % Capacity Factor

-100x8760x0.35 - 306,600MWh per year

Households Served

-Number of Average Households = Output/7.2MWh

-306,600/7.2MWh = 42,580 hourholds

-supple enough electricity for over 42000 households

Emissions Displaced

-GHG emissions are 0.7 tonnes per MWh

-Emissions = electricity output x 0.7

-100MW x 8760 x 0.35 x 0.7 = 214,620 tonnes CO2

-Displace approximately 215,000 tonnes of CO2 or GHG emissions per year

Cars Taken Off the Road

-Annually produce approximately 4.78 tonnes of CO2 emissions

-Number of Cars = emissions displaced/4.78

-215000/4.78 = 44,979

-Equivalent of taking approximately 45,000 cars off the road each year

RURAL ISSUES

Low farm commodity prices

High farm input costs

-fuel prices high and uncertain

-high fertilizer prices

-lubricants

-equipment

-high land costs

Economic development and diversification

Eroding local property tax base

Migration of people to cities

-hollowing out 20-50 age range

Eroding services

-healthcare

-education

-policing

Water shortages and drought

Forestry:softwood lumber/prices

Cattle: BSE/border closing/prices

ECONOMIC DEVELOPMENT

Exploration

-Landowner payments

Construction

-employment

-services

-windfarm, interconnection, transmission

Operations

-employment

-services

-windfarm, interconnection, transmission

-property tax payments

-landowner payments

Tourism

LOCAL ECONOMIC IMPACT OF WINDFARM CONSTRUCT.

100MW/500MW

Construction 25jobs/125jobs

Operations 10jobs/50jobs

Property taxes annual 900,000/...

landowner royalties annual 400,000/...

*the above does not include indirect employment

MD of Pincher Creek Tax Revenues

-several groups (transAlta wind, etc)

-upwards of 1.5 million dollars per year

-Enter into option-to-lease /w landowners

---monitor wind resource, conduct studies

-Enter into long-term lease with landowner when windfarm is to be built

-No 'right of eminent domain' like subsurface in AB - wind similar to freehold rights - on land by invitation

-Landowner receives a royalty based on energy production or per turbine or combination of the two

-Royalty is 'Second Cash Crop' - no inputs

-Very low impact on operations whether pasture or cultivated

---small footprint ~15m2 per turbine (0.004 acre)

---windfarm footprint uses only 1-2% of land

-Complements 'stewardship' approach of many farmers and ranchers

-preserves agricultural land and way of life

SETBACKS

Setbacks are established to deal with four issues:

1)safety

2)sound

3)environmental impacts

4)communication and Radar Interference

Science and best practices are used to develop a range of setback distances.

There is no template or "one size fits all".

Studies into ice shedding and blade failure conclude that risks to objects or individuals directly drop off significantly with increasing distance from the turbine itself.

CanWEA recommmends a distance of blade length plus 10m from public roads, nonparticipating property lines and other developments in an Ontario application

Ice throwing!!

-most fragments are small and don't go very far.

AUDIBLE SOUD

What concerns are raised:

-"turbines emit a horrendous noise that makes it impossible to live anywhere near them"

What we know:

-wind turbines do produce sound "swoosh"

-actual sound level is influenced by many factors including the type of turbine, wind speed, surrounded topography

-Sound often masked by surroundin environment

How we address these concerns:

-All projects must meet regulatory requirements

-CanWEA Best Practices based on acceptable sound levels outside a dwelling: 40dBA at 4m/s rising to 53dBA at 11m/s (reflects fact that ambient sound tends to rise with wind speed)

-Typical resulting separation distances are generally 300-600m (can be less for participating landowners)

The Visual Issue

-Visual Effects is one of the most dificult land use issues to address

-Subjective versus objective

-visual can not be controlled by setbacks or colour/finish

-the turbines can not be made invisible

-how do you define a threshold?

-Burden of proof should be on opponents

Photomontage

Windfarm photomontage is a computerized simulation based on superimposing wind turbine images which are accurately located and scaled as to size onto a photograph for the purpose of creating a realistic representation of a proposed wind farm from a specific view

For example superimposing Vestas V90 wind turbines on 80m towers into photographs from various viewpoints within 30km of a windfarm

"Pictures speak louder than words"

Shadow Flicker

-not the sun seen through a rotating wind turbine rotor

-not what an individual moving through a windfarm may see

-not glint off blades

-it is the mving shadows cast by rotating turbine blades when the sun is low in the sky

Calculate using the geometry of the turbine, latitude and sun position

-computer model calculations are "worst case" (wind always blowing, always sunshine, rotor disk always perpendicular to sun)

Strobe Efect

Sun seen through a rotating wind turbine rotor

Depends on various factors:

-time of day (low sun angles)

-pitch angle of the blade

-location of the viewer

-orientation of the turbine rotor

-rotor rpm

Effect impacts over 350-500m from turbine

What an individual may see moving through a windfarm

Blade Glint

Reflected sunlight off blade surfaces

Depends on various factors:

-time of day

-location of viewer

-orientation of turbine

-profile of the blade

-pitch angle of the blade

-age of the blade

-colour of blade

-surface finish

Light grey colour and low gloss non-reflective surfaces are standard

The minimum wind speed to initiate sediment transport by wind (u_t or u_*t)

It is a critical parameter because it establishes the wind speed above which transport is possible. Due to a number of surface conditions (moisture, temperature, vegetation, bed slope, and crusting) threshold is known to vary over a range of spatial and temporal scales. Much of the focus of threshold research is to resolve the influence of these external controls and thereby increase the accuracy of sediment transport models. Currently, there are a variety of methods and instruments used to measure or derive threshold, but it is now apparent that the application of different methods and instruments imposes ambiguity in the definition of threshold.

Lift

Drag

Gravity

Cohesion

The relative magnitude of each force and the grain position relative to other grains is used to derive the fluid threshold for sediment transport.

Commonly the impact and fluid thresholds are each defined as a single wind speed (or shear).  However, most sediments are composed of a range of grain sizes and shapes. Thus, for a given surface, variability is expected in the positioning of sediment grains. Because the positioning of grains affects their susceptibility to entrainment, the fluid or impact threshold for a given surface is not easily described only by one number. This has been demonstrated in wind tunnel studies where the measured fluid and impact thresholds could not be reproduced, presumably because it is impossible to replicate grain positioning in each test. As a solution, threshold is best defined as a statistical phenomenon, or as two probability distributions (for the fluid and impact thresholds). The distributions describe the probability of a given threshold value occurring for a sediment surface.

Fluid threshold occurs at a higher wind speed than impact threshold.

1)Grain Scale

Sediment transport of particles is reduced to the forces acting on grains and solved mathematically

Commonly the bed is simplified as a population of spherical grains of constant size, and the wind is represented as a constant velocity

There is disagreement over the relative magnitude of lift and drag forces – this is important because it defines the initial movement of grains.

Observations from Chepil (1959) and Bagnold (1941, 1965) indicate grains slide along the bed prior to sediment transport. Contrarily, results from Bisal and Nielson (1962) and Lyles and Krauss (1971) suggest grains lift off vertically under the influence of lift forces. While the exact mechanism is yet unresolved, it is likely that both processes occur in tandem

Bagnold’s (1941) seminal work showed the presence of two quantifiable thresholds: (i) the minimum wind speed for initiation of sediment transport without antecedent sediment transport, or fluid threshold, and (ii) the minimum wind speed for sustaining sediment transport with the presence of sediment transport, or impact threshold. His data suggest that the impact threshold is approximately 80% of the fluid threshold (Bagnold, 1941). This difference is attributed to the positive feedback wherein the presence of impacting grains ejects more grains into the airstream, thereby sustaining the process at a lower wind speed than that required to initiate grain transport

2)Conrolled Experiment/Setting

Quantification of threshold in controlled settings (wind tunnels) requires that wind speed and sediment transport are measured simultaneously

The fluid threshold is denoted by the wind speed corresponding to the first measured instance of sediment transport, while the impact threshold is denoted by the wind speed corresponding to the last measured instance of sediment transport as wind speed decreases

u is commonly measured with pitot tubes or thermal anemometers – these instruments are situated close to the bed (typically 1 cm or lower) and report instantaneous measurements of wind speed at discrete times. The onset of sediment transport is recorded by visual observation, high-speed camera monitoring equipment, impact sensors, or laser based detection systems.

The reductionism inherent in wind tunnels has both advantages and disadvantages. Precise results are possible when the controls of threshold variability can be examined in isolation. However, wind tunnels do not reproduce the turbulent fluctuations in wind speed present in natural settings. Furthermore, reproducing natural surfaces in controlled settings is difficult, thereby challenging the representativeness of wind tunnel experiments

3)Uncontroled experiment

An approach where threshold is measured in the field under natural wind and surface conditions. Due to turbulent fluctuations in the wind speed, sediment transport observed in the field is often intermittent. Threshold wind speed (fluid or impact) is surpassed every instance sediment transport begins or ends. Thus, when sediment transport is intermittent, threshold can be determined repeatedly by measuring the wind speed corresponding to the onset and termination of sediment transport bursts. Advances in datalogger technology and electronic sediment transport sensors have made this approach more popular in recent decades. These technological advances allow investigators to monitor threshold continuously at unattended sites.

u_*t = A(SQRT(((p_p-p_a)gD)/p_a)

where A is an empirical coefficient (0.1 for fluid threshold, 0.08 for impact threshold); pp is the density of quartz sand particles (2.65 × 103 kg m-3); pa is air density (1.22 kg m-3); g is gravitational acceleration (9.81 m s-2); and D is sand grain diameter at study area (0.25 × 10-3 m). These values give an impact threshold of 0.231 m s-1

5.6 m/s for bare, dry sand.

bridging: interstitial pore water... cohesion

Entrainment Threshold

Seasonal and spatial changes in surface conditions (moisture, vegetation, ground freezing) complicate prediction of wind speed required to entrain soil.

Determining threshold in the field withprecision instruments. Sometimes thresholds remain constant over time, while some increase/decrease depending on what is exposed. For example, threshold increases as moist sand is exposed.

High winds

Sparse and low vegetation cover

Fine-grained soils

Aridity

Mainly an issue of land surface sensitivity

Dryland climates are typically associated with thin (ie. grassland) or patchy (ie. creosote) vegetation cover

These vegetation types are more readily affected b drought than forests, and more easily disturbed. Thus, drylands have increased potential for direct exposure of sediment to wind= higher susceptibility to wind erosion.

Vegetation cover is also more susceptible to natural and anthropogenic disturbances (fire, over-grazing, dought, vehicular traffic, etc.)

Dry soils are more readily entrained when exposed by agricultural tilage and land clearing during the initial phases of development.

1)It shelters the soil from the erosive force (shear stress) of the wind

2)It reduces the force of wind near the surface by extracting momentum from wind

3)It traps incoming soil particles - also induces deposition.

Once vegetation is removed, soil drifting potential immediately increases, then slowly decreases (finest is blown away, vegetation grows back, etc)

Winds capable of eroding the ground surface (>25-30 km/h) occur most frequently when vegetation growth conditions are poorest = prime conditions for blowing soil and snow.

Many of the factors that increase southern Alberta's susceptibility to soil erosion by wind also apply to snow drifting (ie. high wind power, low vegetation cover, aridity)

Without effective roughness elements (fences, wind breaks, building design, etc) snowdrifting can, at times, exceed soil drift rates by orders of magnitude. The effects, however, are short-lived, but they also recur each year if left unattended.

Snow drifting depends on temperature, age of snow, wind speed, and heigh of snow cover above the vegetation roughness elements. As the snow age increases, the drift potential decreases.

Vegetation effectivenes decreases as snow depth increases.

wind power is high - our research shows that it drops appreciably only in winter during strong El Nino phases (ie 1998) - otherwise dominated by modest interannual variability

wind direction is westerly- future land development will occur on the west side, thus wind erosion challenges will persist for some time in this sector

wind power is greatest when natural surface cover is least effecive (ie. outside of growing season)- emission reduction techniques must bear this in mind

Southern AB's landscape is sensitive to disturbance - removal of vegetation cover during initial phases of land development lead to an immediate increase of soil drifting - the bulk of mitigation strategies must focus on this period

there is a multi-fold effect of our climate that enhances soil and snow drifting - but there is direct correspondence b/w many of the natural factors that control these processes; therefore, mitigation techniques may be complimentary

Wind speed decreases towards the ground surface as the height of roughness elements increases (momentum extraction).

It also depends on topography.

Wind speed accelerates up to the crest of natural ridges or storage piles= potential for erosion.

Deceleration on the lee side = potential for deposition.

Artificial ridges or recesed (low-lying) areas can be used strategically to shelter some areas from the wind, but the height and profile geometry must be based on achieving maximum wind speed reduction.

Vegetation acts as a "living" wind shleter, reducing wind speed sppreciably for some distance downwind in the sheltered "wake" region. The effectiveness depends on the porosity, lateral extent, and height [H] of vegetation (flow recovery is usually 25-35 times the H)

When protective vegetation is removed, wind erosion potential increases dramatically, and emissions spike in areas with erodible soils under the right conditions.

The goal ust be to limit the exposure time and extent during initial phases of land development, either through adoption of low impact processes or deployment of mitigation techniques.

Threshold wind speed decreases once the surface dries [reduced inter-particle cohesion], or once the protective cover is removed. Thus, it is imperative to ensure that development activities do not unnecessarily reduce the threshold velocity. Mitigation strategies are designed specifically to increase threshold, thereby decreasing the probability of entrainment.

As wind speed [u] increases, the amount of windblown material [q] increases [q=~u³], but there is actually some scatter because the surface conditions change [ie. frozen ground, soil moisture, vegetation growth, etc.]

The challenge for land develoment is how to minimize wind erosion under different wind conditions BUT... We don't want to set arbitrary or unrealistic goals that might be overly restrictive.

Our research shows that there is no single eqution or set of equations that give us the right answer all the time - we need to measure it in the field and develop empirical relations over a broad range of conditions.

Soil Moisture

Surface Roughness

Particle size and density

Air temperature

Humidity

Wind Turbulence

Vegetation heigh and lateral cover

Soil crusts

Ground temperature

Disturbance

Creep

(>20% of transport)

-usually involves the largest particles moved by wind (0.7 - 2.5mm)

-no appreciable downwind effect since most grains are trapped a short distance from where they originated by small hollows are furrows

Saltation

(50-80% of transport)

-particles are generally too large to mobilize more than 1m above the ground surface (0.1-0.7mm)

Suspension (20-50% of transport - considered as air pollution)

-Finest particles (0.001-0.1mm) that travel the longest distance because they can bcarried high in the atmosphere

-Major concern is related to inhalation of these particles (block lung alveoli and can lead to respiratory disease or enhance pre-existing conditions)

PM₁₀ PM_2.5 PM_1.0

PM2.5 is less than 2.5 micrometers in diameter

-human hair average 70 micrometer diameter

Canada Wide Standard for Particulate Matter

In June 2000 the federal, provincial and territorial governments signed the Canada-Wide Standard (CWS) for PM, thereby agreeing to national ambient standards for PM2.5

Each jurisdiction is responsible for meeting the CWS and reporting on achievement once the target dates are reached. The CSW for PM must be achieved by 2010.

The CWS calls for the development and implementation of jurisdictional implementation plans as the primary mechanism for achieving the CWS, as well as programs for pollution prevention, keeping clean areas clean and continuous improvement to manage ambient levels below the CWS.

Alberta has adopted from the CWS, an AB Ambient Air Quality Objective for fine particulate matter (PM2.5) of 30 micrograms per cubic meter as a 24-hour average concentration. There is no 1-hr objective for fine particulate matter (PM2.5). However, after consultation with a multi stakeholder advisory committee, a 1-hr guideline in AB for PM2.5 was finalized at 80 micrograms per cubic meter. The guideline is based on the statistical equivalent of the CWS.

Action triggers:

-mandatory plan to reduce below CWS if goes above 30micrograms or ozone above 65ppb. Below that, have management plan for over 20/58, surveillance actions for over 15, and baseline monitoring below that.

We have measured PM2.5 during blowing dust events associated with land development that exceed these values.

In one case we measured >500 micrograms/cubic meter, averaged over 24 hours.

At the local level, land development policies have an important role to play in achieving the CWS.

Driving hazards

Accessibility (drifts blocking pedestrian mobility)

Water damage (build-up next to building - damage from melting/freezing)

Protracted snow cover (limiting spring drainage, landscaping)

Wind speed and direction

Dataloger and power

Piezoelectric sensor

Other items:

-cell phone modem

-digital camera

-meterological sensors

Use a prototype laser particle counter to measure the onset of particle movement in the field.

Can measure concentration of windblown particles using TSI Dusttrak

1)Health

-in addition to PM levels, there is growing realization that chemicals bonded to particles (pesticides, herbicides, etc) are translocated during wind erosion.

2)Mobility

-Mainly an issue of blowing snow, but costs can be high in areas with persistent problems

3)Aesthetics

-Residential cleanliness is a high priority for most home owners, including indoor air quality, but persistent build-up of soil and snow requires constant, sometimes costly maintenance.

4)Hazards

-Visibility is reduced during blowing dust and snow events.

Unpaved road (~40%)

Paved Road (~10%)

Construction (~15%)

Crops (~15%)

Wind erosion?? (~18%)

-others include cement, livestock, mining, quarries, etc

LAND CLEARING

Land clearing is analogous to the 1930s Dust Bowl on a local scale. By removing the protective surface cover we expose vast quantities of fine grained soils to the wind.

The amount of dust emission is proportional to the size of the area disturbed, the degree of land clearing, and the level of construction activity.

Depending on weather and soil conditon,s scrapers and other vehicles can emit large quantities of dust during land clearing (quickly exceeding the CWS of 30 is less than an hour)

The underlying soil texture here (gravel) indicates that wind erosion will self-affest once the finer particles are removed (ie. small dust reservoir).

UNPAVED ROADS

Vehicular traffic adds to particle suspension (dust emission) because tire contact creates a shearing force with the road surface that lifts the particles into the air.

Moving vehicles also create turbulent wakes that raise particles off the ground.

Natural crusts are easily broken by vehicle movement, increasing the reservoir of dust for emission. Depending on the underlying soil, the reservoir may be virtually unlimited.

Grinding shifts the particle size towards the finer fraction, enabling lift and transport at lower velocities.

In addition to vehicle shape and weight, the major vehicle-specific control on the rate of emissions is speed.

PAVED ROADS

-Dust on paved roads is common in S AB, increasing in winter and spring, and decreasing into summer due to washing from rain events.

A good example of a major issue with paved road dust emissions is the Deerfoot Trail in Cgy several days after a snowfall event.

Dust loadings also build-up from sediment tracked out of construction sites.

STORAGE PILES

Storage piles artifically change the local windflow pattern, leading to acceleration along the crest of the pile. However, sediment contained within most storage piles has a higher threshold because it has been compacted and aggregated (clods) during emplacement.

-coarse particles settle near base in reverse flow area

-dust flows above (aerial separation and organization... heaviest at bottom... settling in air)

-reverse flow occurs in around 4-10 times H of storage pile

-flow re-attachment occurs 0.5H after reversed flow

-re-attached flow occurs after, with recovery.

1)Mitigation strategies have a central goal of ensuring the surface has a high wind erosion threshold

2)The most critical time for mitigation strategies is during and shortly after land clearing

3)The success of a mitigation strategy depends on our ability to measure wind erosion, particularly the dust component, which has the most significant downwind effect.

4)An overall goal is to reduce wind erosion (soil and snow) down to the background level (if not better) as quickly as possible)

Identify factors that might contribute to wind erosion during land development.

soil texture - proportion of fine grained sediment (find sand and silt ractions, 100-20 micrometers), organics, chemical analysis

fetch- how exposed is the area to the prevailing wind?

wind patterns - maximum gust recurrence intervals, seasonal patterns, directional variability

proximity - of existing residential or commercial areas

road access surfaces - will construction vehicles be using paved or unpaved roads to access the site?

existing roughness condition - how effective was the pre-development land surface at trapping snow?

An enforceable regulation/bylaw must also contain test procedures in order to determine whether sources are in compliance

real-time meteorological data- air temperature, humidity, soil moisture, wind speed/direction, precipitation

wind erosion rates - passive dust traps (checked weekly), periodic monitoring with automated devices (Dusttrak), snowdrift rates, digital camera (atmospheric opacity)

daily record keeping - observations of dust plumes, snowdrifting, durface dryness and erodibility, activity levels, effectiveness of control measures

talk to local (downwind) residents - they know best whether things are improving or getting worse

Planning consideration are factors to minimize downwind and peripheral effects.

timing - Initiate land clearing when the probability of negative effects is lowest (ie. summer).

site design - Optimize site layout to reduce funnelling and accumulation - ie. streets oriented parallel to prevailing wind should have wind breaks at their open end.

building design - how to avoid creating local depositional areas for snowdrift accumulation or throughput areas where wind speed is compressed and accelerated.

wind breaks - height, density, number of rows, species composition, length, orientation, and continuity - determines the effectiveness of a windbreak in reducing wind speed.

Upwind and downwind implications, particularly for snowdrifting.

BACMs are methods used to reduce or eliminate windblown dust in areas where natural soils have been disturbed and are thus more prone to erosion by the wind. BACM is defined as the maximum degree of emission reduction feasible for a significant source category. BACM is determined on a case-by-case basis, taking into account technical feasibility, environmental and economic impacts as well as other costs. The process of determining BACM takes into account the most common sources of manmade dust, when they occur, what measures can be used to reduce dust, te relative cost of such measures, and their effectiveness in reducing dust.

For example... roughen surface is 15-64% effective, cross wind ridges (24-93%),

increase soil moisture (90%),

erect wind breaks (4-88%),

prohibit activities during high winds (98%),

apply dust supressant (84%),

wet suppression (50-90%),

minimize trackout onto paved roads (40-80%),

pave the surface (>90%),

re-vegetate (90%),

enclosures around storage piles (75%),

limit vehicle speed (44%)

ridging

increasing surface roughnss, sheltering and trapping

-perpendicular to prevailing wind

clod forming tillage -

-increasing surface roughness and limiting availability of particles (but only effective in silt and clay-rich soils) - not for sandy soils because clods break down quickly

increasing soil moisture

Water adhering to soil particles increasing their mass and surface tension forces, thereby decreasing suspension and transport.

It has been shown that the addition of water to create soil moisture contents exceeding 2% results in >80% reduction of PM10 emissions.

Excesive moisture causes the soil to adhere to vehicles, resulting in greater trackout and accumulation on roadways.

Wind breaks -

Effects (speed reduction) are felt upwind of the break (2-5H) and on the leeward wide for up to 30H, depending on porosity.

Two desirable effects:

1)Trap drifting snow/soil

2)reduce wind speed over exposed soil on leeward side

Porosity of about 40-60% is optimal for reducing erosion. If porous density is below 20%, the wind break does not provide useful wind reductions. If density is above 80%, excessive leeward turbulence may reduce effectiveness beyong 8H.

Wind breaks have a multi-fold positive feedback effect when used properly: decreasing wind speed, trapping snow, enhancing soil moisture, increasing plant growth rates.

Optimized spacing of wind break rows creates a broader-scale increase in surface roughness.

Temporary or semi-fixed wind breaks around storage piles, or in areas with soil excavating/loading/unloading reduces point-source emissions.

Gaps can produce local zones of acceleration due to airflow compression as it squeezes through the opening; hence, identification and repair of these features is paramount to avoid leaky wind breaks and localized throughputs of snow or erosion of soil.

Prohibitive Activities during high winds

Clearly the most effective (98%), but pissible the most costly due to construction downtime.

Some questions need to be addressed before wind speed limites are established, but continuous on-site monitoring of wind speed and ground conditions can provide a good approximation for daily activities.

WInd forecasts will be invaluable for planning purposes.

Apply Dust Suppressant

(salts, resin/petroleum emulsions, polymers, surfactants, bitumens, adhesives, solid materials)

Dust suppresants act to bind soil particles together, making them more resistant to entrainment by wind (ie, increasing threshold).

Some suppressants may negatively impact near-surface water quality and vegetation, and, therefore should only be used for large areas if other techniques fail to produce adequate emission reductions.

Wet Suppression

Wet suppression is an affordable alternative to chemical suppressants, but must be frequently re-applied, particularly during warm, dry, windy periods when evaporative losses are high.

Wet suppression is also feasible over large areas, and is even more effective when used in conjunction with another technique (ie mulching).

Mulching/Hydroseeding

-Mulches can be placed on the ground surface without any subsequent anchoring, or incorporated into the soil with a studded roller or with a tackifier stabilizing emulsion.

Hydroseeding typically consists of applying a mixture of weed fiber, seed, fertilizer, and stabilizing emulsion with hydromulch equipment, to temporarily protect exposed soils.

Hydroseeding may be used alone only when there is sufficient time in the season to ensure adequate vegetation establishment and coverage to provide adequate vegetation establishment and coverage to provide adequate erosion control. Otherwise, hydroseeding must be used in conjunction with mulchine (ie. straw mulch).

Recent application of hydroseed at the AB water and env sci building was very positive in terms of reducing dust emissions.

Limit Vehicle Speed

The downwind travel distance of dust raised by a vehicle increases with wind speed; therefore, vehicle speed should decrease as wind speed increases.

Minimize negative downwind effects associated with land development

1)Gain experience with BACMs - understand how well they work under different conditions

2)Monitor and document progress/setbacks using different control measures.

3)Timing is everything - implement control measures aggressively during initial stages of development.

Developing a knowledge base for land development in a windy climate

-dust control plan, including compliance standards and scheduling

-Wind gust recurrence probabilities - like food forecasting

-Wind categories - restricting certain activities

-Real-time wind information and forecasting

-Process monitoring - how much dust, snowdrift, etc., under different development activities?

-Testing and evaluation of control methods.

Owen's Lake, California: Dust-producing engine of the southwest

About the lake.

In the late 1800s, Owens Lake, at about 110 square miles, was one of the largest natural lakes in California. It was a saline terminal lake with a salinity about 1.5 seawater.

In 1913, the City of Los Angeles Department of Water and Power (LADWP) completed construction of the Los Angeles Aqueduct. The Aqueduct diverted Owens River water destined for Owens Lake 223 miles south to Los Angeles. With the lake's main source of water diverted, by the mid-1920s, Owens Lake had shrunk to a small hypersaline remnant brine pool of about 103 square km, and less than 1m deep.

Owen's Lake, with its unstable saline soils, began to emit large amounts of fugitive dust in the 1920s and has become the largest single source of particulate matter air polution in the US.

-76k tons of PM10 annually.

Currently, approximately 65-100 sq km along the eastern shore of the lake bed emits dust regularly.

Owen's Lake, California: Dust-producing engine of the southwest

Who Cares? and Control measures.

The federal 24hr standard for PM10 is 150 micrograms/cubic meter.

The "significant harm to health" level is 600 micrograms per cubic meter.

***24hr levels of 3,900 have been measured in Keeler and 12,000 at Dirty Socks.

The US EPA AIRS Data for 2002 show that of the 30 highest PM10 days reported nationally, 28 occurred at Owens Lake. Owens Lake's highest day of 7,915 was over 13 times higher than any other location in the USA (590 in El Paso, Texas).

How will the dust be controlled? A multi-million (100s) dollar project.

In 1998, the District adopted a State Implementation Program (SIP) that required the LADWP to control dust emissions from Owens Lake by the end of 2006.

The 1998 SIP required that, within a 90 sq km envelope, 43 sq km of the lake bed had to be controlled by the end of 2003.

It also required the District to continue to collect data on those areas of the lake bed that needed dust controls and revise the SIP in 2003 to incorporate the latest information.

**

Three approved methods of controlling dust that are feasible on a large scale:

1)native vegetation

2)flooding with shallow sheets

3)gravel blanket

The Key is....vegetation.

Research indicates that if 50% of a dust producing area consists of live or dead vegetative cover, dust emissions will be reduced by 99%.

why?

Vegetation is an imporant surface control because it reducs wind erosion in 3 ways:

1)shelters the soil from the shear stress of the wind

2)Reduces the force of wind near the surface by extracting momentum from wind

3)Traps incoming soil particles - induces deposition becuase of (b).

It takes approximately 7 acre-feet of water per acre to reclaim the saline soils and establish vegetation the first year. In subsequent years it takes about 2.5 acre-feed of water per year per acre to maintain the 50% veg cover necessary to control PM10

Saltgrass

Is attractive because:

1)it is a locally adapted native species (@ Owens Lake)

2)It is very  salt tolerant

3)It spreads via underground runners and thus new growth is protected from wind damage

4)It creates a surface protecting mat.

...however.... it is not particularly drought tolerant.

Chris and Owen Brown describe a new twchnique where LiDAR is used to estimate aerodynamic roughness over a large area at fine resolution.

Use z_o = 0.33h^1.07

.

1)Inertial sublayer (free stream) - flow above the roughness elements (small change in velocity with height), and

2)Roughness sublayer - lies inside and just above the roughness elements (near surface)

INERTIAL SUBLAYER - FREE STREAM

Flow in the inertial sublayer, over a smooth surface and thermally neutral air follows a logarithmic increase with height (z) above the surface:

u_z = u_*/k ln(z/z_o), z>z_o

Recall that shear velocity (u_*) is proportional to the rate of change of velocity with height.

Aerodynamic surface roughness (z_o) is the height at which horizontal velocity is zero. On a perfectly flat surface , the value of zo depends on the grain size of sediment at the surface.

With vegetation or other roughness elements, velocity above the elements follows a logarithmic profile. The logarithmic portion can be extrapolated down to a height where the mean horizontal wind speed (u) is zero. However, with roughness elements the height at which u extrapolates to zero is displaced to the top of the elements (displacement height, d).

The wind profile may then be determined from:

u_z = u_*/k ln[(z-d/Z_o)

Where Z_o is the aerodynamic roughness length as defined by the roughness element height, shape, and spacing. It is larger than that of bare soil (Zo>zo) because the roughness elements increase surface drag.

Surface Drag - the Drag coefficient

(more inertial sublayer)

The drag coefficient (C_z) is a dimensionless quantity which is used to quantify the resistance of an object to airflow.

C_z= (u_*/U_z)²

where C_z = the drag coefficient at height z. Often C_z is considered a constant for a given z; however, computations by Hsu and Blanchard (1991) for C₁₀ showed a variation of from 0.0005 to 0.005. In fact, C_z varies with season and wind direction and cannot be considered constant.

The logarithmic profile often does not work at levels below or even near the maximum height of roughness elements. In the laboratory, experiments show that the logarithmic profile works down to a level of approximately 2 times the height of roughness elemens (z=2h).

In the field, it is found that the lower limit of the inertial sublayer is defined as z=h+1.5D, where h is the mean roughness element height and D is the separation distance b/w nearest neighbour elements.

Vegetation interacts with wind within the roughness sublayer in several ways:

-extracting momentum

-producing turbulece in the form of wakes behind obstacles

-breaking down large-scale turbulent eddies into smaller scale motions

Flow in the roughness sublayer is complex - further complcates our ability to assess the potential for sediment transport below the displacement height.

The gradient of the velocity profile within the roughness sublayer is related to several roughnes element length scales:

-height

-width

-spacing

-density

-geometry

Before considering a collection of plants (roughness elements), let's first consider the flow modifications induced by a single plant.

-wake region (deceleration)

-separation

-acceleration

-stalling

Grasses and crops usually provide continuous cover, but shrubs can provide an interspersed array of vegetation and bare soil (American SW - creosote)

Depending on the spacing of shrubs, three types of flow regimes will develop:

1)isolated roughness flow - wide spacing of elements

2)wake interference flow

3)skimming flow

Shading represents wake region - decelerated/protected; light areas represent region of flow where inertial sublayer might be expectd to penetrate to the bed.

As density increases the surface protected by the decelerated region increases.

With decreased spacing the wakes formed by the roughness elements do not fully develop before another element is encountered - wake interference.

In skimming flow the entire soil surface is protected from the recovery of the inertial sublayer even though there may be a considerable portion of bare soil. This is the optimal condition for surface control of wind erosion using vegetation.

2x2cm cubes used to examine effects of element density in a wind tunnel. A cover of greater than 40% results in skimming flow.

Several metrics:

1)plant silhouette area - the vertical cross-section of the plant that the wind encounters

2)density - number of individuals (or thir biomass) per unit area

3)Lateral cover - the ratio b/w silhouette are and total surface area

L_c=DA_s

Where D is density and As is the mean frontal-silhouette area (height x diameter) per area.

Roughness density is derived from..

lamda= A_s/S

Where S is he surface area per plant.

For sparse arrays aerodynamic roughness can be derived from Z₀=lamda/H, where H is the mean height of plants.

Use a quadrat (1sq m)

Roughness density is derived from SUM[nh([wl]/2)/a]

Where n is the # of individuals measured for maximum height (h), ength of the longest axis (l), and length of the perpendicular axis (w), and a is the area of each quadrat (1 sq m).

Percentage veg cover is derived from:

SUM(wl)/a

****LAMDA IS THE SYMBOL FOR ROUGHNESS DENSITY*** (baha)

When the soil surface is obstructed by roughness elements the total force (F0) of the wind is partitioned b/w the roughness elements (Fr) and the intervening bare soil (Fg):

F₀ = F_r + F_g

This is relevant because we must know how much force is extracted by the vegetation, and ow much remains to entrain soil at the surface.

The effect of vegetation an also be examined from the ratio of the impact threshold with and without vegetation - but this must be measured.

After the last iceage, wind reworked the land once the ice and water receded.

There are currently 120 dune fileds (sand hills) and less than 1% are active.

-some up north on AB/SK border... cypress hills... south manitoba.

These areas are islands of biodiversity for species that require this kind of habitat.

Water tables close to the surface is very common for these areas.

Archaeological evidence exists of aboriginal occupation and exploitation.

Dusky Dune Moth is an example of an endangered spp

-also Ord's kangaroo rat, western spiderwort, small-flowered sand-verbena, and many others.

***Of the more than 40 native prairie plant and animal species listed as species at rish in Canada, 25% are found in Prairie Sand Hills

-due to changing ecosystem and changing habitat.

used to be... "miles of burning sand"

OVER the last 200 years, prairie Sand Hill ecosystems have transformed.

Open-sand habitat has decreased substantially, threatening the survival of a number of endangered species.

Wind erosion has a positive role!

Studies have tried to stimulate wind erosion and renew habitat with

-fire

-artificial wind erosion hollows

-grazing attractants

Used post-burn wind erosion monitoring.

Unfortunately, everything grew back very quickly.

In the spring (after 7 months) ground was almost completely covered with vegetation again.

In artificial wind erosion hollow, after 1 year still fairly exposed.

LESSON LEARNED

Fire, artificial hollows and grazing attractants are successful in the short-term, but not in the long-term.

Future Challenges:

-Environmental assessment and mitigation of Oil & Gas development in Prairies.

1)Critical Habitat Mapping

-Remote sensing delineation of sparse-vegetation habitat

2)Terrain sensitivity mapping

-Improving the characterization of wind and water erosion risk

3)Water Resources

-Sand hill near-surface aquifers: volume, recharge rate, extraction.

-Sand hill surficial aquifers: volume, recharge rate

4)Climate Change/Variability

-Adapting to future extremes and trends

-changing terrain sensitivity

-water availability

-shorter drilling season