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Journal of Arid Environments 107 (2014) 18e25
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Journal of Arid Environments
journal homepage: www.elsevier .com/locate/ jar idenv
Detecting patterns of aeolian transport direction
John E. StoutUSDA-ARS, Lubbock, TX, USA
a r t i c l e i n f o
Article history:Received 23 September 2013Received in revised form1 April 2014Accepted 1 April 2014Available online 19 April 2014
Keywords:AeolianBlowing sandSaltationThresholdTransport direction
E-mail addresses: [email protected], johned
http://dx.doi.org/10.1016/j.jaridenv.2014.04.0010140-1963/Published by Elsevier Ltd. This is an open
a b s t r a c t
The direction of sediment transport is of direct interest to those engaged in the study of aeolian pro-cesses. Here, a technique was employed that provides information regarding aeolian transport directionusing measurements of wind direction and aeolian activity. This technique involves detecting one-second periods of blowing sediment, called saltation seconds, with a piezoelectric saltation sensor andassigning active periods to one of sixteen principal wind direction sectors. Saltation seconds are thensummed for each wind direction sector to compute the relative fraction associated with a specific winddirection. Measurements of aeolian activity collected over a fifteen-year period at a large saline playa onthe Llano Estacado of North America were used to compute the relative frequency that sediments aretransported by winds blowing from a specific direction. Results of this study suggest that winds with awesterly component contribute significantly to the transport of playa sediments at this site and thisresult is consistent with the location of massive fringing dunes along the eastern margins of the playa.Results also reveal a significant contribution of strong northerly winds associated with dry continentalpolar cold fronts that often pass through the area, especially during the winter, late fall, and early spring.
Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
1. Introduction
Whenwinds blowwith sufficient strength across a bare patch ofground, grains will be detached and transported in the directionwinds are blowing. Whenwind direction shifts, transport directionwill shift accordingly. As time passes and winds continue to natu-rally change direction, the proper description of transport directionbecomes more challenging. The difficulty lies in the fact thatsediment transport is a vector quantity with both magnitude anddirection (Bagnold, 1937). Whereas the magnitude of sedimenttransport is a scalar quantity and can be simply averaged over timeto obtain a mean value, transport direction must be described as aspectrum of values distributed over the principal directions of thecompass.
The description of transport direction is especially challengingin turbulent flows where wind speed and direction are continuallychanging in a chaotic manner. During a typical blowing event, gustywinds driven by swirling turbulent eddies produce significantvariations in sediment transport and due to the three-dimensionalnature of turbulence; each burst of blowing sediment may betransported in a slightly different direction (Baas, 2008).
Despite these challenges, transport direction remains animportant and fundamental aspect of aeolian research. In fact,
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transport direction is as fundamental to the study of aeolian pro-cesses as wind direction is to the study of the atmospheric sciences.
Here, a relatively new technique was employed that providesinformation regarding aeolian transport direction using routinemeasurements of wind direction and aeolian activity. Details of theexperimental approach will be described later in more detail, butbriefly the goal was to detect 1-s periods of blowing sediment,called saltation seconds, using a piezoelectric saltation sensor whilesimultaneously recording wind direction with the goal ofcomputing the fraction of time that blowing sediment was detectedfor each of sixteen compass directions.
2. Past work
In the field of aeolian geomorphology, the subject of sand driftdirection has been of significant interest for some time. Notablepioneering attempts to understand the relationship between dunetrends and prevailing wind direction may be seen in early aerial-photo studies by Aufrère (1928) in the Sahara and in the work ofMadigan (1936) in Australia.
Fryberger (1979) was among the first to attempt to movebeyond the somewhat qualitative descriptions derived from aerialphotography to a more quantitative approach. Using techniquessimilar to that developed by Skidmore (1965) and building uponthe work of Lettau and Lettau (1978), Fryberger and his assistant
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J.E. Stout / Journal of Arid Environments 107 (2014) 18e25 19
Gary Dean analyzed available surface wind statistics to estimate themagnitude and direction of sand transport or “drift”. They devel-oped the “sand rose,” which is described as a circular histogramthat represents potential sand drift from the 16 directions of thecompass and they reported good qualitative agreement betweencomputed sand roses and dune forms and trends derived fromLandsat imagery. However, this technique has some limitations dueto a number of simplifying assumptions. For example, Frybergerassumed that sand transport could be estimated using a semi-empirical formula first proposed by Lettau and Lettau (1978), butfield experiments were never conducted to confirm estimates ofsand transport. The universal applicability of this method alsosuffers from a questionable assumption regarding threshold. Fry-berger simply assumed a constant value of threshold wind speed of6.2 m/s for all sites, regardless of the location, type of sand, orsurface moisture conditions. This assumption may be adequate indry regions of pure sand but threshold can vary significantly insemiarid regions with clay soils and more frequent rainfall (Stout,2007).
Khatelli and Gabriels (2000) avoided many of these pitfalls bydeveloping a pivoting array of sediment catchers that allowed adirect measurement of transport direction. Samples were collectedthree times a day at intervals of four hours during the day andsixteen hours at night. Such a straightforward measurement ofsand transport does not rely upon questionable mass transportformulae nor does it require assumptions regarding threshold windspeed. The primary limitation of this technique is that it requires afulltime technical staff to empty the array of sediment catchers andweigh the trapped samples. To maintain this sampling routine foran extended period requires a tremendous effort and few re-searchers can devote the time and resources.
At the Fifth International Conference on Aeolian Research, heldin July of 2002, the author delivered an oral presentation in whichhe offered a technique for detecting aeolian transport direction.Nothing was published at that time but others have used thistechnique successfully (see e.g. Gillies et al., 2013). The techniquewill be described in more detail later but briefly, the experimentaltechnique involves the detection of 1-s periods of blowing sedi-ment, called saltation seconds, with a piezoelectric saltation sensorand then active periods are assigned to one of sixteen principalwind direction sectors. Saltation seconds are then summed for eachwind direction sector to compute the relative fraction associatedwith a specific wind direction. This technique has some advantagesover those described earlier. One advantage is that data can becollected by a sampling system that operates unattended forextended periods, yet at the same time provides high-resolutioninformation regarding transport direction. In addition, this tech-nique is not limited by assumptions regarding threshold nor is itdependent upon semi-empirical formulae for the estimation ofmass transport. One disadvantage is that this technique does notprovide a measure of actual mass transport; rather it only providesa measure of the frequency that windblown sediments are trans-ported in a given direction.
3. Field study and methods
Saline playas, also known as salt playas or salt lakes, are amongthe more interesting geomorphic features on the high plains of theLlano Estacado of Texas (Reeves, 1965; Sabin, 1992; Sabin andHolliday, 1995). Saline playas also provide excellent sites for long-term studies of basic aeolian processes. Yellow Lake, the site ofthis study, is one of two irregular shaped saline playas that formedwithin a closed basin located on the Yellow House Ranch ofnorthwestern Texas (Fig. 1). Yellow Lake is roughly 4.4 km long byless than 1.0 kmwidewith a playa surface area of 3.2 km2. The playa
surface represents the lowest level within Yellow House Basin and,during periods of heavy rain, a shallow playa lake forms and oc-cupies a limited fraction of the playa surface (Stout, 2003). Grad-ually, the pool of water evaporates and the playa surface driesleaving an exceptionally flat clay surface lightly dusted withgypsum.
The salinity of surface sediments inhibits plant growth so thatthe playa surface remains free of vegetation. Desiccation cracksappear when the surface dries sufficiently and further weatheringforms clay aggregates that are easily moved by the wind. The finestclay particles often become suspended by turbulent winds, forminglight-colored dust clouds that may extend a considerable distancedownwind of the playa. The larger sand-size clay aggregates saltateacross the playa surface and deposit along the partially vegetatedplaya margins where they form clay dunes, also known as fringingdunes or lunettes (Bowler, 1968; Coffey, 1909; Hills, 1940; Reevesand Parry, 1969; Telfer and Thomas, 2006). Unlike sand dunes,clay dunes do not migrate downwind from where they are firstformed; rather, they tend to remain at playa margins growing withadditional accumulations during successive periods of aeolian ac-tivity (Bowler, 1973; Holliday, 1997). Year after year additionallayers of sediment are deposited providing important clues to thephysical environment and wind regime of the past (Bowler, 1973;Butler, 2003; Hills, 1940; Vincent, 1991). At Yellow Lake, claydunes are found primarily along the eastern and southern marginsof the playa where they extend to as high as 40 m above the playasurface.
Fieldwork at Yellow Lake began in late December of 1998 anddata collection is still ongoing (Stout, 2003). At the end of 2013,fifteen full years of data have been collected with only small datagaps caused by occasional loss of power or equipment malfunction.Data gaps were kept at a minimum by using a digital modem toremotely download data each morning so that system performancecould be checked and repairs could be made quickly.
The experimental system (Fig. 2) used in this study wasdesigned to operate unattended for extended periods at this remotesite. The core of the sampling system consists of a solar-poweredmeteorological tower equipped with a 12-V battery, a datalogger,rain gage, anemometer, pyranometer, and a combinedtemperature-humidity sensor. All meteorological variables weresampled each second and averaged over five-minute intervals.
Aeolian activity was monitored with a Sensit piezoelectricsaltation sensor (Stockton and Gillette, 1990) placed 10 m to thewest of the meteorological tower. During periods of active aeoliantransport, the impact of saltating grains on the piezoelectrictransducer produces pulse signals that are recorded as particlecounts by the datalogger. If the number of particle counts recordedduring a given second is not zero then that second is registered asone “saltation second” and a counter is incremented. This test isperformed each second so that the total number of saltation sec-onds can be counted for each five-minute output interval.
The Sensit was mounted so that the lower edge of the piezo-electric crystal was set flush with the eroding surface. Ideally, onewould prefer to maintain a constant sampling height but due toaeolian deflation, and occasional fluvial deposition, the height ofthe piezoelectric sensor can vary over time. The problem of main-taining a constant sampling height is a common and frustratingproblem in aeolian research regardless of the sampler or transducerused to detect aeolian transport. However, it is actually less of aproblem for studies of playas than it is for studies of sand dunes.Unlike a mobile sand surface, the clay playa surface is fairly stableand only small changes of height were observed over long periodsof time. During routine monthly visits, the sampling system wasinspected and the height of the Sensit was adjusted if necessary. Inmost cases, no adjustment was necessary.
Fig. 2. Photo of the sampling system on the playa surface at Yellow Lake. The systemconsists of a 2-m tall meteorological tower equipped with an anemometer, tempera-ture and humidity sensor, pyranometer, tipping-bucket raingage (to the right) andSensit saltation sensor (to the left). The system is powered by a solar panel that chargesa 12-V battery.
Fig. 1. Aerial photograph of the Yellow House Basin, which contains two saline playas named Illusion Lake and Yellow Lake (33 490 3000 N, 102 270 2700 W).
J.E. Stout / Journal of Arid Environments 107 (2014) 18e2520
It is also important to point out that the exact height of thesensing element is not critical when using the Sensit as an on- oroff-indicator of aeolian transport. This is one of the advantages ofcounting saltation seconds rather than using the raw counts outputof the sensor alone. Although the number of particles that impactthe sensing element will vary with height, it only requires oneparticle count to register a saltation second. The exact value ofparticle counts registered each second is not important. Forexample, if the Sensit outputs 100 counts for a given second at asampling height of 1 mm but only 20 counts per second at asampling height of 10 mm, both will be counted as one saltationsecond. As long as the piezoelectric crystal remains within thelower portion of the saltation zone (0e20 cm for most cases) andthe sensor is impacted by at least one particle, the sensor willindicate sediment movement and register a single saltation second,regardless of the magnitude of the particle counts recorded duringthat second (Stout and Zobeck, 1996).
Analysis of the angular distribution of saltation seconds wasperformed “post-experiment” or after the raw data set had beencollected. The first step in the analysis involves dividing the com-pass into sixteen 22.5� sectors, where each sector is centered aboutone of sixteen principal compass directions. For each active five-minute period, there is a corresponding vectorially averaged orresultant wind direction and it is assumed that sediment is
J.E. Stout / Journal of Arid Environments 107 (2014) 18e25 21
transported in the direction that winds were blowing only duringthose seconds when sediment transport is detected. Depending onthe strength of the wind relative to the threshold velocity of thesurface, some five-minute periods, associated with high winds andlow threshold velocities, may contribute numerous saltation sec-onds to a given wind direction sector. For the case of continuousblowing during a given five-minute period, a maximum total of 300saltation seconds can be contributed to a wind direction sector.During periods with weak winds or high threshold velocities, agiven five-minute period may contribute nothing or only a fewsaltation seconds to a wind direction sector.
The next step in the analysis is to sort the entire data set bywinddirection so that saltation seconds can be summed separately foreach of the sixteen principal wind direction sectors. Then thedirection-specific sum of saltation seconds are divided by the totalnumber of saltation seconds recorded during the entire samplingperiod thereby forming non-dimensional values that represent thefraction of saltation seconds associated with each of the sixteenprincipal wind direction sectors.
It is important to emphasize that this method does not involvesumming the raw particle counts supplied by the Sensit’s piezo-electric transducer, rather particle counts detected during a given1-s period are used to generate a saltation second and it is the sumof saltation seconds, not particle counts, that are used to computetransport direction.
4. Results
The final raw data set consists of measurements of meteoro-logical and saltation data. Meteorological data include wind speed,wind direction, relative humidity, temperature, solar radiation, andrainfall. Saltation data include raw particle counts and saltationseconds measured by the piezoelectric saltation sensor. The com-plete record of saltation activity measured at the site is plotted as atime series in Fig. 3. Here the total number of saltation seconds are
Fig. 3. Time-series plot of hourly saltation activity from 1999 to 2013. Hourly s
summed each hour and divided by 3600 s to form a dimensionlessvalue of hourly saltation activity. These data provide a continuousrecord of saltation activity at the sampling site over the fifteen-yearsampling period.
Periods of aeolian transport, referred to as “blowing events,”appear throughout the record. A typical blowing event begins whenwind speed first exceeds the critical threshold of the playa surface.This can occur at any time of the day but blowing events tend tofollow a fairly regular diurnal pattern with wind speed and salta-tion activity increasing as the sun rises in themorning and saltationactivity decreasing as the sun sets in the evening (Stout, 2010; Yanget al., 2013). During a typical blowing event, wind speed will oftenproduce bursts of blowing sediment during intermittent windgusts interspersed with inactive periods as wind speed frequentlypasses above and below threshold (Stout and Zobeck, 1997).
An annual summary of climatic conditions and annual saltationactivity is presented in Table 1. Here the total number of saltationseconds are summed each year and divided by the total number ofseconds within each year to form a dimensionless value of annualsaltation activity, expressed as a percentage. Results suggest thatthe annual total of saltation seconds and associated saltation ac-tivity varies considerably from one year to the next.
One might naturally assume that aeolian activity of playasgenerally reflects natural changes in climatic conditions. In otherwords, one might assume that high levels of aeolian activity wouldbe associated with dry and windy conditions and low aeolian ac-tivity would be associated with high rainfall and humid conditions.However, a careful examination of Table 1 suggests that the cor-relation between annual saltation activity and annual climaticconditions is fairly weak. For example, the exceptionally dry year of2011 had the lowest annual rainfall, the lowest annual averagerelative humidity and an above-average annual wind speed, yetannual saltation activity was not exceptionally high. At the oppositeextreme, rainfall in 2006 was above average and wind speeds werebelow average yet this year produced the second highest annual
altation activity is the hourly sum of saltation seconds divided by 3600 s.
Table 1Annual summary of saltation activity and meteorological conditions measured at Yellow Lake from 1999 to 2013.
Year Total rain (mm) Avg. windspeed (m/s)
Avg. relativehumidity (%)
Avg. air temp. (C) Total saltationseconds (s)
Annual saltationactivity (%)
1999 494 3.6 56 15.6 79,760 0.32000 231 3.7 55 15.6 337,568 1.12001 248 3.3 61 15.9 32,995 0.12002 451 3.4 56 15.3 116,913 0.42003 301 3.7 49 15.9 1,777,421 5.62004 786 3.7 62 15.1 479,391 1.52005 349 3.4 57 15.5 222,828 0.72006 528 3.6 51 16.1 1,211,786 3.82007 524 3.4 62 14.9 283,509 0.92008 394 4.0 51 15.3 856,649 2.72009 343 3.7 52 15.4 79,665 0.32010 358 3.7 56 15.9 26,229 0.12011 115 4.0 42 17.2 497,736 1.62012 235 3.9 46 17.3 323,345 1.02013 265 3.7 50 15.4 444,897 1.4
J.E. Stout / Journal of Arid Environments 107 (2014) 18e2522
total of saltation seconds. Clearly, the interaction between climaticconditions and aeolian activity is more complex than one mightinitially assume.
It is beyond the limited scope of this short paper to fully discussthe complex interactions of climate and resulting aeolian deflationof a playa, but after fifteen years of careful observation a few factshave become apparent. First, the timing of strong winds is impor-tant. Obviously, strong winds blowing across a wet playa lake willnot generate aeolian activity. Likewise, strongwinds blowing acrossa dry playa surface with deep desiccation cracks or a hardpansurface that otherwise lacks loose erodible material will fail togenerate aeolian activity. For such a supply-limited system, theavailability of erodible material is an important factor that de-termines whether strong winds will initiate aeolian transport.
Another important and somewhat surprising observation is thatheavy rainfall can actually lead to an increase in aeolian activity.Runoff associated with heavy downpours can deliver copiousamounts of sediment to the playa surface and, as the surfaceeventually dries, this sediment supply becomes available foraeolian transport. Thus, rainfall may reduce the erodibility of aplaya surface in the short term but it may ultimately lead to a moreerodible condition after drying. This may partly explain why someyears with above average annual rainfall may also have aboveaverage annual saltation activity.
4.1. Transport direction
One could compute the angular distribution of saltation secondsseparately for each of the fifteen years of this field study; however, asingle year is clearly not sufficient to define transport direction overthe long term. A better overall picture of sediment transport di-rection is obtained by summing saltation seconds over the entire15-year sampling period. Here, saltation seconds recorded from1999 through 2013 are summed separately for each of the sixteenprincipal wind direction sectors.
The results of this analysis show that the highest fraction, 16% ofall saltation seconds, was associated with north winds that trans-port sediment from the north side of the playa to the south (Fig. 4).Strong northerly winds are typically associated with continentalpolar cold fronts that pass through the area during the winter, latefall, and early spring (Schmeisser et al., 2010). Winter on the LlanoEstacado is typically the driest time of year and winter days aremarked by large diurnal temperature variations that lead to freezeethaw cycles that can cause the hard clay crust to soften and crumblethereby providing abundant loose erodible material for aeoliantransport.
The second largest peak of 14% was associated with west windstransporting sediments from the west side of the playa to the east.Overall, the majority (60%) of all saltation seconds were associatedwith winds with some westerly component including windsblowing out of the southesouthwest, southwest, westesouthwest,west, and westenorthwest sectors. This result is consistent withthe observed overall alignment of aeolian landforms on the LlanoEstacado (Carlisle and Marrs, 1982; Melton, 1940; Muhs andHolliday, 2001). In addition, west winds are typically dry windsthat blow downslope from the southern extension of the RockyMountains in New Mexico. These already dry winds cross theChihuahuan Desert before traversing the high plains of the LlanoEstacado and are typically associated with wind erosion and duststorms in this region.
The lowest fraction of saltation seconds is associated with eastwinds, or some component of east winds. East winds are generallyassociated with moist air masses that draw moisture up from theGulf of Mexico (Schmeisser et al., 2010; Wang et al., 2007). Theresulting moist conditions and abundant rainfall limit aeolian ac-tivity at Yellow Lake and on the Llano Estacado in general.
It is interesting to compare the results of this analysis with theoverall distribution of clay dunes at Yellow Lake. Tall fringing dunesalong the eastern margins of the playa are consistent with domi-nant westerlywinds that transport sediment from the playa surfacetoward the east side of the playa. The relatively large peak ofsaltation seconds associated with north winds is also consistentwith the formation of clay dunes along the south side of the playa.The absence of fringing dunes on the west side of the playa is alsoconsistent with the small fraction of saltation seconds associatedwith easterly winds.
4.2. Directional climatology
A similar directional analysis was performed on climatic vari-ables measured at Yellow Lake using data collected from 1999through 2013. As before, the full data set was sorted by wind di-rection and then values of wind speed and relative humidity wereaveraged separately for each of the sixteen principal wind directionsectors. The results of this analysis are presented in Fig. 4.
Results suggest that the angular distribution of wind speed(shown in lower left quadrant of Fig. 4) follows a pattern that isbasically similar to the angular distribution of saltation activitywith some key differences. For example, there is good agreementwith regard to winds with a westerly component. Here, bothsaltation activity and wind speed appear to be relatively high forwinds blowing out of the west. There is also good agreement with
Fig. 4. Angular distribution of saltation seconds, wind speed, relative humidity and dew point for the full fifteen-year sampling period (1999e2013).
J.E. Stout / Journal of Arid Environments 107 (2014) 18e25 23
regard to easterly winds where both saltation activity and windspeed tend to be at a minimum. However, a close inspection revealsan important discrepancy with regard to peak values. Whereas thehighest fraction of saltation seconds was associated with windsblowing out of the north, one finds that there are six other winddirection sectors with average wind speeds greater than that ofnorth winds. Clearly, based upon the computed directional patternof wind speeds alone, it is unlikely that one would suspect that thehighest fraction of saltation seconds would be associated withwinds blowing out of the north.
The angular distribution of relative humidity, shown in theupper right quadrant of Fig. 4, reveals that winds with a westerlycomponent tend to be very dry as expected. This result appears tobe consistent with the fact that the overall majority of saltationseconds were associated with winds with some westerly compo-nent including winds blowing out of the southesouthwest,southwest, westesouthwest, west, and westenorthwest sectors.Relative humidity, however, shows no appreciable depression withregard to north winds as one might expect.
A similar directional analysis can be made of dew point, whichis a good indicator of absolute humidity. Dew point temperaturewas not measured at Yellow Lake but hourly values are availablefrom the National Weather Service station in Lubbock, locatedapproximately 60 km to the southwest of the Yellow HouseRanch. The full record of hourly dew point observations at theLubbock station stretches back to 1945, but here we consideronly the 15-year period that corresponds with sampling at Yel-low Lake (1999 through 2013). Observations of dew point weresorted by wind direction and then values were averaged sepa-rately for each of the sixteen principal wind direction sectors.The angular distribution of dew point, shown in lower right
quadrant of Fig. 4, suggests that winds with a westerly compo-nent have both low absolute humidity and low relative humidity.The results of these analyses also reveal that although northwinds tend to have a high relative humidity, they typically have alow absolute humidity. This discrepancy is most likely related tothe fact that north winds tend to be associated with cold frontsand cooling can effectively increase relative humidity while it haslittle effect on absolute humidity. The combination of moderatelyhigh wind speeds and low absolute humidity may partly explainwhy the fraction of saltation seconds tends to be at a maximumfor north winds.
It is important to emphasize that any conclusions regardingaeolian transport direction based solely upon directional clima-tology will always be prone to error. Analyses of wind speed oratmospheric humidity provide little direct information aboutimportant surface conditions like threshold velocity and theavailability of loose erodible material. By simultaneouslymeasuringsaltation seconds and wind direction one can avoid these diffi-culties and obtain more concise information regarding the direc-tion of transport of windblown sediments.
4.3. Seasonal patterns
It is well known that the wind regime on the high plains of theLlano Estacado varies with the seasons (Bomar, 1983; Carlisle andMarrs, 1982). For much of the year, south winds, or some compo-nent of south winds, are most frequently observed whereas duringthe winter, north winds, or some component of north winds, aremore common due to the passage of cold fronts (Ward, 1916). Onenaturally wonders if there are similar seasonal shifts in aeoliantransport direction.
J.E. Stout / Journal of Arid Environments 107 (2014) 18e2524
An attempt was made to quantify seasonal patterns of aeoliantransport direction through a multistep process. First, each salta-tion secondwas associatedwith one of the four seasons based uponwhen it occurred in relation to the precise timing of the seasons asdefined by the United States Naval Observatory. Then the data setwas sorted by season, forming four seasonal subsets that could besummarized separately. The angular distribution of saltation sec-onds was then computed separately for each of the four seasonalsubgroups by summing the number of saltation seconds for each ofthe sixteen principal wind direction sectors and then dividing bythe total number of saltation seconds associated with each season.The results of this analysis provide seasonal distributions of aeoliantransport direction, as shown in Fig. 5.
Overall, most of the seasonal distributions follow similar pat-terns with negligible aeolian transport associated with winds withan easterly component and larger fractions of saltation secondsassociated with winds from other directions. A close inspection,however, reveals some subtle but important differences.
If one considers the peaks of the seasonal distributions one findsthat peak values tend to shift with the seasons. During the winterthere are two prominent peaks corresponding to north andsouthwest winds. During the spring the highest fraction of saltationseconds was associated with southesouthwest, west, and northwinds. During the summer there is a prominent peak corre-sponding to south winds and very little contribution from northwinds. In the fall the peak shifts 180� to north winds and there islittle contribution to aeolian transport from south winds.
Fig. 5. Seasonal distributions of saltation a
Considering the overall distributions one finds that winter, fall,and spring seasonal distributions all have a core cluster of highvalues associated with winds with a westerly component whereasthis core cluster shifts more toward the south in summer. Inaddition, one finds that winter, fall, and spring seasons typicallyhave large contributions to aeolian transport from winds blowingout of the north whereas this northerly contribution is lessimportant during summer.
5. Conclusions
This paper explores a technique for detecting the fraction oftime that windblown sediments are transported by winds blowingfrom a given direction using a sampling system that can be leftunattended for extended periods. Output from a piezoelectricsaltation sensor is used as an on- or off-indicator of aeolian trans-port, which allows 1-s periods with active movement to be countedand associated with a given wind direction. Saltation seconds arethen summed separately for each specific wind direction sectorover a period of many years to provide a relative measure ofsaltation activity associated with a given wind direction.
Direct measurements of saltation activity along with measure-ments of wind direction taken over a fifteen-year period at YellowLake provided the raw data from which the angular distribution ofsaltation activity was computed. Overall results suggest that windswith a westerly component, such as southesouthwest, southwest,westesouthwest, westenorthwest and especially west winds,
ctivity as a function of wind direction.
J.E. Stout / Journal of Arid Environments 107 (2014) 18e25 25
contributed the majority (60%) of all saltation seconds measuredduring the full fifteen-year sampling period. The overall distribu-tion also reveals a significant contribution of north winds associ-ated with continental polar cold fronts.
Angular distributions of saltation seconds were found to varywith the seasons. During the winter there were two peaks of nearlyequal magnitude corresponding to north and southwest winds.During the spring, peak saltation activity was associated withsouthesouthwest winds and there are other prominent peaks forwest and north winds. During the summer there is a prominentpeak corresponding to south winds with little contribution fromnorth winds. In the fall, the peak shifts to north winds and there islittle contribution to aeolian transport from south winds.
Directional analyses were also performed on climatic variablessuch as wind speed, relative humidity, and dew point. Results ofthese analyses suggest that winds with a westerly component tendto be well above average with regard to wind speed and very dryboth with respect to relative humidity and absolute humidity. Thesituation with northerly winds, however, was found to be morecomplex. Whereas the highest fraction of saltation seconds wasassociated with north winds, one finds that the averagewind speedwas only slightly above average and, despite a reduction of dewpoint; there was no appreciable depression of relative humidity.Based upon the computed directional patterns of wind speed andhumidity, it is unlikely that onewould suspect that an exceptionallyhigh fraction of saltation seconds would be associated with windsblowing out of the north. Clearly, predictions of aeolian transportdirection based solely upon climatic factors will be prone to errorbecause directional climatology provides little direct informationabout changing surface conditions.
Acknowledgments
The author would like to thank James R. Golden for constructingand maintaining the sampling system for nine years. I would alsolike to thank ranch managers Thomas Albus, Terrel Campbell, TracySpencer, and James Caddell, owner of the Yellow House Ranch.Mention of trade names or commercial products in this article issolely for the purpose of providing specific information and doesnot imply recommendation or endorsement by the U.S. Depart-ment of Agriculture. USDA is an equal opportunity provider andemployer.
Appendix A. Supplementary data
Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.jaridenv.2014.04.001.
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