Wind Erosion in the Sahelian Zone of Niger:
Processes,Models,and Control Techniques
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Wind Erosion inthe Sahelian Zone of Niger:
Processes, Models,and Control Techniques
Geert Sterk
Proefschrift
ter verkrijging vandegraadvan doctor
opgezagvanderector magnificus,
dr. C.M. Karssen,
inhet openbaar teverdedigen
op dinsdag 1 april 1997
desnamiddagstevieruurindeAula
vandeLandbouwuniversiteit teWageningen.
ISm ' 9 3 ^ / é
ThesisWageningen Agricultural University
ISBN 90-5485-672-6
LANDBOUWUMVEXSITHT
WAGW#NG«N
ThisstudywasfinanciallysupportedbytheNetherlandsFoundationfortheAdvancementofTropical
Research(WOTRO),whichispartoftheNetherlandsOrganizationfor ScientificResearch(NWO).
Project numberW76-151.
Cover design:Ernst vanCleef.
Stellingen
1.
In de Sahel-zonevanNiger veroorzaakt winderosie een veel ernstiger bodemdegradatie dan
watererosie.
- dit proefschrift.
- Taylor-Powell,E. 1991.Integratedmanagementofagriculturalwatersheds:Landtenureandindigenous
knowledge of soil and crop management. TropSoils Bulletin 91-04. Texas A&M Univ., College
Station.TX.
2.
De veronderstelling van Scott-Wendt et al. en Manu et al. dat winderosie en -depositie de
belangrijkste oorzaken zijnvan variabiliteit in gewasgroei op zandgronden in Niger is waar.
- dit proefschrift.
- Scott-Wendt,J., R.G. Chase,andL.R. Hossner. 1988.Soilchemicalvariability insandyUstalfs in
semi-arid Niger,WestAfrica. Soil Sei. 145: 414-419.
- Manu,A.,A.Pfordresher, SC.Geiger,LP.Wilding,andL.R.Hossner. 1996.Soilparameters related
tocropgrowthvariabilityinwesternNiger,WestAfrica. Soil Sei.Soc.Am.J. 60:283-288.
3
Het gebruik vangeringe hoeveelheden ( s 1000 kg ha"1)gierststengels alsbescherming tegen
winderosie inNiger kan averechtswerken. Tijdens zware stormen met windsnelheden boven
ca. 10m s"1zalde ruwheid van de stengelsjuist meer erosie veroorzaken door een toename
van de turbulentie-intensiteit.
- dit proefschrift.
4.
Nigerijnse boeren hebben eengoede, kwalitatieve kennis van winderosie en onderkennen het
gevaar van bodemdegradatie door wind. Het niet voldoende beschermen van de bodem is
dusgeengevolg vanonwetendheid, maar moetworden verklaard uit economische en culturele
factoren.
- dit proefschrift.
5
Het aanleggen vanbomenrijen voor bodem- en gewasbescherming in de Sahel is een slechte
maatregel. Regeneratie van natuurlijke vegetatie met verspreid staande bomen en struiken
is beter.
- dit proefschrift.
- McNaugthon, K.G. 1988. Effects of windbreaks on turbulent transport andmicroclimate. Agric.
Ecosyst. Environ. 22/23: 17-39.
6
Het concept vanprecisielandbouw ishet reaktiverenvan boerenkennis die verloren is gegaan
door mechanisering en schaalvergroting in de westerse landbouw.
- Deprecisieboervoegtzichnaarzijnland.deVolkskrant, 25januari 1997.
7.
Dearmstelandenvandewereldzijnweinigtot nietgebaat bijontwikkelingshulp indevorm
vanlandbouwkundigeprojecten. Hetisbeteromdefinanciële middelen aantewendenvoor
verbetering vanonderwijs en infrastructuur.
8.
Demeteorologische term 'windrichting' iswiskundig gezien onjuist.
9.
Door het gericht fokken van dierenwordt inteelt bevorderd.
10. Indehuidigewetenschapsbeoefening wordtteveelnadrukgelegdopdekwantiteitenteweinig
op dekwaliteit vanartikelenin vaktijdschriften.
11. / don'thaveadrinkingproblem, exceptwhenI can'tget adrink.
- Uit:Badliverandabrokenheart,TomWaits,SmallChange, 1976.
- WijsheidopgedaantijdensveldwerkinNiger.
Stellingen behorendebij het proefschrift:
'Wind Erosion inthe SahelianZone ofNiger: Processes,Models, and Control Techniques'
Geert Sterk, Wageningen, 1 april 1997.
'The windcarriesawayfertile sandandleavesafertility whichislessfertile'
HassaneAdamou
FarmerinLiboréBangou Banda, Niger
Acknowledgments
Theresearchdescribed inthisthesiswascarried out attheDepartment ofIrrigation and Soil
&Water Conservation, WageningenAgricultural University (WAU), TheNetherlands, andthe
InternationalCropsResearchInstitutefor the Semi-Arid Tropics(ICRISAT) SahelianCenter at
Sadoré, Niger. The scientific and logistic support from these two institutions is gratefully
acknowledged.
Manypeoplehavecontributed insomewayto the completion ofthethesis, and Iam grateful
toallofthemfor their cooperation and support. Aspecialword ofthanksgoestothe following
persons:mysupervisorsLeoStroosnijderandPieterRaats,fortheirneverendingsupport;thefellow
graduate students at ISC,Holger Brück, Steve Gaze, JörgHaigis, Ludger Herrmann, Martina
Mayus,MarkSmith, andAlexWezel,for theircooperation, friendship andthemanyliftsto and
from ISC;HabibouHalidou,Boubacar Soumana,andmanyday-labourersfor theirgreat helpwith
thefieldwork at times with temperatures well above 40°C; Syne van der Beek, for the many
stimulating e-mailsand discussionsattheVlaamscheReus.
Lastbutnotleast,IwanttothankAnita,whotypedalotoftext,madesomeverygood figures
forthethesis,helpedmewith software problems,but atthe sametime, shemademerealizethat
obtaining aPh.D.isnice,but notthemost important thinginlife.
Contents
Chapter 1
Introduction
Chapter2
Theeffect ofturbulent flow structures on saltation sand
1
transport intheatmospheric boundarylayer
Chapter3
11
Comparison ofmodelsdescribingthevertical distribution
ofwind-eroded sediment
Chapter 4
33
Mappingwind-blownmasstransportbymodelingvariability
inspaceandtime
Chapter 5
51
Wind-blownnutrienttransport and soilproductivity changes
insouthwestNiger
Chapter 6
Wind erosion controlwithcrop residuesinthe Sahel
Chapter 7
Farmers' knowledge ofwind erosionprocesses and control
methodsinNiger
Chapter 8
91
111
Towardsaregionalmassbudget ofeoliantransported
materialina Sahelianenvironment
Chapter 9
71
Summary and conclusions
125
137
Samenvatting enconclusies
143
Résuméetconclusions
147
Curriculum vitae
152
Chapter1
Introduction
Introduction
T
heSahelianzoneofAfrica drewworldattentionduringthe 17yearsofdrought that started
in 1968. Some25millionpeoplefaced famine aswellassocialand economic disruption.
Thelongperiod ofdroughtwasevenmoretragicastheSahel,already oneoftheworld's poorest
regions,isalsothemostsubjectedtodesertification(Valentin,1995).Thetragedypainfullyhighlighted
theurgent socialneed to investigate causesand consequences ofdrought and desertification in
the Sahel.
Theterm"Sahel"isderivedfromtheArabicwordSahilwhichmeansacoast orborder(Hillel,
1991).Theregioncanbeseenasthetransitionzonebetweenthe arid Saharainthenorth andthe
morehumid Sudanzoneinthesouth.Inthisthesis,theSahelisdefined asthezone approximately
200-400kmwide,centeredonlatitude 15°N,justsouthoftheSahara.Itcoverssignificant portions
ofSenegal,Mauritania,Mali,BurkinaFaso,Niger,Chad,Sudan,andEritrea.Thelimitscorrespond
roughlywithameanannualrainfall of200mminthenorthand600mminthe south(LeHouerou
andPopov, 1981).
About90%oftheSahelianpopulationlivesinvillagesand islargely dependent on subsistence
agriculture (Sivakumar, 1989). Theagricultural environment ischaracterized bychemically and
physicallyimpoverished soilsthatgenerallyhavesandytosandyloamtextures, loworganic matter
contents, and lownativefertility, withphosphorus beingthenutrient most limitingcrop growth
(Manuetal., 1991).Thesesandysoilsarestructurally unstable, proneto crusting and hardsetting
(Valentin, 1995),andhavelowwater-holdingcapacities(Payneet al., 1990). Inaddition, climatic
conditionsareharsh,withhighlyvariablerainfall duringashortrainyseason, hightemperatures,
andpotentialévapotranspirationexceedingprecipitationformostoftheyear(Fig.1).Thiscombination
ofpoor soilsandharshclimaticconditionsmakescropproduction difficult.
Thesedentaryfarming systemsoftheSahelcombinefree-roaming livestock withrainfed crop
production.Mostfarmerskeepsheep,goats, and sometimescattle,for milkand meat. The major
cropispearlmillet(Pennisetumglaucum),whichisoftenintercroppedwithalegume,usuallycowpea
(Vignaunguiculata). Milletissownwiththefirstrainsintherainyseason.Inintercropping systems
the second crop isnot sownuntil 2to 3weeksafter themillet (Spencer and Sivakumar, 1987).
More favorable micro-environments with better moisture and nutrient conditions areused for
Chapter 1
400
300
E
E,
HLU
O.
200-
08
Û.
100-
J
F
M
A
M
J J A S O N
Month
Figure1.AgroclimaticconditionsforNiamey,Niger. AdaptedfromFAO(1984).
D
sorghum (Sorghum bicolor), maize (Zea mays), sorrel (Hibiscussabdarifa), okra (Hibiscus
esculentus),andpeanuts(Arachishypogaed).Manioc(Manihotesculentd)isoftengrowningardens
nearvillages, andwomenusually cultivate smallvegetableplots(Taylor-Powell, 1991).
Continuous cropping causes soilorganic matter andplant-available nutrientsto decline. To
restoresoilfertility, farmerstraditionallykeptlandunderbushfallowfor periodsof 10to 20years.
However,rapidpopulationgrowth, at annualrates of s=3%duringrecent decades,hasincreased
demandforfood. Insteadofintensifying fanning systems,for instancebyusingmineral fertilizers,
farmershavetriedtoenhanceproductionbyexpandingthecroppedarea.Thepreviouslysustainable
fallow systemhasbrokendown, yieldshavedeclined, andmoremarginalland,whichusedto be
communal grazing land, is now cropped (Broekhuyse and Allen, 1988). Consequently, overexploitationhasresultedinlanddegradation,ordesertification, onalargescale(Hillel, 1991). Land
degradationimpliesareductionofresourcepotentialbyasingleprocessoracombinationofprocesses
actingontheland. Theseprocessesincludeerosionbywater andwind, crusting and hardsetting
ofsoils,salinizationandalkalinization,andlong-termreductionintheamountordiversityofnatural
vegetation (Dregne etal., 1991;Valentin, 1995).
Introduction
WIND EROSION
Winderosioncanbecomeaproblemwheneverthesoilisloose, dry,bareornearlybare,and
thewindvelocityexceedsthethreshold velocityfor initiation ofsoilparticlemovement (Fryrear
andSkidmore, 1985).IntheSahel,thefarming systemsandsoilconditionsareveryfavorable for
winderosion.Except for afew monthsinthegrowing season, theground ismostlybare andno
adequatemeasures aretakento sufficiently controlwind erosion.Moreover, the sandytextures
and dryclimaticconditionsmake soilsverysusceptibleto erosionfor most oftheyear.
Erosivewindsthat exceed thethreshold wind speed mayoccur duringtwo distinct seasons.
Duringthedryseason(October-April),theareaisinvadedbydryandrather strong northeastern
winds,locallyknownasHarmattan,thatmayresultinmoderatewinderosion(Michelsetal.,1995a).
TheHarmattanwindsoriginateoverthe Saharan desert, andfromJanuarytoMarchtheyusually
carrymuchdustfromremotesources.PartofthetransporteddustisdepositedintheSahel,enriching
soilswithnutrients(Dreesetal., 1993).Dustdepositsareparticularlyrichinsodium, potassium,
magnesium, and calcium, but poor inphosphorus (Herrmann etal., 1996).
Thesecondandmostimportantwinderosionperiodistheearlyrainyseason(May-July),when
rainfall comeswith heavythunderstorms that movewestward throughthe Sahel." '•••""=> fully
developedthunderstorm strongverticaldowndrafts occur, causingaforward outflow ofcoldair
thatcreatesthetypicalduststormsoftheSahel.Theseeventsareusuallyshort-lived, approximately
10to30minutes,butthestormsmayresultinintensesoilmovement(Michelsetal, 1995a).Generally,
threedifferent modesofparticletransportaredistinguished(Bagnold, 1973). Saltating sand grains
jumpandbounceoverthesoilsurface,therebyinducingcreep,therollingandslidingoflargeparticles
overthesurface, andsuspension,theraisingoffinesoilparticles(Fig.2).Thelattertransport mode
resultsinthespectaculardustclouds,whichareoften seentobepushedforward byathunderstorm.
Partofthedustmayberedepositedbytherainthatimmediatelyfollowsthedust storm (Herrmann
etal, 1996).
Cropseedlingssufferfromabrasionandburialinsandduringtheseearlyrainyseasonstorms.
Abrasion,orsandblasting,damagesplantsbythescouringeffect ofsaltatingsand particles. Young
plantsburiedduringstormssufferfromtheweight ofthesand, reduced sunlightinterception, and
highsoiltemperaturesduringdaytime.Thedamagerangesfromreduced growth and development
tototal destruction ofcrops(Michels etal., 1995b).
Chapter 1
wind profile
/
suspension
Figure2.Threemodesofwind-blownparticletransport.
Apartfromdirectdamagetoseedlings,winderosioncontributestosoildegradation bytheloss
oftopsoil. Thisisbecausemost plant-available nutrients arelocated inthetopfew centimeters
ofthesoilandwinderosionpreferentially removesthe organicmatter and clay,whichhold these
nutrients(Lai, 1988).However,itisunknownhowmuchdamageisactuallydonetosoils(Dregne,
1990).Intheliterature,therearenoreportsofstudiesthathavequantified soilandnutrient losses
bywind erosioninthe Sahel. According toFryrear andLyles(1977),part oftheproblemisthe
lackofsatisfactorysamplingequipmentforstudyingwinderosioninthefieldandthecomplexnature
oftheprocesses involved. Although samplingtechniqueshaveimprovedgreatly duringthepast
20years(Fryrearetal., 1991),noentirelyadequatetechniquesfor quantifyinglossesofsoilparticles
andnutrientshavebeendeveloped.
ThegrowingproblemposedtocropproductionbywinderosionisemphasizedbyTaylor-Powell
(1991).InasurveyintheHamdallayewatershedinNiger,shefoundthatfarmers seldommentioned
watererosionasaproblem.However,winderosion emerged asamajor concernbecause farmers
fearitspotentialdamagingeffects. Waysofcopingwiththeseproblemsmentioned bythe farmers
included achangeintheir cropresiduemanagement intheprevious 10years. Crop residues are
nowleft onthefieldafter harvestto protectthe soilagainst erosivewinds.
Introduction
Milletresidueisbyfar themost commonlyusedmulchmaterialfor soilconservation, but its
availabilityislimitedbecauseofitsmultipleusesforfuel,fodder andconstruction material (Lamers
andFeil, 1993).AccordingtoMichelsetal.(1995a),atleast2000kgha"1 ofmilletresidueisneeded
foradequatesoilprotectionintheSahelianzone.Underthe current biomassproductionlevelsof
2200kgha"1 (Manuetal, 1991)andthehighdemandforotherpurposes,itisunrealisticto expect
thatfarmerswillbeabletoadequatelyprotectmostoftheirfields.Hence,thereisaneedforimproved
crop residuemanagement, andpossiblyfor additionalmeasuresfor wind erosion control.
Althoughthetechnicalmethodsarewelldocumented(e.g.,FryrearandSkidmore, 1985;Tibke,
1988),muchlessisknownabouttheadoptionofthosemethodsbySahelianfarmers. Forinstance,
althoughprotectionagainstwinderosionbyerectingwindbreaksisapromisingmeasure, farmers
arereluctant toimplement itbecause ofuncertainty aboutitsbenefits (Michels, 1994).
Animportantrequirementfordesigningwind erosioncontrol measuresisthattheyfitintothe
local,Saheliansituation.ThisisillustratedbyBenSalem(1991):"Buildingupon, not abandoning,
traditionallandmanagementistherealchallengefor sustainabledevelopment ofrenewablenatural
resourcesinaridregions.Theproblemofwind erosionneedstobeaddressed withinthisbroader
context."Indigenousknowledgeofwinderosionandtraditionalmethodsforsoilandcropprotection
shouldformthebasisforimprovingordesigningwinderosioncontrolmeasuresintheSahel.On-farm
surveyslikethestudybyTaylor-Powell(1991)areimportantfor ascertainingthefeasibility ofwind
erosion control methodsinthe landmanagement systemsoftheSahel.
AIM
Theaimofthestudydescribedinthisthesisistoimproveunderstandingofwinderosionprocesses
intheSahelduringearlyrainyseasonstorms.Inparticular,anattemptismadetoquantify the effect
oferosivestormsonchangesinsoilproductivity inpearlmillet cropping systems, andto explore
thefeasibility ofwind erosioncontrolmeasuresthatfit intothecurrentfarming systems.
STUDY OUTLINE
ThefieldworkforthisstudywasdoneduringthreemeasurementcampaignsinsouthwestNiger,
inapearlmilletfieldof170by90m.Eachcampaignlasted3months,frommid-Mayuntilmid-August
intheyears 1993,1994,and 1995.Duringthefieldwork,wind-blown sediment movingbetween
thesoilsurface and aheight of 1mwasstudied. Thisheight range comprised allthreetransport
8
Chapter 1
modesofcreep,saltation,andsuspension(Fig.2).Fine,suspended dust movingabove 1 mheight
wasnot studied, sincetheapparatusrequired for thiswasnotavailable.
In order to studywind erosion processesinthefield,adequate measurementtechniques are
needed.Duringthefirstfieldcampaignin 1993,emphasiswasonthedevelopmentof measurement
techniquesandrelatedmodelstoquantifythemassofsoilparticlesandnutrientstransported during
storms.Inchapter3,asimplesedimentcatcherformeasuringhorizontalmassfluxesofwind-blown
particlesisdescribed,andamethodtocalculatethetotalmasstransportrateatthepointofobservation
isdeveloped.Using21sedimentcatchersinaplot of40by60mmadeitpossibleto study spatial
variationinmasstransport.Inchapter4,geostatisticaltheoryisappliedtomodelspatialdependence
betweenobservations,andtoproducestormbased mapsofmasstransport. Thesemapsareused
tocalculatesoillossesfromtheexperimentalplot.Moreover, thelossesoffour nutrients (K,C,
N,andP)duringtwoseverestormsarecalculatedfromchemicalanalysisofthetrapped sediments
(chapter5).
Thesecondandthirdfieldseasonsin1994and 1995dealtwith (i)the effect ofturbulentflow
structuresontransportofsandbysaltation,(ii)winderosionprotectioncreatedbysmallquantities
ofmilletresidues, and (iii)farmers' perceptions ofwind erosionprocessesand soil conservation
techniques.
Turbulenceisanaturalcharacteristicofwind.Itcausesfluctuationsinwindvelocitythat create
additionalshearstresssuperimposed ontheshearstressresultingfrom theaverageflowcondition.
Fluctuations inshear stress atthe soilsurface are considered to beimportant for wind erosion
processes.Measurementsofinstantaneouswindspeedandsaltationfluxenabledtheroleofvelocity
and shear stressfluctuationson soilparticlemovement bysaltationtobedescribed (chapter2).
Giventhelimitedavailabilityofmulchmaterialfor soilprotection,itisessentialto managecrop
residuesefficiently. Therefore,theeffect oftwolowapplications ofmilletresidue onstormbased
sedimenttransportwasquantified. Inchapter 6,theoptimumquantity ofmilletresiduesfor wind
erosioncontrolinthe Sahelisdetermined.
Tocomplementtheexperiments,anon-farm surveywasconductedinsevenvillagesinsouthern
Niger. Intotal, 138farmerswereinterviewed to ascertaintheirknowledge ofwind erosionand
depositionprocesses,thedamagecausedbyblowingsand,andtheirtraditionaltechniquesfor wind
erosion control (chapter7).
Introduction
The soil and nutrient losses calculated in this thesis are from one field only. To quantify the
impactofwinderosiononfarming systemsataregionalscale,different measurementand computation
techniques need to beintegrated inthe same area. In chapter 8, a method is proposed to calculate
a regionalmassbudget ofwind-blown material. Themethod combines a wind erosion model with
a geographical information system. Input datafor themodel areobtained from remote sensing and
ground based experiments in key areas selected for their typical surface characteristics. Chapter
9, finally, summarizes the main conclusions ofthis thesis.
REFERENCES
Bagnold, RA. 1973.Thephysicsofblownsand anddesertdunes.5thed.,ChapmanandHall,London.
BenSalem,B. 1991. Prevention andcontrolofwinderosioninaridregions.Unasylva 164:33-39.
Broekhuyse,J.T.,andA.M.Allen. 1988.Farmingsystemsresearch. HumanOrganiz.47:330-342.
Drees,L.R.,A.Manu,andL.P.Wilding.1993.CharacteristicsofaeoliandustsinNiger,WestAfrica. Geoderma
59:213-233.
Dregne,H.E. 1990.ErosionandsoilproductivityinAfrica. J. SoilWaterConserv.45:431-436.
Dregne,H.E.,M.Kassas, andB. Rosanov. 1991.Anewassessmentoftheworldstatusof desertification.
Desertification ControlBull.20:6-18.
FAO. 1984.AgroclimatologicaldataforAfrica,Vol. 1. Countriesnorthoftheequator. FAOPlantProduction
andProtection Series,no.22.FAO,Rome,Italy.
Fryrear,D.W.,andL.Lyles.1977.Winderosionresearchaccomplishmentsandneeds.Trans.ASAE20:916-918.
Fryrear, D.W., andE.L.Skidmore. 1985. Methodsfor controllingwinderosion,p.443-457.In R.F.Follet
andB.A. Stewart(ed.)Soilerosionandcropproductivity.ASA-CSSA-SSSA, Madison,WI.
Fryrear,D.W.,J.E.Stout,L.J.Hagen,andE.D.Vories. 1991.Winderosion:Fieldmeasurementandanalysis.
Trans.ASAE34: 155-160.
Herrmann,L,K.Stahr,andM.V.K.Sivakumar. 1996. DustdepositiononsoilsofsouthwestNiger,p.35-47.
In B. Buerkert et al. (ed.)WinderosioninWestAfrica: Theproblemanditscontrol. Proc.Int.Symp.,
Stuttgart, Germany. 5-7 Dec. 1994.MargrafVerlag,Weikersheim, Germany.
Hillel,D.J. 1991.Outoftheearth:Civilization andthelife ofthesoil.TheFreePress,NewYork.
Lai,R. 1988. Soildegradation andthefuture of agriculture insub-SaharanAfrica. J. SoilWater Conserv.
43:444-451.
Lamers,J.P.A.,andPR. Feil. 1993.Themanyusesofmilletresidues.ILEIANewsletter 9:15.
LeHouerou,H.N.,andG.F.Popov. 1981.Aneco-climaticclassification ofintertropicalAfrica. FAOPlant
Production andProtection Paper,no.31. FAO,Rome,Italy.
10
Chapter 1
Manu,A.,A.Bationo,andS.C.Geiger. 1991.FertilitystatusofselectedmilletproducingsoilsofWest Africa.
SoilSei. 152:315-320.
Michels,K.1994.WinderosioninthesouthernSahelianzone:Extent,control,andeffects onmilletproduction.
VerlagUlrichE.Grauer, Stuttgart, Germany.
Michels,K.,M.V.K.Sivakumar,andB.E.Allison. 1995a.Winderosioncontrolusingcropresidue I. Effects
onsoilflux andsoilproperties.Field CropsRes.40: 101-110.
Michels,K.,M.V.K.Sivakumar,andB.E.Allison. 1995b.WinderosioncontrolusingcropresidueII. Effects
onmilletestablishment andyields.FieldCrops Res.40: 111-118.
Payne,W.A.,C.W.Wendt,andRJ.Lascano.1990.Rootzonewaterbalancesofthreelow-inputmillet fields
inNiger,WestAfrica. Agron.J. 82:813-819.
Sivakumar,M.V.K.1989.Agroclimaticaspectsofrainfed agricultureinthe Sudano-Sahelian zone.p. 17-38.
In Soil,crop,andwatermanagementintheSudano-Sahelian zone.Proc.Int.Worksh.,Niamey,Niger.
11-16Jan. 1987.ICRISAT,Patancheru,India.
Spencer,D.S.C.,andM.V.K.Sivakumar. 1987.PearlmilletinAfrican agriculture,p. 19-31.In Proceedings
oftheinternationalpearlmilletworkshop.Patancheru, India. 7-11April 1986.ICRISAT, Patancheru,
India.
Taylor-Powell,E.1991.Integratedmanagementofagriculturalwatersheds:Landtenureandindigenousknowledge
ofsoilandcropmanagement. TropSoilsBulletin91-04.TexasA&MUniv.,College Station,TX.
Tibke,G. 1988.Basicprinciples ofwinderosioncontrol.Agric.Ecosyst. Environ. 22/23: 103-122.
Valentin,C. 1995.Sealing,crusting andhardsettingsoilsinSahelianagriculture,p.53-76.In H.B.Soetal.
(ed.)Sealing,crustingandhardsettingsoils:Productivityandconservation.Aust.Soc.ofSoilSei.,Brisbane,
Australia.
Chapter2
TheEffect ofTurbulent FlowStructures onSaltation Sand Transport
intheAtmospheric Boundary Layer
G. Sterk,A.F.G.Jacobsand J.H.vanBoxel
Submitted to:Earth Surface Processes and Landforms.
13
The Effect ofTurbulent FlowStructures onSaltation Sand Transport
intheAtmospheric Boundary Layer
ABSTRACT
Theeffect ofturbulentflowstructures onsaltationsandtransportwasstudiedduringtwoconvective
stormsinNiger,WestAfrica. Continuous,synchronousmeasurements ofsaltation fluxes and turbulent
velocityfluctuations weremade with a sampling frequency of 1Hz.Theshear stress production was
determined from theverticalandstreamwisevelocity fluctuations. The greatest stress bearing events
wereclassified asturbulentstructures,withsweep,ejection,inwardinteraction,and outward interaction
described accordingtothequadranttechnique.Theclassified turbulent structures accountedfor63.5%
oftheaverageshearstressduringthefirst storm,and56.0%duringthesecond storm.The percentage
ofactivetimewasonly20.6%and15.8%,respectively.Highsaltationfluxeswereassociatedwithsweeps
andoutwardinteractions.Thesetwostructurescontributepositively(sweeps)andnegatively (outward
interactions)totheshearstress,buthaveincommonthatthe streamwisevelocity component is higher
thanaverage.Therefore,thehorizontaldragforceisprimarilyresponsiblefor saltationsand transport,
andnottheshearstress.This was also reflected bythelowcorrelation coefficients (r)between shear
stress and saltation flux (0.12 and 0.14,respectively),whilethe correlation coefficients between the
streamwisevelocity component and saltation flux weremuch higher (0.65and 0.57,respectively).
A
turbulent fluid flow over a solid surface impartsinstantaneous and localized levels of shear
stressto thefluid-solid interface which arewellabovetheaverage flow shear stress (Nearing
and Parker, 1994).For example, Lapointe (1992) found that 80% ofthe total shear stress exerted
bywater intheFraserRiver (British Colombia, Canada) could be attributed to isolated events of
3 to 8 s duration,which occupied only 12% ofthetime. The short eventswere identified as ejection
and inrush structures of the turbulent bursting mechanism.
These turbulent structures can be defined byusing horizontal and vertical turbulent velocity
fluctuations. The instantaneous streamwise velocity u can be partitioned into a time average u
and aturbulent fluctuating partu', superposed ontheaverage. The samecanbedone for the vertical
velocity component v. An ejection isanupward movement oflow-velocityfluid from nearthe solid
surface (u' <0,v' >0),whileadownward movement ofhigh-velocityfluidtowards the solid surface
(u' >0,v' < 0)iscalledinrushor sweep (Dyer, 1986).Both eventsresult inadownward momentum
transport and, hence, a positive contribution to the turbulent shear stress or Reynolds stress. In
14
Chapter2
addition,twoweakermotions,inward and outward interactions, exist. Anoutward interactionis
anupwardmovementofhigh-velocityfluid(u'>0,v' >0),andaninwardinteractionisadownward
movementoflow-velocityfluid(u'<0,v'<0).Botheventsresultinanupwardmomentumtransport
andcontributenegativelytotheshearstress.Forrealisticflows,apositiveshear stress exists. So,
.onaveragetheabsolutemagnitudeofthenegativecontributionshavetobelowerthanthepositive
contributions givenbyejections and sweeps.
Ejectionandsweepshaveoftenbeenassociatedwithdetachmentandtransportationofsediment.
Sweepsareusually associated withtheinitiation andmovement ofbed-load transport (saltation
+ creep), whereasejections aresupposed tobemore effective inliftingfinesuspended material
awayfrom the surface (Dyer, 1986).Thepresent knowledge ofthelinksbetweenthe turbulent
burstingmechanismandsedimenttransport dynamicswasmainlyobtained from investigationsin
waterflow,usuallyunderlaboratoryconditions(e.g.,Sutherland, 1967;Mülleret al., 1971;Sumer
andOguz, 1978;SumerandDeigaard, 1981; Grass, 1983),butalsoingeophysicalboundary layers
(e.g.,Heathershaw and Thorne, 1985;Thome et al., 1989;Lapointe, 1992).These geophysical
studieshaveconfirmedtherelationbetween(i)ejectionsandsuspensiontransport(Lapointe, 1992),
and(ii)sweepsandbed-loadtransport (Heathershaw andThorne, 1985;Thorne etal., 1989).In
addition,thelattertwostudiesrevealedthatoutwardinteractions,althoughweakerandless frequent
thansweeps,werecapableofsupportingbed-load movement aswell.Heathershaw and Thorne
(1985) hypothesized that shear stress is a necessary but not sufficient condition for bed-load
transport,andthatformdragonindividualparticlesmayhavegreater dynamical significance than
the shearstress.
Althoughmuchofrelevanceto sedimenttransport inturbulent airflows canbegleaned from
thestudiesinaqueousenvironments,bycomparisontheroleofturbulence inwind-blown particle
transport hasreceived verylittle attention (Butterfield, 1993).From afew wind tunnel studies,
theimportanceofturbulencefor entrainmentofparticleshasbeeninferred (e.g.,BisalandNielsen,
1962;LylesandKrauss, 1971;Braaten etal., 1990), andthreewindtunnel studies (Butterfield,
1991and 1993;Hardisty, 1993)providedataofinstantaneouswindspeed and sediment transport.
Reports offieldexperiments are even more scarce. Only two studies were found (Lee, 1987;
Butterfield, 1991). However, these wind tunnel andfieldstudies did not identify the different
turbulent structurestorevealtheir significance for wind-blown sediment transport.
TheEffect ofTurbulenceonSaltationTransport
Abetterunderstandingofthewinderosionprocess,forinstanceformodelingpurposes,requires
detailedmeasurements ofparticletransport inrelationtotheturbulent windflow. According to
Butterfield (1993),itisessentialthatbothmassflux andwindvelocityhistoriesare characterized
tofrequencies ofatleast 1 Hzifrealistic and environmentally useful sedimenttransport relations
aretobederived.Inthisstudy,dataofsynchronousmeasurementsofturbulentvelocitycomponents
andsaltation sandtransport duringconvective stormsintheWest African Sahelwere collected.
Onlysaltationtransport wasmeasured, becauseitisgenerallymore easilyquantified than creep
and suspension transport. Furthermore, saltationisconsidered to initiatetransport bythe other
twomodes(Shaoetal., 1993).So,understanding the saltationprocessgivesalsoinsight increep
andsuspensiontransport.Theobjectivesofthestudywere(i)todeterminethemagnitudeandduration
ofpeakReynoldsstresses,and(ii)toinvestigatethesaltationresponsetovelocity and shear stress
fluctuations created byturbulent structures.
MATERIALS AND METHODS
Study Site
AfieldexperimentwasconductedattheInternationalCropsResearchInstitutefortheSemi-Arid
Tropics(ICRISAT) SahelianCenterinsouthwestNiger(13°16'N;202rE),duringtherainy seasons
of 1994and 1995. Theclimate oftheregionistypical Sahelian,with oneshort (4months)rainy
seasonandhightemperaturesallyearround.Intheearlyrainyseason(May-July),largecumulonimbus
clouds develop throughout the Sahel and bring thefirstrains of the new rainy season. Often,
cumulonimbuscloudsareaccompanied byshort (10-30 min)wind stormsthat precede rainfall.
Thestormsaretheresult of strong downdrafts withinthe cloud that causeaforward outflow of
coldair.Theviolentwindsmaycreate aspectacular rolling dust cloud that movesinfront ofthe
cumulonimbuscloud.Ingeneral,thecumulonimbuscloudsmovefromeasttowestandtheresulting
wind direction during stormsisusuallyeast.
Thefieldusedfortheexperimentwas90by90minsize.Itwasbordered bydirt roads atthe
northernandeasternsides,byafieldprotected againstwinderosionwithcropresiduesinthesouth,
andbyawindbreakatthewestern side.Theequipmentwaspositioned suchthat distances from
instrumentstothefieldboundariesexceeded 50minthenorthern and eastern directions, andwas
about40minthesouthernandwestern directions. Thewholefieldwasplanted withpearlmillet
(Pennisetumglaucuni)on 17June 1994and 21June 1995. Sowingwasdoneaccording to the
15
16
Chapter2
traditionalSahelianmethod,withsowingholes,orpockets, atwide spacings of 1 by 1 m.Ineach
holeapproximately50to 100seedswerethrown.Threeweeksafter sowing,thenumber ofplants
ineachpocketwasmanuallyreduced tothree.
Thesoilatthemeasurementfieldisasandyalfisolwith92.2%sand, 3.0% silt, and4.8%clay
inthetopsoil.Theaggregatesizedistribution,determined bydrysievingofsoilsamples, isshown
inTable 1.Thesesandysoilsareverypronetocrustformationbyhigh-intensityrainfall intheearly
rainy season. Strong structural crusts areformed that havetypicallytwolayers. At some depth
(5-10 mm),athinand denseplasmiclayerexists,which consists offineparticles (clay, silt,and
fine sand)thatwerewashed out from thetop layer. Thetop layer consistsofloose, cohesionless
sand,whichiseasilyerodedbywindorwater. Suchacrust existed allthetimeinthefieldduring
theexperiments.Itwasbrokenbyweedingonlytwotimesper season, butreturned immediately
duringthenextrain.
Thesoilsurfacewassmoothandwithoutanyroughnessotherthanthatcreatedbythesoilparticles
themselves,characterizedbyaroughnesslengthofapproximately 0.001 m.Just after weeding the
roughnesslengthincreasedtoapproximately0.01m,butinbothseasons,nowind storms occurred
duringtheseperiods.Theroughnesscreatedbyyoungmilletplantswasnegligibleduringthe first
fourweeksaftersowing.Thelimitedsizeoftheplants(<0.10m)andthelowplantingdensityassured
thatsaltationtransportwasnotsignificantlyinfluencedbythecrop.Inthesurroundingsofthe field,
obstacles such astrees andbusheswerepresent. During storms,theupwind distancesfrom the
measurement locationtothe obstacles exceeded inallcases20timestheheight ofthe obstacle.
It was therefore assumed that thewindfieldatthe measurement locationwas not significantly
Table1.AggregatesizedistributionoftopsoilatICRISAT
SahelianCenter.
Sizeclass
Hm
Mass
%
<63
3.1
63-125
18.2
125-250
35.7
250- 500
32.8
500-1000
10.0
> 1000
0.2
TheEffect ofTurbulenceonSaltationTransport
17
disturbed bythose obstacles. Saltating sand enteringthefieldwasnot observed, but suspended
dustfrom other areaswas clearlymovingintothefield duringperiods ofstrong storms.
Measurements
WindspeedwasrecordedwithaGillUVWpropeller anemometer (R.M.Young Co.,model
27005),whichmeasuresthreeorthogonalcomponentsofthewindvector. It consistsofpropellers
withadiameterof0.22 m,attached totheanemometer byshaft extensionswithalength of 0.45
m.Theanemometerwasinstalled at 3mabovethe soilsurface, whichmeansthatthehorizontal
componentsUandWweremeasuredat2.95and3.05m,respectively,andthevertical component
Vat3.45m.Usewasmadeofexpanded polystyrenepropellers,whichhaveadistance constant
of1.0m.Thepropellerresponds onlytothat component ofthewindwhich isparalleltoitsaxis
ofrotation,andoffaxisresponsecloselyapproximatesacosinecurve.Thepropellerdoesnotrotate
whenwindflowisperpendiculartoitsaxis.Therangeofwindspeedsthatcanbemeasured is from
0.3to25.0ms"1. TheanalogDCvoltage signalsofthethree sensorswere sampledwith aCR10
datalogger(CampbellScientificLtd.).Sincetheanemometerwasnew, itwasnotcalibrated prior
tofieldinstallation.Therecorded signalswereconverted towind speedsbyusingthe calibration
constant givenbythe manufacturer.
side-view
a = vanes
d = ball bearing
Figure1. Thesaltiphone.
b = microphone
e = connection cable
c = tube
]8
Chapter2
Saltationtransport wasmeasured withthree saltiphones. Thesaltiphoneisarobust saltation
sensorthatrecordsparticleimpactswithamicrophone. Adetailed description ofthe devicewas
givenbySpaanandVandenAbeele(1991).Itconsists(Fig. 1)ofamicrophonewithamembrane
of201mm2,placed insideastainless steeltube(diameter =0.05 m,length=0.13 m).Thetube
ismounted onaballbearingandiscontinuouslypositionedintothewindbytwovanes attheback.
Someofthesoilparticlesmovingthroughthetubehitthemembrane ofthemicrophone. The
frequency ofthecreatedsignalsdependsonthemomentumoftheimpactingparticles.High frequency
signals are formed by high momentum particles, like saltating sand grains. Byamplifying high
frequencies andfilteringlowfrequencies,thesignalscreatedbysaltating sand canbe distinguished
from othernoises,createdforinstancebywindorsuspendeddust.Theamplified signalofaparticle
impactproducesapulsethatiscutoffafter 1 ms.Eachtimeapulseisgenerated, noother particle
impact canbe detected. So,theoretically, the maximumnumber ofparticleimpacts that canbe
detectedis 1000persecond.Theactualnumberofparticleimpacts canbehigherthanthenumber
of counted pulses, dueto overlap ofparticleimpacts duringthe samepulse. Theoutput ofthe
saltiphone (S)incountsperunit oftime, therefore, isarelativemeasureofthe saltationfluxat
theheightofthemicrophone.Windtunneltestswiththesaltiphone(Sterk, 1993)showed thatthe
pulsecountrateislinearlyrelatedtothemeasuredmassfluxatthesameheight (Fig.2).However,
therangeofmassfluxesduringthoseexperimentswassomewhatnarrow,anditisuncertainwhether
therelationship is stillvalidfor higher andlower fluxes.
Threesaltiphoneswereinstalledinthefield.Allthreesensorswerepositioned around theUVW
anemometer, at 2.0mfrom themastinnorthern, easternand southerndirections. Theheight of
thecenterofthemicrophonesabovethesoilsurfacewas0.10m. Thesaltiphoneswere connected
toapulsecountexpansion(SDM-SW8A)ontheCR10datalogger.Themaximuminput frequency
oftheSDM-SW8Apulsechannelsis 100Hz,whichisnot sufficient for the saltiphone. Inorder
toreducethenumberofincomingpulses,aself-constructed pulsedividerwasplaced between the
saltiphoneandthedatalogger. Ofeverytenincomingpulses,ninewerefilteredand onlyonewas
senttothedatalogger.Intheoutput,thenumberofpulseswasmultipliedagainbyten.Furthermore,
anautomatic raingauge(tipping-bucket) wasinstalled to determinetheexact moment ofonset
ofrainfall.Allsensors,UVWanemometer,saltiphones,andraingauge,weresampledwitha frequency
oflHz.
TheEffect ofTurbulenceonSaltationTransport
19
0.30
0.25
X
3
V)
</>
(0
0.20
0.15
150
200
225
250
300
1
Saltation flux (cts s )
Figure2.Relationshipbetweensaltationflux,measuredwithasaltiphone,andmassflux,measuredwitha
sedimenttrapinawindtunnel.
Analytical Procedure
Fromthethreemeasuredwindcomponents,theinstantaneouswindvector Fand its direction
wwerecalculated,withwbeingtheangleofFrelativetothenorth. ThemeanwindvectorFand
itsdirectionwwerecalculatedforthestorm duration, orfor periods of 10min,incaseof storms
with along duration. Anew orthogonal coordinate systemwaschosenwiththepositivex-axis
parallel to the surface inthe directiona> ofthe mean flow F, the positive y-axis normal to the
surfaceinupwarddirection,andthepositivez-axisparalleltothesurfacetotherightofthepositive
x-axis.TheinstantaneousvelocitycomponentsU,V,andWwereconvertedtothenewcomponents
u,v,andw,withubeingtheinstantaneous velocity parallelwithx,vtheinstantaneous velocity
parallelwithy, andwtheinstantaneousvelocityparallelwithz.
Theinstantaneousvelocity componentswere decomposed intoanaverageand a fluctuating,
turbulentpart:u=u+u';v=v+v';w=w+w'. Bydefinition,w iszero,whereasvwillbeclose
to,butnotnecessarilyequaltozero.Withinaconvective storm moving ahead ofacumulonimbus
cloud,strongupdrafts existthatlocallyresultinapositivevcomponent.Thisisequivalenttosaying
Chapter2
20
that thevertical component oftheturbulence exerts anetupward fluid force, which appearsto
explainwhydensemineralparticles canbetransported insuspensionbyaturbulentwind (Allen,
1994).Thetime-averagedvelocityfluctuationsü7,v7,andw7arezerobydefinition.Thetime-averages
ofthesquaresandmixedproducts,however,arenon-zero, and createtheReynolds stresses. The
averagestresscomponent x =-pu'v' (Nm"2)givesthe streamwise shear stressinahorizontal
plane, and isusually considered tobedirectlyrelatedto sedimenttransport dynamics.Dividing
theshearstressbythefluiddensity(p)givestheaveragekinematic stress -u'v' (m2s"2),whilethe
correspondinginstantaneousvaluesofkinematicstressarerepresentedby-u'v'. Inthenextsections
ofthispaper,emphasiswillbeontheinstantaneousandaveragevaluesofthestreamwisekinematic
stress.
Forthedetectionofturbulentflowstructures,usewasmadeofthequadranttechnique(Wallace
etal., 1972).InanEuleriansystem,thefourdiscretecategoriesofmomentumexchange, ejection,
sweep,inwardinteraction,andoutwardinteraction,weredefined onthebasisoftherelative signs
ofu' andv' (Fig.3).Inorderto avoidtheproblem ofassigningadiscrete structure to individual
lowmagnitudestresscontributionspurelyonthebasisofthevaluesofu' andv',athresholdcriterion
wasdefined. Onlythoseeventsthatexceededtheaveragekinematicstressbyatleast one standard
v' > 0
1
II
outward
interaction
ejection
u' > 0
u' < 0
inward
interaction
sweep
IV
III
v' <0
Figure3.Quadrantplotoffour discretemomentumexchangestructures,basedontheturbulentvelocity
fluctuations inhorizontal(u')andvertical(v')directions.
TheEffect ofTurbulenceonSaltationTransport
21
deviation(a)wereidentifiedasstructures.Thus,instantaneouscontributionstotheaveragekinematic
stressintheinterval [-u v -a, - u ' v ' +o]werenot assigned byamomentumexchange category
from Fig.3.
RESULTSAND DISCUSSION
Atotalof20 stormswasrecorded duringthe 1994and 1995rainy seasons. Ofthe collected
data,onlythoseperiodswithmoreorlesscontinuoussaltationtransport andwithout rainfall were
usedfortheanalysis.Twotypicalstormson27June 1994(storm 1)and25 June 1995(storm2),
bothwithadurationofabout 10minandnearlysimilaraveragewindspeeds(Table2),wereselected.
Duringboth stormsthewind directionwaseast, hence,thedatafrom the saltiphoneeast ofthe
UVW anemometer wasused for theanalysis.
InFig.4,plotsofrecordedwindspeedandsaltationresponsearegivenforthetwostormevents.
Individualfluctuations inwind speed displayarangeofperiods, orfrequencies intheturbulence
spectrum.Lowfrequency oscillationswithaperiodicity ofseveralminutes areevident aswellas
shortgustswithadurationof1 to5s.Thesizeofthesmallestquasi-horizontal structures or eddies
thatcanbedetected fromthedataisdetermined bytheused samplingfrequency (1Hz) andthe
averagewindspeed.Thewavelengthofthesmallest detectable structures isequaltothe product
Table2.Descriptivestatisticst ofwindparametersandsaltationtransportduringtwostormsatICRISAT
SahelianCenter.
25 June 1995
27 June 1994
F
ms'1
u'
m s"1
0
v'
ms'1
-u'v'
S
u'
F
1
m2 s'2
cts s"1
m s"
0
0.41
97.7
9.49
v'
1
m s"
m s'
0
0
1
-u'v'
S
2
2
cts s"1
0.36
42.4
m s"
Mean
9.67
Median
9.45
-0.22
0.02
0.09
40.0
9.41
-0.11
-0.03
0.11
10.0
Stand, dev.
2.31
2.33
0.62
1.49
119.4
2.15
2.15
0.57
1.23
66.5
Skewness
0.44
0.48
0.08
0.94
1.34
0.23
0.22
-0.08
2.17
2.53
Kurtosis
-0.31
-0.28
1.53
5.63
1.11
-0.57
-0.59
2.85
17.49
7.91
Range
12.63
12.65
5.37
15.44
520.0
10.94
10.75
5.59
18.39
480.0
-5.35
-3.03
-6.82
0
5.39
2.56
11.57
480.0
Min
4.59
-4.98
-2.71
-7.83
0
4.06
Max
17.22
7.68
2.66
7.62
520.0
15.00
t Fismewmdspeed;u'andv'aremehorizc)ntdandverticalturbulentvelœityflucttations;-u'v'^
stress;S isthesaltation flux.
Chapter2
22
2000
T
r
4
5
6
Time (min)
7
8
9
10
2000
Time (min)
Figure4.Recordsofwindspeed(F)andsaltationflux(S)fortwoSahelianwinderosioneventsatICRISAT
SahelianCenteron(A)27June 1994and(B)25June 1995.
TheEffect ofTurbulenceonSaltationTransport
oftheaveragewindspeedandthesamplingperiod.Forbothstorms,theminimumsizeisapproximately
9.5m.Hence,itisassumedthatthe smallest quasi-horizontal eddiesdetected at 3mheightwere
largeenoughtocauseatthesametimestronghorizontalvelocityfluctuationsnearthe soil surface.
Adetailed analysisoftheturbulent structures,i.e. aspectral analysisoftheturbulent frequency
spectrum,willbedescribedinaseparatepaper.Here,emphasisisonthesaltationresponsetowind
speed and shear stress fluctuations.
ThetwoplotsinFig.4clearlyshowthatthesaltationfluxwasintermittentinnature,withsporadic
burstsofintensesaltationtransportimmediatelyfollowed byperiodswithout transport. The flow
conditionsduringbothstormswereonlyslightlyabovethreshold,andasaresultsaltationtransport
occurredonlyduringgustsofvarying durations.Thesaltation systemresponded quicklytowind
speedfluctuations,andingeneral,agoodrelationshipbetweeninstantaneouswindspeedandsaltation
flux exists. Correlation coefficients (r)for thetwo storms are0.65 and 0.57, respectively. The
correlation is slightlybetterwhenthe saltiphonerecordings areassumed to lag 1sbehindwind
speed (0.71 and 0.65). Withan assumed lag of2sther-valuesare0.64 and0.60, respectively,
and decrease rapidlywithincreasing lag. Thebetter correlation at alagof 1sindicatesthat the
responsetimeofthe saltation systemisintheorder of 1 sdueto inertia effects. Thisresult isin
accordancewiththeresponsetimeasitwascalculated from numerical simulationsbyAnderson
andHaff (1988), andwas confirmed byexperiments ofButterfield (1991).
Fromthedata,thethresholdwindspeedconditionsforinitiationandcessationofsaltationtransport
couldbedetermined. Thethreshold wind speed atinitiation ofsaltationwas defined byBagnold
(1973)asthefluidthreshold,i.e.thethresholdatwhichsandmovement startsowingtothe direct
force ofthefluidonly.Thethresholdwind speed atwhich saltation ceasesissimilartoBagnold's
impactthreshold, whichwas defined asthethreshold wind speed atwhichaninitial disturbance
ofthesandbecomesacontinuousmovementdownwind.Inotherwords,thewindaloneisinsufficient
for continuous saltationtransport, but saltationissustained bythecombined action ofthewind
force andtheimpacts ofdescendinggrains.
Duringboth storms, periods ofcontinuous saltationtransport alternated with periods ofno
transport (Fig.4).Byselecting eachisolated period ofcontinuous saltation,thewind velocities
atinitiationandcessationofsaltationtransport weredetermined. Onaverage, saltation started at
8.48ms"1(fluidthreshold)andceasedat7.66ms"1(impactthreshold)duringthefirststorm.During
thesecondstorm,the averagefluidthreshold was9.60ms"1 andtheimpactthreshold was equal
23
24
Chapter2
to 8.45ms'1.Thehigherthresholdconditionsduringthesecondstormcanbeexplained bywetting
of the topsoil due to alight rain (2.0 mm) some 36h earlier. Soil moisture causes water films
surrounding the soilparticles that createcohesive forces betweentheparticles. Thewind force
requiredtoliftparticlesfromamoistsurfaceisthereforehigherthanduringdryconditions (Chepil,
1956).Thisalsoexplainsthelower averagesaltationflux duringthe second storm(Table2).
Theinstantaneouscontributionstotheaveragekinematic stressfor both storms areshownin
Fig.5.Theaveragestressistheresult ofshortbutintensepositive contributions, superposed on
negativeandweakerpositivecontributions.Theinstantaneousstresslevelscouldbe 10to 20times
strongerthantheaveragestresslevel,buttheyoccurred onlyduring averylimited period oftime.
Thisintermittencyinstressproduction occurs despitethe fact thatu' andv' are approximately
Gaussiandistributed(Table2)andrandomlyfluctuating quantitieswhentakenseparately.Thesmall
deviationsfromthenormal distribution causeanon-normal distribution ofthekinematic stress,
whichistypicalforturbulence (Panofsky andDutton, 1984). Thekinematic stressdistributionis
characterizedbyapositiveskew(Table2),indicating arelatively frequent occurrence ofextreme
values.
Thekinematicstresseventsthatexceededtheaveragevaluebyatleast one standard deviation
wereclassifiedasturbulentflowstructuresaccordingtoFig.3.Somecharacteristicsofthestructures
aregiveninTable3.Ofthe averagestressat sensorlevel,theclassified structures accounted for
63.5%duringthefirststorm,and56.0%duringthe second storm. Thepercentage oftime during
whichthe structureswereactivewasonly20.6%for thefirst,and 15.8%for the second storm.
Sweepsandejections were25%morefrequentthantheinward and outward interactions.Also,
thepositive contributionstothe shear stressbysweepsand ejections were about 70%stronger
thanthenegative stress contributions, resultinginanoverallpositive shearstress.
Awelldefined relationshipbetweentheinstantaneouskinematic shear stressand saltation flux
doesnot exist. Thecorrelation coefficients for both storms are0.12 and0.14, respectively, and
whenthesaltationfluxisassumedtolag 1 sbehindkinematic stress,thecoefficients are0.05 and
0.15, respectively. Also,no correlation between kinematic shear stress and saltationflux exists
when onlythetimeperiodswith classified turbulent structures areconsidered. However, mean
saltationfluxesforthefourclassified structures(Table3)revealthatsweeps(class4) and outward
interactions(class 1)wereassociatedwithhighsaltationfluxes,whereastheir stress contributions
werepositiveandnegative,respectively.Ejections(class2)andinward interactions (class3)were
TheEffect ofTurbulenceonSaltationTransport
25
IA
IA
«0
O
CS
E
O)
C
10
IA
1200
IA
IA
X
3
£
i ^
«J
IA
O
'•C
CS
C
O
*-»
CO
800
*•»
E
(S
Q>
C
CO
2
Time (min)
Figure5.Plotsofinstantaneouskinematicstress(-uV ) andsaltationflux (S)fortwoSahelianwinderosion
eventsatICRISATSahelianCenteron(A)27June 1994and(B)25June 1995.
Chapter2
26
>—i
fi
•—'
en
(N
>-<
VÇ
yj,
TheEffect ofTurbulenceonSaltationTransport
27
notcapableofsupportingappreciablesaltationtransport. Obviously, instantaneous contributions
tothe shear stresswere oflittle significance interms ofsaltation transport.
Sweepsandoutwardinteractionshaveincommonthatu' ispositive(Fig. 3),meaningthatthe
instantaneoushorizontalwindspeedishigherthanaverage.Ejections andinward interactionshave
negativeu' values,orlowerthanaveragehorizontalwindspeeds.Correlation coefficients between
u' andsaltationfluxareexactlythesameastheearliergivencorrelation coefficients betweenwind
speed(F)andsaltationflux(0.65and0.57),whereasthecorrelationbetweenv' and saltation flux
isweak(-0.18and-0.22).ThisisalsoillustratedinFig.6,whereu',v', andthesaltationfluxduring
thefirst3minofthesecondstormaregiven.Theclosecorrespondencebetweenu' andthesaltation
flux isclear.Thevalueofv' tendedtobenegativeduringperiodswithsaltationtransport,butmany
exceptionscanbefound aswell.Theseresultssuggestthatthehorizontalvelocityfluctuations are
ofmuchmoreimportancefor saltationtransportthantheverticalvelocity fluctuations.
Intheforegoing analysis,instantaneous saltationfluxwasrelated to shear stress fluctuations
measured at 3m, assuming similar shear stressfluctuations being activenearthe soilsurface at
thesametime.Itisdoubtful whetherthisassumptioniscorrect. Asimilar assumptionwasmade
2000
1600
in
1200
(A
x
3
C
O
Ü
">
800i
3
m
400
Time (min)
Figure6.Saltationflux(S)inrelationtothehorizontal(u')andvertical(v')turbulentvelocityfluctuations
duringthefirst3 minofastormeventatICRISATSahelianCenteronJune25,1995.
28
Chapter2
fortheinstantaneouswindspeed,andtheminimumsize(9.5m)ofdetectablequasi-horizontaleddies
indicatesthatthisassumptionwascorrect. Hence,positiveu' valuesat3mwere associatedwith
positivevaluesnearthe soilsurface. Apositivev' at3mdoesnotnecessarilymeanthatv' near
thesoilsurfacewaspositiveaswell.Theverticalvelocityfluctuations areproducedbysmalleddies,
thediameterofwhichareoftheorderoftheheightabovetheground (PanofskyandDutton, 1984).
So,theobservationofadownwardmovingeddyat3mdoesnotnecessarilymeanthat atthe same
timethe shear stress createdbytheeddywasfelt atthe soilsurface. Furthermore, suchaneddy
was moved horizontally withthe averagewind speed,whichwas anorder ofmagnitude higher
thantheverticalwind speeds(Table2),resultinginshear stressatthe soilsurface downwind of
theanemometer. Thisuncertaintymayhaveobscuredthe shear stress-saltationfluxrelationship.
For instance, thedatapresented heredonot showanexclusiveroleofsweepsfortheinitiation
ofsaltationmovement,assuggestedbyGrass(1983).Moredetailedmeasurementsofinstantaneous
shear stressnearthe soilsurface would possiblyrevealthat sweeps aretheprincipal structures
associatedwithinitiation ofsaltation transport.
Despitetheuncertaintyinthe shear stress -saltationfluxrelationship, itisconcluded that for
saltationtransportthehorizontalwindspeedcomponentisofmuchmoresignificancethanthevertical
component.Turbulentstructureswithapositiveu' component, sweepsand outward interactions,
areabletoinitiateandsustainsaltationtransport,whereasstructureswithanegativeu' component
donot.Apparently,itisnotthestreamwiseshear stress component butthehorizontal drag force,
whichisproportionaltou2,isthedrivingforceforsaltationsandtransport.Thesamewasconcluded
forbed-loadtransportaboveaseabed(HeathershawandThorne, 1985;Thome etal., 1989).This
conclusion suggeststhat saltationtransport should notbepredicted onthebasisof shear stress
(orfriction velocity) alone,asmost ofthecurrenttransport equationsdo(Greeley and Iversen,
1985).Itwouldbemoreuseful ifhorizontalwindspeedanditsfluctuations,for instancedescribed
bytheaverageand standard deviation,wereincorporated insaltationtransport models.
CONCLUSIONS
Measuredfluxesofwind-blown saltationsandtransport duringtwo convective stormsinthe
SahelianzoneofNigershowedahighdegreeofintermittency.Fluctuations insaltationfluxwere
directlyrelatedtothegustinessofthewind.Thebestcorrelationbetweeninstantaneouswind speed
andsaltationfluxwasobtainedwhenthemeasured saltationfluxwasassumedto lag 1sbehind
TheEffectofTurbulenceonSaltationTransport
29
windspeed. Thisresult confirms thattheresponsetimeofthe saltation systemisinthe order of
1 s, asitwascalculated byAndersonandHaff (1988).
Duringthetwo storms, classified turbulent structures accounted inisolationfor 60%ofthe
averageshearstressatsensorlevel,buttheactivetimewasonly18%.Ofthefourturbulentstructures
thatweredistinguishedbythequadrant technique (Fig. 3),onlysweeps and outward interactions
wereableto initiateand sustainsaltationtransport. Sweepsresulted inpositivecontributions to
theaverageshearstress,whereasoutwardinteractionscontributed negativelytotheaverage shear
stress.Thetwostructureshaveincommonthatthehorizontalwind speed component washigher
thanaverage.Notthestreamwiseshearstress,therefore,butthehorizontaldragforcewasprimarily
responsiblefor saltationsandtransport.Thisresultindicatesthatsaltationtransport modelsshould
incorporate thehorizontal wind speed anditsfluctuations as drivingvariables, instead ofusing
the shear stress orfriction velocity alone,asmanyofthe current modelsdo.
ACKNOWLEDGMENTS
The research was funded bytheNetherlands Foundation for the Advancement of Tropical
Research (WOTRO). The logistic support of the ICRISAT Sahelian Center is gratefully
acknowledged.WethankGijsvandenAbeeleoftheWageningen Agricultural Universityfor his
helpwithconstruction andinstallation oftheelectronicfieldequipment.
REFERENCES
Allen,J.R.L. 1994.Fundamentalpropertiesoffluidsandtheirrelationtosedimenttransportprocesses,p.
25-60.InK.Pye(ed.)Sedimenttransportanddepositionalprocesses. BlackwellScientificPublications,
Oxford,UK.
Anderson,RS.,andP.K. Haff. 1988.Simulationofeoliansaltation.Science24: 820-823.
Bagnold,R.A. 1973.Thephysicsofblownsandanddesertdunes.5thed.,ChapmanandHall,London.
Bisal,F.,andK.F.Nielsen. 1962.Movementofsoilparticlesinsaltation.Can.J.SoilSei. 42: 81-86.
Braaten,D.A.,K.T.PawU,andRH.Shaw.1990.Particleresuspensioninaturbulentboundarylayer-observed
andmodeled.J.AerosolSei.21:613-628.
Butterfield,G.R.1991. Graintransportratesinsteadyandunsteadyturbulentairflows.ActaMech. [Suppl]
1:97-122.
Butterfield,G.R.1993. Sandtransportresponsetofluctuatingwindvelocity,p.303-335.InN.J.Clifford et
al. (ed.)Turbulence: Perspectivesonflowandsedimenttransport.JohnWiley& Sons,Chichester,UK.
30
Chapter 2
Chepil,W.S. 1956. Influenceofmoistureonerodibilityofsoilbywind.SoilSei.Soc.Am.Proc.20:288-292.
Dyer,K.R. 1986.Coastal andestuarinesedimentdynamics.JohnWiley&Sons,Chichester,UK.
Grass,A.J.1983. Theinfluenceofboundarylayerturbulenceonthemechanicsofsedimenttransport,p.3-18.
InB.M.SumerandA.Müller(ed.)Mechanicsofsedimenttransport.ProceedingsEuromech 156.Balkema,
Rotterdam,TheNetherlands.
Greeley,R, andJ.D.Iversen. 1985.WindasageologicalprocessonEarth,Mars,VenusandTitan. Cambridge
University Press,Cambridge,U.K.
Hardisty,J. 1993.Frequencyanalysisofsandtransportinaturbulent airflow.p.295-304.InN.J. Clifford
etal.(ed.)Turbulence:Perspectivesonflowandsedimenttransport.JohnWiley&Sons,Chichester,UK.
Heathershaw,A.D.andP.D.Thorne.1985.Sea-bednoisesrevealtheroleofturbulentburstingphenomenon
insedimenttransportbytidalcurrents.Nature 316:339-342.
Lapointe,M. 1992.Burst-likesedimentsuspensioneventsinasandbedriver.EarthSurf.Proc.and Landforms
17:253-270.
Lee,J.A. 1987.Afieldexperimentontheroleofsmallscalewindgustinessinaeoliansandtransport. Earth
Surf.Proc.andLandforms 12: 331-335.
Lyles,L.,andRK.Krauss. 1971.Thresholdvelocitiesandinitialparticlemotionasinfluencedbyairturbulence.
Trans.ASAE 14:563-566.
Müller,A.,A.Gyr,andT.Dracos. 1971. Interactions ofrotatingelementsoftheboundarylayerwithgrains
ofthebed:Acontributiontotheproblemofthethreshold ofsedimenttransportation. J.HydraulicRes.
9:373-411.
Nearing, M.A., and S.C.Parker. 1994. Detachment of soilby flowing waterunder turbulent and laminar
conditions. Soil Sei.Soc.Am.J.58: 1612-1614.
Panofsky, H.A., and J.A. Dutton. 1984. Atmospheric turbulence: Models and methods for engineering
applications. JohnWiley&Sons,NewYork.
Shao,Y.,M.R Raupach,andP.A.Findlater. 1993.Theeffect ofsaltationbombardmentontheentrainment
ofdustbywind.J. Geophys.Res.98: 12719-12726.
Spaan,W.P.,andG.D.vandenAbeele. 1991.Windborneparticlemeasurementswithacousticsensors. Soil
Technology4: 51-63.
Sterk,G. 1993. Sahelianwinderosionresearchproject, ReportIII.Description andcalibration ofsediment
samplers.Dep.ofIrrigationandSoil&WaterConservation,WageningenAgric.Univ.,TheNetherlands.
Sumer,B.M.,andR Deigaard. 1981.Particlemotionsnearthebottominturbulentflowinanopenchannel.
Part2.J.FluidMech. 109:311-337.
Sumer,B.M.,andB. Oguz. 1978.Particlemotionsnearthebottominturbulentflowinanopenchannel.J.
FluidMech. 86:109-127.
TheEffect ofTurbulenceonSaltationTransport
Sutherland,A.J. 1967.Proposedmechanism for sedimententrainmentbyturbulentflows. J. Geophys.Res.
72:6183-6194.
Thome,P.D.,J.J.Williams,andA.D.Heathershaw. 1989.Insituacousticmeasurements ofmarinegravel
threshold andtransport. Sedimentology 36:61-74.
Wallace,J.M.H.,H.Eckelmann,andR.S.Brodkey. 1972.Thewallregioninturbulent shearflow. J.Fluid
Mech.54:39-48.
31
Chapter 3
Comparison ofModelsDescribingtheVertical Distribution
ofWind-Eroded Sediment
G. Sterk andP.A.C. Raats
Published in: Soil Science Society ofAmericaJournal 60: 1914-1919.(1996).
Reproduced bypermission ofthe SoilScience Society ofAmerica.
35
Comparison ofModelsDescribingtheVertical Distribution
ofWind-Eroded Sediment
ABSTRACT
Forthestudy offieldwinderosion,detailed observations ofwind-blown sediment transport in the
field are needed.The objective ofthis study was to determinethebest method to quantify the mass
ofwind-blown material movingpast afixed point during four storms.Twenty-one Modified Wilson
and Cooke(MWAQsedimentcatcherswereinstalled in a pearl millet (Pennisetum glaucum) field in
theSahelianzoneofNiger,onasandy,siliceous,isohyperthermicPsammentic Paleustalf.Each catcher
trappedmaterialsatsevenheightsbetween0.05and 1.00m.Theverticalprofiles ofmeasured horizontal
mass fluxes were described by two different models,a three-parameter power function and a fiveparameter combinedmodel,whichisa combination ofan exponential function and a power function.
For allfour storms,both models described accurately themass fluxes between 0.05and 0.26m, but
fitted massfluxesat0.50,0.75,and 1.00mdeviated from measured fluxes.Deviationswere 21.1,45.2,
and60.6%forthepowerfunction, and 12.4,18.5,and38.0%for the combined model.Mass transport
rateswerecalculatedbyintegratingthemassflux profiles across height.Thedifferences in calculated
mass transport rates were small,but because ofthe better fit, the combined model was preferred.
Correctingforthetrappingefficiency oftheMWACcatchers(0.49)andmultiplyingbythestorm duration
resultedintotalmasstransportvalues,whichareequaltothemass ofsoilpassing a strip of1m width
perpendicular to the mean wind direction. The average mass transport values were 102.7, 15.5,
31.8,and 149.8kgm"1,respectively,for thefour storms.
W
ind erosionis a common phenomenon in arid and semi-arid areas, which are extensive
and comprise about one-third of the world's land area (Lai, 1990). The frequent dust
stormsinthese areas may have a very spectacular character, showing nature's power in moving
soilparticles;atthe sametime, they canbe devastating for agricultural systems. Wind erosion may
damage crops by abrasion and burial in sand. It also gives rise to soil degradation inthe source
areas by the loss of fertile topsoil. Deposition of wind-blown sand may create problems of sand
dune formation in or at some distance from the source area.
In the wind erosion process, three different modes of transport can be distinguished: creep,
saltation, and suspension (Bagnold, 1973).Particlestransported bycreep are too heavy to be lifted
from the surface and so they roll or slide along the ground. Particles transported by saltation are
36
Chapter3
smallerthanparticlestransportedbycreep.Theymoveinseriesofshorthopsatheightsgenerally
wellbelow 1 m.Thesmallestparticlesmoveinsuspension. Theseparticlesmaybecarried with
verticalwindstogreatheightsand aresubject to longrangetransport. Undertypicalconditions,
Hudson(1973)suggeststhatparticlediametersvaryfrom 0.5to 2mmfor creep,varyfrom 0.05
to0.5mmforsaltation,andaresmallerthan0.1mmfor suspension. Theoverlapindiameters for
suspensionandsaltationindicatesthatcertainparticlesmaybemovedbydifferent transportmodes,
dependingontheparticledensityandthewind speed. So,theamounts ofmaterialtransported by
thethreemodesdependonwindspeed,particledensity, andthetexture ofthetopsoil. According
toanestimateofChepil(1945),theproportionsvaryfrom 50to 75%insaltation, from 3to40%
insuspension andfrom 5to 25%insurface creep.
For the study offieldwind erosion and the design and evaluation ofwind erosion control
techniques, detailed observations of wind erosion processes are needed. Wind-blown particle
transportinthefieldisusuallysampledwithsedimentcatchers(e.g.,Bagnold, 1973;Wilsonand
Cooke, 1980;Fryrearetal., 1991).Althoughthe catchersdescribed intheliterature differ insize
andshape,theygenerallyconsistofaverticalarrayofsedimenttraps.Duringawind erosion event,
eachtrap collectsmovingmaterialatacertainheight.Fromtheweight ofthetrapped materials
andthestormduration, horizontalmassfluxes arecalculated. Amasstransportrate atthepoint
ofobservation isobtained byintegratingthemassfluxprofile acrossheight. Severalmodels for
thevertical distribution ofhorizontal massfluxwere described intheliterature.
AccordingtoVoriesandFryrear(1991),therelationshipbetweenhorizontalmassfluxandheight
canbedescribedby:
q(z) = az b + cexp(-dz)
whereq(z)(kgm'2s'1)isthemassfluxatheightz(m)anda,b,c,anddareregression coefficients.
Thefirsttermattherightisconsideredtodescribethesuspensionmassflux(Nickling, 1978),whereas
thesecondtermissupposedtodescribethesaltationmassflux,includingcreep(Fryrear and Saleh,
1993).Aproblemwiththefirsttermontheright sideofEq. [1]isthatitcausesthemassfluxto
goto infinity when z approaches zero,becausethe exponent inthepowerfunction isnegative.
Extrapolationtothesoilsurfacegivesunrealisticvaluesofthemassfluxnearandatthesoil surface
(VoriesandFryrear, 1991).Thisproblemcanbesolvedbyintroducing aconstant lengtha inthe
power function:
[1]
ComparingModelsofVerticalDistributionofSediment
q(z) = a'(z + <x)"b' + cexp(-dz)
37
(a > 0)
[2]
(a > 0)
[3]
Equation [2]canberewrittenas:
q(z) = a"(L
+
i)-"' + cexp(-|)
a
l
ß
wherea"= a'cTb.Likec,thecoefficient a" hasdimensionsofmassflux (kgm"2s"1).Thesumof
thecoefficients a"andcrepresentsthemaximummassfluxatz=0.Thecoefficient b'(dimensionless)
andthelengthscale ß (m)canbeinterpreted asmeasuresofthedecreaseinmassfluxwithheight.
Equation [3]isageneral,combinedmassfluxmodelthat describesthevertical distribution of
horizontalmassfluxesfromthesoilsurfaceto anyheight. Itcombines amodified power function
andanexponentialfunction. Theexponentialfunction wasused inseveralwind tunnel studiesto
describesaltationmassfluxprofiles(e.g.,HorikawaandShen, 1960,Williams, 1964).Undernatural
conditions,withmovingsedimentsbeingamixtureofsaltationandsuspensionmaterial,anexponential
functionisnotsufficient, sinceitisrestrictedtosaltationtransport only(Fryrear and Saleh, 1993).
Themodified power function resemblesthemassfluxmodelfirstusedbyZingg(1953):
q(z) = q 0 (* + 1)-P
whereq0isthemassfluxatz=0,a isalength scale,and pisadimensionless exponent. Equation
[4]issupposedtoadequatelydescribetheverticalprofileofhorizontalmassfluxfromthesoilsurface
toanyheight(Zingg, 1953;Fryrearetal., 1991).Ontheotherhand,thetheoreticallyderivedmodel
ofScottetal.(1995)revealsthatapowerfunctionisonlyvalidfor conditionswherethemassper
unit ofvolume of air containing the driving grains is constant inthe vertical. Thisrestricts the
applicabilityofsuchafunction tomaterialmovinginsuspension,andthustheyincluded aseparate
(logarithmic) saltationtermtodescribethefullprofile.Fittingtheircombinedmodeltowind tunnel
datashowed,however,thattheinclusionofthesaltationtermresulted inonlyaslight improvement
inthefitcompared withthemore simple,power function. Itwasconcluded thattheextraterm
canbeignored asfar asthe concentration profile isconcerned.
Thepurpose ofthis study isto quantify thewind-blown soilmassmovingpast afixedpoint
inaSahelianpearlmilletfield,byusingasimple,lowcost,sedimentcatcher.Twomassfluxprofile
[4]
'
38
Chapter3
models,thecombinedmassfluxmodel(Eq.[3])andthemodified power function (Eq. [4]),were
appliedfor calculatingmasstransportrates.Themodelsweretestedontheirperformance of fitting
themassfluxprofiles throughmeasured data.
MATERIALS AND METHODS
Sampling
WilsonandCooke(1980)developedawind erosion samplerthat trapsmovingmaterialatsix
heightsbetween0.15mand 1.52m.Eachtrapconsistsofaplasticbottlewithaninletandanoutlet
glasstube, mounted onawindvanethatrotatesabout acentralpole. Thevanes assurethat the
inlettubespointintothewind.Wind-borneparticlesenterthroughtheinlet, airescapes through
the outlet, andthe sediment iscollected inthebottle.
Usingthesameprinciple,Kuntzeetal.(1990)connected sixsimilartrapsto aframe ofcopper
tubes, and named ittheModified Wilson and Cooke (MWAC) sediment catcher. Theinletand
outlettubes ofthe samplebottles areglasstubeswith aninternaldiameter of 8.0 mm,resulting
inanopening of50.3mm2. Thedifferences withthe originalWilsonand Cooke catcher arethe
horizontalpositionofthebottles,insteadofaverticalposition,andtheuseofonlyonelargevane.
Theconstructionissimpleandcheap,andoperationinthefieldiseasy.Inthisstudy, theMWAC
catcherwasusedforfieldmeasurements. Aseventhtrapwasadded, andtheintended measuring
heightswere0.05,0.12,0.19,0.26,0.50,0.75,and 1.00mabovethesoilsurface (Fig. 1),butthese
changed(5-20mm)after soilsurface changes.Theheightrangeassuredthatthetrapped materials
were amixofsaltation and suspensionparticles. Creepparticleswerenot trapped.
Twenty-oneMWACcatcherswereinstalledinanexperimentalplotof40by60mwithinapearl
milletfieldatthe International CropsResearch Institute for the Semi-Arid Tropics (ICRISAT)
SahelianCenter (ISC).Thecenter islocated at Sadoré(13°16lN;202rE)insouthwest Niger, 45
kmsouthofthecapitalNiamey.TheclimateatISCistypicalfortheSahelianzone ofWest Africa,
withhightemperatures allyearround and onerainy season.Rainfall inthefirsthalfoftherainy
season(May-July)isoftenprecededbyshortperiods(typically10-30min)ofstrongwinds,leading
to severe erosiononunprotected soils.
Thesoilatthemeasurementfield isasandy, siliceous,isohyperthermicPsammentic Paleustalf
oftheLabucheri soil series(West et al., 1984),with92.2%sand, 3.0% silt, and4.8%clay. The
sizedistributionofdryundispersedparticles,includingaggregates, ofthetopsoil (Table 1)issuch
ComparingModelsofVerticalDistributionofSediment
39
copper frame
outlet
/
inlet
\
sample bottle
sample bottle
pvc tube
Figure 1.TheModified WilsonandCookesedimentcatcher(pvc=polyvinylchloride).
Table 1.Aggregatesizedistribution!oftopsoil attheICR1SAT
Sahelian Center.
Size class
Mass
<63
3.1
63-125
18.2
125-250
35.7
250 - 500
32.8
500-1000
10.0
>1000
0.2
%
t Thesizedistributionofdryundispersedparticles determined
bydrysievingwithasetofvibratingsieves.
thatsoilparticlescanbetransportedineitherofthreetransportmodes:creep,saltation,andsuspension.
Thewholefield was uniformly covered with millet stalks of the previous year crop. Theamount
of crop residueswas equalto800kgha"1, corresponding toanestimated soil cover of3.5%.The
40
Chapter3
field wassurroundedbyroadsandotherfieldsinwhichobstaclesliketreesandbusheswerepresent.
The distancefromthe experimental plottoupwind obstaclesexceeded inallcases20timesthe
heightoftheobstacle.Hence,itwasassumedthatthedisturbanceofthewindfieldintheplotwas
negligibleduring astorm. Saltating sandmoving overtheroadsintothemeasurementfieldwas
not observed, but suspended dustwasclearlyenteringthefieldduringheavystorms.
Wind Tunnel Calibration
Beforeusingthecatcherinthefield,itwastestedandcalibratedinthewindtunneloftheResearch
InstituteforAgrobiologyandSoilFertilityatHaren,TheNetherlands (Sterk, 1993). Thesoilused
forthecalibrationwasfromISC.Theoveralltrappingefficiency r| oftheMWACcatcherisdefined
astheratioofmeasured(orcalculated)masstransportrate,Q(kgm"'s"1) andtotalmasstransport
rate, Q,(kgm"1s"1),measured inthewindtunnel:
Themeasuredmasstransportratewasobtainedbyintegratingtheverticalprofileofmeasured mass
fluxesacrossheight.Thetotalmasstransport ratewasobtained byweighingthelossofsoil from
traysduringsimulationofastorm.Theaverageoveralltrappingefficiency from 12runswithwind
speedsrangingfrom9.9to 11.5m s"1 was0.49,withastandard deviation of0.03(Sterk, 1993).
Thetrapping efficiency showed norelationwithwind speed.However, the efficiency ofawind
erosionsamplermaybeparticlesizedependentbecausesaltatingsandgrainsareeasiertotrapthan
suspended dust (Shao et al., 1993). Therefore, ahigherproportion ofthemovingmaterialmay
be collectedwiththelowesttraps comparedwiththehighesttraps, dueto arelativeincreasein
suspension-sizeparticleswithheight.Apartfromalowertrappingefficiency, thequantitiesoftrapped
materialat0.50, 0.75, and 1.00 mareverysmall,usually<1g,whichmaypotentiallyresult ina
largeerrorincalculatedfluxes.Nevertheless,itwasassumedthat(i)theoveralltrapping efficiency,
asitwasdeterminedinthewindtunnel,maybeused for calculatingthetotal masstransport rate
(Q,), and (ii)thevalueofQtisnot greatlyinfluenced bytheincreaseinexperimental error with
height sincethe low massfluxes atthehigher levelscontribute littletothetotal masstransport
rate.
ComparingModelsofVerticalDistributionofSediment
41
Calculation ofTotal Mass Transport
Fromtheweightsofthetrappedmaterialsandthestormduration,meanhorizontal massfluxes,
q(z)(kgm'2s'1),atheightz(m)werecalculated.FittingEq.[3]and[4]throughthemeasured mass
fluxescanbedonewithanynonlinearregression procedure. Inthisstudy, eachsediment catcher
providedsevendatapoints,whichissufficientforfittinganequationwiththreeregressioncoefficients,
likeEq. [4],Itisquestionablewhether anequationwithfiveregression coefficients, likeEq.[3],
maybefittedfrom suchalimiteddataset. Therefore, thenumber ofcoefficients inthe regression
analysis was reduced to four byfixing one. Thecoefficient ais alengthparameter for shifting
the curve across height, and it was assumed that it can be set at a constant length. As afirst
approximation cc wassetat 1 m.Thesensitivityofthemodelfordifferent valuesof cc willbetested
laterinthepaper. Equation [3]thenreducesto:
q(z) = a"(z'
+
1)"' + cexp(-|)
[6]
where z'(=za _ 1 ) is a dimensionless height. The NONLIN module ofthe SYSTAT statistical
package,whichmakesuseofaquasi-Newtonminimizationmethod(Wilkinson, 1987),wasapplied
for fitting Eq. [4]and [6]throughthemeasured massfluxes.
Thecurveswerenot extrapolated toward heights>1m, sinceno observations ofsuspended
massfluxesabove 1 mwereavailable.Itwasassumedthatthecontributionofsuspensiontransport
abovethe 1 mleveltothetotalmasstransport isnegligible. Integration ofEq. [4]and [6] across
height (from z = 0 to z = 1m) resulted in measured (or calculated) mass transport rates Q
(kgm"1s"1) atthepointofsampling. Thetotal masstransport rate Q,(kgm'1s"1) wasobtainedby
dividingQbytheoveralltrapping efficiency r\. Multiplying Q,bythe storm durationresultedin
atotalmasstransport valueM(kgm"1),whichisequivalenttothemassofsoilpassing astrip of
1mwidthperpendicular tothemeanwind direction.
RESULTSAND DISCUSSION
Duringthe 1993rainy seasontherewereonlyfour wind erosionevents. Compared withthe
threepreviousyears,with 21, 13,and 15 wind erosion events,respectively (Michels, 1994),the
seasonrepresentedaweakwinderosionseason.Thedates,durations, andwind conditions ofthe
four storms aregiveninTable2.
42
Chapter3
Table2.Date,duration,andaveragevaluesofwindspeedand
winddirectionduringfourstormsatICRISATSahelianCenter,
1993rainyseason.
Date
Duration
Wind speedf
Wind direction
s
ras'
13 June
1481
10.3
SE
27 June
1320
7.6
S
30 June
1321
8.9
SE
1 July
3004
9.2
SSE
t Meanwindspeedmeasuredat2m.
Foreverycatcherand storm, acurvewasfitted throughthemeasured massfluxes. Fitting of
themodified powerfunction (Eq.[4])gavenoproblems,butthesuccessoffitting Eq. [6]through
thesevenmassfluxesappearedtobedependentonthestartingvaluesfortheregression coefficients
in the NONLIN program. For obtaining a first estimate of the values of a",b', c, andß, the
method describedbyFryrearandSaleh(1993)wasused. Throughmeasured fluxes from the four
highestsamplebottles(z=0.26,0.50,0.75,and 1.00 m),amodified powerfunction (Eq. [7])was
fittedresulting intwo estimates(a'"andb")oftheregression coefficients a"andb'inEq.[6]:
q(z) = a'"(z' + l)"b"
z' > 0.26
[7]
The estimatesc'and ß'of c and ß (Eq. [6]) were obtained by fitting an exponential function
throughthefluxes measured atthethreelowest positions(z=0.05,0.12, and 0.19m):
q(z) = c'exp(--| 7 )
z < 0.26
[8]
The values of a'", b", c' andß' were used as starting values for fitting Eq. [6] through the
measured massfluxes.
Comparingthemodified powerfunction (Eq.[4])withthecombinedmassflux model(Eq. [6])
showedinnearly allcasesasmalldifference betweenthetwo curves,which isillustrated inFig.
2.Bothmodelsresultedingoodfitsofthemeasured massfluxes at0.05,0.12, 0.19, and 0.26m.
At0.50,0.75,and 1.00m,thecalculatedmassfluxesdeviatedmorefromthemeasuredmassfluxes,
perhapsreflecting thelargerexperimentalerrorattheseheights.Thedeviationswereapproximately
twotimeslargerwiththemodified power function thanwiththe combined model(Table 3),and
ComparingModelsofVertical DistributionofSediment
43
1q
^
Eq. [4]
A
Eq. [6]
0.1 1
D)
X
3
^^^.
0.01i
•v^^^
V.
.
"
(A
(A
10
^^
-x^^-^^
\ ^^~^^^
0.001 -_
0.00010.0
1
1
1
1
1—
'
I
'
•
Height (m)
0.1-
r
X
_3
0.01 -
</>
tf)
re
0.001 -
0.0001
0.4
0.6
Height (m)
Figure2.Fittedmassfluxprofilesthroughmeasured datafor onecatcherduringtwostormson(A) 13June
1993and(B)27June 1993.
1.0
44
Chapter3
Table 3.Averagedeviationsbetweenmeasuredmassfluxesand
massfluxescalculatedbytwomodelst duringfour storms at
ICRISATSahelianCenter, 1993rainy season.
Height
Model1
Model2
m
%
%
0.05
0.2
0.1
0.12
1.9
0.7
0.19
5.5
3.5
0.26
6.3
4.5
0.50
21.1
12.4
0.75
45.2
18.5
1.00
60.6
38.0
t Model 1 isthemodified powerfunction (Eq. [4]);Model2is
thecombinedmassfluxmodel(Eq.[6]).
generally,themodified powerfunction slightlyunderestimatedthemassfluxes,whereasthe combined
modelwas closer to the measured fluxes (Fig. 2). So, inclusion of the exponential term resulted
ina small improvement of the curve fitting, which agrees with the results of Scott et al. (1995).
Both modelswere used to calculatetotalmasstransport rates(Q t ) and total mass transport values
(M). The averagevaluesfor QtandM show small differences between the two models (Table 4).
Because ofthe slightlybetter performance forfittingthe field data, the combined mass flux model
ispreferred andused inthecontinuation ofthispaper, althoughthe simpler modified power function
may be sufficient in many field studies.
Table4.Summarystatisticsoftotalmasstransportcalculatedbytwomassfluxprofile modelst, during four
stormsatICRISAT SahelianCenter, 1993rainyseason.
Model 2
Modell!
Date
n
Qt
M
CV
M
Qt
CV
%
g m" s
kg m '
%
g m s"
kg m-1
13 June
20
71.8
106.3
31.8
69.3
102.7
35.9
27 June
21
12.5
16.5
37.1
11.8
15.5
33.5
30 June
21
26.6
35.2
42.8
24.1
31.8
46.6
1 July
21
56.3
169.2
32.9
49.9
149.8
34.5
1 -1
-1
1
t Model 1isthemodified powerfunction (Eq. [4]);Model 2isthe combinedmassfluxmodel (Eq. [6]).
Î nisthenumberofobservations; Q t istheaveragetotalmasstransportrate; M istheaveragetotalmass
transportvalue;CVisthecoefficient ofvariation (similarfor QtandM).
ComparingModelsofVerticalDistributionofSediment
45
Ameasure ofunit mass ofmaterialpassing aunitwidth (M)isuseful when soillosses from
acertain area arestudied. Butwhen studyingcrop damagebywind erosion, ameasure ofmass
passingaunitwidthperunitoftime(Qt)ismoreappropriate, sinceitistheblasting effect ofsand
thatcausesthegreatestdamagetocrops(WilsonandCooke, 1980).Forexample,duringthefourth
storm,theaveragetotalmasstransportvaluewas46% higherthan duringthefirststorm, whereas
theaveragetotalmasstransportratewas 28% lower(Table4). Thus, it is expectedthatcropdamage
duringthefirststormwas moreseverethanduringthe fourthstorm.In the measurementfield,sowing
wasdoneafter thefirststorm,butinotherfieldsatISC,wheremilletwas sownoneweek earlier,
severecropdamagewasobserveddirectlyafterthefirststorm.Duringthefourth storm,twoweeks
later, no crop damageinthemeasurementfieldandotherfields wasnoticeable.
AccordingtoVoriesandFryrear(1991),integrationoftheseparatetermsofthecombinedmass
fluxmodelproducespredictionsofthe suspensionand saltationmassfluxes,respectively.Itisevaluated
nowwhether thesepredictions arecorrect. Bysievingthetrapped materialsfrom two catchers,
the masspercentages of saltationmaterial (>63 urn)and suspension material (<63 urn)ineach
bottleweredetermined.Onlythe materialfromthefivelowestbottleswas used,becausethequantity
oftrappedmaterialinthe two highestbottleswas notsufficient forsieving. The measuredpercentages
werecomparedwiththe modelpredictions(Table5). Thepredictedpercentagesofsaltationmaterial
decreasemorerapidlywithheightthanthemeasured percentages. Hence,thepredicted saltation
massfluxesaretoo lowcomparedwiththe measurements. As aconsequence,the predictedsuspension
massfluxwasoverestimatedbythemodel.Althoughtheparticle sizeof 63 urnisrather small for
Table5. Predictedand measuredmasspercentagesofsuspensionandsaltationmaterial.f
Catcher 1
Catcher2
Su""
Su«
Sa'1"
Sa ( m >
%
%
%
%
%
95.3
97.3
4.6
2.3
95.4
97.7
5.8
80.4
94.2
17.0
6.0
83.0
94.0
55.1
14.5
44.9
85.5
47.2
15.4
52.8
84.6
86.3
27.3
13.7
72.7
79.9
31.4
20.1
68.6
0.01
51.3
99.9
50.0
0.01
50.0
Su<>"
Su<m>
Sa*'
m
%
%
%
0.05
4.7
2.7
0.12
19.6
0.19
0.26
Height
0.50
99.9
48.7
Sa
(m)
t Suis suspensionmaterial; Saissaltationmaterial;(p)=predictedbythecombinedmassfluxmodel
(Eq. [6]); (m)=measuredby dry sieving(63-ummeshsize)oftrappedsedimentwithavibratingsieve.
46
Chapter3
discriminatingbetweensaltationandsuspension,itisconcludedthatthecombinedmassfluxmodel
doesnot actuallypredict saltationandsuspensionmass fluxes.
Sincethecoefficient a inEq. [3]wasarbitrarily setat 1 m,thesensitivityofthecombinedmodel
fordifferent valuesof awastested bycalculating Qfor severalvaluesof a (Table 6).Thesame
catcherasinFig.2wasusedforthecalculations.Withvaluesofa closetozero,themodified power
functiontendstoincreasesharplywhenzapproacheszero,resultinginahighintercept q(0)and,
obviously, inahighestimateofthemasstransport rateQ.Witha varyingfrom 0.25 to 5.00m,
thecalculatedmasstransport rates areverysimilar. Themassfluxprofile nearthe soilsurface is
mainly determined by the exponential term, which is in accordance with several wind tunnel
studies(e.g.,HorikawaandShen, 1960;Williams, 1964;Sterk, 1993).Whence istaken>5.00m,
Qdeviatesslightlyfromthevaluescalculatedwithabetween0.25and5.00m.Hence,itisconcluded
that settinga at 1mwas areasonable assumption for extrapolation ofthe curve.Whether the
Table6.Calculatedmasstransportratesforonecatcherduringfourstormswithdifferent valuesfor
coefficient ainthecombinedmassfluxmodel.
Qî
a
13 June
m
1
1
27 June
1 1
30 June
1 July
1
g m-1 s'1
1
g m' s"
g m' s'
g m' s'
0.001
93.3
10.9
11.2
25.7
0.01
47.9
4.4
10.3
20.4
0.05
37.3
4.3
10.0
18.6
0.10
35.5
4.3
10.0
18.3
0.25
34.8
4.3
9.9
18.2
0.50
34.7
4.3
9.9
18.2
1.00
34.6
4.3
9.9
18.2
1.50
34.6
4.3
9.9
18.0
2.00
34.6
4.3
9.9
18.0
2.50
34.6
4.3
9.9
17.9
17.9
3.00
34.6
4.4
9.9
5.00
34.6
4.4
9.9
17.9
10.0
34.6
4.3
9.6
17.9
100.0
33.8
4.3
9.5
17.9
t QisthemasstransportratecalculatedwithEq. [3].
ComparingModelsofVerticalDistributionofSediment
extrapolation ofEq. [6]towards the soilsurface iscorrect cannotbeconfirmed untilwe obtain
massflux measurements inthisheightrange.
ThetotalmasstransportrateasdeterminedbytheMWACcatcherandthecombined mass flux
model ishighly dependent onthe overalltrapping efficiency ofthe sampler. Theefficiency was
determinedinawindtunnelwhere,compared withthefield, thewindisrather homogeneousand
thedegreeofturbulencelow.Rapidchangesinwinddirectionarelacking,aswell asverticalwind
speedsthatcreatethemainliftforces for suspensiontransport. Thecharacter ofthewindfieldin
awindtunnelmayresultinatrappingefficiency thatisnot correct forfieldconditions. Sofar, no
techniquesfordeterminingtheefficiency ofsamplersinthefieldexistand estimatesoftotalmass
transportrateshavetobebasedontrappingefficiencies determined inwindtunnels.Inthe future,
morestudiesontestingwinderosionsamplersunderfield conditionsshouldbe done,with perhaps
more attention paidtotheparticle sizedistribution asafunction ofheight.
CONCLUSIONS
Thequantity ofsoilmaterialtransported bythewind duringfour stormswasmeasured with
MWACsedimentcatchers(Fig.1),whichareinexpensiveandeasytoconstruct.Wind-blownmaterial
wastrappedatsevenheightsbetween0.05and 1.00m.Athree-parameter,modified power function
(Eq. [4])accurately described themeasured massfluxes below aheight of0.5m.Atthehigher
measurementlevels,thecalculatedmassfluxesgenerallyunderestimated themeasured fluxes. The
two-term,combinedmassflux model (Eq. [6])described themeasured massfluxes atallheights
moreaccuratelythanthemodified powerfunction. Itisconcludedthatthecombinedmodelisbetter
forfittingtheverticalprofile ofhorizontal massflux, althoughthemodified power function may
be sufficient inmanyfieldstudies ofwind-blown sand transport.
Thetwoseparatetermsinthecombinedmassfluxmodelshouldnotbeusedtopredictthesaltation
andsuspensionmassfluxes, asclaimedbyVories andFryrear (1991).Thepredicted suspension
massfluxesfrom0.05to0.50mwereapproximately threetimeshigherthanthe suspensionmass
fluxesthatweredeterminedbydrysievingthetrapped sedimentsfromtwocatchers. So,themodel
overestimatesthesuspensionmassfluxes,andobviously,thesaltationmassfluxesareunderestimated.
Integrationoftheverticalmassflux profile acrossheight from z=0 m t o z = 1 mresulted in
ameasured orcalculatedmasstransportrate(Q)atthepointofsampling.Thetotal masstransport
rate(Qt)wasobtained after correctingfortheoveralltrapping efficiency oftheMWACcatchers.
47
48
Chapter 3
Thistrapping efficiency was determined inthewind tunnel anditisuncertainwhether it is the same
underfieldconditions. Inawind tunnel,wind ismore homogeneous and less turbulent than in the
field, which may result in a different efficiency.
ACKNOWLEDGMENTS
The research was funded by the Netherlands Foundation for the Advancement of Tropical
Research (WOTRO). We thankthe ICRISAT Sahelian Center for providing thenecessary research
facilities and for the assistance duringthefieldexperiments. The constructive comments, including
some useful references, by three anonymous reviewers are gratefully acknowledged.
REFERENCES
Bagnold, R.A. 1973.Thephysicsofblownsandanddesertdunes.5thed.,ChapmanandHall,London.
Chepil,W.S. 1945.Dynamicsofwinderosion.I.Natureofmovementofsoilbywind. Soil Sei.60:305-320.
Fryrear, D.W.,andA. Saleh. 1993.Fieldwinderosion:Verticaldistribution. Soil Sei. 155:294-300.
Fryrear,D.W.,J.E.Stout,L.J.Hagen,andE.D.Vories. 1991.Winderosion: Fieldmeasurement andanalysis.
Trans.ASAE34: 155-160.
Horikawa, K, and H.W. Shen. 1960. Sandmovementbywind:Onthecharacteristicsofsandtraps.Tech.
Mem. 119.BeachErosionBoard,U.S.Army,Washington DC.
Hudson,N. 1973. Soilconservation. Batsford andEducational Ltd.,London.
Kuntze,H.,R.Beinhauer,andG.TetzlafF. 1990.Quantification ofsoilerosionbywind,I.Finalreportofthe
BMFTproject.Projectnr.0339058A,B,C.Inst,ofMeteorologyandClimatology,Univ.of Hannover,
Germany,(inGerman).
Lai,R. 1990.Soilerosioninthetropics: Principles andmanagement. McGrawHillInc.,NewYork.
Michels,K.1994.WinderosioninthesouthernSahelianzone:Extent,control,andeffects onmilletproduction.
VerlagUlrichE.Grauer, Stuttgart, Germany.
Nickling,W.G. 1978.Eoliansedimenttransportduringduststorms:SlimsRiverValley,YukonTerritory.
Can.J.EarthSei. 15:1069-1084.
Scott,W.D.,J.M.Hopwood,andK.J. Summers. 1995.Amathematicalmodelofsuspensionwithsaltation.
ActaMech. 108: 1-22.
Shao,Y, G.H.McTainsh,J.F.Leys,andMR. Raupach. 1993.Efficiencies ofsediment samplers forwind
erosionmeasurement. Aust. J. SoilRes. 31: 519-532.
Sterk,G. 1993. Sahelianwinderosionresearchproject, ReportIII.Descriptionandcalibrationofsediment
samplers.Dep.ofIrrigationandSoil&WaterConservation,WageningenAgric.Univ.,TheNetherlands.
ComparingModelsofVerticalDistributionof Sediment
Vories,E.D.,and D.W. Fryrear. 1991. Vertical distribution ofwind eroded soilover asmooth,bare field.
Trans.ASAE34: 1763-1768.
West,LT.,L.P.Wilding,J.K.Landeck,andF.G.Calhoun. 1984.SoilsurveyoftheICRISAT Sahelian Center,
Niger,WestAfrica. TropSoils,TexasA&MUniv.,CollegeStation,TX.
Wilkinson,L. 1987.SYSTAT:Thesystemfor statistics. SystatInc.,Evanston,IL.
Williams,G. 1964. Someaspectsoftheeoliansaltationload.Sedimentology 3:257-287.
Wilson,S.J.,andRU. Cooke. 1980.Winderosion,p.217-251.In M.J.KirkbyandR.P.C.Morgan(ed.)Soil
erosion. JohnWiley&Sons,Chichester,UK.
Zingg,AW. 1953.Windtunnel studiesofthemovementofsedimentarymaterial,p. 111-135./« Proc.of
the5thHydraul.Conf.,StateUniv.ofIowaStudiesinEngineeringBull.34.
49
Chapter4
Mapping Wind-BlownMassTransport byModeling Variability
inSpaceand Time
G. Sterk andA. Stein
Accepted for publicationin:SoilScience SocietyofAmericaJournal.
Reproduced bypermission ofthe SoilScience Society ofAmerica.
53
Mapping Wind-Blown MassTransport byModeling Variability
inSpaceand Time
ABSTRACT
Fieldobservationsofwind-blownparticletransportareoften characterizedbyaconsiderable spatial
variation,whichmakes quantitative modeling ofwind erosion difficult. This study examines how the
horizontaldistribution,orpattern,ofmasstransport canbedeterminedfrom alimitednumber of point
measurements.Twenty-one sediment catchers wereinstalled inanexperimental plotinthe Sahelian
zoneofNiger, on a sandy,siliceous,isohyperthermic Psammentic Paleustalf.Masstransport values
during four storms ranged from 24.0to 213.6 kgm"1,7.2to 26.0kgm"1,9.6to 68.9kgm"1,and 68.9
to282.7kgm'. Geostatisticaltheorywasappliedtoproducestormbasedmapsbymodelingthe spatial
correlation structure withthevariogram. Toestimatethevariogram from 21observations,the four
stormsweretreated asindependenttemporalreplicates.Two geostatistical mapping techniques were
applied.Kriging (a spatial interpolation technique)produced maps ofmass transport providing the
best possible estimates ofnet soillossesfrom the plot,whichwere 12.5,2.0,4.6,and 26.8Mg ha'1,
respectively.Toovercomesmoothing,possiblerealizations ofactual mass transport were created by
stochasticsimulationswithsimulatedannealing.Thesimulatedmapsreproducedthestatisticalproperties
oftheobservations,andallowedadistinctionbetweenerosionanddepositionareaswithintheexperimental
plot.
W
ind erosion causes serious agricultural problems inmany parts ofthe world, especially
inregionswithloose, dry, sandy soils,littlevegetativeprotection of the soil, and periods
of strongwinds (Skidmore, 1988). Quantitative modeling ofwind erosion in the field is difficult
because ofthe different spatial scales on which the transport processes occur. Sediments can be
carried across distances ranging from afew centimeters to thousands ofkilometers, at agreat range
of heights, and in any direction (McTainsh et al., 1992).
On afield scale, observations of sedimenttransport often show a considerable spatial variation
causedbydifferences insoilcharacteristics,surfaceroughness,topography,vegetationcharacteristics,
andwindfield(Wilson and Cooke, 1980;Fryrear et al., 1991).Inpractice, it is virtually impossible
to measure and describe allfactors at every point inthe field to explain the variation in observed
sediment transport. It maybe doubted aswell whether such detailed information is necessary for
54
Chapter4
winderosionstudies.Analternativeapproachistoproducestormbasedmapsofsedimenttransport
andtorelatethemtomapsofsoilerodibilityfactors. Anextensiveliterature searchmadeclearthat
studies ofthiskind arenonexisting inthewind erosion literature. Inwater erosion studies,itis
morecommontoproduceerosionmaps(e.g.,SchwingandVogt, 1980;Morgan, 1986;Mellerowicz
etal., 1994).Thesemapsareusuallyconstructed onthebasisofaerialphotographs, field survey,
or modelpredictions usinginformation ontopography, soiltype,management, etc. Theyshow
erosionfeatures ortheerosionhazardinacertainarea,butdonotshowthehorizontal distribution
ofactual,measured sediment transport.
Mapsofasampledproperty,orregionalizedvariable,areeffectively obtainedwith geostatistics
(Cressie, 1991). Geostatistical theoryusesthe concept of spatialcorrelation, whichmeansthat
observationsofaregionalizedvariableatanytwopointscloseto eachother aremore similarthan
observationsattwopointsatalargerdistance.Bymodelingthe spatialcorrelation structurewith
thevariogram,goodqualitymapsoftheregionalizedvariableareobtainedbythespatialinterpolation
techniquekriging.Alternatively,possiblerealizationsoftheregionalizedvariablemaybereproduced
bystochastic simulations.
InawinderosionresearchprojectinNiger,WestAfrica, measurements ofair-borne sediment
weremadeinapearlmillet(Pennisetumglaucum)field (Sterk andRaats, 1996).Duringthe 1993
winderosionseason,four stormswere sampledwith21 sediment catchers.For eachcatcher and
storm, apointmeasurement ofparticlemasstransport wasobtained. Inthisstudy, theresulting
datasetsareusedtodeterminethehorizontaldistribution,orpattern,ofmasstransport inthe field.
Mapsofwind-blownsedimenttransportcanbeproducedwithgeostatisticsaslongasa sufficient
numberofpointobservationsisavailableto determinethevariogram. Webster andOliver(1992)
investigatedtheconfidencelimitsofvariogramsestimatedfromavaryingnumber ofobservations.
Theyconcludedthatvariograms computed onfewer than 50observations areoflittlevalue,and
recommended that preferably 100ormore observations should beused. Inthis study, only21
observationsperstormwereavailable.Therefore,theanalysisofspatialvariabilityisextended into
thespace-timedomainbypoolingthefourstormstoestimatethevariogram.Byusingthisprocedure,
stormbasedmaps ofsedimenttransport canbe createdwithkrigingand stochastic simulation.
Alternativemappingproceduressuchassplinesandinversedistancecalculationswereconsidered
aswell,but notused. Bothtechniques arebased onamodel ofthe spatialcorrelation structure
thatisnotverifiablebymeasurements. Forinstance,whenusing splines,the spatialcorrelationis
MappingWind-BlownMassTransport
55
modeledbyalineartrendwithalogarithmicgeneralizedcovariancefunction (Cressie, 1991).Inverse
distanceinterpolationassignsweightsproportionalto d"e to eachneighboring observation, where
disthedistancefromaneighboringpointtothepredictionpoint ande isaparameter. Hence,an
assumptionforthevalueof ehastobemade. Theprocedurethatisproposed herehasatleasta
certaindegreeofvalidationinfieldmeasurements,whereasthementionedalternativesrequiremore
severe assumptions.
Theobjectiveofthisstudyistoproduce stormbased mapsofsedimenttransportbyapplying
geostatistics.Itisexaminedhowthespatialcorrelationstructurecanbemodeledwiththevariogram,
when onlyfour data setsof21observations areavailable.
THEORY
Regionalizedvariabletheoryisappliedtomodelthespatialcorrelationstructurewiththevariogram
(JournelandHuijbregts, 1978).Eachobservationyisconsidered therealization ofaregionalized
variableY(s),dependinguponthemeasurementlocations.Thevariabilitybetweenanytwoquantities
Y(s) and Y(s +h),at two points sand s+hseparated bythevector h, ischaracterized bythe
variogram. ThevariogramyCh)asafunction ofthe separationvector h,but independent ofs,is
defined ashalfthe expectation ofthe squared differences ofY(s) and Y(s+h):
Y(h) = iE[Y(s)-Y(s + h)] 2
whereEdenotesthemathematical expectation. Thevariogram canbeestimated byreplacingthe
expectationwiththemeanvalue,takenfor allpair differences ofobservations (y;, yi+h ):
1
n(h)
wheren(h)isthenumber ofpairs(y;, y i+h ) separated bythevectorh, andtheindexiindicates
the different spatiallocations oftheobservations.
Toovercomethelack ofsufficient observations, theanalysisisextended intothe space-time
domainbyusingobservationsfromdifferent storms.Themainassumptiontojustify thisstepis
that sediment transport inthe experimental plot duringthefour stormscanbe characterized by
aspatialcorrelationstructurethatissimilarfor eachindividualstorm,irrespectiveofduration,wind
speed,andwind directionofthe storm. Thisimpliesthatthe spatialvariability ofmasstransport
(1]
56
Chapter4
duringdifferent storms canbecharacterized bythe samevariogrammodel structure. Itdoesnot
mean,though,thatthe spatialdistribution ofmasstransport wasthesamefor eachstorm.
Mass transport values were measured during four successive storms, denoted by y^,with
i= 1,..,21,thespatiallocation,andj = 1,..,4,thestormnumber. Topoolthespatialvariationin
masstransport,thestormsarestandardized tothemeanmasstransport valueofallfour storms:
v
ij = v ij -
[3]
wherey{- isthe standardized masstransport at observationlocation iandfor stormj , and ûand
fisarethestorm'smeanmasstransportandthestandardizedmeanmasstransportvalue,respectively.
Lackofobservationstoestimatethevariogramiscircumventedbyusingthefollowing equation:
Y(h)=- J - £ £ ( y i r y i W 2
[4]
2n(n)j = i i=i
whereVjj andy^y denote the ithpair of standardized observations at time j , separated by the
vector h, ofwhichtherearen/h). Thetotalnumber ofpairsofpointsfor eachvector hisequal
to n(h). Sinceobservations from different stormsmust not be subtracted from eachother, n(h)
is equal tothe sumofthenj(h)'s. Inthisway, eachpairofobservationswithinthe samestorm
contributestoestimatethestandardizedvariogram,irrespectiveofthetimethatthe measurements
weremade.
Inpractice,pairsofobservationswithapproximatelythesameseparation vector haregrouped
intoclasses.Thebasicunitofthedistanceclassisthelagdistanceh^. For afinitenumber (m)of
multiplesofh,^, mvariogramvaluesareobtained. Throughallthepairs[x,y(x)]withx=khlag,
k= l,...,m,avariogrammodelg(h)isfittedtofacilitateinterpretation,andtoallowspatialinterpolation
(kriging)andstochasticsimulations.Variogrammodelsarecharacterizedbytwoparameters:the
silland therange (Journel andHuijbregts, 1978).Thesillisthelimitingvalueofthevariogram
modelg(h)ashincreases.Therangeisthedistanceatwhichthevariogram reachesitssillvalue.
Itgivesthedistanceacrosswhichspatialdependencies exist.Beyondtherange,twopointsinthe
field arenolongercorrelated.Attheotherendofthevariogram,y(0) =0bydefinition. However,
inmanystudies,g(h)doesnottendtozerowhenhapproacheszero.Thisdiscontinuityattheorigin
iscalledthenuggeteffect andiscaused bynonspatialvariation suchasmeasurement errors,and
MappingWind-BlownMassTransport
thespatialvariationthatoccursatvery smalldistances. Sometimes,the sillisequalto the nugget
effect. Suchapurenugget effect correspondstothetotal absence ofspatial correlation.
Aregionalized variablewith aconstant expectation (notrend) and for whichthevariogram
existsissaidtoobeytheintrinsichypothesis.Iftrue, theconditionsfor thegeostatistical mapping
techniqueskrigingandstochasticsimulationaremet(JournelandHuijbregts, 1978).Bothtechniques
makeuse ofthe observations andthevariogram, and areexplained briefly here.
Krigingusesalinearcombinationoftheobservationstomakeunbiasedpredictionsofanunsampled
valuewithminimumerrorvariance.Itthereforeprovidestheso-calledbestlinearunbiasedpredictor
(BLUP)oftheregionalizedvariable(SteinandCorsten,1991).Krigingestimatesastochasticvariable,
insteadofaparameter, suchastheexpectationofanobservation. Prediction isusually associated
with ahigheruncertainty. Theinformation used for prediction consists ofthe observations and
thevariogrammodel.Althoughkrigingprovidesapredictorwithminimalvarianceoftheprediction
errorateveryposition,itdoesnotreproducethestatisticalpropertiesoftheobservations.Minimization
ofthepredictionerrorvarianceinvolvesasmoothingoftheactualvariability(JournelandHuijbregts,
1978), i.e., alossofvariationintheunderlying stochastic field.
Stochasticsimulationmaintainsthestatisticalpropertiesoftheobservationsbutdoesnotprovide
thebestpossiblepredictions(JournelandHuijbregts, 1978).Whenvaluesaresimulated onNgrid
nodes,theseNsimulated valueshavethesamemean,variance,histogram, andvariogram asthe
original set ofobservations. Simulation aimsat reproducing the fluctuations that arepresentin
theobservations,instead ofproducingthebest possiblepredictions.Moreover, the simulationis
calledconditionalifthemeasurementvaluesandthesimulatedvaluesarethesameatthemeasurement
locations. Different conditional simulatedfieldswillbedifferent from eachother, except atthe
measurement locations.
MATERIALS AND METHODS
Sampling
IntheSahel,severewinderosion occursmainlyintheearlyrainy season (May-July).Inthat
time oftheyear, heavythunderstorms develop and bringthefirstrains ofthe new season. The
thunderstormsareoften accompaniedbystrongwindsthatresult insevere erosion ofunprotected
soilsbefore rainfall starts.
57
Chapter4
58
AfieldexperimentwasconductedattheInternationalCropsResearchInstitutefortheSemi-Arid
Tropics(ICRISAT) SahelianCenterinsouthwest Niger (13°16'N;2021'E), duringthe 1993rainy
season. Thesizeofthemeasurementfieldwas 170by90m.Thesoilwasclassified asasandy,
siliceous,isohyperthermicPsammenticPaleustalf(West etal., 1984),with92.2%sand, 3.0% silt,
and4.8%clayinthetopsoil.Theplantresidues,milletstalks,oftheprevious cropwere uniformly
distributedacrossthefield.Theamountwas«800kgha"1,correspondingtoanestimatedsoilcover
of3.5%.Pearlmilletwassownon 14Juneinplantingholesspacedat 1 by 1 m(traditional sowing
method).Thefieldwascharacterizedbyanundulatingtopography. Distancesbetweencrestsand
depressionswerefrom 25to 50m,withmaximumheight differences of »1 m.
Withinthemeasurementfield,anexperimentalplot of40by60mwasselected suchthatthe
distancefromtheplotboundariestothefieldboundariesexceeded 25minalldirections. Theplot
wasinstrumented with 21Modified Wilson and Cooke sediment catchers.Adescription ofthe
catcherandamethodforquantifyingtotalmasstransport(kilogramspermeter)fromtrappedmaterial
+
+
+
+
+
+
60-
i 40 +
o
+
+
+
30-
+
+
+
+
?
Distanc«
c
+
+
+
+
+
+
+
10-
I
10
I
20
I
30
40
Distance east (m)
Figure1.Experimentalplotwiththepositionsof21ModifiedWilsonandCookesedimentcatchers.
MappingWind-BlownMassTransport
59
wasgivenby Sterk andRaats(1996). Threerowsofsixcatcherswereregularly distributed ina
north-southdirectionacrossthewholeexperimentalplot(Fig. 1).Withinarow,thedistancebetween
twoneighboringcatcherswas 10 mandthedistancebetweenrowswas 17m.Betweenthe second
andthirdrow,thethreeremainingcatcherswereplacedinsuchawaythatdistancesbetween these
catchers andneighboring catcherswasalso »10m.Distancesfrom theplotboundariesto small
(<1.25mheight)obstacleslikebushesandfences exceeded 30minalldirections. Duringstorms,
thedistancestolargerobstacles,mainlysingletreeswithmaximumheightsof5m,inupwinddirection
ofthe experimental plot exceeded 100m.Althoughtheinfluence ofobstaclesonthewind field
mayextendindownwind directionto »40timestheheightoftheobstacle,thedisturbancesbecome
very minor at adistance of »20timesthe height (Jacobs, 1984).Theinfluence ofthe obstacles
onthewindfieldintheplotduringastormwasthereforeassumedtobenegligible,andthusparticles
were moved atthe maximummasstransport rate.During erosion events, suspended dust from
surroundingareaswasclearlyenteringthemeasurementfield,butsaltationorcreepmaterialmoving
intothefieldwasnot observed.
Variogram Model
Severalmodelsexistthatcanbeusedforfittinganestimationvariogram. Inthisstudy,usewas
madeofthe sphericalvariogram model,whichisdefined as:
g(h) =
C„[l - ô.(h)] f C
C0 + C
2 a 2 a3
0<h<a
[5]
h>a
wheretheKronecker delta function,ôk(h),is 1 for h=0and vanishes elsewhere. Theparameter
C0 is the nugget constant, C the sill parameter, and a is the range parameter of the spherical
variogrammodel.TheparametersC„,C,andawereestimatedwithaweightednonlinearregression
procedure.
The spherical variogram model, estimated from the standardized data set, wasconverted to
fourvariogrammodels,oneforeach storm. Therangeparameter ofthemodel isthe samefor all
storms,butthenuggetconstant(C0)andthesillparameter(C)aredependent onthe storm's mean
masstransport.Newvalueswerecalculatedusingthemeanmasstransportvaluesofthefour storms
(£j) and the meanmasstransport valueofthe standardized data set (ps):
60
Chapter4
C
• ^ 2
oj = C o , s ( ^ ) 2
[6]
C,= Cs&)2
[7]
wherej denotesthestormnumberand sthestandardized dataset.
Mapping Procedures
Maps ofwind-blown masstransport wereproduced withkriging and conditional stochastic
simulationsbyusing software from the Geostatistical Software Library (GSLIB) (Deutsch and
Journel,1992).Forkriging,theprogramOKB2Dwasapplied,whichusesatwo-dimensionalordinary
krigingalgorithm.Itpredictsavalueoftheregionalized variable(Y)atacertainlocation(s0)on
thebasisofanumber (p)ofsurrounding observations orneighborhood points. Thepredictor T
for thevalueY(s0)isalinear combination ofthepobservationsy1;
,yp:
p
E
I *iYi
i=i
Thepweights À arecalculatedsuchthatTisunbiasedandthatthevarianceofthepredictionerror
isminimal.Thisprocedurerequiresinformation aboutthevariogram oftheregionalized variable.
Adetaileddescriptionofthecalculationprocedurecanbefound ingeostatistical handbooks(e.g.,
JournelandHuijbregts, 1978;Cressie, 1991).
Severalprocedures areknownto makeconditional stochastic simulations.Inthis study,use
wasmadeofsimulatedannealingwiththeGSLIBprogram SASIM(Deutsch andJournel, 1992).
Simulatedannealingisageneraltechniqueforcombinatorialoptimization(Kirkpatrick etal., 1983)
andhasbeenadaptedinthepasttogenerate afieldwith agivenvariogram. Thebasicideaisthat
afieldcreatedwithanoisyvariogramisimprovedstepwisetoafieldwithawell-structured,imposed,
variogram.ThisisaccomplishedbyassigningtheobservationstotheNobsgridnodesthatareclosest
totheobservationlocationsandrandomvaluestotheN-Nobsremaininggrid nodes. Therandom
valuesaredrawnfromtheprobabilitydensityfunction obtainedfromtheuser-specified histogram.
Acommonapproachistousethehistogramfromtheconditioningdata(DeutschandJournel,1992).
[8]
MappingWind-BlownMassTransport
Theinitialimageissequentiallymodified byswappingthevaluesinpairsofgridnodesnotinvolving
conditioning data. Aswapisaccepted ifthe objective function Oislowered:
h
Y(h)
where y*(h)isthevariogramofthesimulatedrealization,andy(h)isthe specified variogram. Not
allswapsthat raisetheobjective function arerejected. Thesimulationiscompletewhen further
swapsdonotlowertheobjectivefunctionorwhenaspecifiedminimumobjectivefunctionisreached.
RESULTS AND DISCUSSION
Althoughmanythunderstormsoccurredduringthe 1993 rainyseason,onlyfour were preceded
byperiodsofstrongwindsresultinginerosion. Ingeneral,thethunderstormsmovefrom east to
westand,hence,thewinddirectionduringastormisusuallyeasterlybutcanbevariable,depending
onthelocationrelativetothecenterofthestorm.Thewinddirectionduringthefoursampledstorms
variedfromsoutheastto south(Table 1).Duringthefirstevent, onecatcherwasnot functioning
andwas,therefore, notusedfor theanalysis.Thesummary statistics ofmeasured masstransport
(Table2)showthat meanandmedianvaluesarevery similarfor aparticular storm, andthat the
coefficientsofvariationarelow.ThisindicatesthatthedistributionisclosetotheGaussiandistribution.
Interms oftotal masstransport, thefour stormswereverydifferent inmagnitude (Table2).
Thesecondandthirdstormcanbeclassified asweakstorms,whereasthefirstandthefourth were
strongstorms.Forallfour storms,therangeinmasstransport valueswaslargeincomparison to
Table1. Date,duration,andaveragewindspeedandwinddirection
duringfourstormsatICRISATSahelianCenter,1993 rainyseason.
Storm date
Duration
Wind speedf
s
ms'
Wind direction
1
13 June
1481
10.3
SE
27 June
1320
7.6
S
30 June
1321
8.9
SE
1 July
3004
9.2
SSE
t Meanwindspeedmeasuredat2m.
61
Chapter4
62
Table2.Summarystatisticsf ofwind-blownmasstransportduringfour stormsatICRISAT Sahelian Center,
1993rainyseason.
CV
Stormdate
-
kgm'
kgm '
%
Range
kgm'
1
Median
kgm - 1
13 June
20
102.7
36.9
35.9
24.0-213.6
102.4
27 June
21
15.5
5.2
33.5
7.2-26.0
14.2
30 June
21
31.8
14.8
46.6
9.6-68.9
29.7
1 July
21
149.8
51.8
34.5
68.9-282.7
149.9
f n=numberofobservations; (i=mean; a= standard deviation; CV=coefficient ofvariation.
1400-
20
30
40
Lagdistance (m)
Figure 2.Calculatedvariogramofwind-blownmasstransport andthefitted sphericalmodel.
the mean, indicating that mass transport is indeed variable in space. The 83 observations were
standardized withEq. [3]to 75kg m"1,corresponding to themean mass transport value of all four
storms(jîs). The resulting data setwasused for thevariogram calculations with Eq. [4].The fitted
sphericalmodel (Eq. [5])throughthe calculated variogram values (Fig. 2) has a range parameter
(a)of 52.1m, anugget constant (C0)of 15.1kg2m"2,and a sillparameter (C) of 1220 kg 2 m"2. The
low nugget/sill ratio (= 0.01) indicates that the variation due to measurement errors and other
60
MappingWind-BlownMassTransport
Table3.Parameters! ofthesphericalvariogrammodel,usedfor
krigingandstochasticsimulations.
Stormdate
C„
2
C
2
2
2
a
kg m-
kg m-
m
13June
28.3
2287.6
52.1
27June
0.7
52.1
52.1
30June
2.8
222.1
52.1
1 July
60.3
4873.5
52.1
f C0=nuggetconstant;C=sillparameter;a=rangeparameter.
nonspatialsourcesissmallcomparedwiththespatialvariationinwind-blown masstransport. The
standardized variogramwasconverted tofour sphericalvariogramswithEq. [6]and [7](Table
3).
Theintrinsichypothesis,anecessarycriterionforkrigingandconditionalstochasticsimulations,
isobeyedforthreeofthefourstormssince(i)thevariogramexists,and(ii)notrendinmasstransport
valueswasfoundbyamultiplelinearregressionanalysis.Thethirdstorm,however, showedatrend
inmasstransportvalues,and,hence,theexpectation isnot constant but dependsonthe position.
For this storm, it was assumed that the hypothesis of quasi-stationarity is fulfilled when the
neighborhood sizeforkrigingandstochasticsimulationissufficiently small(JournelandHuijbregts,
1978). In other words, the intrinsic hypothesis is not true for the whole plot, but in smaller
neighborhoods,theexpectation andvariogrammaybeconsidered asstationary.
ForkrigingwiththeprogramOKB2D,thefollowing inputwasused: the sphericalvariogram
models(Table3),the21observations,aminimumof4andamaximumof 16(8forthethirdstorm)
neighborhood pointswith amaximum searchradius of30. Thekrigingpredictions for the four
storms arepresented ingrayscalemaps(Fig. 3).The SASEVIsimulations (Fig.4)arebased on
thesphericalvariogrammodels(Table3)andthe21observations aswell.Forthe user-specified
histograms,the21 conditioningdatapoints(theobservations)weretaken,withthefollowing specified
ranges:storm 1:0to240kgm'1;storm2:0to 35kgm"1;storm 3: 0to 75kgm"1;storm4: 50to
300kgm"1. Usewasmadeofatwo-part objective function and 100lagsfor conditioning, which
meansthat the experimental variogram iscalculated from the 100nearestgrid points. Thegrid
sizeforkrigingandstochasticsimulationwas41x 61,hence,eachgridcellinFig.3 and4corresponds
to anareaof 1 by 1 mintheexperimentalplot.
63
Chapter4
64
Masstransport
(kg m 1)
Masstransport
(kgm-1)
I25
200
1160
20
120
sy
15
80
10
40
10
20
30
10
20
30
40
Distanceeast(m)
Distanceeast(m)
Masstransport
(kgm-1)
Masstransport
(kg m-1)
1280
240
200
160
120
80
10
20
30
Distanceeast(m)
10
20
30
Distanceeast(m)
Figure3.Maps ofmasstransportproducedbykrigingwiththeprogram OKB2D. Stormdates are(A) 13
June,(B)27June,(C)30June,and(D) 1 July1993.
MappingWind-BlownMass Transport
65
Masstransport
(kgm-1)
Mass transport
(kg m-1)
30
25
20
10
'
10
*•*\ <t<* *
20
30
Distanceeast(m)
40
10
20
30
40
Distance east(m)
Masstransport
•kg m-1)
280
240
200
160
120
80
10
20
30
Distanceeast(m)
10
20
30
40
Distanceeast(m)
Figure4.Mapsofmasstransportproducedbysimulated annealingwiththeprogram SASIM. Stormdates
are(A) 13June,(B)27June,(C)30June,and(D) 1 July1993.
66
Chapter4
Theinterpolatedmaps(Fig.3)showthatthekrigingalgorithmtendsto smooth out detailsand
extremevaluesoftheoriginal data set. Thevariabilitythatwaspresentinthe observationsisnot
reproduced.However, krigingprovidesthebestprediction ofmasstransport at eachunsampled
location atagiventimeandistherefore well suited for calculatingnet soillossesfrom theplot.
Forallfour storms,amassbudgetwasdetermined byaveragingthekrigingpredictions alongthe
four boundaries ofthe experimental plot. Thebest possible estimate ofnet soillossisobtained
whentheboundariescoincidewiththeoutermostrowsofsediment catchers,becausethevariance
inpredictionerrorislowestalongtheserows.Duringthefirst,third,andfourth storms,thesediment
movedintotheplotacrossthe easternand southernboundaries andleft theplot viathe northern
and western boundaries. During the second storm, onlythe southern and northern boundaries
contributedtoinputandoutputofmasstransport.Thecalculatedsoillossesbyusingkriging(Table
4)arecomparedwithsoillossesdeterminedbyaveragingthemeasuredmasstransportvaluesalong
thesameboundaries(linearinterpolation).Thetotalsoillossfromtheplotasdeterminedbykriging
isslightly (5.8%) higherthan thetotal soillosscalculated withlinear interpolation. Comparing
individualstorms,however, showsthatlarger differences innet soillosses existbetweenthetwo
calculation methods. Sincekrigingtakesthe spatial correlation structure ofmasstransport into
account, itgivesthebetter estimateofnet soillossesfrom theexperimental plot.
Stochastic simulations (Fig. 4) typically serve a different purpose than interpolated maps.
Reproducingthevariationthatwaspresentintheobservationstakesprecedenceoverlocalaccuracy.
AlthoughtheoverallpatternsofmasstransportareverysimilarinFig.3and4,theextremevalues
ofmasstransport,whichcreatemostsoilandcropdamage,aremoredistinctinthesimulatedmaps.
Furthermore,thesemapsemphasizethestrongvariationinmasstransport acrossshortdistances.
Table4.Calculatedsoillossesfromtheexperimentalplot
Net soilloss
Stormdate
Linear interpolation
Kriging
Mgha'
Mgha 1
13June
8.4
12.5
27June
2.0
2.0
30June
6.6
4.6
1July
26.4
26.8
Total
43.4
45.9
MappingWind-BlownMassTransport
Becauseofthisvariation,thetraditionalmethodofdescribingsoillossperunitarea(Table4)becomes
rathermeaningless(WilsonandCooke, 1980).Itismoreusefultodistinguisherosionanddeposition
areasintheplotfromdownwind gradientsingrayvalues.Positivegradients(from lightto dark)
areassociatedwitherosion,negativegradients(fromdarktolight)withdeposition,andzerogradients
withtransportonly.
Multipleconditionalsimulationsofonestormproducedifferent realizations,andthe differences
amongthealternativerealizationsprovideameasure ofspatialuncertainty (Deutsch andJournel,
1992).Foreachstorm,fivesimulationsweremadeandthe correlationbetween allpossiblepairs
ofrealizationswasdeterminedfrom250simulatedvaluesofeachrealization.Foraparticularstorm,
10correlationcoefficients (r)werecalculated,andthe average correlation coefficients were0.60,
0.74,0.77,and0.75,respectively,forthefour storms.Althoughmultiple simulationsofonestorm
areexpectedtobecorrelated, thehighdegreeofcorrelation suggeststhatthe simulated patterns
ofmasstransport represent the real,unknown sedimentation pattern. Hence,itisassumed that
21sediment catcherswas sufficient to characterizethe spatialvariation ofmasstransport inthe
experimentalplot.Multiplesimulationscanbeused aswellto determinetheminimumnumber of
conditioningdatapoints(orobservations)neededforreproducingthereference spatialvariability.
Inthisway, sampling schemes canbestatisticallytested ontheir performance.
Theinterpolated andsimulatedmapsarebasedonavariogrammodelthatwasestimatedfrom
four different storms, assumingasimilar spatial correlation structure for the storms. Totest the
validityofthisassumptionbyestimatingavariogramforeachstormwouldrequireasamplingscheme
withatleast50,butpreferably 100,catchersintheexperimental plot (Webster and Oliver, 1992).
Inwinderosionstudies,samplingatsuchahighdensityisusually notpossiblebecauseofthehigh
Table5.Resultsofcross-validationswiththeprogramXVOK2D.
Stormdate
MAEf
kgm'
RMAE{
1
%
13June
26.6
25.9
27June
4.6
29.9
30June
6.6
20.5
1July
38.9
26.0
t MAE=meanabsoluteerror.
J RMAE=relativemeanabsoluteerror(relativetotheaverage
masstransportvalue).
67
68
Chapter4
costsofequipmentandlabor. Asanalternative, itispossibletotestthe quality ofthevariogram
modelbymeansofacross-validation.Todoso,thevariogrammodelisusedtore-predicttheactual
observationsfrom neighboring observations. Cross-validation wasdonefor allfour stormswith
the GSLIB program XVOK2D(Deutsch and Journel, 1992),yieldingthe meanabsolute error
(MAE)andtherelativemeanabsoluteerror (RMAE),whichisthemeanabsolute error relative
tothestorm'smeanmasstransportvalue(Table5).Themeandeviationsbetweenpredictionsand
actualobservationsare«25%, anditisconcludedthatthequalityofthevariogramwas sufficient
for thepurpose ofthisstudy.
CONCLUSIONS
Mapsofwind-blownmasstransportwereproducedforfour stormsfrom21observationswith
krigingandconditionalstochasticsimulation.Bothtechniquesrequireinformation aboutthe spatial
structureofmasstransport,whichwasmodeledwiththevariogram.Tohavesufficient observations
for estimating the variogram, the four sampled storms were treated as independent temporal
replicates.Theobtainedvariogrammodel(Fig.2)showsthatthevariationintheobservationswas
mainlycausedbyspatialvariability,whereasnonspatialvariabilitywassmall.
Maps of storm based masstransport produced bykriging (Fig. 3)areuseful for quantifying
soillossesperunit areabut lessuseful for the study ofwinderosionprocesseswithinthe field.
Minimization ofthevariance oftheprediction error resulted inalossofthereal, observational
variation.
Mapsobtainedbyconditionalstochasticsimulation(Fig.4)reproducethe statisticalproperties
ofthe observations andbetter showthe spatialvariabilityinmasstransport. Thesemapscanbe
usedfordetailedstudiesoferosionanddepositionprocesseswithinthefield.Byusingageographical
information system, the spatial information on erosion and deposition can be combined with
information onsoilerodibility,crusting, surface roughness,topography, and crop characteristics.
Thismayleadto abetterunderstanding offield wind erosionprocesses.
Producingfivesimulationsfor eachstormresulted ingood correlationsbetweenthe different
realizations of a particular storm, indicating that 21 observations was enough for a full
characterization ofthe spatialvariability ofmasstransport intheexperimental plot.
MappingWind-BlownMass Transport
ACKNOWLEDGMENTS
The research was funded by the Netherlands Foundation for the Advancement of Tropical
Research (WOTRO). We thank theICRISAT Sahelian Center for providingthenecessary research
facilities and for the assistance during the field experiments. The technical assistance of P.J.J.F.
Torfs, G. Bier, and H. Stomphorst of the Wageningen Agricultural University for preparing this
manuscript is gratefully acknowledged.
REFERENCES
Cressie,N.A.C. 1991.Statistics for spatial data.JohnWiley&Sons,NewYork.
Deutsch, C.V., and AG. Journel. 1992. GSLIB: Geostatistical software library anduser's guide. Oxford
University Press,NewYork.
Fryrear,D.W.,J.E.Stout,L.J.Hagen,andED.Vories. 1991.Winderosion:Fieldmeasurement andanalysis.
Trans.ASAE34: 155-160.
Jacobs,A.F.G. 1984.Windreductionnearthesurfacebehind athinsolidfence.Agric.For.Meteorol.33:
157-162.
Journel,AG., andCh.J.Huijbregts. 1978.Mininggeostatistics.AcademicPress,London.
Kirkpatrick,S.,CD.GelattJr.,andM.P.Vecchi. 1983.Optimizationbysimulated annealing. Science220:
671-680.
McTainsh,G.H.,C.W.Rose,G.E. Okwach,andR.G.Palis. 1992.Water andwinderosion:Similaritiesand
differences, p. 107-119.In H.HurniandK.Tato(ed.)Erosion,conservation, andsmall-scale farming.
WalsworthPubl. Co.,Marceline,MS.
Mellerowicz,KT.,H.W.Rees,T.L.Chow,andI.Ghanem, 1994.Soilconservationplanning atthewatershed
levelusingtheUniversal SoilLossEquationwithGISandmicrocomputertechnologies:Acasestudy.
J. SoilWater Conserv.49: 194-200.
Morgan, R.P.C. 1986.Soilerosion andconservation. LongmanGroup,Essex,UK.
Schwing, J.F., and H.Vogt. 1980.An attempt at alarge-scalenon-experimental cartographic approachto
thevariabilityoferosionfeatures andlandsensitivitytoerosionintheAlsace(France)vineyards,p.207214.InM.DeBoodtandD.Gabriels (ed.)Assessmentoferosion. JohnWiley&Sons,Chichester,UK.
Skidmore,EL. 1988.Winderosion,p.203-233.InR Lai(ed.)Soilerosionresearchmethods. SoilandWater
Conserv. Soc,Ankeny,IA.
Stein,A.,andL.C.A. Corsten. 1991. Universalkriging andcokrigingasaregressionprocedure. Biometrics
47:575-587.
69
70
Chapter 4
Sterk,G.,andP.A.C.Raats. 1996.Comparisonofmodels describingtheverticaldistribution ofwind-eroded
sediment. Soil Sei.Soc.Am.J. 60: 1914-1919.(Chapter 3inthisvolume).
Webster,R.,andMA. Oliver. 1992.Sampleadequatelytoestimatevariograms ofsoilproperties.J. Soil Sei.
43: 177-192.
West,LT.,LP.Wilding,J.K.Landeck,andF.G.Calhoun. 1984.SoilsurveyoftheICRISAT Sahelian Center,
Niger,WestAfrica. TropSoils,TexasA&MUniv.,CollegeStation,TX.
Wilson,S.J., andR.U.Cooke. 1980.Winderosion,p.217-251.InM.J. Kirkby and R.P.C.Morgan(ed.) Soil
Erosion.JohnWiley&Sons,Chichester,UK.
Chapter 5
Wind-BlownNutrient Transport and SoilProductivity Changes
inSouthwestNiger
G. Sterk, L.Herrmann andA.Bationo
Published in:Land Degradation &Development 7:325-335.(1996).
Reproduced bypermission ofJohnWiley&Sons.
73
Wind-BlownNutrient Transport and SoilProductivity Changes
in Southwest Niger
ABSTRACT
Thisstudywasconductedtoquantify nutrientlossesbysaltationand suspension transport. During
twoconvectivestorms,massfluxesofwind-blownparticlesweremeasured inapearlmillet(Pennisetum
glaucum)fieldinsouthwestNiger,ona sandy,siliceous,isohyperthermic Psammentic Paleustalf. The
trapped materialatthreeheights(0.0S,0.26and0.50m)and asampleofvertically deposited dust were
analyzedfortotalelement(TE)contentsofK,C,N,andP.Thenutrient content ofthematerial at 0.05
mwassimilartothenutrient content ofthetopsoil.At 0.50m,thematerial wasthree times richer in
nutrientsthanthetopsoil,whereasthe deposited dust,trapped at 2.00m,was 17times richer. For all
four elements,a TE mass flux profile was fitted throughout the observations. From theTE profiles,
thefollowing nutrient lossesfrom theexperimental plot wereestimated: 57.1kgha"1K,79.6kgha"1
C,18.3kgha'1 N,and 6.1 kgha"1P.TheTE profiles showed amaximum valueinthe saltation layer.
Thesuspended TE mass fluxes abovethe saltation layer werean order ofmagnitude lower than the
saltationfluxes,butextendedtogreater heights.Therefore, saltation and suspension areboth able to
transport significant quantities ofnutrients.While saltation resultsin only a local redistribution of
nutrients, suspension may transport dust over thousands ofkilometers,resulting in a regional loss
ofnutrients.
R
ainfall inthe Sahelhas shown ageneral decline sincethe 1960's (Sivakumar, 1992). In the
1970's and early 1980's, droughts and several years of crop failure occurred. At the same
time,rapid population growth, with growth rates close to 3%per year during recent decades, has
resulted inan expansion ofthecropped area onto more marginallandwhichwaspreviously utilized
for communal grazing. Theuse ofthefallow system, which was traditionally applied for restoring
soilfertility, hasbeen dramaticallyreduced and cropyieldshavedeclined (Ramaswamy and Sanders,
1992). Consequently, the combination ofdrought and over-exploitation has caused desertification
on alarge scale. The land degradation processes include erosionbywater and wind and deposition
elsewhere, longterm reduction inthe amount and diversity of natural vegetation, and salinization
of soils (Dregne et al., 1991).
Inthe Sahel, severewind erosion occurs mainlyinthe first halfoftherainy season (May - July).
Then therainfall occurs inheavy thunderstorms that are often preceded by violent winds, which
74
Chapter5
resultinsevereerosionofunprotected soils.Agricultural damageistwofold: (i)youngseedlings,
whichare sownafter thefirstrains,aredamaged bysandblastingandburial,forcing farmers to
resowseveraltimesinsomeyears;(ii)decreasingsoilproductivityduetothelossoffertile topsoil.
Duringthedryseason(October -April),strongwindsmayalsoresultinmoderatewind erosion
(Michels, 1994),whereastheHarmattanwindsinthe second halfofthe dry season (January March) transport dustfromremote areas inthe Sahara towards the Sahel, where part of it is
deposited, enrichingthe soilswithfineparticles (Drees et al., 1993).
Inthewind erosionprocessthreetransport modescanbedistinguished: creep, saltationand
suspension(Bagnold, 1973).Creepparticlesarelargeandtooheavytobelifted bythewind. They
rollorslideoverthesurface. Saltationparticlesbounce overthe soilsurface, reachingmaximum
heights ofabout 1m,but thebulk of saltation particlesmovesjust abovethe soil surface. The
smallest particles areheld aloft bythewind as suspended dust. Thisdistinction inparticle size
classesforthedifferent transportmodesisonlyarbitrary.Atthetransition oftwomodes, particles
ofaparticular sizemaybemoved bybothmodes, depending ondifferences indensity andwind
speed.Here,thefollowing sizeclassesareused: suspension material,<63 urn;saltationparticles,
from 63to 500urn;andcreepparticles,>500 um.Duringaparticular event, creep cantransport
particleshorizontally from afew centimetersupto severalmeters. Thesaltationrangeisfrom a
fewmetersupto afew hundred meters,whereas suspended dust maytraveluptothousands of
kilometers.
Thelossofplantnutrientsfromsoilsisusuallyattributedto lossesbysuspension (e.g., Zobeck
and Fryrear, 1986a;Leysand McTainsh, 1994). Suspension selectively removesthefinest soil
particlesthat contain disproportionately greater concentrations ofplant nutrients (Young etal.,
1985).Althoughthereseemstobeaconsensusamongscientiststhat soillossesbysuspension are
themajor causeofdecreasingsoilfertilityinthesourcearea,noinformationisavailableonnutrient
lossesbysaltation and creep. Saltation, however, movesthemainmassofwind-blown particles
(Chepil, 1945),andthusmaybeanimportantcauseoflossesofplantnutrients.Creepisconsidered
notto result insignificant nutrient losses.Creepmainlytransports coarse sand,whichisusually
richinsiliconandpoor inplantnutrients.
Theobjectiveofthisstudywastoquantify nutrient lossesfrom a Sahelianpearlmilletfieldby
wind erosion. The distinction between losses by saltation and suspension is emphasized. The
contributions ofthesetwotransport modesto changesinsoilproductivity arediscussed.
Nutrient Transport andSoilProductivity Changes
MATERIALS AND METHODS
Afieldexperimentwasconducted attheInternational CropsResearch Institute for the Semi-Arid
Tropics (ICRISAT) Sahelian Center, abbreviated hereafter to ISC, during the 1993 rainy season.
The center islocated in southwest Niger, at Sadoré, 45 km south of the capital, Niamey. A field
was selected for the experiment that had been cropped with pearl millet (Pennisetum glaucum)
duringthe previousthreeyears. Thewholefieldwas planted with pearl millet on 14 June. Sowing
was done inplanting holes spaced 1mby 1mapart. Plant residues (millet stalks from the previous
crop)wereuniformly distributed over thefield,corresponding to a soilcover of 800 kgha"1. Within
thefield,an experimental plot of40 by 60 m was chosen. The distances from the plot boundaries
to obstacles in the upwind direction during storms exceeded 20 times the height of the obstacle
inallcases.Hence,itwasassumedthatduringstorms(i)thewindfieldintheplotwasnot significantly
disturbed bythose obstacles, and (ii)wind-eroded material was moving at the maximum transport
rate. The soilatthe selectedfieldisa sandy, siliceous, isohyperthermic PsammenticPaleustalf (West
etal., 1984),with92.2%sand,3.0% silt,and4.8%clayinthetopsoil. Theaggregate size distribution
ofthetopsoil (Table 1),determined by dry sieving ofsoil samples, showsthat the bulk of soil mass
is in the saltation size range.
Forthe measurements ofwind-blown masstransport, 21 Modified Wilson and Cooke (MWAC)
catchers(SterkandRaats, 1996)wereinstalledintheexperimentalplot(Fig. 1).TheMWAC catcher
has onelargevanethat ensures that the catcher is positioned facing into the wind. Seven erosion
traps are attached on a central pole at heights of 0.05, 0.12, 0.19, 0.26, 0.50, 0.75, and 1.00 m.
Eachtrap consists of a small (100 ml) PVC sample bottle, closed with a cap through which inlet
Table 1.Aggregate sizedistribution ofthetopsoil atthe
experimentalplot.
Size class
\im
Mass
%
<63
3.1
63-125
18.2
125-250
35.7
250 - 500
32.8
500-1000
10.0
> 1000
0.2
75
Chapter5
76
Row1
en
Row2
Row3
+
+
+
+
+
+
50*~*.
E 40**^
.E
+
+
r.
o
o
u
c
18
30
+
+
+
"
+
*•
+
+
£
20Q
+
+
+
+
+
+
+
10n
0
1
i
10
20
30
1
40
Distance east(m)
Figure 1. Positionsof21 MWACcatchersontheexperimentalplot.
andoutlettubesenterthebottle.Theseareglasstubeswithaninternal diameter of8mm,and are
eachbent at 90°outsidethebottlebutinoppositedirections.
Theefficiency oftheMWACcatcherfortrapping soilatISCwas determined inawind tunnel
(Sterk, 1993).Theoveralltrappingefficiency wasdennedastheratio ofmeasured masstransport
rate,determinedwiththeMWACcatcher(seenextsection),andthetotalmasstransport rate.The
totalmasstransportratewasobtainedbyweighingthe soilintraysbefore and after simulation of
astorm.Theaverageoveralltrappingefficiency from 12runs,withwind speedsvaryingfrom 9.9
to 11.5m s"1 was 0.49. Theefficiency showed norelationtowind speed.Whether thetrapping
efficiency isparticle sizedependent isnot known.
Fromtheweightofthetrappedmaterialsandthedurationofthe storm, meanhorizontal mass
fluxes q(z) (kgm"2s"1) atthe sampling height z (m)were calculated. Therelationship between
horizontalmassfluxandheightwasbestdescribedbyatwo-termmassfluxmodel(SterkandRaats,
1996):
NutrientTransportandSoilProductivityChanges
q(z) = a ( - + l)~b + cexp(--)
a
p
77
m
wherea,a,b,candßareregressioncoefficients. Themodeldescribestheverticalprofileofhorizontal
massfluxfromthe soilsurface (z=0)to anyheightz.Ittherefore includes creep, saltation, and
suspensiontransport.Foreachcatcherandstorm,Eq.[1]wasfittedthroughthemassfluxobservations
bynonlinearregression.Inthisstudy,Eq. [1]wasonlyusedto describethemassfluxprofile from
z=0to 1 m,sincenoobservationswereavailableatgreaterheights.Integration overheight (from
0to 1 m)resulted inameasured masstransport rateQ(kgm'1s'1)atthepoint ofsampling. The
totalmasstransportrateQ,ateachobservationlocationwasobtained bycorrecting for the overall
trapping efficiency oftheMWACcatcher.
Samplesfor nutrient measurementsweretakenateachrow ofsixMWAC catchers(rows 1,
2, and 3inFig. 1).Thetrapped materialswere collected atthreeheight levels,thelowestlevel
(0.05m),thefourth samplinglevel(0.26m),andthefifthsamplinglevel(0.50 m). Samplesfrom
the sameheight ineach separate rowwere grouped sothat therewereninesamplesper storm.
Soilsampleswerealsotakenfromthetopsoilinthe experimental plot. Some soilwastaken from
thetoplayer(0-0.02m)nexttoeachcatcher.Onesoilsamplewasmadeforeachrowofsixcatchers
bygrouping the sixsamples.
Apartfromhorizontalparticletransport atthemilletfield,vertically oriented dust deposition
wasmeasuredoverthesameperiod. Tworectangular bulk deposition samplerswereinstalled at
2mheightinafallow areaat »1 kmfromthemeasurementfield.Thesesamplershaveacollection
surfaceof0.18m2andarecoveredwithapolyethylenemesh(meshsize2mm).Themesh prevents
birdsandinsectsfromentering,andalsoavoidsresuspensionofdustonceithassettled.Dustdeposition
duringthesamplingperiodmainlytookplaceasrainwash-out(Herrmannet al., 1996). Therefore,
the deposition rate atthefallow siteisapproximately equaltothedeposition atthemilletsite.
For allsamples,thetotal element (TE) contents ofpotassium (K),phosphorus (P), nitrogen
(N),andcarbon(C)weredetermined.TotalKandPweremeasuredbyX-rayfluorescence (Siemens
SRS200).Thesampleswereground(<20|im),mixed 1:1 withMowiol(polyvinylalcohol),pressed
intotablets,andmeasuredagainststandardsusingaCr-anode.Total CandNweremeasured with
agasChromatograph(CarloErbaNA 1500).Inthisprocedure, ground samples(20-50mg)are
burnt. ThenCisoxidized to C0 2 byCr203 and Co304 at 1020°C,andNisreduced to N2byCu
''
78
Chapter5
at600°C.TheresultingC0 2andN2arequantified bythermal conductivity against areference gas
(He).
AccordingtoZobeckandFryrear(1986a),theextractablecationcontentofwind-erodedmaterial
asafunction ofheight canbedescribedwithasimplepower function:
X(z)=pz*
[2]
whereXistheextractablecationcontent(mgkg"1),andpandqare(positive)regression coefficients.
Theequationshowedgoodcorrelationsbetweenfitted andmeasured extractable cation contents
ofNa,Ca,Mg,andK.LeysandMcTainsh(1994) havepublished data ofthe contentsof organic
C,totalN,andtotalPinwinderosionsamplesatsevenheights.Comparisonwiththesedatashowed
that Eq. [2] accurately described the vertical profiles of C, N, and P (R2 = 0.88, 0.98, 0.97,
respectively),andtherefore Eq. [2]wasused inthisstudyasamodelfor thevertical distribution
oftheTEcontentwithheight.Inthismodel,theTEcontent iszero atthesoilsurface, suggesting
thatcreepisnottransportingplantnutrients.MultiplicationofEq. [1]andEq.[2]yieldsanequation
that describesthevertical profile ofTEmassflux:
f(z) = pz«[a(i. + I)"" + cexp(-|)]
a
p
[3,
wheref(z) isthehorizontalmassflux (mgm"2s"1)ofacertain element atheight z.TheTEmass
fluxprofileswerenumericallyintegratedoverheightfromz=0to 1 m.ThetotalTEmasstransport
ratesF,(mgm'1s"1)wereobtainedbycorrectingmeasured TEmasstransport ratesfor theoverall
trapping efficiency oftheMWACcatcher.
RESULTS
Ingeneral, thunderstorms inthe Sahelmovefrom easttowest. Thewind direction duringa
stormisusuallyeasterly, butmayvaryfrom northto south depending onthe location relativeto
thecenterofthestorm.Althoughmanythunderstormsoccurredduringthe 1993rainyseason, only
fourwereprecededbyperiodsofstrongwindsresultinginwinderosion(Table2).Thewinddirection
duringthe stormsvaried from southeast to south.
ForeachMWAC catcher and storm, Eq. [1]wasfitted through themeasured massfluxes at
sevenheights.Ingeneral,thefitted massfluxprofiles showed good agreement with observations.
'
Nutrient Transport andSoilProductivity Changes
79
Table 2.Descriptive statistics offour storms atICRISATSahelianCenter, 1993rainyseason.
Date
Duration
Wind speedf
Wind direction
1
Q{
Soilloss§
-1
1
Mg h a 1
s
m s'
13 June
1481
10.3
SE
69.3
12.5
27 June
1320
7.6
S
11.8
2.0
30 June
1321
8.9
SE
24.1
4.6
1 July
3004
9.2
SSE
49.9
26.8
g m s'
f Meanwindspeedmeasured at2m.
J Averagevalueof21totalmasstransportrates.
§ ForcalculationprocedureseeSterkandStein(1997).
Average deviationsbetweenmeasured and calculated massfluxesincreased from 0.1% atthe lowest
sampling level to 38.0% at the highest level (Sterk and Raats, 1996). Figure 2 shows two fitted
mass flux profiles for one catcher during the storm events of 13 June and 1 July. Note the
underestimation ofmeasured massfluxesat0.75 and 1.00 m during the erosion event of 13 June.
Fromthefittedmassflux profiles, thetotalmasstransport rates(Q t ) per catcher were calculated.
The average values (Table 2) show that interms of mass transport the magnitude of the storms
was variable. Soil losses from the experimental plot were calculated from storm based maps of
masstransport (Sterk and Stein, 1997). The losses were rather different, showing that high mass
transportratesdonotnecessarilyleadtohighsoillosses.Thestormdurationandthespatialdistribution
of mass transport also have important effects on the resulting soil loss.
The stormsof 13Juneand 1Julywere strong enoughto provide sufficient quantities of trapped
material for chemical analyses. Two dust sampleswere collected on 9 July, and were grouped into
one sample. This represented the deposition from 7 June until 9 July at the fallow site. The total
dust deposition over this period was equal to 0.24 Mg ha"1.
The TE contents ofthetopsoil (Table 3) do not show any significant differences between rows.
Therefore, the average values ofthe three rows were used for comparison with the TE contents
ofthewind-blown material. Thevalues obtained are very similar to those reported by West et al.
(1984),who described soilprofiles andtopsoilproperties ondifferent fields atISC.TheTE contents
ofthe material trapped with the MWAC catchers show only slight differences between the three
rows.Betweenthetwostorms,somedifferences weremanifest, mainlyatthe0.50mlevel.Ingeneral,
theTEcontentsincreased withheight.However, duringthefirststorm some exceptionswere found.
Chapter5
80
0.001
Height (m)
0.001
Height (m)
Figure2.FittedprofilesthroughmeasuredmassfluxesforoneMWACcatcherduringthewinderosionevents
of(A) 13Juneand(B) 1 July 1993.
Nutrient Transport andSoilProductivity Changes
81
Table3.Totalelementcontentsofthetopsoilintheexperimentalplot, adustdeposition sampleina fallow
site,andthematerialstrappedwith 18 MWACcatchersduringtwostormsatICRISAT Sahelian Center, 1993
rainyseason.
Row
Height
m
Topsoil
K
C
N
P
%
%
%
mg kg' 1
1
0
0.10
0.15
0.05
145
2
0
0.12
0.19
0.04
144
3
0
0.12
0.18
0.04
146
AVG
0
0.11
0.17
0.04
145
Dust sample
-
2.00
1.10
5.36
0.79
728
13 June
1
0.05
0.13
0.19
0.03
130
2
0.05
0.12
0.26
0.04
137
3
0.05
0.14
0.23
0.03
160
1
0.26
0.20
0.50
0.07
176
2
0.26
0.19
0.36
0.04
153
3
0.26
0.24
0.36
0.06
150
1
0.50
0.21
0.40
0.08
140
2
0.50
0.23
0.61
0.09
161
3
0.50
0.24
0.53
0.08
193
1
0.05
0.15
0.23
0.04
151
2
0.05
0.14
0.26
0.03
134
3
0.05
0.13
0.26
0.03
110
1
0.26
0.29
0.47
0.06
203
2
0.26
0.28
0.47
0.05
227
3
0.26
0.28
0.40
0.05
177
1
0.50
0.46
0.70
0.10
389
2
0.50
0.44
0.83
0.08
234
3
0.50
0.47
0.89
0.09
238
1 July
For example, the C content in the first row was lower at 0.50 mthan at 0.26 m. This is probably
due to the relatively larger measurement errors for the low quantities trapped at 0.50 m.
The ratio of the amount of a particular element inthe transported material to the amount of
that element inthe parent soilisdefined asthe enrichment ratio (ER). Average ER values for both
storms (Table4) indicatethat atthelowest level(0.05 m)the chemical composition of the erosion
82
Chapter5
Table4.AverageenrichmentratiosofadustsampleandtrappederosionmaterialsfortwostormsatICR1SAT
SahelianCenter, 1993 rainyseason.
Enrichmentratiof
Height
K
C
Dust sample
2.00
10.00
31.53
19.75
5.02
13 June
0.05
1.18
1.33
0.83
0.98
0.26
1.91
2.39
1.42
1.10
0.50
2.06
3.02
2.08
1.14
0.05
1.27
1.47
0.83
0.91
0.26
2.58
2.63
1.33
1.40
0.50
4.15
4.74
2.25
1.98
1 July
N
t RatiooftheTEcontentoftheerodedmaterialtotheTEcontentofthetopsoil.
materialwasvery similar tothat ofthetopsoil. Thematerial atthehighest samplinglevel(0.50
m)wasaboutthreetimesricherinnutrientsthanthetopsoil,whereasthe sampleofdeposited dust
was 17times richer.
FittingEq.[2]toallTEcontentsresultedinfourpairsofregressioncoefficients for eachstorm
androwofMWACcatchers.Thefittedmodeldescribedthemeasuredvaluesreasonablywell,with
meanR2valuesof0.97,0.90,0.88,and0.71 forK,C,N,andP,respectively.Useoftheregression
coefficients ofEq. [1]andEq. [2]inEq.[3]resultedinthemassflux profile, f(z), ofeachelement
inthetransported material.Figure3showstwofitted curves ofpotassium for the samecatcher
asinFig.2.Thefittedcurvesfor theotherelementsresulted insimilarshapes.
Nutrient losses from theexperimentalplotwereestimated from thetotal TEmasstransport
rates(F,).Amassbudget(AFt)for theplotwas determined for both storms(Table 5).Thetotal
TE mass transport rates along the four plot boundaries were averaged. For this purpose, the
outermost rowswithMWAC catcherswerechosenasboundaries. Themeanwind direction of
astormdetermined theboundariesthat contributed to input (F,i) andtheonesthat contributed
to output (F, Î) of erosionmaterial. Duringboth storms, the materialmoved intotheplot over
the eastern and southernboundaries, and left theplotviathenorthern andwesternboundaries.
Multiplying AFt with halfthe circumference ofthe plot and the storm duration resulted inthe
nutrient lossesfromtheplot,whichwereconverted tokilogramsperhectare.
P
NutrientTransportandSoilProductivity Changes
83
400
Height (m)
400
0.4
0.6
Height (m)
Figure3.Fittedprofilesthroughmeasuredpotassiummassfluxesfor oneMWACcatcherduringthestorm
eventsof(A) 13Juneand(B) 1 July 1993.
1.0
84
Chapter5
Table 5.Estimatednutrientlosses from theexperimental plotduringtwo storms at ICRISAT Sahelian Center,
1993 rainy season.
Date
Element
F.Jt
F,t{
1
mg m' s~'
13June
1July
AFt§
1
1
mg m' s"
Nutrientloss
1
mg m' s~'
kgha"
K
93.9
109.2
-15.3
11.2
C
157.2
188.9
-31.7
23.2
N
22.0
28.6
-6.6
4.9
P
9.9
11.1
-1.2
0.9
K
68.4
99.3
-30.9
45.9
C
120.3
158.3
-38.0
56.4
N
14.6
23.7
-9.1
13.4
P
5.3
8.8
-3.5
5.2
t F,l =averageincomingTEmasstransportrate.
X F,t =averageoutgoingTEmasstransportrate.
§AFt=Ftl -Ftt =TEmassbudget.
Comparedwiththeamountsofnutrientspresent inthefirst0.10mofthetopsoil,whichwere
calculatedfromtheTEcontentsofthetopsoil(Table3)andadrybulkdensityof 1650kgm"3 (Klaij
andHoogmoed, 1989),theestimated nutrientlosseswereequalto 3.2%, 2.8%,2.8%,and2.6%
ofthetotal for K, C,N, andP,respectively. Nutrient inputbydust depositioninthefallow site
overthesameperiodwassimplycalculatedbymultiplyingthetotal dust inputbythe TE contents
ofthesample(Table3),resultingininputsof2.5 kgha"1 K, 13.0kgha"1 C, 1.9 kgha"1 N,and 0.2
kgha"1 P.
DISCUSSION
Thehorizontalmassfluxofwind-blownmaterialdecreases stronglywithheight (Fig.2).Just
above the soil surface, saltation isthe dominant transport mode,whereas suspension becomes
dominantaroundthe 1 mlevel.At0.50 m, saltationand suspensionareequallyimportant (Sterk
andRaats, 1996).Thefollowing (arbitrary)heightclassesweredistinguished:(1)0-0.15 m,where
saltationisdominant;(2)0.15-0.85 m,wheresaltationand suspension arebothimportant; (3)
0.85-1.00m,wheresuspensionisdominant;(4)>1.00m,wherethereisonlysuspensiontransport.
As stated earlier, itisnotknownwhether theefficiency ofthe erosiontrapsisparticle size
dependent. Saltationparticlesaregenerallyeasiertotrapthanparticlesmovinginsuspension (Shao
etal., 1993).IfthisisalsotruefortheMWACcatcher,themeasured suspensionmassfluxeswere
NutrientTransportandSoilProductivityChanges
underestimated,whichisirrelevantinthefirstheight class,but not inthe second andthird height
classes.
Thecalculated TEmassfluxprofiles (Fig.3)showthatthemainmassofnutrientsistransported
inheight class (1),where saltationisdominant. ThesehighTEmassfluxescanbeexplainedby
thepresenceofsmallaggregates. Theaggregate sizedistribution ofthetopsoil (Table 1)shows
thatonly3.1%is<63urn,whereasdispersed particle sizeanalysisrevealedthatthereis7.8%of
siltandclayinthetopsoil. So,muchofthefine,nutrient-richmaterialisnotpresent asdispersed
particles,buthasformed particlebonds.Thelargeraggregatesaretransportedbysaltation,whereas
theverysmallaggregatesstillcanbetransported bysuspension (Zobeck andFryrear, 1986b).In
thesecondheightclass,theTEmassfluxdecreaseswithheight,firstsharplyandthenmoregradually
assuspensionbecomesmoreimportant.Inthethirdandfourthheightclasses,thegradual decrease
oftheTEmassfluxcontinues.
Ingeneral, suspended dustisricherinnutrientsthanthe coarser saltationmaterial(Table3),
owingtoahigherpercentageofclayandsiltparticles(ZobeckandFryrear, 1986b).Thesuspension
particlemassfluxes,however,aremuchlowerthanthesaltationmassfluxes,evenwhenthey are
underestimated bythe MWAC catcher. Theresulting TEmassfluxesmoved bysuspension are
anorderofmagnitudelowerthanthesaltationTEmassfluxes,butareextendedtoaheightofseveral
hundredmeters,andthussuspension canalsotransport considerable amounts ofplantnutrients.
Saltationtransportcanonlyresultinalocalredistribution ofsoilparticles andnutrients. Once
picked upbythewind, saltating soilparticlesaremoved inadownwind directionuntilthey are
depositednearsomeobstaclesuchastrees,bushes,fences, etc.InsouthwestNiger, the landscape
isdominatedbyoldlatériteplateaus and aparkland, with scattered trees andbushes,onthe sand
plainsbetweentheplateaus.Theparklandisdominatedbymilletfieldsinwhichtheshrubsareusually
cutdownatthebeginningofthegrowingseason,butregrowafterthecropisharvested. Although
there ismuchlessthan afew decades ago,thereisalsofallow landwithadenservegetation of
bushes,grasses,andherbs.Therefore, saltationleadstoshortrangetransport,withthemainsources
ofsoilparticlesandnutrientsbeingthebaremilletfieldsinthedry season and earlyrainy season,
andthemainsinksbeingthefallow areaswithgoodvegetationcover.Thefertility statusofafallow
siteisimproved attheexpenseofdecreasingsoilproductivityinthesurrounding milletfields.This
situationhastwoimplications.First,thenutrient lossesfrom thecropped areasmeanarestricted
cropping period relativeto thepotential. Second, the crop-fallow systemfunctions onlywitha
85
86
Chapter5
sufficientareaoffallowland,otherwisetheregionalbudgetofsaltationparticlesandnutrientsbecomes
negative.Thefirstindicationsofsuchanegativebudgetweregivenfor theMaradiregion insouth
Niger andwere explainedbyagricultural over-use (Mainguet and Chemin, 1991).
Thefunction offallowvegetationintrappingsoilparticlescanbesimulatedbyadequate mulch
cover. Geiger etal.(1992)measured differences of0.15to 0.20 minsurface elevationbetween
mulchedandbaremilletplotsatISCinonlyfiveyears. They concluded thatthe elevated surface
was dueto entrapment ofwind-blownmaterial, andthe stabilization ofthe original soil surface
againstwinderosiveforces.Applyingmulchesondegraded surfacesmayevenresultinregeneration
ofthesoil.Trappingofwind-andwater-deposited sedimentsbytreebranches on abarren, crusted
surfaceresultedinnaturalrevegetationofthesurface after afew monthsintherainy season. This
revegetationwasrelatedtobetterfertilityandimprovedwaterinfiltration (ChaseandBoudouresque,
1987).Onasmallerscale,individualobstacles,especiallyshrubs,actassinksfor saltation particles
fromthesurrounding sourceareas. Thetrapped sedimentstend to accumulate around thebases
oftheshrubs,formingmicro-dunes.Thesedunesareknowntofarmersashavingthebestproductivity
aftertheshrubshavebeencutdown.Similarobservationsofnutrient-rich depositsnear obstacles
havebeenreported from Australia(Ludwigand Tongway, 1995).
Thesinksandsourcesfor saltationtransport arenot stable,but changewithtime.Millet fields
thathavebeencultivatedformanyyearsmaybeturnedintofallowland,becomingasinkforsaltation
material, and fallow siteswillbeused for crop production againafter afew years. Ifthesenew
fields are not well protected againstwind erosion, the siteswillchangefrom sinksinto sources
for saltationmaterial.Furthermore, mulchcovers onaparticularfieldmaychangefrom yearto
yearduetothelimited availability ofmulches. Cropresidues arethemost easilyavailablemulch
material,butarealsoneeded for fuel, construction, and fodder. Inaddition, applied residues are
subjecttodecompositionbytermites.Therefore, milletfieldsusuallyhaveinsufficient mulchcover,
orthemulchisconcentrated onjust onefield,leaving otherfields unprotected.
Thefinesuspended dustwhichisraisedfrom thefieldbyaconvective stormmaybecarried
overlongdistances,resultinginalossoffineparticlesandnutrientsfromtheareaandthusenhancing
regionalsoildegradation.For example,Prospero et al.(1970)were abletotrace dust arrivingat
BarbadosfromacrosstheAtlanticOceantoaseverestormthatoriginatedinWestAfricafivedays
earlier.SimilarobservationsofdustcrossingtheAtlanticOceanwerereportedbyCarlsonandProspero
(1972) andWestphal et al. (1988). Apart from losses, there arealso inputs ofdust.During the
NutrientTransportandSoilProductivityChanges
Harmattan season,finesuspended dust istransported towardsthe Sahel,whereitpartly settles.
During the earlyrainyseason, someofthedustraisedbyaconvective stormisdeposited again
bygravity orrainwash-out. Drees etal.(1993)measured 50%ofthetotal annualdustinput at
ISCintheearlyrainy season,whereasthecontribution oftheHarmattan seasontothetotalwas
only 15%.Whether thereisanetlossorgainofdust dueto suspensiontransport inthe Sahelis
unclear. Soilsurfaces that arewellprotected against erosionbygood vegetation cover canonly
benefitfromdustdeposits.Forexample,wemeasured0.24Mgha"1 ofdustdepositioninthefallow
siteatISCduringthe 1993earlyrainy season,whereassoillossesbywind erosionfrom thissite
werenegligible owingto densevegetation that gave adequate protection to thesoilsurface. In
areaswithinadequateprotectionagainststrongwinds,soilsprobablylosemorefineparticlesthan
theygain.Thecalculatedtotalsoillossfromtheexperimentalplotduringthefour stormswasequal
to45.9Mgha'1(Table2). Usingtheroughassumptionthatthelossdueto suspension transport
was3.1%(=masspercentageofaggregates<63 uminTable 1)ofthetotal, the dustinputinthe
fallow wasequalto only 17%ofthe suspensionlossfromtheplot.
Theestimatednutrientlosses(Table5)fromtheexperimentalplotduringthetwo storm events
showthatwind erosion canremove significant quantitiesofplantnutrients. Compared withthe
nutrientinputsinthefallow siteduringthe sameperiod,the estimated nutrient losseswere 10to
30timeshigher.Theactualnutrientlossesfrom the experimental plot duringthe 1993earlyrainy
seasonwereevenhigherthantheestimated valuesbecauseof(i)the storm events of23Juneand
30June,and(ii)thesuspensionlossesabovethe1 mlevel.Furthermore,thepossibleunderestimation
ofthesuspensionmassfluxes mayhaveresulted inalowerestimateofthenutrientlosses.
Inotheryears,thesoilandnutrientlossesfrommilletfieldsareprobablymuchhigherthanthe
numberspresented here.The 1993rainy season,with onlyfour storms,was classified asaweak
wind erosion season. Duringtherainy seasonsofthepreviousthreeyears,21, 13,and 15wind
erosion events, respectively, were recorded at ISC (Michels, 1994). Considering the quantities
ofsoilmassandplantnutrientsthatcanberemovedbyasinglestorm,thenegativeimpact ofwind
erosion on soilproductivity insouthwestNiger canbevery seriousinsomeyears.
CONCLUSIONS
Thetwomodesoftransportofwind-eroded particles, saltation and suspension, have different
consequencesfor soilproductivityintheSahel.Onalocalscale,saltationmoves soilparticlesand
87
88
Chapter5
nutrientsovershortdistances,frombare,unprotected soilstowardsareaswithsufficient vegetation
ormulchcover,orindividualobstacleslikebushes.Inthesourceareas,soilproductivityisdeclining,
whereasthesinksareenrichedandhencesoilproductivityisenhanced.Onaregionalscale,saltation
doesnotnormallyresultinanetlossofnutrients.Itmerelycausesaredistribution ofsoilparticles
andnutrientsfrombare,arablefieldstofallowland.Whentheareaunderfallowbecomestoosmall,
saltationmayleadto anegativeparticleandnutrient budget.
Suspensionmaytransportnutrient-richdustfromtheSahelforthousandsofkilometers,exporting
nutrientsto other parts oftheworld. Atthesametime,the Sahelbenefitsfromdust depositions
duringtheHarmattanseasonandtheearlyrainy season. Areaswithagoodvegetation cover, like
fallow sites,particularlybenefitfromdustdepositions.Unprotected surfaces, however, losemore
fine soilandnutrientsbysuspensiontransportthantheygainfrom dust inputs. Thedata presented
arenotsufficienttopermitanyfinalconclusionstobedrawn,buttheyindicatethatasingleconvective
stormcanleadtoalossofnutrientsfromanarablefieldthatexceedsthetotalannualinputbydust.
Sincemorelandhasbeenturned into cropland inthelastfew decades,itislikelythat nowadays
thereisanetloss offinesoilparticles and nutrientsbysuspensiontransport inthe Sahel.
Asfar as soilfertility and agriculturalproduction areconcerned, the emphasis shouldbeon
(i)theprotection offields against erosivewindscaused byconvective stormsintheearlyrainy
season,and(ii)reductionofsaltationtransportwithinfieldsduringthedryseason.Soilandnutrient
conservationintherainyseasonallowsaprolongedandmoreeffective croppingonthelowfertility
soils in southwest Niger. Reduction of saltationtransport inthe dry season prevents irregular
distributionofnutrientsinthefield,makingcrop standslessheterogeneousbyimproving nutrient
availability. Withthe currentfarming practicesinNiger, soilconservation canonlybeachieved
byeffective useofcropresiduesasmulchcover.However, thepresentbiomassproduction isnot
sufficient for soilprotection. Furtherresearchisneededto explorethepossibilities ofalternative
mulchmaterial andtoincreasebiomass production.
ACKNOWLEDGMENTS
Theauthorsgratefully acknowledgethefinancial support oftheNetherlandsFoundation for
theAdvancementofTropicalResearch(WOTRO).TheassistanceandcooperationoftheICRISAT
SahelianCenterduringthefieldexperimentismuchappreciated.Thenutrientanalyseswereconducted
atthe Soil ScienceDepartment oftheUniversity ofHohenheim. WethankL. Stroosnijder and
Nutrient Transport andSoilProductivity Changes
P.A.C. Raats ofthe Wageningen Agricultural University for their constructive comments on an
earlier version of the manuscript.
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Stuttgart, Germany. 5-7 Dec. 1994.MargrafVerlag,Weikersheim, Germany.
Klaij,M.C.,andW.B.Hoogmoed. 1989.Cropresponsetotillagepractices inaSaheliansoil.p.265-275In
Soil,crop,andwatermanagementintheSudano-Sahelianzone.Proc.Int.Worksh.,Niamey,Niger. 11-16
Jan. 1987.ICRISAT,Patancheru,India.
Leys,J., andG. McTainsh. 1994.Soilloss andnutrient declinebywinderosion-causefor concern.Aust.
J. SoilWater Conserv. 7:30-35.
Ludwig,JA.,andD.J.Tongway.1995.Spatialorganisationoflandscapesanditsfunctioninsemi-aridwoodlands,
Australia. Landscape Ecology 10:51-63.
Mainguet,M.,andM.C.Chemin. 1991.WinddegradationonthesandysoilsofMaliandNigeranditspart
indesertification. ActaMech. [Suppl]2: 113-130.
Michels,K.1994.WinderosioninthesouthernSahelianzone:Extent,control,andeffects onmilletproduction.
VerlagUlrichE.Grauer, Stuttgart,Germany.
Prospero,J.M., E.Bonatti,C.Schubert, andT.N. Carlson. 1970.DustintheCaribbean atmospheretraced
toanAfrican duststorm.EarthPlanetary Sei.Letters 9:287-293.
89
90
Chapter 5
Ramaswamy,S.,andJ.H.Sanders. 1992.Populationpressure,landdegradation andsustainable agricultural
technologies inthe Sahel.Agric.Systems40:361-378.
Shao,Y.,G.H. McTainsh,J.F.Leys,andM.R. Raupach. 1993.Efficiencies ofsediment samplersforwind
erosionmeasurements.Aust. J. SoilRes. 31:519-532.
Sivakumar,M.V.K.1992.ClimatechangeandimplicationsforagricultureinNiger.ClimaticChange20:297-312.
Sterk,G. 1993.Sahelianwinderosionresearchproject, ReportIII.Descriptionandcalibration ofsediment
samplers.Dep.ofIrrigationandSoil&WaterConservation,WageningenAgric.Univ.,TheNetherlands.
Sterk,G.,andP.A.C.Raats. 1996.Comparisonofmodelsdescribingtheverticaldistributionofwind-eroded
sediment. SoilSei.Soc.Am.J. 60: 1914-1919.(Chapter 3inthisvolume).
Sterk,G.,andA.Stein. 1997. Mappingwind-blownmasstransportbymodelingvariabilityinspaceandtime.
Soil Sei.Soc.Am.J.(inpress).(Chapter4inthisvolume).
West,LT.,LP.Wilding,J.K.Landeck,andF.G.Calhoun. 1984.SousurveyoftheICRISAT Sahelian Center,
Niger,WestAfrica. TropSoils,TexasA&MUniv.,CollegeStation,TX.
Westphal,D.L.,O.B.Toon,andT.N. Carlson. 1988.Acasestudyofmobilization andtransportof Saharan
dust. J.Atmos. Sei.45:2145-2175.
Young,R A , A.E.Olness,CK. Mutchler,andW.C.Moldenhauer. 1985.Chemicalandphysical enrichments
ofsedimentfromcropland,p. 107-116.In ErosionandSoilProductivity.ASAE PublicationNo. 8-85.
Zobeck, T.M., andD.W. Fryrear. 1986a.ChemicalandphysicalcharacteristicsofwindblownsedimentII.
Chemicalcharacteristics andtotal soilandnutrientdischarge.Trans.ASAE29:1037-1041.
Zobeck, T.M., andD.W. Fryrear. 1986b. Chemical andphysicalcharacteristics ofwindblown sedimentI.
Quantities andphysicalcharacteristics. Trans.ASAE29: 1032-1036.
Chapter 6
Wind Erosion Controlwith Crop ResiduesintheSahel
G. Sterk andW.P. Spaan
Accepted for publicationin: Soil Science Society ofAmericaJournal.
Reproduced bypermissionofthe Soil Science Society ofAmerica.
93
Wind Erosion Controlwith Crop ResiduesintheSahel
ABSTRACT
MulchingforwinderosioncontrolinSahelianfarming systemsislimitedbylowbiomassproduction
anduseofcropresidues for other purposes.The aimofthis studywasto testthe effectiveness in soil
protectioncreatedbytwolowamountsofcropresidues.Afieldexperimentwasconductedin southwest
Niger,onaPsammenticPaleustalf (sandy,siliceous,isohyperthermic) duringtheearly rainy seasons
of1994and 1995.Particlemasstransport was quantified intwo plots of55by 70m.Duringthe first
stormsofbothseasons,theplotswerewithout a mulch cover.Afterward, oneplot was covered with
flatpearlmillet(Pennisetumglaucuni)stalks.Theapplicationrateswere 1500and 1000kgha"1during
thefirst andsecond seasons,respectively.Toquantify themulcheffect, mass transport rate differences
betweenthetwobareplotswerequantified with a multiplelinear regression model(R2=0.89),using
windspeed(7.4-12.3ms'1),wind direction, and storm duration (464-3835s).Total mass transport
rateswere reduced from 365.2to 132.9gm ' s"1(63.6%)with 1500kgha"1,and from 325.1to 188.0
gm's'(42.2%)with1000kgha"1ofcropresidues.Soilprotection tended to decreasewith increasing
wind speed. Linear regression indicated that the reduction inmass transport becomeszero at wind
speedsof11.1and 16.0ms"1forthe1000and 1500kgha"1covers,respectively.The 1000kgha"1cover
evenenhancedsedimenttransportby6.5%duringonestormwithawindspeedof 11.3m s"1.The 1500
kgha"1mulchcoverreducedsedimenttransportfrom49.7to80.2%duringfivestormswithwindspeeds
varyingfrom 8.3to 10.6ms'1, and istherefore recommended asthebetter application rate for wind
erosion control inthe Sahel.
W
ind erosion is a common phenomenon on sandy soils of the African Sahel. During the
dry season (October -April), strongHarmattanwindsblow from thenortheast and cause
moderate erosion (Michels et al., 1995a). The main erosion period, however, is during the early
rainyseason(May-July),whenseverebutshortduration(10-30min)windstormscreate spectacular
dust clouds.These stormsaregustfronts, formed bystrong downdrafts ofcold airin cumulonimbus
clouds, orthunderstorms, that bring the first rains of the new rainy season. Agricultural damage
bywind erosion is twofold. It may damage seedlings that are sown at the beginning of the rainy
season(Michelsetal., 1995b),anditcausesland degradationbythelossofnutrient-rich soilmaterial
(Sterketal., 1996a).
94
Chapter6
Mulchingisoneofthecheapestandmosteffective measurestoprotect the soilagainst erosive
winds.Furthermore,mulcheshelpreducewater erosion, reduceintense solarradiation, suppress
extremefluctuations ofsoiltemperatures, and reducewater lossthrough evaporation, resulting
inmore stored soilmoisture. Theseeffects helpto createimproved conditionsfor plant growth
inmanycircumstances (Morgan andRickson, 1995).
Testingtheefficacy ofmulchmaterialinreducingwind erosionhasmainlybeen doneinwind
tunnels(e.g.,Siddowayetal., 1965; LylesandAllison, 1981;Fryrear, 1985).Windtunnelshave
theadvantagethat experimental conditionslikewind speed,wind direction, and storm duration
can be controlled. Moreover, a certain storm canbe repeated as often asnecessary. Themain
disadvantage ofusingwindtunnels isthehomogeneous andlessturbulent flow compared with
theatmosphericboundarylayer,makingituncertainwhetherthelaboratoryresultscanbetranslated
to natural conditions. Inthefield,it ismuchmore complicated to dosimilar experiments.With
realstorms,thenumber, duration, averagewind speed, andwind directioncannot becontrolled.
Also,whentestingacertainquantityofmulchmaterial,themeasured soilerosioniscompared with
anunprotected controlplot. Thesoilsofthecontrol andthetestplotsmustbe equallyerodible,
thewindfieldduringstormssimilar, andthere should benomutualinfluence ofthemulched and
theunprotected plots.
FortheSahelianfarming systems,itisofspecialinteresttotesttheefficacy ofsmallquantities
ofcropresidueinreducingwinderosion.Althoughthebenefitsareobvious,mulchingisnotwidely
practiced. Stalksofpearlmillet(Pennisetumglaucum), whichisthemaincrop grownbySahelian
farmers, arebyfarthemostavailablemulchmaterial,but arealsoneeded for other purposes,like
fodder, fuel, andconstructionmaterial(LamersandFeil, 1993).Theavailability ofmilletresidues
for soilprotection istherefore limited.
ASahelianfieldexperimentwithflatmilletstalksrevealedthat asoilcover of500kgha"1does
not result inanoverall decrease ofparticlemassflux duringearlyrainyseason storms(Michels
etal., 1995a).However,clear differences existedbetweenindividual storms. Sediment transport
wasasoftenenhancedasitwasreduced.Amuchbetterprotectionofthesoilsurface wasobtained
with anamount of2000kgha"1,whichreduced theparticlemassflux onaverageby47%.
Underthecurrentbiomassproductionlevels,withanaveragemillet stoverproduction of2200
kgha"1(Manu et al., 1991), cropresidue amounts of2000kgha"1for soilconservation arenot
realisticinthe Sahel.Therefore, theeffect oflowerquantities onwinderosionwas studied. The
WindErosionControlwithCropResidues
objectivewastodeterminethereductioninwind-blownmasstransport created by 1000and 1500
kgha'1offlatmillet stalksduring earlyrainyseasonstorms.
MATERIALS AND METHODS
AfieldexperimentwasconductedattheInternationalCropsResearchInstitutefortheSemi-Arid
Tropics (ICRISAT) Sahelian Center (ISC)insouthwestNiger, duringthe 1994and 1995rainy
seasons.ThelocationofISC(13°16'N;202rE)is45kmsouthofthecapital,Niamey.Thunderstorms
intheearlyrainyseasongenerallymovewestward,andtheresultingwind direction duringastorm
isusuallyeast.Therefore, afieldwasselectedattheeasternsideofthecentertoreducedisturbance
ofthewindfieldbyobstacleslikefences,buildings,andexperimentalwindbreaksthat arepresent
at ISC. Theroughness oftheterraineastward ofthemeasurementfieldresembled the situation
intheregion, with scattered trees andbushes.Theheight oftheseobstaclesrangedfrom0.5 to
5m. Distances ofthemainobstaclestothecenter ofthefieldwere sufficiently largeto assume
thatthewind profile inthefieldwas onlynegligibly disturbed.
Thesoilatthemeasurementfieldisclassified asasandy,siliceous,isohyperthermic Psammentic
PaleustalfaccordingtotheU.S.soiltaxonomy(Westetal., 1984).Thetextureofthetopsoilconsists
of92.2%sand,3.0%silt,and4.8%clay.Thedryaggregatesizedistributionofthetopsoilisgiven
inTable 1.
ThesandySaheliansoilsoftenhaveastrong structural crust, formed byhigh-intensity rainfall
intheearlyrainyseason.Structuralcruststypicallyhavetwolayers(ValentinandBresson, 1992).
Table1.AggregatesizedistributiontoftopsoilattheICRISAT
SahelianCenter.
Size class
Um
Mass
%
<63
3.1
63-125
18.2
125-250
250- 500
35.7
32.8
500-1000
10.0
> 1000
0.2
t Thesizedistributionofdryundispersedparticlesdetermined
bydrysievingwithasetofvibratingsieves.
95
96
Chapter6
Atadepthofafewmillimeters,athinanddenseplasmiclayerisformed bytheclayandsiltparticles
thatarewashedoutfromthetoplayerbyraindrops.Theplasmiclayeriscoveredbyloose,cohesionless
sand,whichiseasilyerodedbywind orwater. Duringboth seasons,thecrustwasbrokentwice
byweeding,butreturned immediately duringthenextrain.
Priortoinstallationofequipment,thewholefieldwasclearedbyremovingweedsand residues
from theprevious crop.Pearlmilletwas sownon 17Juneduringthe 1994rainyseason, and on
21Juneofthefollowingyear. Sowingwassimilartothetraditional method,withplantingholes,
orpockets, spaced atthecornersofsquaresof 1 by 1 m.Ineachpocket, 50to 100seedswere
thrown, and2weeksafter emergencethenumber ofplantswasmanuallyreduced tothree.The
lowplantdensityandthelatesowingdatesassuredthatyoungmilletplantsdidnothaveasignificant
influence onthewindfieldduringthe experiments. Thesoilsurface betweenthemilletpockets
waskept clearofweedsbyhoeingat3and6weeks after sowing.
Thesizeofthefieldwas 170by90m,andwithinthefieldtwo experimental plotswith asize
of55by70mwereselected.Bothplotswereequippedwithtensedimentcatchersthatwereuniformly
distributedoverthewholeareaoftheplot(Fig. 1).Inthecenter ofPlotII(north),three acoustic
saltationsensors,orsaltiphones(SpaanandVandenAbeele, 1991),and ameteorology mastwere
placed.Themeteorologicalmeasurementsincludedprecipitation, wind speed, andwind direction.
Precipitationwasmeasuredwithatippingbucketraingauge,wind speedwithafast-response cup
anemometerat2mheight,andwinddirectionwasdetermined from thethreeorthogonal velocity
components measured withathree-dimensional propeller anemometer at 3m.
Thesaltiphonerecordsimpacts ofsaltating sand grainswithamicrophonewith amembrane
of201 mm2. Themicrophoneisplacedinsideasteeltube (diameter =0.05 m,length=0.13m)
thatprotectsitfromsevereweatherconditions.Thetubeismountedonaballbearingand hastwo
vanesatthebackto keepitoriented intothewind.
Duringerosion,partofthesaltatingsandgrainsmovingthroughthetubehitsthe microphone
andcreateshighfrequencysignals.Byamplifyingthesesignalsandfilteringlow-frequency signals,
saltating sand canbedistinguished from othernoiseslikethosecreatedbywind andrain. Every
amplified signal,orpulse,iscutoffafter 1 ms,so,theoretically,amaximumnumber of 1000grains
persecondcanberecorded.Theactualnumberofimpactsmaybehigherduetooverlap ofparticle
impactsduringthe 1 mspulse duration.
WindErosionControlwithCrop Residues
170
160
150
140
130
120
!+
;+
5
+
+
+
PlotII
+
Ü 11°
£ 100
° 90
g 80
« 70
+
;+
+
+
!+
+
+
eo
SO
40
30
20
10
()
;+
I +
+
+
+
+
PlotI
+
10 20 30 40 50 60
70 80 90
Distance east m)
Figure 1.Layoutofthemeasurementfield,withtwoexperimentalplotsandthepositionsoftheModified
WilsonandCooke(MWAC)sedimentcatchers.
Thethreesaltiphoneswereinstalledwiththecenter ofthemicrophonespositioned at0.10m
height.Thecreated pulseswerecontinuously recorded and storedwithasamplingfrequency of
1Hz.Theoutput,incountspersecond,showsthetemporalvariability ofthe saltationflux,which
wasused to determinethe exact startingtimeand durationofstorms.
Themassofsoilparticlesmovedbythewindwasquantified withModified Wilsonand Cooke
(MWAC)sedimentcatchers(Sterk andRaats, 1996). Thecatcher consists ofacentralpolewith
sevensedimenttrapsattachedbetween0.05and 1.00m.Alargevaneatthebackkeepsthecatcher
orientedintothewind. Eachtraphasa 100mlPVCbottle,withtwo glasstubes, aninletandan
outlet,enteringthebottlethroughthecap.Thetubeshaveaninternal diameter of8mm,and are
bent90°inoppositedirectionsontheoutside.Duringastorm, dust-ladenwind entersthebottles
throughtheinlet, airescapesthroughtheoutlet, andthesoilparticlesaretrapped inthebottles.
After eachstorm,thematerialinthebottleswascollected, dried, andweighed. Dividingthe
particlemassineachbottlebythestormdurationandtheareaoftheopeningoftheinlettuberesulted
97
98
Chapter6
insevenhorizontal massfluxes for eachcatcher. Throughtheverticalprofile ofhorizontal mass
fluxes, thefollowingmodelwasfittedwithanonlinearregressionprocedure(SterkandRaats,1996):
q(z) = a ( - + l)" b + cexp(-|-)
a
m
ß
whereq(z)isthehorizontalmassflux(kgm"2s"1)atheightz(m),anda,a, b,c,andß areregression
coefficients. Integratingtheprofilesacrossheightresultedinmeasured(orcalculated)masstransport
rates Q(kg m"1s"1)atthe sampling point. Theoretically theupper limitfor integration could be
takenatinfinity.However,nomeasuredmassfluxes above 1 mheightwereavailableto calibrate
the modelinthat height range.Giventhe strong decrease ofparticlemassfluxwithheight, itis
assumedthatthemassofsedimentmovingabove 1 misnegligiblecompared withthemassbelow
1m.Therefore, thelimitsforintegrationweretaken atz=0and 1 m.DividingQbythe trapping
efficiency oftheMWACcatcher, equalto0.49forthisSaheliansoil(Sterk, 1993;Sterk andRaats,
1996),resultedinatotalmasstransport rateQtatthepoint ofsampling. ThevalueofQ,isequal
tothetotalmassofparticlesbelow 1 mheight that passed, perunit oftime, astrip 1 mwideand
perpendicular tothemeanwind direction.
Inbothseasons,theplotswereleftbareforthefirst3 weeksafter installation ofthe equipment.
Thiswasdonetomakeacomparisonbetweenthetwoplotspossibleandto evaluatewhetherthe
plotswereequallyeroded during storms.Afterward the southernplot (Plot I)was covered with
milletstalks.Lengthofstalksrangedfrom0.5to 1.5m,withdiametersrangingfrom 10to 20mm.
Theapplicationrateswereequalto 1500kgha"1in 1994,and 1000kgha"'in 1995, corresponding
to estimated soilcovers of7.1and4.7%,respectively. Theresidueswereuniformly distributed
withoutaspecificorientationofthestalks,andredistributed everytimeafter weeding. Theweight
ofthematerialwas sufficiently highto assurethat stalkswerenotblown awayduringstorms.
Underbareconditions,thesoilsurfacewassmoothandwithout anyroughness otherthanthat
createdbythesoilparticlesthemselves,characterizedbyaroughnesslengthofapproximately0.001
m.Onlyjust after weeding theroughnesslengthincreasedto approximately 0.01m,but inboth
seasonsnowindstormsoccurredduringtheseperiods.Coveringthesoilsurface withmillet stalks
resulted inanincreaseinroughnesslengthto estimated valuesof0.02and 0.03 mfor the 1000
and 1500kgha"1rates, respectively.
l
'
WindErosionControlwithCropResidues
99
RESULTS AND DISCUSSION
Comparedwiththe 1993 rainyseason,whenfourerosivestormsoccurred(Sterket al., 1996a),
the 1994and 1995rainyseasonswere characterized bymanyerosion events.Intotal 20 storms
occurred,whichwererathervariableintermsofwind speed,wind direction, andduration (Table
2).Thisvariabilitycanbeexplainedbythelocal character ofthethunderstorms. Themost severe
conditionsareexpectednearthecenterofthecumulonimbuscloud,whereaforward, i.e.,eastward,
outflow ofcoldairoccurs(Cotton andAnthes, 1989).Awayfrom the center, conditions areless
severewithlowerwindspeedsandawinddirectionthatisshifted eithernorthward or southward.
Furthermore, the duration ofwind stormsislikelyto changewithpositionrelativetothe center
ofthecloud.Theprobabilityofraindecreasesawayfromthecenter,whichmaycause anextended
wind erosionperiod at the northern and southernlimits compared with the center. Hence, the
characteristicsofastormat acertainlocation depend onthedistancetothecenter ofthe cloud.
Thesimultaneousrecordingofwindspeedandsaltationfluxwithonesaltiphoneduringatypical
Sahelianstorm(Fig.2)clearlyillustratesthealternation ofquietperiods,withlittleactivity,and
intensebursts ofsaltationtransport. Agood correlationbetweeninstantaneouswind speed and
2000
1600
u. 1200x
•o
0)
CU
Q.
(O
•o
3
s
800
c
CO
400
6
9
Time (min)
Figure2.Graphofinstantaneouswindspeed(u)andsaltationflux(S)vs.timeforatypicalSahelianwind
erosioneventon13 July1995.
100
Chapter6
Table 2.Characteristicsf ofstormsduringthe 1994and 1995rainyseasonsatICRISAT Sahelian Center.
pioti
Date
u
Wdir
Dur
Cover
Q,
piotn
CV
Cover
CV
Q.
1 1
%
kg ha"
0
12.8
63.5
0
17.6
39.1
464
0
196.1
20.6
0
153.9
25.2
107.5
2007
0
12.7
33.7
0
7.0
29.2
15.8
47.4
942
0
ndj
nd
0
nd
nd
18 June
10.7
94.4
1209
0
56.6
17.4
0
50.8
21.0
27 June
9.4
118.1
515
1500
43.6
38.1
0
71.9
24.8
1 July
8.4
150.9
584
1500
16.6
105.9
0
71.7
27.7
4 July
10.6
81.2
838
1500
39.3
37.6
0
78.0
16.5
9 July
8.3
94.5
822
1500
10.2
58.2
0
21.6
27.2
0
40.3
18.5
1
degr
s
7 June
7.7
180.0
3835
10 June
12.3
37.8
14 June
7.4
15 June
ms'
kg h a '
g m' s'
1
-1 -1
gm s
%
1994
9.4
75.7
902
1500
23.2
19.0
28 May
8.6
160.4
1983
0
97.7
34.1
0
137.1
16.4
5 June
9.0
175.2
2157
0
21.5
69.4
0
52.7
15.1
13 June
9.1
153.8
600
0
117.2
21.6
0
119.5
14.4
14 June
11.1
37.6
1086
0
132.8
15.5
0
107.8
14.1
17 June
9.4
173.3
1893
0
63.7
34.2
0
99.0
18.4
20 June
8.8
160.4
1662
0
68.8
37.7
0
104.9
18.3
25 June
9.6
86.9
415
1000
41.7
33.9
0
74.0
22.7
0
65.0
16.8
12 July
1995
8 July
9.3
131.1
1092
1000
20.2
37.7
13 July
11.3
91.7
723
1000
118.2
17.5
0
123.8
16.1
16 July
8.9
175.6
1034
1000
7.9
96.0
0
54.0
28.6
t û = averagewindspeed;Wdir=averagewinddirection(0°=north);Dur=stormduration;
Q t = averagetotalmasstransportrate;CV = coefficient of variation.
I nd=notdetermined.
saltationfluxexists(r=0.76). Thebest correlation,however, isobtained ifatimelag of 1s between
saltationfluxandwind speed (r = 0.79) is assumed, indicating that the response time of saltating
sand grains to wind speed fluctuations is in the order of 1s (Sterk et al., 1996b).
WindErosionControlwithCropResidues
101
Forallstormsbutone,Eq. [1]wasfittedthroughthemeasured massfluxes ofeachcatcher.
Thedataofthestormof 15 June 1994werenotusedfortheanalysis.Thisstormwasimmediately
followedby25mmofraininonly35min.Althoughtheaveragerainintensitywasmoderatelyhigh
(42.9mmh"1),theinstantaneousvalueexceeded 100mmh"1 severaltimes,andcreated muchsplash
erosionwhiletheinstantaneouswindspeed exceeded 20ms"1.Part ofthe splashmaterial entered
thesedimenttrapsandgotmixedwithwind-blownmaterial. Thisproblemdidnot occur during
theotherevents, although severalwind stormswereimmediatelyfollowed byrain.During some
ofthose events splash materialhad clogged theinlettubes ofthelowesttraps,butitwasnever
observed to have entered thebottles.
Theaveragetotalmasstransportrates(Q t ; Table2)showthat significant differences between
thetwoplotsexistedwhenbothplotshadabaresoilsurface. Thedifference isnot consistent, but
changesfromstormtostorm,whichpartlycanbeexplainedbyavalanching(Chepil and Woodruff,
1963).Duringanerosionevent,themasstransportrateQtasafunction ofthedistance downwind
from anonerodibleboundaryincreasesfromzero attheboundarytoward amaximumtransport
rate.Withaneasterlywind,thedownwinddistancefromthenonerodibleboundary,i.e.,adirtroad,
to bothplots is similar. Hence, nobig differences inaveragemasstransport rates are expected,
exceptfordifferences causedbyspatialvariabilityinmasstransport. Withasoutherlyor northerly
wind,thesituationisdifferent, withoneplotbeingmuchcloserto thenonerodibleboundary than
theotherplot.Forinstance,duringthestormof5June 1995theaveragetotalmasstransport rate
inPlotI (south)was 60%lowerthaninPlot IIwhilethewindcamefrom the south. During the
storm of 10June 1994thewind directionwasnorth-northeast andthetotalmasstransport rate
wasthen27%higherinPlot I.
Todeterminetheeffect ofmilletresiduesonsedimenttransport, the difference inaveragetotal
masstransportrateswhenbothplotswerebareneedstobequantified. Althoughwind direction
isoneofthekeyparameters,linearregressionrevealedthatdifferences cannotentirelybe explained
bywinddirectiononly(R2=0.49).Therefore, amultiplelinearregression analysiswascarried out,
andathree-parameter model,usingaveragewind speed (u), averagewind direction (Wdir),and
storm duration (Dur),wasobtained (R2=0.89;n= 10):
A = 420.158 - 29.275Ü" - 0.995Wdir - 0.013Dur
[2]
102
Chapter6
whereAisthedifference (%) inaveragetotalmasstransport rates(Qt)betweenthetwoplots,
relativetoPlotII:
A = 100Q t f j Q m
[3]
Theeffect ofmilletresiduesonsedimenttransport wasdetermined byusingtheregressionmodel
andtheaveragetotal masstransport ratesinthetwoplots.First, Awascalculated withEq. [2]
from measuredwindspeed,winddirection, and stormduration. Thenthe averagemasstransport
rateinPlot Iwhenthe surfacewould havebeenbare(Q^)wasestimatedby:
% =Q g i ^
+
!)
[4]
Thereduction inaveragetotalmasstransport rates,Red(%), causedbythemillet stalksisnow
equalto:
Red = 100
tJ
_
^
Qu
Thecalculated values ofRed aregiveninTable3.
Bysummingthevaluesof Q TandQ'T,theaveragereductions inmasstransport during five
(1994)andfour(1995)events,respectively,werecalculated. Thetotalmasstransport rateswere
reducedby42.2%,from325.1to 188.0gm"1 s"1,withacoverof 1000kgha"1,andby63.6%, from
365.2to 132.9gm'1s"1,withasoilcoverof 1500kgha"1.It can,therefore, safely beassumed that
soillossesfrom theprotected plotwere significantly lowerthanfrom theunprotected plot.
Compared withtheresults ofMichelsetal.(1995a),whomeasured anaveragereduction of
47.1%inparticlemassfluxwithasoilcoverof2000kgha"1,bettersoilprotectionwithlower crop
residueamountswasobtainedinourstudy.TheyusedthesamefieldatISCandsimilarmulchmaterial,
but their experimental setup was entirely different. Theydivided thefieldintotwo rows ofnine
plotsof 19by45m,withthreereplicationsof0(control),500,and2000kgha'1treatments ineach
row(cross-overdesign).Suchasetuphasthedisadvantageofdifferent treatmentsinfluencing each
other.Particletransportinthecontrolplotswithprotectedplotsintheupwinddirectionwasreduced
[5 ]
WindErosionControlwithCropResidues
1Q3
Table3.Reductionsinaveragetotalmasstransportratescausedbytwodifferent soilcoversofflatpearl
milletstalks.
Date
Cover
Af
Q^t
Red§
kgh a '
%
27 June
1500
20.5
86.7
49.7
1 July
1500
17.2
84.0
80.2
4 July
1500
19.4
93.2
57.9
9 July
1500
74.0
37.7
73.0
12 July
1500
57.7
63.6
63.5
25 June
1000
47.6
109.2
61.8
8 July
1000
3.1
66.9
69.8
13 July
1000
-10.4
111.0
-6.5
16 July
1000
-29.6
38.0
79.1
gm's-'
%
1994
1995
t A=difference inaveragetotalmasstransportrateswhenbothplotswouldhavebeenbare,ascalculated
withEq. [2].
J Q'j =averagetotalmasstransportrateinPlotIifthesoilwouldhavebeenbare.
§ Red=reductioninaveragetotalmasstransportratescausedbythemulchcover.
duetothesheltercreatedbythemulch,resultinginalowincomingmasstransportrate.In contrast,
whenaprotectedplotisdownwind ofacontrol plot, the incomingparticlemassfluxisrelatively
highandthemeasuredparticlemassflux insidetheplot could behigherthaninthe situationwith
twoprotectedplotsfollowing each other. So,itislikelythatthemeasured reductionin sediment
transportcreatedby2000kgha'1ofmilletstalksdidnotreflectthepotentialreduction.Ontheother
hand, suchanexperimentalsetuphastheadvantage ofeverysingle storm actually contributingto
theestimateofthereductioninsedimenttransport.Withtheexperimental setupused inthis study,
about halfoftheerosion eventswereneeded to quantify differences insediment transport rates
betweenthetwoplots.However,itisbelievedthat quantifying differences between experimental
plotspriortotestingmulchesgivesbetter information, irrespective ofthenumber ofdatapoints.
Thereductionsintotalmasstransport rate (Table3) showacleartendency ofdecreasing soil
protectionwithincreasingaveragewindspeedofthestorm. Thisisillustrated inFig. 3,wherethe
following linear regression modelswerefitted throughthe datafor1000(R2=0.99;n=4)and
1500kg ha"1(R2=0.74;n= 5),respectively.
Chapter6
104
Red = 420.49 - 37.78u
[6]
Red = 152.02 - 9.47u
[7]
AlthoughtheR2valuesindicategoodcorrelationsbetweenreduction andwind speed, thenumber
ofdatapointswasnotsufficient foraproperanalysis.Hence,themodelsmayonlybeused to give
anindicationoftherelationbetweenwind speed andreductioninmasstransport.
Thedifference inprotectivequalityofthetwomulchcoversbecomesapparentwiththestrength
of a storm. During weak storms, defined as eventswithwind speeds varying from 7.5 to 10.0
ms'1,bothquantitiesgaveagoodprotectiontothe soilsurface. During strong storms,withwind
speedsexceeding 10.0ms"1,the 1000kgha"1ofmilletresidueswasnot sufficient. According to
thelinearregressionmodel(Eq.[6]),thereductioninsedimenttransportbecomeszeroatanaverage
windspeedof11.1 ms"1. Withstrongerstorms,erosionmayactuallybeenhanced(Fig.3).Although
thisobservationisbased ononlyonestorm, itissupported bythedata ofMichels et al.(1995a),
1UU-
\
\
"*
«•*
\
^
- ^
80-
•
""•-^
--60-
•o
40-
\
\
•
20-
1500kgha-1
\
\
A
\
1
1000kgha-
\
o-
\
-207.0
\
i
8.0
1
9.0
10.0
1
'
11.0
Wind speed (ms-1)
Figure3.Relationshipbetweenaveragewindspeedandthereductioninaveragetotalmasstransportrates
causedbymulchcoversof1500and1000kgha"1 offlatpearlmilletstalks.
12.0
WindErosionControlwithCropResidues
1Q5
andbythewindtunnel studyofEnninga (1994),whoobtained astrong enhancement oferosion
atlowsoilcoverrates.Ofthe20stormsduringtherainyseasonsof 1994and 1995,only sixstrong
stormsoccurred(Table2),whichindicatesthatsedimenttransportwouldhavebeenreduced effectively
during atleast 14storms.
Amulchcoverof 1500kgha"1 canreduce sedimenttransport effectively during strong storms
aswell.Theregressionmodel(Eq.[7])suggeststhat thereductionbecomeszero at awind speed
of 16.0ms"1.However, itremainsuncertain atwhichwind speed sedimenttransport isactually
reduced,sincetherewerenotenoughstrongstormstocalibratetheregressionmodelforhighaverage
windspeeds.Basedontherecorded storms(Table2),itisconcluded thatthemulchcoverwould
havesufficiently protectedthesoilsurfacefrom severeerosionduring atleast 19ofthe20storms.
Therelationship betweenwind speed andreductioninsedimenttransport was also observed
bySiddowayetal.(1965)andBilbroandFryrear(1994).Unfortunately, inneitherofthetwostudies
wasthisrelationship discussed inanydetail.Aphysicalexplanation ofthe decreasing efficacy in
soilprotectionwithincreasingwindspeedwasnotfoundinthewinderosionliterature.Forinstance,
anoften-applied techniquetoquantify theeffects ofroughness elements onthreshold wind speed
for erosionisdragor stresspartitioning(Raupach etal., 1993).Theoverall dragforce F canbe
partitionedintoaforceFrexerted ontheroughness elements,i.e., themillet stalks, and aforce Fs
exerted onthebare soilsurface betweentheroughnesselements:
F +F
Adecreaseinefficacy ofsoilprotectionwithincreasing averagewind speedwould suggestthat
theratioFr/Fsisnotconstant, but decreases,resultinginarelativelyhigher stress atthebaresoil
surface.However, intheliterature no evidenceexistsfor theFr/Fsratioto decrease significantly
withincreasingwindspeedwhenthe soilcoverisnot changing,whichwasthecaseinthisstudy.
Itcertainlycannot explainwhytheaveragemasstransport rateduringtheevent of 13July 1995
waseven6.5%higherintheprotectedplotthaninthebareplot.ThisimpliesanegativeFr/Fsratio,
whichisnot realistic, andthus, adifferent explanationhastobegiven.
Oneofthesimplifications ofthestresspartitioningtheoryisthatitavoids direct consideration
ofthenatureofturbulenceclosetothesurface(Raupachetal., 1993).Lylesetal.(1971)presented
wind tunnel data that show an important effect of roughness elements on turbulent velocity
fluctuations. Roughnesslowersmeanwindspeednearthesurface andshelterserodiblegrains.But,
[8]
106
Chapter6
atthesametime,increasingroughnesssubstantiallyincreasesvelocityfluctuations inthemean flow
direction. Inotherwords, therelativeturbulence intensity Tu,dennedas(Hinze, 1975):
T.-f
n
where ou(ms"1) istheroot meansquare(RMS)ofthefluctuating velocity component, and u is
theaveragewindspeed,ishigherfor arough surface thanfor asmooth surface. Furthermore,Tu
isindependentofwindspeedfor acertainroughness,butdecreaseswithheight abovethe surface.
Based onthese findings, it ispossibleto explainthereduced efficacy insoil protection with
increasingwind speed. Onarough surface, theaveragewind speed nearthe surface isreduced,
but theprobability distribution ofvelocityfluctuations ismuchwiderthan onasmooth surface.
ThisisexplainedbythehigherRMSvalue,whichisapproximately equaltothe standard deviation
ofvelocityfluctuations. Hence,theprobabilitythat highinstantaneousvelocities,relativeto the
averagewindspeed,occurishigherabovearoughsurfacethanaboveasmoothsurface. The effect
isenhancedbythelargeandpositiveskewnessofthe streamwisevelocityfluctuations over rough
surfaces (Raupach et al., 1991), whereas above smooth surfaces the velocity fluctuations are
approximately Gaussiandistributed (Sterk etal., 1996b).
Nearthethresholdwindspeedfor erosion,equalto 8ms'1for thissoil,roughness reduces the
averagewind speed belowthethreshold wind speed, but enhancesturbulence. Onlythose gusts
thatexceedthethresholdwindspeedareabletoerodesoilparticles.Withincreasing averagewind
speed,theprobabilitydistributionofvelocityfluctuations shifts toward thethreshold wind speed.
Thepositiveskewnessresultsinrelativelymore stronggusts,whicharethemainevents causing
particletransport (Fig. 2).Hence,thebenefits from roughening arebeinglost bytheincreasing
gustinessofthewind.Thiseffect isstronger for lowmulchcoversthanfor highcovers, sincethe
averagewind speed nearthe soil surface isreducedless.
CONCLUSIONS
Coveringthe soilsurface with 1500kgha'1offlat millet stalksgavegood protection against
erosive winds. On average, sediment transport was reduced by 63.6% during five storms. The
protectivequalityofamulchcover of 1000kgha"1 wasless,but stillreduced sediment transport
by42.2%duringfour storms.
Wind Erosion ControlwithCropResidues
1Q7
Ingeneral, the efficacy inreducing sediment transport decreased with increasing average wind
speed of a storm. This effect can be explained by an increase in the relative turbulence intensity
(Eq. [9])dueto the roughness elements. The decrease inprotection with wind speed was stronger
for the 1000 kg ha"1 cover since it reduces less the average wind speed compared with the 1500
kg ha"1 cover.
Both quantities ofmillet stalksprotected the soil surface sufficiently during weak storms, with
wind speeds between 7.5 and 10.0 m s'1. During strong storms, with wind speeds exceeding
10m s"1,the 1000kg ha"1mulch applicationwasnot sufficient, and even caused anincrease of 6.5%
in sedimenttransport during one storm with awind speed of 11.3 m s"1. The 1500 kg ha'1 mulch
application did still result in a 57.9% reduction of sediment transport during a strong storm with
a wind speed of 10.6 m s"1. However, some uncertainty exists as to which wind speed level this
application will still lead to a reduction in sediment transport.
Finally,itisconcludedthatthebetterapplicationrateofmilletresiduesforwind erosion protection
inthe Sahel is 1500 kg ha"1. A quantity of 1000 kg ha"1may protect soils against erosion during
weak storms,but involvestherisk ofincreasing erosion during strong storms. In years with many
strong storms, thereduction obtained duringweak storms could be nullified during strong storms.
ACKNOWLEDGMENTS
This research was funded by the Netherlands Foundation for the Advancement of Tropical
Research (WOTRO), andwas conducted inclose cooperationwiththe ICRISAT Sahelian Center.
Thelogistic support from ISC andthe assistance ofHabibou Halidou and Boubacar Soumana with
thefieldwork isgratefully acknowledged. We like to thank L. Stroosnijder and P.A.C. Raats for
their comments on a draft of this paper.
REFERENCES
Bilbro,J.D.,andD.W. Fryrear. 1994.Winderosionlosses asrelatedtoplantsilhouette area andsoilcover.
Agron. J. 86: 550-553.
Chepil,W.S.,andN.P.Woodruff 1963.Thephysicsofwinderosionanditscontrol.AdvancesinAgron. 15:
211-302.
Cotton,W.R., andRA. Anthes. 1989.Stormandclouddynamics.AcademicPress,SanDiego,CA.
108
Chapter6
Erminga,F. 1994.Thewinderosionprotection offlatmaizeresiduesonasandySaheliansoil.M.S.thesis,
Dep.ofIrrigation andSoil&WaterConservation,WageningenAgric.Univ.,TheNetherlands.
Fryrear,D.W. 1985.Soilcoverandwinderosion. Trans.ASAE28:781-784.
Hinze,J.O. 1975.Turbulence. 2nded.,McGraw-Hill,NewYork.
Lamers,J.P.A.,andR.P.Feil. 1993.Themanyusesofmilletresidues.ILEIANews! 9:15.
Lyles,L.,andB.E.Allison. 1981.Equivalentwinderosionprotectionfromselectedcropresidues.Trans.ASAE
24:405-408.
Lyles,L.,L.A.Disrud,andR.K. Krauss. 1971.Turbulenceintensityasinfluenced bysurface roughness and
meanvelocityinawind-tunnelboundarylayer.Trans.ASAE 14: 285-289.
Manu,A.,A.Bationo,andS.C.Geiger. 1991.FertilitystatusofselectedmilletproducingsoilsofWest Africa.
SoilSei. 152:315-320.
Michels,K.,M.V.K.Sivakumar,andB.E.Allison. 1995a.Winderosioncontrolusingcropresidue I. Effects
onsoilfluxandsoilproperties.Field CropsRes.40: 101-110.
Michels,K.,M.V.K.Sivakumar,andB.E.Allison. 1995b.WinderosioncontrolusingcropresidueII. Effects
onmilletestablishment andyields.FieldCropsRes.40:111-118.
Morgan,RP.C,andRJ.Rickson. 1995.Slopestabilizationanderosioncontrol:Abioengineering approach.
Chapmann&Hall,London.
Raupach,M.R, RA.Antonia,andS.Rajagopalan. 1991.Rough-wallturbulentboundarylayers.Appl.Mech.
Rev.44: 1-25.
Raupach,M.R,DA.Gillette,andJ.F.Leys. 1993.Theeffect ofroughnesselementsonwinderosionthreshold.
J. Geophys.Res.98:3023-3029.
Siddoway,F.H.,W.S.Chepil,andD.V.Armbrust. 1965.Effect ofkind,amount,andplacementofresidue
onwinderosioncontrol.Trans.ASAE8:327-331.
Spaan,W.P.,andG.D.vandenAbeele. 1991.Windborneparticlemeasurementswithacousticsensors.Soil
Technol. 4:51-63.
Sterk,G. 1993.Sahelianwinderosionresearchproject,ReportIII.Descriptionandcalibrationofsediment
samplers.Dep.ofIrrigationandSoil&WaterConservation,WageningenAgric.Univ.,TheNetherlands.
Sterk,G.,L.Herrmann,andA.Bationo. 1996a.Wind-blownnutrienttransportandsoilproductivity changes
insouthwestNiger.LandDegradationDevelopm. 7:325-335.(Chapter 5inthisvolume).
Sterk,G.,A.F.G.Jacobs,andJ.H.vanBoxel. 1996b.Theeffect ofturbulentflowstructures onsaltationsand
transportintheatmosphericboundarylayer.Submittedto:EarthSurf.Proc.andLandforms. (Chapter2
inthisvolume).
Sterk,G.,andPAC. Raats. 1996.Comparisonofmodelsdescribingtheverticaldistributionofwind-eroded
sediment. Soil Sei.Soc.Am.J.60: 1914-1919.(Chapter 3inthisvolume).
Wind ErosionControlwithCrop Residues
Valentin,C, andL.M.Bresson. 1992.Morphology,genesis andclassification ofsurface crustsinloamyand
sandysoils.Geoderma55:225-245.
West,L T , L.P.Wilding,J.K.Landeck,andF.G.Calhoun. 1984.SoilsurveyoftheICRISAT Sahelian Center,
Niger,WestAfrica. TropSoils,TexasA&MUniv.,CollegeStation,TX.
109
Chapter 7
Farmers' KnowledgeofWind Erosion Processes and
Control MethodsinNiger
G. Sterk andJ.Haigis
Submitted to: Agricultural Systems.
113
Farmers' KnowledgeofWind Erosion Processes and
Control MethodsinNiger
ABSTRACT
On-station research onwind erosion processes inSahelianAfrica has revealed that wind-blown
particletransport forms aconstraintfor localcropproductionsystems.Thispaper describesthe results
ofanon-farm surveyonwinderosionprocesses and soilconservation practices.Interviews were held
with 138farmers from sevenvillages in southern Niger. Oftheinterviewed farmers, 6 3 % consider
wind-blownparticletransportasdamagingtotheircroppingsystems.Intheirview,seedlingsaredamaged
byscouringsand grains,orarelostwhenburiedinsand deposits.Production was said to be negatively
influenced byretarded growth and development ofthe crop.Nearly allfarmers reported to observe
differences betweenfieldswithrespecttowinderosion.Fieldsthat are mainly eroded were said to lose
fertility andproduce less,whereas deposition ofmaterial resultsin abetter fertility and production.
These differences occur also on a smaller scale,with erosion and deposition spots inthe same field.
Mostfarmers (96%) arefamiliarwithtechniquestoreducewinderosion,and92%applied oneor more
ofthosetechniquesinthefield.Theindigenoussoilconservation techniques are application of manure
andmulchingwithcropresiduesortreebranches.Newtechniquesaretreeplanting,natural regeneration
ofwoodyvegetation, and application ofzai,a method ofsoilpreparation from Burkina Faso.These
techniqueshavebeenintroducedintwovillagesby an agricultural development project. The farmers
who have applied these measures reported to have less wind erosion problems in their fields. It is
concluded that the stimulation of regeneration ofnatural, woody vegetation isthe most promising
measureto reducewind erosion problems in Niger.
L
and degradation and the consequent reduction of crop production potential is a serious
problem throughout the Sahelian zone of Africa. Increasing population pressure and
competingusesfor land haveresulted inreduced fallow periods and an expansion ofthe cropped
area into marginal land (Taylor-Powell, 1991). Infertile sandy soils common to the region are
susceptible to degradation by wind and water erosion, particularly when the natural vegetation
cover has been depleted. Water erosion ismainly a problem on the slopes of low mountains, or
plateaus,which occupy only aminorfraction ofthe area. Wind erosion, however, is a widespread
phenomenon throughout the Sahel, especially in the early rainy season (May - July) when erosive
storms occur locally (Sterk et al., 1996).
114
Chapter7
Despitethewiderecognitionofthepotentialproblemsassociated withwind erosion, it did not
getmuchscientific attentiontillthelate 1980's. Sincethen, afewfieldexperiments, mostly onstation,weredonetodeterminetheeffects ofwinderosiononcropsandsoils,andto test methods
for wind erosioncontrol. These studieshaverevealed that sandtransport may severely damage
youngcrops(KlaijandHoogmoed, 1993;Michels, 1994;Michelsetal., 1995a; Gaouna, 1996),
andsoilproductivitydeclineswhenfertiletopsoilisbeingremovedbywind(MainguetandChemin,
1991;Sterketal., 1996).Winderosioncanbecounteractedbytechnicalcontrolmeasures. Several
studieshaveshownthatparticletransportissufficiently reducedbyleavingcropresiduesasamulch
onthe soil surface (Michels et al., 1995b;Buerkert et al., 1996;Sterk and Spaan, 1997), orby
plantinglivingwindbreaksperpendiculartothepredominantwinddirectionduringstorms (Renard
andVandenbelt, 1990;Banzhafetal., 1992;Michels, 1994;Mohammed etal., 1995).Also,tillage
operations that create ridges at the soil surface may reduce soil particle transport (Klaij and
Hoogmoed, 1989).
Oneaspectthatwasnever considered inanyofthementioned studiesisthefarmers' opinion
aboutwinderosionprocessesandtheirneedfor controlmeasures.However, anydiscussion and
planning on wind erosion control must take into account farmers' views (Rinaudo, 1996).
Understanding traditional land management should be one of the references for improving or
designingwinderosioncontrolmeasuresthatfitintothelocalfarming systems(Ben Salem, 1991).
Forinstance,Neefetal. (1996),who studiedtheinfluence oflandright systemsonthe adoption
oferosioncontrolmeasuresinsouthwestNigerfound that customarytenure doesnot allownonowners of land to plant trees on borrowed fields. This creates an important constraint when
agroforestry systemsliketreewindbreaks shouldbe introduced.
Onlytwo reports ofon-farm studieswerefound intheliteraturethat includedwind erosion
asaperceivedagriculturalproblemintheSahel.InasurveyintheHamdallayewatershed, southwest
Niger,nearlyallinterviewedfarmers mentionedthatwind erosion causeslossesoffertile topsoil,
andreducesyieldswheneoliansedimentsburycropseedlings(Taylor-Powell, 1991).To copewith
theseproblems,thefarmers reported tohavechanged cropresiduemanagement byusingmillet
stalksasaprotectivemulchafterharvest.Rinaudo (1996)reported resultsofalong-term project
intheMaradiregion,southerncentralNiger.Ingeneral,conventionalwinderosioncontrolmethods
werenotadoptedbyfarmers. Good resultswere obtained, though,withfarmer-managed natural
regenerationofwoodyspecies,whichisacheapmethodthatfitseasilyintolocalfarming systems.
Farmers'KnowledgeofWindErosioninNiger
115
Inthisstudy,Sahelianfarmerswereinterviewed to ascertaintheir knowledge ofwind erosion
processesand control techniques. Theobjectives were (i)to evaluatetheimpact ofwind-blown
particletransportonlocalcropproduction systems, and (ii)to determinethetechniquesforwind
erosioncontrol appliedbyfarmers.
SURVEY METHODOLOGY
AsurveywasconductedinsouthernNiger, duringthe 1995rainyseason(May- September).
Semi-structured interviewswereheldwithlocalfarmers for data collection. Thismethod ispartly
inaccordancewiththetopicalRapidRuralAppraisal concept, that includes data collection from
othersourcesaswell(ConwayandBarbier, 1990).Atotalof 138 farmers from sevenvillageswas
interviewed. Thenames,locations, and othercharacteristics ofthe selected villages aregivenin
Table1.
Thesedentaryfarming systemscombinepastoral activitieswithrainfed crop production. The
maincropispearlmillet(Pennisetutnglaucum),oftenintercroppedwithcowpea(Vignaunguiculata).
Othercropsgrownbyfarmersfrom theselectedvillagesaresorghum {Sorghum bicolor),sorrel
{Hibiscussabdarifd), andgroundnut{Arachishypogaed).Sowing isgenerally doneafter the first
good rainevent inthe earlywet season. Inmilletintercropping systems,the second cropisnot
sownuntil2to 3weeksafter themillet (Spencer and Sivakumar, 1987).
Table 1.Characteristics ofselected villagesinthesurvey.
Mainethnic
Village name
Location
Sample size
group
0
Project
Name
Period
Sounga-Dossado
12°52'N;2 26'E
19
Djerma
Energy II
since 1994
Kirtachi-Seybou
W47U,2°2m
20
Djerma
Energy II
since 1994
0
,
14°15'N;3 26 E
20
Haussa
SAAf
1974-1987
Boulkass
13°49'N;3°05'E
19
Djerma
GTZ$
1992-1994
Serkin Hatchi
13°36'N;7016'E
Chical
Danldo
Liboré
27
Haussa
MIDP§
since 1981
,
13
Haussa
lyQDP
since 1981
,
20
Djerma
-
-
13°44'N;6°58 E
13°25'N;2°13 E
t ServiceArrondissementald'Agriculture.
Î Gesellschaft furTechnischeZusammenarbeit.
§ MaradiIntegratedDevelopmentProject.
116
Chapter7
Beforestartingtheactualinterviews,apre-surveywasheldwith15farmerstotestthequestionnaire,
andtogetanideaaboutthepossibleanswersgivenbyfarmers. Theused questionnairewassemistructured,withamixtureofopen-endquestionsandquestionswithcodified answers. It consisted
ofthreeparts.Thefirstpartdealtwithcropdamagecausedbywind-blown particletransport. A
distinctionwasmadebetweenplantlossesduetoburialinsandandplantdamagebyabrasion.Abrasion
damage iscaused by scouring sand grainsthat candamageleaves and stemsofplantsbut does
not necessarily killplants.Burial ofseedlingsindeposited sandisoften harmful, sincehighsoil
temperaturesduringdaytimemaykilltheplants(Michels, 1994).Inthe second part, farmers were
askedtodescribetheeffects oferosionanddeposition onsoilfertility atdifferent scales.Farmers
hadtoindicatedifferences between entirefieldsthat eithergainorlose soil,andbetween erosion
anddepositionspotswithinthesamefield.Thethirdpartdealtwiththetechniquesusedby farmers
toreducewinderosiondamage,includingtheinfluence ofnaturalvegetation onerosionintensity.
Becausefarmersinthe selectedvillagesonly speaklocallanguages,theinterviewswereheld
withthehelpofexperiencedinterpreters.Interviewsweregenerallyheldatthefarmers' compounds,
usuallyearlyintheevening.Theresulting databasewas analyzed for farmers' perceptions ofthe
threemaintopics,i.e.cropdamage,soilfertilityaspects,andcontrolmeasures.Ingeneral,nodistinction
between the seven different villages was made. Onlywhen farmers from certain villages gave
significantlydifferent answerscomparedwiththerest,thesedifferences weretakenintoaccount
and are discussed.
RESULTS AND DISCUSSION
CropDamage
Nearlyallfarmers reported to observeplantlossesduringthefirstweeksoftherainy season
(Table2). Seedlingsaremainlylostbylivestockbrowsing,butwind-blown sand and drought were
alsomentionedasimportantreasons.Plantsburiedinsandoftendiebecauseofreducedphotosynthesis,
theweightofthe sand deposits, andtheveryhighsoiltemperatures during daytime,resultingin
alowerplantdensity. Inextremecases,farmers areforced to resowtheirfields,whichresultsin
latedevelopmentofthecropand,therefore,alowerproduction.Cropsreportedtobeverysusceptible
tosandcoveragearemilletandcowpea. Sorghumandsorrelarelesssusceptible,whereasgroundnut
isthemostresistantcrop(Table3).Thediffering susceptibilitytosandcoverage ispossibly caused
bythedifference insowingdates.Milletandcowpeaareusuallysownduringtheearlyrainyseason,
Farmers' KnowledgeofWindErosioninNiger
117
Table 2.Farmers'perceptions ofplantlossesandplantdamage
intheearlygrowthstages.
Observation
Reason
nf
Yes
No
%
%
89
11
138
57
43
123
Drought
33
67
123
Sand transport
46
54
123
Other
48
52
123
80
20
138
Animals
40
60
111
Drought
32
68
111
Sand transport
59
41
111
Other
38
62
111
Plant losses
Animals
Plant damage
t n=numberoffarmers interviewedonspecific question.
Table 3.Susceptibilityoffivecropstolossesordamageduetowind-blownsandtransport.
Observationoflosses
Crop
VOf
STf
NVf
%
%
%
Observationofdamage
nî
VO
ST
%
%
NV
n
%
Millet
70
26
4
57
54
41
5
66
Cowpea
54
37
9
54
73
19
8
63
Sorghum
44
23
33
43
29
33
38
55
Groundnut
27
19
54
41
40
23
37
43
Sorrel
41
29
30
49
42
33
25
57
t VO=veryoften; ST=sometimes;NV=never
t n=numberoffanners plantingthespecific crops.
whenerosionactivityismostsevere.Theothercropsaresownlaterintherainyseason,when erosion
isusually less intense.
Apart from loosing entireplants,mostfarmers also reported to observe damaged plants in the
earlygrowth stages (Table2).Abrasion damage by sand transport was given as the main reason.
Animals, i.e. livestock browsing and insects, and drought were considered important reasons as
well.Thefarmers describedthedamagecausedbyblowing sand asburntparts onthe crop seedlings,
118
Chapter7
particularly onleaves,but also on stems.Itinfluences theirproductionbyretardinggrowthand
developmentofthecrop.Also,plants areweaker, but ingood rainfall yearstheinfluence onthe
totalproductionwassaidtobelimited.Aswithsandburial,milletandcowpeaarethemostsusceptible
crops. Sorghum, groundnut, and sorrelarelesssusceptible,but canalsobedamaged (Table3).
Theobservationsonmilletarepartly supported byresearchresults,but noinformation about
wind erosion damage onthe other crops exists.Michels (1994)concluded thatmillet seedlings
areparticularlydamagedbyburialinsand,but areveryresistant against abrasion. Ofallfarmers,
26%mentionedbothkindsofdamage,37%reported to haveonlyonekind ofdamage, and37%
didnotmentionsandtransportatallasareasonofproductionlosses.Hence,63%oftheinterviewed
farmers consider wind erosion apotential threatfor their crop production systems.
SoilFertility Aspects
Wind-blownsoilistransportedfromonelocationto another. Depending onwind speed, soil
materialiseithererodedfromunprotected areas,wherewindspeedisatitsmaximum,ordeposited
atlocationswherewind speed isreduced byobstaclesor roughnessofthe soilsurface. Farmers
were asked to point out differences insoilfertility, orproductionpotential, between areaswith
deposition ofsoilmaterialand areasfrom which soilisgenerally eroded.
Nearlyallfarmersindicatedtoobservedifferences insoilparticletransportbetweenfields(Table
4).Only6%ofthefarmerssaidtoobserveneithererosion,nordepositionintheirfields. Ingeneral,
itisbelievedthat sedimentistravelinglimited distances;from orto neighboringfields,although
somefarmersthinkthatthematerialmayalsotravelacrosslonger distances.Differences between
fields weresaidtobecausedbytopographicdifferences, andthepresence or absence oftreesand
soilconservation measures.
Ofthefarmersthatreportedtohavedeposition ofwind-blown materialinoneor more fields,
98%indicatedthatsoilfertility, andthusproductionpotential,oftheentirefieldisimproved.Several
farmers (14%) alsomentioned improved soilmoisture characteristics.
Contrary to improved soilfertility bydeposited material, soillosses areconsidered to result
indecreasingsoilfertility. Ofthefarmersthatreported tohaveerodedfields,97%saidthat either
soilfertility orproduction potentialisreduced inthosefields. Fewfarmers (5%) alsomentioned
worse soilmoistureproperties.
Farmers'KnowledgeofWindErosioninNiger
119
Table4.Farmers'observationsofwinderosionanddeposition
processes(n=138).
Yes
No
%
%
Depositioninentire field
87
13
Lossfromentire field
89
11
Transportwithin field
86
14
Observation
Apartfromdifferences betweenfields,86%ofthefarmers saidtoobserveredistribution ofsoil
materialwithinthesamefield(Table4).Again, erosion spots areconsidered to resultinreduced
fertilityandlowerproduction,whereasdepositionareasareconsideredtobecomericherinnutrients
andhaveahigherproductionpotential.
Thefarmers' perceptionsofsoilproductivity changesbywind-blown particletransport arein
agreementwiththeresearchresultsofSterketal.(1996).Inthatstudyitwasshownthatwind-blown
sandmaytransport considerablequantitiesofnutrientsoverlimiteddistances.Theyconcluded that
nutrientsareeithererodedfromunprotectedfieldsanddepositedinprotectedfields,orareredistributed
withinthe same field.
Control Measures
Before questioningfarmers about theirtechniquesfor wind erosioncontrol, theywereasked
whethertheyconsiderwinderosionaproblemfor their cropproduction.Most farmers (81%)do
consideritaproblem,mainlybecauseofdecreasingsoilfertilityand,toalesserextent,cropdamage.
Thefarmersthatdonotthinkthaterosionisaproblemreported earliertohavemainly deposition
intheirfields, andhence,theybelievetobenefit from nutrient-rich soildeposits.
Mostfarmers(96%)knowtechniquestoreducewinderosion, and92%applied oneor more
ofthoseinthefieldduringthe 1995rainyseason(Table5). Severaltechniqueslikemulchingwith
branchesweremorepracticed thantheywerementioned aswind erosioncontrolmeasures. This
indicatesthatsomefarmersdonotconsiderthosespecific techniquestoreducewind erosion. For
instance,farmersusebranchesoftreesandshrubsonbare,crustedspotsfor soilregeneration. The
organicmaterialattractstermitesthatbreakthecrust,butatthesametime,themulchmaterialmay
trapblowingsandandthusitalsoreduceswind erosion(Chase andBoudouresque, 1987).None
ofthefarmers mentioned windbreaks orridgingaspossibilitiestoreducewind erosion.
120
Chapter7
Table5.Knowledgeandapplicationofwinderosioncontrol
measuresinNiger(n=138).
Winderosioncontrolmeasure
Known
%
%
Mulchingwithmilletresidues
80
78
Mulchingwithbranches
46
52
Treeplanting
32
25
Regeneration ofvegetation
26
29
Applicationofmanure
30
33
7
23
Applicationofzaif
Practiced
t AsoiltillagemethodfromBurkinaFaso,usingpitsfilledwith
compostforsowingcrops.
Mulching increases soilroughness,whichgivesareduction ofthe surfacewind speed. Ifan
adequatemulchquantityisused,itisveryeffective inreducingwinderosion.However,thequantity
ofmilletresiduesavailableinthelowinputfarmingsystemsisgenerallynotsufficientforsoilprotection
(Michelsetal., 1995b;Sterk and Spaan, 1997).Althoughnot studied, itislikelythatthe sameis
truefor branches, giventhewidespread degradation ofwoody speciesinthe Sahel.
Planting oftrees and natural regeneration ofvegetation aremeasuresthat havean influence
onthewindfieldinacertain area. Theyareparticularly effective whenapplied onavillage scale
orlargerscales.Then,thetrees and shrubsact asroughness elementsandreducewind speedsin
thewholearea(Stigter et al., 1993).Furthermore, shrubswithdensecanopies startingnearthe
soilsurfacemaytrapwind-blown particles andprotect thesoilfrom erosion (Sterk etal., 1996).
Inaddition, moretreesand shrubs enhancetheavailability ofmulchmaterial.
Applicationofmanureandzaiarenotrealwind erosion control measuresbutmerely cultural
practicestoimprovesoilfertility. Fertilizationresultsinbetter growthand development ofcrops,
making plantsmore resistant against damage caused by sandtransport (Buerkert et al., 1996).
Moreover,biomassproductionwillbegreaterandthusmoremulchmaterialwillbeavailable after
harvest.However,applicationofmanureandzaiarealsolimitedbyinsufficient availabilityofmanure
and organicmaterialforzaipits(LamersandFeil, 1995).
Theknowledgeofthedifferent winderosioncontrolmeasureswasobtainedfromseveralsources
(Table 6).Treeplanting,natural regeneration of(woody)vegetation, andzai aremeasuresthat
havebeenintroducedandpromotedbyagriculturalprojects. Thesethreetechniquesweremainly
Farmers'KnowledgeofWindErosioninNiger
121
Table6.Sourcesofknowledgeofdifferent winderosioncontrolmeasures.
Sourceofknowledge
Father
Other
Farmer
%
%
Mulchingwithmilletresidues
37
Mulchingwithbranches
Extension
officer
Project
agent
Other
%
%
%
11
3
39
10
108
32
7
0
60
1
72
TreePlanting
0
0
0
94
6
34
Regeneration ofvegetation
0
0
0
95
5
40
40
7
2
13
38
45
0
0
0
100
0
32
Applicationofmanure
Applicationofzai%
t n=numberoffarmerspracticingthespecificwinderosioncontrolmeasure.
% AsoiltillagemethodfromBurkinaFaso,usingpitsfilledwithcompostforsowingcrops.
applied inthetwo villageswheretheMaradiIntegrated Development Project (MIDP)isactive
(Table 1).Althoughsomefarmersfromothervillagehaveknowledgeaboutthesenewtechniques,
onlyveryfew applied theminthefield. Application ofmanureandmulchingwith cropresidues
andtreebranchesaretheindigenoustechniquesforcontrollingwinderosion.Thelattertwomeasures
havebeenpromotedbyprojectsaswell. Onlyfour farmers reported tohaveobtained knowledge
aboutwinderosioncontrolfrom extension officers, whichindicatesthatthe extension serviceof
Nigeriseithernotadvocatingsoilconservationmeasures,orhasnotbeenactiveinthesevenvillages.
Mostfarmers(84%)believethatthewinderosionintensitychangesfromyearto year. Exactly
halfofthemsaidthatwinderosionisbecominglesseveryyear,whereastheotherfarmers believe
thaterosionisincreasingnowadays. Theformer group consisted mainlyoffarmers from the two
MIDPvillages(Table 1),wherewind erosion control measureshavebeen successfully adopted
(Rinaudo, 1996).Themainreasongivenfor the decreaseinparticletransport ismore and better
woodyvegetation.Theotherfarmersfromvillageswherewind erosionproblemswere said tobe
increasingblame drought and theremoval oftreesforfirewood.Allofthem areawarethat the
naturalvegetation canhelpto reducewind erosionbutthey apparently donot havepossibilities
tostimulateregenerationofthevegetation.AccordingtoRinaudo (1996),theft oftreesfor wood
is such a serious problem, that farmers haveno otherpossibilitiesthan to chop downthe trees
themselves.Furthermore, competitionwithcropsfor moisture andnutrientsisoften areasonto
removeyoungtreesandshrubsfromarablefields.
nt
122
Chapter7
CONCLUSIONS
FarmersfromsevenvillagesinsouthernNigerviewwind erosionasaserious constraint for
theircropproductionsystems.Ingeneral,theinterviewedfanners haveagood knowledge ofwind
erosionanditseffects oncropsandsoils.Intheirview, cropsare damaged, and often diebecause
ofwind-blownparticletransport.Moreover, soilproductivity isnegativelyinfluenced byerosion,
whereasdepositionresultsinabetterproductivity.Theseobservationsareinaccordancewithresults
from on-stationwind erosion research.
Traditionaltechniquesto combatwind erosion areapplication ofmanure, andmulchingwith
milletresiduesortreebranches.Applicationofthesemeasuresislimitedbytheinsufficient availability
ofmanureandmulchmaterial.Measuresthathavebeenpromoted byanagricultural development
project intwo villagesincludetreeplanting, regeneration ofwoodyvegetation, and application
ofzai.Accordingtothefannersthatapplythesemeasures,theyareverysuccessfulinsoilconservation
andcrop protection.
Naturalregenerationoftreesandshrubswasalsoindicatedbytheotherfarmers asapossibility
toreducewinderosion. However, theyapparentlydonothavethemeansorpossibilitiesto stop
thecurrentdegradation ofthenaturalvegetation. Itisrecommended thatfuture research should
concentrateondevelopingstrategiesto regeneratenaturalvegetation onfarm andvillagescales.
Animportantrequirementisthatthespeciesoftreesandshrubsinfarmers fields maynot compete
stronglywithcrops,otherwiseitisnot acceptable for farmers. Selecting species should therefore
be doneincooperationwithfarmers.
REFERENCES
Banzhaf,J.,D.E. Leihner,A.Buerkert,andP.G.Serafini. 1992.Soiltillageandwindbreakeffects onmillet
andcowpea: I.Windspeed,evaporation,andwinderosion. Agron.J.84:1056-1060.
BenSalem,B. 1991.Preventionandcontrolofwinderosioninaridregions. Unasylva 164: 33-39.
Buerkert,A.,J.P.A. Lamers,H. Marschner,andA.Bationo.1996. Inputsofmineralnutrientsandcropresidue
mulchreducewinderosioneffectsonmilletintheSahel.p.145-160.InB.Buerkertetal. (ed.)Winderosion
inWestAfrica:Theproblemanditscontrol. ProtInt. Symp.,Stuttgart,Germany. 5-7Dec.1994.Margraf
Verlag,Weikersheim,Germany.
Chase,R.,andE.Boudouresque.1987.MethodstostimulateplantregrowthonbareSahelianforestsoilsin
theregionofNiamey,Niger. Agric.Ecosyst.Environ. 18: 211-221.
Farmers' KnowledgeofWindErosioninNiger
123
Conway,G.R, andE.B.Barbier. 1990.After thegreenrevolution; Sustainableagriculture for development.
Earthscan Publications,London.
Gaouna,B.O. 1996.WinderosioninChad:Thevastness ofdamages,thebeginningofcontroland solutions
inBokororegion,p. 173-180.In B.Buerkertetal. (ed.)WinderosioninWestAfrica: Theproblemand
itscontrol.Proc.Int.Symp.,Stuttgart,Germany.5-7Dec. 1994.MargrafVerlag,Weikersheim, Germany.
(inFrench).
Klaij,M.C.,andW.B.Hoogmoed. 1989.CropresponsetotillagepracticesinaSaheliansoil. p.265-275.
In Soil,crop,andwatermanagement intheSudano-Sahelian zone.Proc.Int.Worksh.,Niamey,Niger.
11-16Jan. 1987.ICRISAT,Patancheru,India.
Klaij,M.C.,andW.B.Hoogmoed. 1993.Soilmanagement forcropproductionintheWestAfrican SahelII.
Emergence,establishment, andyieldofpearlmillet. SoilandTillageRes.25:301-315.
Lamers,J.P.A.,andPR. Feil. 1995.Fanners' knowledgeandmanagementofspatial soilandcropgrowth
variability.Netherlands J.Agric. Sei.43:375-389.
Mainguet,M, andM.C.Chemin. 1991.WinddegradationonthesandysoilsoftheSahelofMaliandNiger
anditspartindesertification. ActaMech. [Suppl]2: 113-130.
Michels,K.1994.WinderosioninthesouthernSahelianzone:Extent,control,andeffects onmilletproduction.
VerlagUlrichE.Grauer, Stuttgart, Germany.
Michels,K.,M.V.K.Sivakumar,andB.E.Allison. 1995a.Winderosioncontrolusingcropresidue II. Effects
onmilletestablishment andyields.FieldCropsRes.40: 111-118.
Michels,K.,M.V.K.Sivakumar,andB.E.Allison. 1995b.WinderosioncontrolusingcropresidueI. Effects
onsoilflux andsoilproperties.FieldCrops Res.40: 101-110.
Mohammed,A.E.,C.J. Stigter,andHS.Adam. 1995. Movingsandanditsconsequencesonandnearaseverely
desertified environment andaprotectiveshelterbelt. Arid SoilRes.andRehabil. 9:423-435.
Neef,A.,J.Haigis,andF.Heidhues. 1996.Impactofinstitutional andlegalpluralism ontheintroductionof
erosioncontrolmeasures-ThecaseofNiger,p.283-296.InB.Buerkertetal.(ed.)WinderosioninWest
Africa: Theproblemanditscontrol.Proc.Int.Symp.,Stuttgart,Germany.5-7Dec. 1994.MargrafVerlag,
Weikersheim, Germany,(inFrench).
Renard,C,andR.J.Vandenbelt.1990.AndropogongayanusKunthbordersasameanstocontrolwinderosion
intheSahel.AgronomieTropicale45:227-231. (inFrench).
Rinaudo,T.1996. Tailoringwinderosioncontrolmethodstofarmers' specificneeds,p. 161-171.ƒ« B.Buerkert
etal.(ed.)WinderosioninWestAfrica: Theproblemanditscontrol.Proc.Int.Symp.,Stuttgart, Germany.
5-7 Dec. 1994.MargrafVerlag,Weikersheim, Germany.
124
Chapter 7
Spencer,D.S.C.,andM.V.K.Sivakumar. 1987.PearlmilletinAfrican agriculture,p. 19-31.In Proceedings
oftheinternationalpearlmilletworkshop. Patancheru,India. 7-11April 1986.ICRISAT,Patancheru,
India.
Sterk,G.,L.Herrmann,andA.Bationo. 1996.Wind-blownnutrienttransportandsoilproductivity changes
insouthwestNiger.LandDegradationDevelopm. 7:325-335.(Chapter 5inthisvolume).
Sterk, G., andW.P. Spaan. 1997.WinderosioncontrolwithcropresiduesintheSahel. SoilSei.Soc.Am.
J.(inpress). (Chapter 6inthisvolume).
Stigter,C.J.,R.M.R.Kainkwa,A.E.Mohammed,andL.O.Z. Onyewotu. 1993.Essentials andcasesofwind
protectionfromscatteredtreesandshelterbelts.PaperpresentedattheICRAFInt.Symp.onFarmedParklands
intheSemi-Arid LandofWestAfrica. Oct.25-27.Ouagadougou, BurkinaFaso.
Taylor-Powell,E.1991.Integratedmanagementofagriculturalwatersheds:Landtenureandindigenousknowledge
ofsoilandcropmanagement. TropSoils Bulletin91-04.TexasA&MUniv.,CollegeStation,TX.
Chapter 8
Towards aRegional Mass BudgetofEolianTransported Material
ina Sahelian Environment
L.Herrmann and G. Sterk
Publishedinrevisedformin:B.Buerkertetal.(ed.) 1996.WinderosioninWestAfrica:Theproblem
anditscontrol.Proc.Int.Symp.,Stuttgart,Germany.5-7Dec. 1994. MargrafVerlag,Weikersheim,
Germany, p.319-326.
127
Towards aRegional Mass BudgetofEolian Transported Material
ina Sahelian Environment
ABSTRACT
Winderosionresearchinthepasthasmainlyconcentrated onstudyingsingletransportprocesses
ratherthanontotalmassbudgets.Tounderstandtheeffects ofwinderosionanddepositionprocesses
oncroppingandecosystems,itisneededtointegratedifferent measurementtechniquesinthesame
area.Amethodologyisproposedfor quantifying amassbudgetofeoliantransportedmaterialona
regionalscale.Thestrategyisbasedonkeyunitswhicharedennedbydifferent surface characteristics.
Thebudgetofeachunitcanbecalculatedonthebasisofsoilparticlefluxesinsaltationandsuspension
modes.Toestimatethebudgetonaregionalscale,itisnecessarytocombinegroundbasedexperiments,
winderosionmodeling,remotesensing,andageographicalinformation system.Themethodologyis
explainedbytakingsouthwestNigerasanexample.Theinfluence ofthekeyunitsonthemassbudget
andmeasurement constraintsarediscussed.
S
incethedroughtsofthe 1970'sandearly 1980'swinderosionhasbeenanimportantresearch
topicinthe Sahel.However, quantitative data onerosion and depositionprocesses inthe
Sahelarescarce.Thisismainlyduetothemeasurementproblemsrelatedtothewind-driventransport
mechanisms.Sedimentscanbecarriedoverdistancesrangingfrom afewcentimetersto thousands
ofkilometers, at agreat range ofheights, and inanydirection(McTainsh etal., 1992).
Usually,measurementsintheSahelhaveconcentratedonsingletransportmodes,like saltation
transportinagriculturalfields(e.g.,Michelsetal., 1993;SterkandRaats, 1996)or dust deposition
onaregionalscale(e.g.,Dreesetal., 1993;Herrmann etal., 1996).Atotalmassbudget ofeolian
transported material, including creep, saltation, and suspensiontransport, would giveimportant
information about soiland nutrient losses or gainsbywind action. To estimate suchabudget,
measurementtechniquesforthedifferent transport modesneedtobeintegrated inthe samearea.
Theobjective ofthispaperisto describethe outlineofaproposed methodfor quantifying mass
budgets on a regional scale of approximately 100km2. Themethod is explained byusing the
circumstancesinsouthwestNigerasaguide.Theexistingmeasurement constraintsarediscussed
and it isshownhownewtechniqueslikeremote sensingcanbeused for estimating eolianmass
budgets.
128
Chapter8
METHOD
Theproposedmethodfor quantifying astormbasedregionalmassbudgetofeoliantransported
materialconsistsof: (i)selectionofkeyunits;(ii)quantification ofmasstransport ineachkeyunit;
(iii)calculation ofthetotal massbudget based onthecontributions ofseparate keyunits,
ad(i).Keyunitsareareaswhicharemoreorlessequalincredibility. Selectionofkeyunitsisbased
onsurface characteristicslikesoiltype, soil surface roughness, andvegetation characteristics.
Also,thepresence ofsoilconservationmeasures should betakenintoaccount,
ad(ii).Sedimenttransport cantakeplaceineither ofthethreetransport modes: creep, saltation,
andsuspension.Itisassumedthat creeptransport canbeincluded inthe saltation component
(Fryrear and Saleh, 1993).Thisresultsinthefollowing massbudget equation:
AS = Sai - Sat + Sul - Sut
[1]
where AS isthemassbudget(kgm"2),thesubscriptsaandu denote saltation and suspension,
andthearrows 1 and t indicateinput and output, respectively. For eachkeyunit and storm,
thefourmassbudgetcomponentsneedtobedetermined byexperimentation at selected sites,
resultinginaset ofexpressionsfor saltation and suspension transport.
ad (iii).A stormbased massbudget for thedefined regioniscalculated from the distribution of
the key units within the region, the boundary conditions, the expressions for saltation and
suspensiontransport,andthemeanwinddirectionduringthe storm. Theboundary conditions
forinputandoutputofparticlemasstransportaredeterminedbythemeanwinddirectionduring
thestorm event.
Thesethree stepsarenowfurther explained for anenvironment insouthwest Niger.
REGIONALMASSBUDGET ESTIMATION
Environment
ThelandscapeofsouthwestNigerisdominatedbybroad, gently slopinglatériteplateaus,with
eroded,heavilycrustedsoilsandsparsevegetation. Sometimesthecrusted soiliscovered byeolian
deposits,whichareoftenused for agriculture. Inthevalleysbetweentheplateaus,broadplains
ofdeepsandysoilsarewidespread(WildingandDaniels, 1989).These sandplainsform themain
agriculturalareaintheSahel,withpearlmillet(Pennisetumglaucum)asthemaincrop.Traditionally,
farmers leavepartsoftheirlandunderbushfallow for restoring soilfertility. Dueto population
RegionalMassBudgetofEolianTransportedMaterial
129
pressure,theareaunderfallowhasdecreased dramatically duringthepastfew decades (Klaijand
Hoogmoed, 1989). Thishasledto severesoildegradation, resultinginareaswithbare, crusted
surfaces.
Ingeneral, two seasonscanbedistinguished inwhicheoliantransport processestakeplace.
Inthedryseason(October-April),theHarmattanwindtransports dustinsuspensionfrommajor
Saharan sourcesinasouthwesterly direction. Alongthewindtrajectory, depositiontakesplace
mainlybygravitationalsettlingduringnighttime,whenwindspeedsarelow.Inaddition, vegetation
canactasadusttrap,duetoanincreaseinsurface roughness. Overall,the dry seasonisassumed
to result inanet input ofwind-blownparticles on Saheliansoils.
Duringthefirsthalfoftherainyseason(May-July),heavythunderstorms,whichtravelinan
east-westdirection,occurfrequentlyintheSahel.Thesestormsareusuallyprecededbyshortperiods
withhighwindspeeds,resultinginsevereerosionofbare,unprotected soils.Very often, arolling
dustcloudinfrontofathunderstorm isformed. During suchanevent, soilmaterialismovedby
creep, saltation, and suspension. The suspended materialispartly deposited againwith rainfall
followingthedustcloud,butdustmayalsobesubjecttolong-rangetransport. Saltation and creep
particlesfromerodibleareasmaybetrappedbymorevegetatedareasdownwind.Overall,theearly
rainy season causes anet output ofeoliantransported material.
KeyUnit Scale
Based onthe surface characteristics ofsoilandvegetation, threekeyunits are distinguished
insouthwestNiger:baresurface, milletland, andfallow land. Possibly afourth unit,i.e. plateau,
couldbeadded,butitisassumedthatthethreeunits aresufficient to describe alsothe conditions
ontheplateaus.Thoughrealizingthatsubdividinganarea ofsome 100km2inonlythree different
unitsisveryrough,itispreferred for simplicityreasons.Inalaterstage,morekeyunitscanpossibly
be selected. Maps already existing, and aerialphotographs or satellite images(remote sensing)
canbeused to determinethekeyunit distribution inacertainarea.
Fallowland actsmainly asadeposition areafor saltationand suspension materialduringthe
earlyrainyseason,andasadustdepositionareaduringtheHarmattan.Milletlandandbare surfaces
actasdust deposition areasduringHarmattan events, and arethemainerosion areasduring the
earlyrainyseason.InTable 1,theimportanceofeachkeyunitfortheregionalmassbudgetofeolian
transported materialisshown.
130
Chapter8
Table 1.Theimportancef ofdifferent keyunitsforthemass
budgett ofeolianmaterialinsouthwestNiger.
Keyunit
SaJ
Sat
Sul
Sut
Millet land
+
++
Fallow land
++
0
++
0
Bare surface
+
++
+
++
t ++=important; +=relevant; 0=ofnorelevance.
t Sa=saltation;Su=suspension;1 =input; Î =output.
For eachkey unit, a representative sitefor the field measurements is selected. At these sites,
thefour massbudget components are quantified. Saltation mass transport rates on millet land and
bare surfaces depend on storm duration andwind speed. Saltationtransport can be quantified with
simple sediment catchersliketheModified Wilson and Cooke (MWAC) catchers (Sterk and Raats,
1996). During the 1993 rainy season, Sai and Saî were quantified during four storm events in
amilletfieldat Sadoré, southwest Niger (Sterk and Stein, 1997). All four storms resulted in a net
loss of saltationmaterial (Table2), and the total loss was equal to 4.6 kg m"2,which is equivalent
to a soil layer of «2.7 mm.
Infallow land, incoming saltationmaterial istrapped due to the increase in surface roughness.
This is virtually impossible to measure. However, under conditions of a sufficient dense fallow
vegetation, it can be assumed that the saltation output (Sat) from millet fields or bare surfaces
upwind from thefallow isequalto the saltationinput (Sai) inthe fallow, and is alltrapped by the
vegetation. The distance acrosswhich saltating particles penetrate into the fallow depends mainly
on the vegetation density inthe fallow site.
Table 2.Saltationmassbudgetf offour stormsonamillet field
insouthwestNiger, 1993rainyseason.
Storm
Sal
kgm
Sat
2
kgm'
ASa
2
kgm" 2
1
4.7
5.9
-1.2
2
0.2
0.4
-0.2
3
1.4
1.9
-0.5
4
6.2
8.9
-2.7
Total
12.5
17.1
-4.6
t Sa=saltation;! =input; Î =output; ASa=saltationmass
budget.
RegionalMassBudgetofEolianTransportedMaterial
0.05
JFMAMJJASONDJFMAMJJASONDJFMAMJJASOND
Month
Figure1.VerticalcomponentofsuspensioninputinafallowsiteatSadoré,1992-1994.
Quantification ofsaltationtransportwithsedimentcatchersdependsonthetrapping efficiency
ofthe sampler. Usually, the efficiency isdetermined inawindtunnelwhere, compared withthe
field, thewindisratherhomogeneousandthedegree ofturbulencelow. Thisreduced turbulence
mayresult inatrapping efficiency that isnot correct forfieldconditions. Sofar, notechniques
for determiningthetrapping efficiency ofsamplersunderfieldconditionsexist.
Inputofsuspensionmaterialcanbedividedintotwoparts:(i)verticaldepositionbygravitational
settling or rainwash-out; (ii)trapping ofhorizontal suspensiontransport mainlybyvegetation.
The vertical component can be measured with passive dust catchers (e.g., Drees et al., 1993;
Herrmannetal., 1996).InFig. 1,measuredquantities ofvertically deposited dust inafallow area
atSadoréareshown.Thedepositionpatternisbimodalandseason-dependent.Thehighestdeposition
rates,upto45gm"2month"1,weremeasured atthe start oftherainy seasonwiththe occurrence
of convective storms. Duringthose events,thegreatest sharewas deposited byrainfall directly
following thedust storms(Herrmann etal., 1996).
131
132
Chapter8
Currently,therearenoappropriatemeasurementtechniquesfor quantifying themore dynamic
horizontaldustdepositioncomponent,i.e.fall-out bycollisionoradhesion. Amethod to quantify
thetotalsuspensioninput atthe soilsurface isbeing developed (Herrmann, 1996).Thismethod
usesartificial soilsurfaces consistingofwashedquartzsandofthemiddle-sizesandfraction (125500um),whichisthemaingrain sizefraction inthepredominant sandy soilsoftheregion. The
suspensioninput(Sui)canbedeterminedbywetsievingthedustdepositafter exposingtheartificial
soilsurface for acertainperiod oftime.
Suspension output (Sut) isdifficult tomeasure.First estimatesweremadebyusingvolume
samplersto quantify vertical profiles ofsuspensiontransport (Nicklingand Gillies, 1993; Rajot
etal., 1996).SuspensionlossescanpossiblybequantifiedwithMWACcatchers asthese samplers
alsotrapsuspensionmaterial.Althoughthemaximumsamplingheightisonly1 m,theverticalprofile
throughmeasuredhorizontalmassfluxescould beextrapolated togreater heights, andresultsof
Nickling (1978) indicatethat thisisactuallypossible.However, priortousingthistechnique,a
propercalibrationofthecatchersforthesuspensioncomponentisneeded,forinstancebycomparing
theextrapolatedmassfluxprofiles withsuspension massfluxesmeasuredwithvolumesamplers.
Solvingthemeasurementconstraintsstillrequiresfurther research. Thisresearch should focus
on(i)improvingtechniquesforthequantification ofsuspensiontransport and deposition, and(ii)
development ofmethodsfor determiningthetrapping efficiency oferosion samplersunder field
circumstances.
Regional Scale
Thefielddataobtainedfromtheselectedkeyunitsitescanbeusedfor calibrationandvalidation
ofastormbased wind erosionmodel, e.g. theWindErosionPrediction System(Hagen, 1991).
This dynamic model is process based and has a modular structure. It includes weather, soil,
vegetation,hydrology, andtillage components.Wind-blown particletransport ismodeled asthe
timedependentconservationofmassoftwospecies,saltationandcreep,withtwosources,emission
andabrasion,andtwosinks,surfacetrappingandsuspension.Thesoilfluxissimulatedatsub-hourly
intervals when the friction velocity exceeds the threshold levels which were defined by field
measurements. The soilsurface conditions areupdated periodically.
After validation ofthewind erosionmodel,theregionalmassbudget iscalculated usingthe
schemeshowninFig.2.Remotesensingprovidesdataonvegetationandsoilsurfacecharacteristics.
RegionalMassBudgetofEolianTransportedMaterial
Ground
based
experiments
Remote
sensing
l
key unit
distribution
1
GIS
i'
Sai Sat Sut
^
h.
Wind
erosion
model
Figure2.Integratedsystemfortheestimationofaregionalmassbudgetofeoliantransportedmaterial.
Basedonthesedata,thedifferent keyunitsareselected andtheboundaries ofthesinglekeyunit
areas determined. Thedata are stored inageographical information system(GIS).Theground
based experiments includemeteorological measurements for thewind erosionmodel, and dust
depositionmeasurements sinceinput ofdust (Sul) from remote areascannotbe calculated with
thestormbasedwinderosionmodel.Themodelcalculatesthemassbudget components Sal, Sat,
and Sut onthebasisofthemeteorological data (wind speed, winddirection, rainfall, etc.)and
geometry information ofthe singlekeyunit areas.Based onthemassbudgetsfor each separate
keyunitarea,thetotal massbudget for theregioniscalculated bytheGIS.Inaddition,theGIS
providesthepossibilitytoproducemapsthatshowthespatialdistribution ofmasstransport inthe
region.
CONCLUSIONS
Theestimationofaregional massbudget ofeoliantransported material isdifficult dueto the
complex nature of the different transport processes. Nevertheless, it is important to develop
approaches in order to understand the effects of wind erosion and deposition on crop- and
133
134
Chapter 8
ecosystems. Only a net budget of creep, saltation, and suspension material permits any reliable
conclusions to be drawn about the regional effects of wind erosion.
Thefirstconstraintsonthewaytowards aregionalmassbudget arethemeasurement techniques,
especially ofthe suspensionfluxes.Thereisagreat need to develop methods for the quantification
of suspension losses from agricultural fields. Furthermore, no reliable techniques exist that can
quantify the trapping of suspended dust by vegetation canopies. As far as saltation transport is
concerned, techniques to determine the trapping efficiency of sediment catchers inthe field are
needed.
Totransfer theresultsofwind-blownmasstransportmeasurements onthefieldscaleto aregional
massbudget, itisnecessary to integratetoolsthatwork at different scales. In our approach, these
arethefieldmeasurements andthewind erosion model on the field scale, and remote sensing and
GIS ontheregional scale. The calibration ofthe wind erosion model by the field experiments and
theinventory ofthe keyunitsbyremote sensingneed intensive measurementswith ahigh resolution
and aretherefore time consuming. However, inthelong run the regional mass budget can be event
based and the measurements can be reduced to the collection of meteorological and suspension
input data.
The main difficulty in the Sahelian environment for this approach isthe determination of the
sizeand distribution of the key units. These units are dynamic due to the nature of the cropping
system and population pressure. Therefore, theinventory ofthekeyunits may have to be repeated
regularly.
REFERENCES
Drees,L.R.,A.Manu,andL.P.Wilding. 1993.CharacteristicsofaeoliandustsinNiger,WestAfrica. Geoderma
59:213-233.
Hagen,L.J. 1991.Awinderosionpredictionsystemtomeetuserneeds.J. SoilWater Conserv. 46: 106-111.
Fryrear,D.W., andA. Saleh. 1993.Fieldwinderosion:Verticaldistribution. Soil Sei. 155:294-300.
Herrmann,L.1996.DustdepositiononsoilsofWestAfrica:Propertiesandsourceregionsfordustandinfluence
onsoilandsiteproperties.HohenheimerBodenkundlichHefte36.Univ.ofHohenheim,Stuttgart,Germany.
(inGerman).
Herrmann,L.,K.Stahr,andM.V.K.Sivakumar. 1996. DustdepositiononsoilsofsouthwestNiger,p.35-47.
In B. Buerkertetal. (ed.)WinderosioninWestAfrica: Theproblemanditscontrol. Proc. Int.Symp.,
Stuttgart, Germany. 5-7 Dec. 1994.MargrafVerlag,Weikersheim, Germany.
RegionalMassBudgetofEolianTransported Material
135
Klaij, M.C.,andW.B. Hoogmoed. 1989.Cropresponsetotillagepractices inaSaheliansoil.p.265-275.
In Soil,crop,andwatermanagement intheSudano-Sahelian zone.Proc.Int.Worksh.,Niamey,Niger.
11-16Jan. 1987.ICRISAT,Patancheru,India.
McTainsh,G.H.,C.W.Rose,G.E. Okwach,andR.G.Palis. 1992.Waterandwinderosion:Similarities and
differences, p. 107-119.In H.Hurni,andK.Tato(ed.)Erosion,conservation,andsmallscale farming.
WalsworthPubl. Co.,Marceline,MS.
Michels,K.,M.V.K.Sivakumar,andB.E.Allison.1993.WinderosioninthesouthernSahelianzoneandinduced
damagetopearlmillet.Agric.For.Meteorol.67:65-77.
Nickling,W.G. 1978.Eoliansedimenttransportduringduststorms:SlimsRiverValley,YukonTerritory.
Can.J.Earth Sei. 15:1069-1084.
Nickling,W.G,andJA. Gillies. 1993.DustemissionandtransportinMali,WestAfrica. Sedimentology40:
859-868.
Rajot,J.L.,M.Sabre,andL.Gomes. 1996.Measurementofverticalfluxes ofsoil-derived dustduringwind
erosioneventsinaSahelianregion(Niger),p.49-56.InB.Buerkertetal.(ed.)WinderosioninWestAfrica:
The problem and its control. Proc. Int. Symp., Stuttgart, Germany. 5-7 Dec. 1994. Margraf Verlag,
Weikersheim, Germany.
Sterk,G, andP.A.C.Raats. 1996. Comparisonofmodelsdescribingthevertical distributionofwind-eroded
sediment. SoilSei.Soc.Am.J. 60: 1914-1919.(Chapter 3inthisvolume).
Sterk,G.,andA.Stein. 1997.Mappingwind-blownmasstransportbymodelingvariabilityinspaceandtime.
Soil Sei. Soc.Am.J. (inpress). (Chapter4inthisvolume).
Wilding,L.P.,andR.Daniels. 1989.Soil-geomorphicrelationshipsinthevicinityofNiamey,Niger. TropSoils
Bulletinno. 89-01.North Carolina StateUniv.,Raleigh,NC.
Chapter 9
Summary and Conclusions
139
Summary and Conclusions
R
ainfed agricultureintheSahelianzoneofNigerischaracterizedbyphysicallyandchemically
impoverished sandysoils,andharsh climaticconditions.Crops canonlybegrown during
theshortrainyseason,fromtheendofMayuntiltheendofSeptember.Winderosionoccursduring
twodistinctseasons.Duringthedry season(October -April),the strongHarmattanwind blows
andmaycausemoderate erosion. Inthe second halfofthedry seasonit often carries dust from
remoteSaharansourcesandsomeofthisisdepositedintheSahel.Thesecondand most important
winderosionseasonistheearlyrainyseason(May-July).Then,thunderstormsdevelopthroughout
theSahelandbringthefirstrainsofthenewseason.Theraineventsareusually preceded by short
(typically 10-30 min)wind stormsthat severely erodeunprotected soils.
Duringastorm,soilparticlesaremovedbysaltation,creep,andsuspension. Saltatingsandgrains
jumpandbounceoverthe surface, reachingmaximumheightsof «1 m.When saltatingparticles
falltothesoilsurfacetheynotonlyeject othersaltatingparticlesbut alsoinduce creep,therolling
andslidingoflargerparticles,andsuspension,theraisingoffineparticles.Thethreetransportmodes
result indifferent travel distances oftheparticles. Creep movesparticles across distances from
afewcentimetersuptoseveralmeters.Thesaltationrangeisfromafewmetersuptoafewhundred
meters, and suspended dustmaytraveluptothousands ofkilometers.
Thewindsduringearlyrainy season stormsarecharacterized byahighdegree ofturbulence.
Instantaneousmeasurementsofwindspeedandsaltationfluxcarried outinthisstudy showed that
saltationtransportishighlycorrelated withfluctuations inhorizontalwind speed. Fluctuationsin
verticalwindspeeddidnotinfluence saltationflux,indicatingthatthehorizontaldragforce ismore
importantfor saltationtransport thantheturbulent shear stressgenerated. Therefore, instead of
usingtheshearstress,asmanycurrentmodelsofwinderosiondo,thehorizontalwind speed and
itsfluctuations should beused asthedrivingvariableinwind erosionmodels.
Dataonwind-blownmasstransportwerecollectedusingModified WilsonandCooke(MWAC)
sedimentcatchers.Thecatcherhasseventraps attached to acentralpole atheightsbetween 0.05
and1.00m.Eachtrapconsistsofaplasticbottlewithaninletandanoutletenteringthebottlethrough
thecap.Theinlet and outlet areglasstubeswithanopeningof50.3mm2, and arebothbent 90°
inoppositedirectionsontheoutside.Thematerialstrappedatsevenheightsduringanerosionevent
wereusedtocalculatesevenhorizontalmassfluxes.Throughtheobservations, amodelwas fitted
140
Chapter9
todescribetheverticalprofile ofhorizontal massfluxes.Two existingmodelsweretested andit
wasshownthatatwo-term,combinedsaltation-suspensionmodelgavethebestresults. Ingeneral,
theprofiles showedamaximummassfluxatthesoilsurface which decreased rapidlywithheight.
Byintegratingtheprofileoverheight,andcorrectingforthetrappingefficiency ofthecatcher(0.49),
atotalmasstransportrateatthepointofsamplingwas obtained. Thisvaluerepresented the total
massofmaterialpassing astrip 1 mwideperunit oftime.
Intheliterature,ithasbeenmentionedthattheseparatetermsofthecombinedsaltation-suspension
modeldescribesaltationandsuspensionmassfluxes,respectively.However,sievingtrappedmaterials
from twocatchersrevealedthatthemodelshouldnotbeusedforthispurpose.Itmayonlybeused
to determinetotalmassfluxesofamixtureofsaltationand suspensionmaterial.
Fieldmeasurements ofwind-blown masstransport areoften characterized byaconsiderable
spatialvariation,whichmakesquantitativemodeling ofwind erosion difficult. Here, geostatistics
wereappliedto modelthe spatialvariation oftotalmasstransport observations, quantified with
21MWACsedimentcatchersinaplot of40by60mduringfour storms. Tohave sufficient data
for the analysis, thevariance ofthefour stormswaspooledbycreating onelarge data set from
thefour separatedata sets. Stormbased mapsoftotal masstransport werecreated bykriging,a
spatialinterpolation technique, and stochastic simulationwith simulated annealing.
Thesimulatedmapsclearlyshowed the spatial distribution ofmasstransport from whichsink
and source areasfor erosionmaterialcould bedistinguished. Combiningthesemapswithother
mapsofsoilcharacteristics,surfaceroughness,topography,etc.mayelucidatewinderosionprocesses
inthe field.
Themapsproducedbykrigingwereusedto calculate amassbudget, sothat stormbased soil
lossescouldbeestimated. Intotal,45.9Mgha"1 waslostfrom the experimental plot during the
four sampledstorms.Thisisequivalentto asoillayer »2.7mmthick. Asthe sandy Sahelian soils
areverydeep(>3m),soillossesofafewmillimetersperyeararenotthebiggestconcernforfarmers.
Thelossofplantnutrientswiththewind-blownmaterialismoreimportant.
Duringthefirstandthefourth stormofthe 1993season,materialstrappedatthreeheights(0.05,
0.26,and0.50m)werecollected, andtotal element (TE) contentsofpotassium (K), carbon(C),
nitrogen(N),andphosphorus(P)weredetermined. Ingeneral,theparticlestrapped atthelowest
levelwereasrichinnutrientsasthetopsoil.Atthe0.50mlevel,thematerialwasabout threetimes
richer innutrientsthanthetopsoil. Theincreaseinnutrient contentwithheightwas explainedby
SummaryandConclusions
anincreaseintheproportionofsiltandclayparticlesthatcontainlargeramountsofnutrientscompared
withthecoarsersandthatistransportedjust abovethe soilsurface. Combiningtheverticalmass
fluxprofilewiththeverticalprofilesofTEcontentsresultedinmassfluxprofilesofthefourelements,
K,C,N,andP.Theseprofiles showed amaximumvalueinthe saltationlayerjust abovethe soil
surface,anddecreasedsharplywithheight. TheTEmassfluxes transportedbysaltationwerean
order ofmagnitude higherthanthe suspended TEmassfluxes. Byintegrating theTEmass flux
profilesoverheightandcalculatingamassbudget,thelossesofthefourelementsfromtheexperimental
plotduringthetwostormswereestimated.Theywerefound to be *=3%oftheTEmassespresent
inthetop 0.10mofthesoil.
Assaltationisashort-rangetransport processitmerelyresultsinaregional redistribution of
soilparticlesandnutrients.Materialmaybetransportedfromunprotectedfieldstowards protected
areas,suchasmulchedfieldsorvegetatedareas.Within-fieldtransportofsoilparticlesandnutrients
mayalsooccur,sincemanyfieldshaveobstaclesliketreesand shrubsthattrap saltationmaterial.
Althoughthe absolutefluxesaremuchsmallerthanthe saltationfluxes,suspended material can
betransported over long distances, resulting inregionallossesofsoilparticles andnutrients. It
should therefore beconsidered asaserious soildegradation process aswell.
To determinetheeffects ofwinderosiononascalelargerthanthescaleofindividualfields,
itisnecessarytointegratedifferent measurementtechniquesinthe samearea. Aproposed method
toestimatetotalmassbudgets ofeolianmaterial at scalesof »100km2combinesremote sensing
withawind erosionprediction modelandfieldmeasurements. Theareaisdivided into different
keyunits,basedonsurfacecharacteristics.Thewinderosionmodeliscalibrated for eachkeyunit,
using field data from selected sites. Ageographical information system isused to combineall
information andtocalculatethemassbudgetforthewholearea. Severalmeasurement constraints,
mainlyconcerningquantification ofsuspensiontransport need tobe solved before suchamethod
canbeimplemented.
Soilandnutrientlossesbywinderosion canbeprevented byleavingcrop residuesinthe field
asamulch.Inthe Sahelianfarming systems,mulchingislimited bylowbiomassproduction and
multipleuses ofthe stalks. Inaprevious studyitwas shownthat 2000kgha"1ofmillet residues
givessufficient protection,whereasamulchcoverof500kgha"1doesnotreducesedimenttransport.
Inthisstudy,two lowmulchcoverrates of 1000and 1500kgha"1weretested for their efficacy
insoilprotectionduringtwowinderosionseasons.The1500kgha"1 coverrategavegoodprotection
141
142
Chapter9
duringallsampledstorms.However,thelowerrateprotectedthesoiladequatelyduringweakstorms
withwindspeedsbelow 10ms'1only.Itdidnotresultinsufficient reduction during strong storms.
Duringonestormwithawindspeedof 11.3ms"1thesedimenttransport intheprotected plotwas
evengreaterthaninthecontrolplot.Thisincreaseinerosionisattributableto enhanced turbulence
aroundthemillet stalks.Itistherefore recommended touse atleast 1500kgha"1ofmillet stalks
for wind erosionprotectionintheSahel.
To complement the on-station research, anon-farm surveywas conducted insevenvillages
in southern Niger. A total of 138 farmers was interviewed to ascertain their knowledge and
perceptions ofwind erosionprocesses.Mostfarmers (63%)considerwind-blown soiltransport
asdamagingtotheircrops.Intheirview,plantsaredamagedbyabrasion, or arelost dueto burial
in sand. Nearly allfarmers have aclear perception ofsoilproductivity changes caused bywind
erosion. Fieldsor isolated spots that gainmaterialbydepositionwere saidtohave abetter soil
fertilitythanerodedareas.Mostfarmers(92%)applyoneormorewinderosioncontrol techniques
in the field. The indigenous measures are mulching with crop residues or tree branches, and
application of manure. New techniques have been introduced by an agricultural development
project. Thesetechniques arefarmer-managed regeneration ofwoodyvegetation, treeplanting,
and application ofzai, a method of soil preparation from Burkina Faso, using pitsfilledwith
compostforplanting crops.Regeneration ofwoody specieswasreported tobeveryeffective in
reducing wind erosion, and is the most promising control method available, given the limited
availability ofmulchmaterial andmanureunder currentfarming practices.
143
Samenvatting en Conclusies
R
egenafhankelijke landbouw indeSahel-zonevanNigerwordt gekenmerkt door fysisch
enchemischarmezandgrondeneneenextreemklimaat. Gewassenkunnenalleenworden
verbouwdtijdens het korteregenseizoen datvaneindmeitot eind september duurt. Winderosie
treedtoptijdenstweeseizoenen.Inhetdroge seizoen(oktober -april)waait dehardeHarmattan
winddiematigeerosieindeSahelkanveroorzaken.Tijdensdetweedehelft vanhet droge seizoen
voertdeHarmattanveelstofaandatafkomstig isuitdeSahara.Eendeelvanditstofwordt afgezet
indeSahel.Hettweedeenmeestbelangrijke erosieseizoenishetbeginvanderegentijd (mei-juli).
IndieperiodeontwikkelenzichindeSahelzwareonweersbuiendiedeeersteregensvanhetnieuwe
seizoenbrengen.Voorafgaand aanderegentredenvaakhogewindsnelheden opgedurende korte
periodes(10-30 min),waardoor veelerosiewordt veroorzaakt.
Tijdens een dergelijke stormwordenbodemdeeltjes getransporteerd door drieverschillende
processen:saltatie,kruipensuspensie. Salterendezandkorrelsspringenover het oppervlak waarbij
maximalehoogtesvanca. 1 mwordenbereikt. Alseensalterend deeltje botst methet oppervlak
wordennietalleenanderezandkorrels ineensalterendebeweging gebracht, maarwordentevens
groterekorrelsvooruitgeroldofgeschoven(kruip)enfijnbodemmateriaal insuspensie gebracht.
Dedrieprocessentransporterenhetbodemmateriaaloververschillendeafstanden.Kruipendmateriaal
legtafstandenafvaneenpaarcentimeterstotenkelemeters.Door saltatiebeweegtmateriaal over
afstandenvariërendvaneenmetertotenkelehonderdenmeters,terwijlhetfijnestofgetransporteerd
kanworden over afstanden tot enigeduizendenkilometers.
Dewindtijdensstormeninhetvroegeregenseizoenisinhogemateturbulent.Continuemetingen
vansaltatiefluxen vertoonden een sterkefluctuatie diegoed gecorreleerd was met de fluctuaties
indehorizontalewindcomponent. Fluctuaties indeverticalewindcomponent vertoonden geen
correlatiemetdesaltatieflux.Hieruitkanwordengeconcludeerddatdesleepkrachtvangroterbelang
isdandeschuifspanning. Modellenvansaltatietransport zouden daaromgebruik moeten maken
van dewindsnelheid ennietvandeschuifspanning zoalsdemeestehuidigemodellen doen.
Voor het bepalen van het massatransport tijdens een storm werd gebruik gemaakt van
sedimentvangersvanhettypeModified WilsonandCooke(MWAC).Ditinstrument heeft zeven
vangeenhedendieovereenhoogtevan0,05tot 1,00maaneenmastbevestigdzijn.Elkevangeenheid
144
bestaatuiteenplasticflesje datafgesloten isdooreenschroefdop. Indedopzijn eeninlaat eneen
uitlaatbevestigd.Ditzijnronde,glazenbuisjes meteenopeningvan 50,3mm2.Beidebuisjes zijn
aandebuitenkant90°integengestelderichtinggebogen.Hettijdenseenstormingevangenmateriaal
werdverzameldengebruiktompervangerenperstormzevenhorizontalemassafluxenteberekenen.
Door de zevenwaarnemingenwerd een model gepast omhet verticale profiel van horizontale
massafluxentebeschrijven. Tweebestaandemodellenwerdenhiervoorgetest enhetbleek dat een
gecombineerd saltatie-suspensiemodeldebesteresultatengeeft. Deverticale massafluxprofielen
vertoonden eenmaximumaanhet oppervlak ennamen sterk afmetdehoogte. Door het profiel
teintegrerenoverdehoogteenvervolgenstecorrigerenvoordeefficiency vandesedimentvangers
(0,49)werdeentotaalmassatransport ophetpuntvanobservatieverkregen. Dezewaarde isgelijk
aandetotale massa aanbodemmateriaal dieeenstrook van 1 mpertijdseenheid isgepasseerd.
Indewinderosie-literatuurisgemelddatdeafzonderlijketermenvanhetgecombineerdesaltatiesuspensie model respectievelijk saltatie- en suspensie-massafluxen beschrijven. Echter, door
ingevangenmateriaaltezevenentewegenbleekdathetmodelhiervoornietgebruiktmagworden.
Het kan slechts worden toegepast om totale massafluxen, bestaande uit zowel saltatie- als
suspensiemateriaal tebepalen.
Veldmetingenvanmassatransportwordenvaakgekenmerktdooreengroteruimtelijkevariabiliteit,
waardoor kwantitatieve modellering vanwinderosie bemoeilijkt wordt. In dit onderzoek werd
geostatistiek toegepast om de ruimtelijke variabiliteit inwaarnemingen van massatransport te
modelleren.Metbehulpvan21 MWACsedimentvangerswerdenmetingengedaanineen proefveld
van40bij60mtijdensvierstormeninhetregenseizoenvan 1993. Omvoldoende waarnemingen
tehebbenvoordeanalysewerden devier stormen samengevoegd tot ééngegevensset. Voor elk
vandevierstormenwerdenkaartengemaaktvanhettotalemassatransportmetkriging(eenruimtelijke
interpolatietechniek) en simulated annealing (een stochastische simulatietechniek).
De gesimuleerde kaartentoonden duidelijk deruimtelijke verdelingvanhet massatransport.
Dekaartenzijngeschiktomerosie-endepositieplekkeninhetveldte onderscheiden. Combineren
vandekaartenmetkaartenvanbodemkarakteristieken, oppervlakteruwheid, topografie enz.kan
eenbeter inzichtverschaffen inwinderosieprocessen.
De geïnterpoleerde kaarten werden gebruikt om massabalansen te berekenen, waardoor
bodemverliezen per stormkondenwordenbepaald. Intotaalging45,9Mgha"1 verloren vanhet
proefveld gedurende de vier stormen. Dit verlies komt overeen met een bodemlaag van ca.
145
2,7mmdikte.Uithetfeit datdezandgrondeninNigerdiepzijn (>3m)blijkt dat bodemverliezen
vanenkelemillimetersperjaarniethetgrootsteprobleemzijnvoordeNigerijnseboeren.Vangroter
belangishetverliesaannutriënten dattijdens destormen optreedt.
Tijdens tweevandevier stormenin 1993werd ingevangen sediment op driehoogtes (0,05;
0,26en0,50m)verzameld. Van ditmateriaalwerdendegehaltesaantotale elementen(TE)van
kalium(K),koolstof(C),stikstof(N)enfosfor (P)bepaald.Overhetalgemeenbevattehetmateriaal
op0,05mevenveelnutriëntenalsdebovengrond.Op0,50mwashet sediment ca. driekeer rijker
innutriëntendandebovengrond.Dezetoenameinnutriëntengehaltes metdehoogte kanworden
verklaard uit de toename van de gehaltes aan klei- en siltdeeltjes in het sediment. Ditfijne
bodemmateriaalbevat meernutriënten danhetgroverezand datnet boven het bodemoppervlak
wordt getransporteerd.
HetcombinerenvanhetverticaleprofielvandemassafluxmetdeverticaleTE-profielenresulteerde
inTE-massafluxprofielen voor devier elementenK, C,N enP. Dezeprofielen vertoonden een
maximuminde saltatiezonenetbovenhet oppervlak ennamensterk afmet dehoogte.Door de
TE-massafluxprofielen teintegreren over dehoogte enmassabalansen teberekenen werden de
verliezen aanK, C,NenPvanhetproefveld geschat. Dezeverliezenbedroegen ca. 3%vande
totalemassa dieaanwezigwasindeeerste0,10mvandebovengrond.
Saltatietransporteertmateriaalovergeringeafstanden endaardoorresulteert het voornamelijk
ineenregionaleherverdelingvanbodemdeeltjes ennutriënten.Hetmateriaalwordt getransporteerd
vanonbeschermdeakkersnaargebiedendiebeschermdzijndoorvegetatieofbodemconserveringsmaatregelen.Ookkanherverdelingoptredenbinnenhetzelfdeveld.Vaakzijnerindeakkersbomen
enstruikenaanwezig diesalterend materiaaluit deomgevinginvangen. De suspensiefluxen zijn
veelgeringerdandesaltatiefluxen,maarhetmateriaalinsuspensiewordtoverveelgrotereafstanden
getransporteerd. Suspensietransport kandaardoortot eenregionaal verliesaannutriënten leiden
enmoet dusook alseenbelangrijk bodemdegradatieproces worden beschouwd.
Voorhetbepalenvandeeffecten vanwinderosieopeen schaalgroter dandeveldschaal ishet
nodigdatverschillendemeettechniekenwordengeïntegreerdinhetzelfdegebied. Een voorgestelde
methodevoorhetschattenvaneentotalemassabalansvaneolischmateriaal ineengebiedvanca.
100km2combineertremotesensingmeteenwinderosiemodel enveldmetingen. Het gebied wordt
daarbij onderverdeeld inuniforme eenheden diegeselecteerd worden opbasisvanoppervlaktekenmerken.Hetwinderosiemodelwordt geijkt voor iedereuniforme eenheid door middelvande
146
veldgegevens.Eengeografisch informatie systeemwordt gebruikt voor het combinerenvanalle
informatie enhetberekenenvandetotalemassabalansvaneolischmateriaalvoor hethelegebied.
Alvorensdezemethodetoegepastkanwordenishet noodzakelijk dat eenaantal meetproblemen,
voornamelijk betrekkinghebbendeopdesuspensiecomponent, wordt opgelost.
Bodem-ennutriëntenverliezen kunnenwordentegengegaan door gewasresteninhetveldte
laten als mulch. Een probleem is dat onvoldoende materiaal beschikbaar is voor een goede
bodembescherming. IndeSahelisdebiomassa-produktie laag enwordengewasresten ook voor
anderedoeleindengebruikt.Ineeneerdere studiewerd aangetoond datbedekkingvandebodem
met2000kgha'1gierststengelseengoedebeschermingtegenwinderosiegeeft, terwijl 500kgha'1
geeneffecthad.Inditonderzoekwerddereductieinwinderosiedoortweehoeveelhedengierststengels
(1000en 1500kgha'1)getestgedurendetweeseizoenen(1994en1995).Bedekkingvandebodem
met 1500kgha"1 gafeengoedebescherming tijdens allegemeten stormen.Echter, debedekking
met 1000kgha"1 gafslechtsvoldoendebeschermingtijdens zwakke stormenmet windsnelheden
onderde 10ms"1. Tijdenséénstormmeteenwindsnelheidvan 11,3ms"1tradzelfs meersedimenttransport opalsgevolgvandegierststengels.Dezetoenameinerosiekanwordenverklaard door
eenversterkte turbulentie rond degierststengels. Daaromwordt geadviseerd omtenminsteeen
hoeveelheid van 1500kgha'1gierststengelstegebruikenvoorbodembeschemingindeSahel.
Naastdeveldexperimentenwerden 138boerenuitzevendorpengeïnterviewd naarhunkennis
vanwinderosieprocessenenbodemconserveringstechnieken. Demeesteboeren(63%)beschouwden
winderosiealsschadelijkvoorhungewassen.Plantenwordenbeschadigddoordeschurendewerking
vanzand(abrasie),ofzegaanverlorendoordatzewordenbedektmetzand.Bijnaalleboerentoonden
eengoedbegripvandeinvloedvanwinderosieopdebodemvruchtbaarheid.Naarhunmeningworden
velden of plekken waar eolisch materiaal wordt afgezet verrijkt, terwijl erosie een verlies aan
bodemvruchtbaarheid veroorzaakt.Demeesteboeren (92%)gebruikten éénofmeerderebodemconserveringstechniekeninhetveld.Detraditionelemaatregelenzijnbedekkingvandegrondmet
mulchenbemestingmetorganischemest.Nieuwetechniekenzijngeïntroduceerd door landbouwprojecten. Dezetechniekenzijnregeneratievannatuurlijke vegetatie, aanplantvanbomenenhet
gebruik vanzai.Dezelaatsteiseentechniek afkomstig uitBurkinaFasowaarbij gezaaid wordt
inmetcompostgevuldegaten.Regeneratievannatuurlijkevegetatiewerddoordeboeren diedeze
techniektoepassenalssuccesvolomschrevenenlijktdemeestgeschiktebodemconserveringsmethode,
omdatdehoeveelhedenmulchmateriaalenmestbeperktzijnbinnendehuidige landbouwsystemen.
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Résuméet Conclusions
L
'agriculturepluvialedanslazoneSahélienneduNigerestcaractériséepardessolssablonneux
pauvresenmatièresphysiqueetchimiquecombinéeàunclimatextrême.L'agriculture n'est
pratiquéequependantlacourtesaisondespluiesquivadefinmaiàfinseptembre.Ilyadeuxsaisons
pendantlesquellesilestquestiond'érosionéolienne.Lasaison sècheapporte leventfort, nommé
Harmattan, quiprovoqueune érosionmodérée dansleSahel.Aucours deladernièrepartiede
cettesaisonbeaucoupdepoussièreenprovenance du Sahara estapportéeparl'Harmattan. Cette
poussièreretombepartiellement dansleSahel.Ledébut delasaison despluies (mai-juillet) est
lapérioded'érosionlaplusimportante.Pendant cetemps-là detrèsforts orages sedéveloppent
dansleSahelapportantlespremièrespluiesdelanouvellesaison.Cesoragessontsouventprécédés
decourtespériodes(de 10à30minutes)deventsoufflant àgrandevitessecequicausebeaucoup
d'érosion.
Pendantunetelletempêtedesparticulesdesolsontsoulevéesettransportéesaumoyendetrois
processusdifférents: saltation,reptationetsuspension. Onparle desaltationlorsquelesgrainsde
sablesedéplacent surlasurface parbonds successifs atteignant deshauteursmaximales d'à peu
près 1 m.Au moment oùuntelgraindesableretombe surlesolnon seulement d'autresgrains
desablesontheurtésetcommencentàbondir(saltation),maiségalement desgrainsplusgros sont
poussésenavant(reptation)etdesmatièresplusfinessontmisesensuspension.Parlestroisprocessus
nommésci-dessusdesparticules desolsont déplacées surdesdistances différentes. Du matériel
enreptationsedéplacedequelquescentimètresàquelquesmètres.Lasaltationcauseundéplacement
dematérielquivaried'unmètreàquelquescentainesdemètres,tandisqueletransportdesmatières
plusfinesen suspensionpeut atteindreunedistance dequelquesmilliersdekilomètres.
Leventquisoufflependantlestempêtesdudébutdelasaisondespluiesestextrêmementturbulent.
Lemesurage continu desfluxdesaltationmontraituneforte fluctuation quiétait en corrélation
avec lesfluctuationsdelacomposante horizontale delavitesse duvent. Lesfluctuationsdela
composanteverticaledelavitesseduventnemontraientpasdecorrélationaveclefluxdesaltation.
Cecijustifielaconclusionquelaforcedefrottement estdeplushauteimportance quela contrainte
decisaillement. C'est pourquoi desmodèles detransport par saltation devraient plutôt seservir
delavitesseduvent quedelacontrainte decisaillement, commeilenest question actuellement
danslaplupart desmodèles.
148
Pourdéterminerletransportdemassependantunetempêteonutilisedescapteurs de sédiment,
dutype"Modified Wilson and Cooke"(MWAC).Cet instrument est composéde septunitésde
captagequisontfixéessurunmâtàdeshauteursvariantde0,05à 1,00m.Chaqueunitédecaptage
estconstituéed'unepetitebouteilledeplasticfermée parunbouchonvissant. Dans cebouchon
uneadmissionetunéchappementsontfixés.Cesontdestubesdeverrerondsavecuntrou de 50,3
mm2.Al'extérieur, lesdeuxtubessontcourbésà90degrés endirectioninverse.Lematériel ainsi
obtenuaucoursd'unetempêteestattrapéetutilisépourcalculer, par capteur etpartempête, sept
flux demassehorizontaux. Aumoyendessept observationsunmodèle est ajusté pour décrirele
profil vertical desfluxdemassehorizontaux. Danscebut deuxmodèlescourants ont ététestés
etilsetrouvequ'unmodèlealliantsaltationetsuspensiondonnelesmeilleursrésultats.Les profils
defluxdemasseverticauxmontrentunmaximumàlasurfacedusolquidiminuentfortement selon
leshauteurs.Enintégrantleprofilenhauteuretaprèscorrectiondel'efficacité d'attraper descapteurs
desédiment(0,49),untransportdemassetotal fut obtenu àl'endroit d'observation. Cettevaleur
estconforme àlamassetotaledumatérieldesolquiapasséunebanded'un mètreparunitéde
temps.
Lalittératureausujet del'érosionéoliennesignalequelestermesséparésdumodèle combinant
saltationet suspension décrivent respectivement lesfluxdemasse desaltationet desuspension.
Aprèstamisageetpesagedu matérielattrapéils'est cependant avéré quecemodèlenepeut pas
êtreutiliséàceteffet. Cemodèlenepeutêtreappliquéquepourladéterminationdesflux demasse
totaux quisont composésdematérielaussibiendesaltationquede suspension.
Lesmesuragesdeterraindutransportdemassesontsouventcaractérisésparunegrandevariabilité
spatiale,cequirenddifficiled'évaluerquantitativementl'érosionéolienne.Pourcetexamen,l'analyse
géostatistiqueestappliquéepourmodelerlavariabilité spatialedanslesobservations detransport
demasse.Al'aide de21capteursdesédimentMWACdesmesurages deterrainfurent faits sur
unchampd'expérimentationlargede40à60mètrespendantquatretempêtesdelasaisondespluies
de1993.Afind'avoirsuffisamment d'observationspourréaliserl'analyse,onajoint cellesdesquatre
tempêtes.Pourchaquetempêtedescartesfurent faitesdutotaldetransportdemasseavec"kriging"
(une technique d'interpolation spatiale) et "simulated annealing"(unetechnique de simulation
stochastique).
Lescartessimuléesmontrèrentclairementladivisionspatialedutransport demasse. Cescartes
sontutiliséespourdistinguerlesendroitsd'érosionetdedéposition surlechamp. Sil'on combine
149
lescartesaveccellesdespropriétésdusol,delarugositédusoletdelatopographie, etc.,onpeut
arriver àmieuxcomprendrelesprocessusd'érosion éolienne.
Les cartes interpolées furent employées pour calculer lesbilans de masse, ce quipermit de
déterminerlespertesdusolpartempête.Lapertetotaledu champ d'expérimentation fut de45,9
Mgha"1pendant lesquatretempêtes. Cettepertecorrespond àunecouche desold'environ 2,7
mm en épaisseur. Du fait quelesterrains sablonneux auNiger sont profonds (plus de 3m de
profondeur)onpeutconclurequelapertedusoldequelquesmillimètresparann'estpasleproblème
majeurdesagriculteursNigériens.Lapertedesnutrimentscauséeparlestempêtesestdeplusgrande
importance.
Pendantdeuxdesquatretempêtesen 1993, dusédimentfut attrapéàtroishauteurs (0,05; 0,26
et0,50m).Lematérielobtenuainsiquelaquantitéd'éléments totaux (ET) enpotassium (K),en
carbone (C),enazote(N)etenphosphore (P),fut déterminée. Engénéral, lematériel obtenu à
unehauteurde0,05mcontenaitautantdenutrimentsquelesolensurface. A0,50mlesédiment
étaitàpeuprèstroisfoisplusricheennutrimentquelesolensurface.Cetteaugmentationenvaleurs
denutrimentsselonlesdifférentes hauteurspeut êtreexpliquéeparl'augmentation desvaleursde
particules d'argiles et delimondu sédiment. Cematérielfindu sol contient plus denutriments
quelesableàplusgrosgrainsquiesttransportéjuste au-dessus delasurface dusol.
EncombinantleprofilverticaldufluxdemasseaveclesprofilsETverticauxonobtintlesprofils
ET deflux de masse desquatre élémentsK, C,NetP. Cesprofils montrent unmaximumdans
lazone de saltationjuste au-dessus delasurface et diminuentfortement selonleshauteurs. En
intégrant lesprofils ET defluxdemasse selonlahauteur et encalculantlesbilansdemasseon
arrivaitàestimerlespertesenK,C,NetPsurlechampd'expérimentation. Cespertes s'élevaient
à 3%environ delamassetotaleprésente danslespremiers 10centimètres du soldela surface.
Parsaltation, dumatérielesttransporté surdeminimesdistances, cequidonnepour résultat
qu'iln'estquestionquederedistributionrégionaledeparticulesdesoletdenutriments.Lematériel
esttransporté de solsnon-protégésversdesendroitsprotégésparlavégétation oupar mesures
deconservationdusol.Onvoitégalementlaredistributiondusolàl'intérieurdesbordsd'unterrain.
Cesontsouventlesarbresetlesbuissonssurleschampsquiattrapent lematériel ensaltation des
environs.Bienquelesfluxdesuspension soientbeaucoupmoinsgrandsquelesfluxde saltation,
lematérielensuspensionesttransportésurdesdistancesbeaucoupplusgrandes.Decettemanière,
150
letransport en suspension peut mener àune perte régionale desnutriments et ainsi il doit être
considéré commeunprocessusimportant dedégradation dusol.
Pourladétermination deseffets d'érosion éoliennesuruneéchelleplusgrandequel'échelle
deterrain,ilestnécessairequelesdifférentes techniques demesure soient intégrées danslamême
région.Uneméthodeproposéepourestimerlebilandemassetotaldematérieléoliendansunendroit
d'environ 100km2combinelatélédétection avecunmodèled'érosion éolienneet desmesurages
de terrain. Pour cela, l'endroit est divisé en unités uniformes sélectionnées sur la base de
caractéristiquesdesurface. Pour chaqueunitéuniforme, lemodèled'érosion éolienne est vérifié
aumoyendesdonnéesdeterrain.Unsystèmed'informationgéographiqueestemployépourcombiner
toute information recueillie et pour calculerlebilandemassetotal dematériel éolienpour tout
leterrain.Avantdepouvoirappliquercetteméthodeilestnécessaire qu'unnombredeproblèmes
demesurage, serapportant principalement àlacomposante desuspension, soitrésolu.
Lespertesdusoletdesnutrimentspeuventêtreréduitesenutilisantlesrésidusderécoltecomme
paillage.Cependantilyaleproblèmed'unmanquedematérielnécessairepourunebonneprotection
dusol.DansleSahellaproductiondebiomasseestpeuélevée.Deplus,lesrésidus derécolte sont
utiliséspour d'autres buts.Uneétudefaite antérieurement aprouvé quelerecouvrement dusol
avec2000kgha"1detigesdemilassureunebonneprotectioncontrel'érosionéolienne;unequantité
de500kgha'1nedonnaaucunrésultat.Lorsdecetexamenonatestélaréductiond'érosionéolienne
àl'aidededeuxquantitésdetigesdemil(1000 et 1500kgha"1)pendant deuxsaisons(en 1994
eten 1995).Lerecouvrement dusolavec1500kgha"1 donnaunebonneprotectionpendant toutes
lestempêtesmesurées.Cependant, quand ils'agissait derecouvrement du solavec 1000kgha"1,
laprotectionétaitinsuffisante pendantdestempêtesfaibles(développant desvitessesduvent sous
10ms"1). Pendantunetempêteavecunevitesse duvent de 11,3ms"1 onamêmemesuré qu'ily
avaitplusdetransport desédiment àcause destigesdemil.Cetteaugmentation d'érosion était
causéeparuneturbulence plusforte autour destiges demil.C'est laraisonpour laquelle ona
recommandéd'utiliser aumoins 1500kgha'1detigesdemilpourlaprotectiondusoldansleSahel.
En plusdes expérimentations surleterrain, onainterviewé 138agriculteurs enprovenance
deseptvillagesafindevérifierleurconnaissancedesprocessusd'érosionéolienneetdestechniques
deconservationdusol.Laplupartdesagriculteurs(63%)considéraient l'érosion éolienne comme
unecauseimportantedespertes deleur récoltes.Desplantes sont abîméespar abrasion du sable
ousontperduesparcequ'ellessontcouvertesdesable.Ils'estavéréquelamajoritédesagriculteurs
151
aunebonnenotiondesinfluences d'érosionéoliennesurlafertilité dusol.D'après euxlesterrains,
oùlematérieléolienretombe,sontrendusplusfertiles,tandisquel'érosion causeune dégradation
delafertilité dusol.92%desagriculteursutilisaientuneouplusieurstechniques de conservation
dusol.Lesmesurestraditionnellessont: l'application depailleavecdesrésidusderécolte ou des
branches,ainsiquel'amendement defumier. Desnouvellestechniquessontintroduitesparlemoyen
de projets agricoles. Cestechniques sont:larégénération devégétation naturelle, leplantation
d'arbres etl'usagedezai,unetechniqueprovenant duBurkinaFaso oùl'on sèmelesgrainesou
plantesdansdestrousremplisdecompost.Lesagriculteursappliquantlarégénérationdevégétation
naturellelaconsidéraient commeunetechniquequidonnedebonsrésultats, etelleal'aird'être
latechniquelaplusutilepourlaconservation du sol,parcequelesquantitésdematérieldepaille
et defumier sont limitéesenvuedessystèmes agricolesactuels.
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Curriculum vitae
Geert Sterkwasborn atEeinthenorthernpart ofTheNetherlands on23November 1966.
Afterfinishingsecondary school, he started studying atWageningen Agricultural Universityin
1985.In 1991hegraduatedinSoilandWaterManagement.Duringhisstudies,hewenttwotimes
to South-East Asia. In 1988, he stayed seven months in Indonesia, where he worked on a
hydrological description ofawatershed inthe southernlimestoneareaofeast Java. In 1991he
stayedthreemonthsintheMekong deltaofsouthernVietnam, and studied leachingprocessesin
acidsulphatesoils.After graduating, hestartedworking attheDepartment ofIrrigation and Soil
&Water Conservation. First asaresearch assistant, andin 1992hecontinued withworking on
thewinderosionresearchprojectinNiger.CurrentlyheisworkingontheEU-projectWELSONS:
WindErosion andLossof SOilNutrientsinsemi-arid Spain.