The state of the art in pedometrics

16 Pages·1997·0.11 MB·English

Geoderma, 62 ( 1994) 3 1 l-326 311
reiveslE ecneicS ,.V.BmadretsmA
ehT etats fo eht tra niscirtemodep
re t.eAP ,shguorruB nahoJ bamuoB d ntatoc S.R csetaY
‘Department of Physical Geography, University of Utrecht, Utrecht, The Netherlands
‘USDA/ARS, U.S. Salinity Laboratory, Riverside, Ca., USA
) 3 l9,i 98rn1poAisi vree rtdfeatpe c; c2 ha9,c 99rd1aeMvieceR(
ABSTRACT
sih Tr ey plsafwpeeiirv beerht etats efgodelw ofnok e hltait a npdlosnaiartoapi mrfeaotv liossa
re b,m n e3e pt-gdop1nlh ei essS nnhkcnei rio gdor iraeWtfseW se osdnsmeen iuohsiecdtohsejtiPedr
.2991 ehT sreesp s ae,u,pescsr nsthyoic tlide, etpydmasrnac aoani,elshpltpoaot ni smret fotnerruc
gnidna tdsnraedn ue hhtcr asecsiepro ttaht ew dlu oghnsi teabgi tnsievni eht txen wef .sraeeryutuF
snoi trcoefri deh tyduts fyoti lld iieebosrassaiur cansvii dsmret f oseus sriof l,i yosesevursussriof
,sgenui sln,srslosdoiei eofdt , r ho asydudtmfc elndneoieulaeamnv sacuirsno-mtoiirnmcffpioecffe
lacit syitti aloest itlrsnt bbeo oula asef io iiylugol.tbxorliiaaaisataotm d vnvsarnnfeadoAeorfprpuac
.dedulcni osla si erawtfos
INTRODUCTION
ehT eltit fo neehpgtonhisnkergoawW ,”scirtemodeP ,“saw denioc yb-orP
reolsAsef x yentarBcM to describe the quantitative study of the variation of
dlei f. lhigousoht leAht mret sa hre hgtno inenadaiesmt ulo i,oescneic stisaw
ylet ariadeelmcmi ot sltisoist nteaihcts eht drow sah owtstoor : srefoetr
pedo
dle ilfiosna d srefer ot evitat istenhacuaqorppa htob rofstnemerusaem
metric
and area1 characterization. “Pedometrics” is also the eponymous title of a
gnikr opwuorg fo eht ,S SnSoIisivid ,5 hcihw saw tes pu ot yduts eht-itnauq
evita tstcepsa fo eht laitaps dna lar onpomiettairav of dleif .lios
li osStsitnei cesvah neeb erawa fo eht melborp fo eht laitaps dnalaropmet
variation of field soils since the beginning of the 20th century (Beckett and
Webster1,9 71S;m ith1,9 38W;e bster1,9 94)H.o weveriw,tan sou tn titlh e
lat1e9 60’asn1 d9 70’tsh afti elsdc ientistbse gatsnot udsyo ivla riatioiann
ci t.aymae wtte s nhssyteTetssd isrne deierfutfpe’te wosdlni iosspam nihcihw
lios noitairav saw nees sa na emocl eewcnnuasiun taht decuder pam-libailer
ity. Gradually the general nature of soil variation, and its unpredictability,
have led us to see variability as a key soil attribute rather than a nuisance,
tropeR fo eht ”redniojer“ ,noisses ,scirtemodcP ,ncgnincgaW 3-l rebmetpeS 1992.
00 1 607-6 00.70$/49/l 0 4991 reiveslE ecneicS .V.BlA l sthgir .deweser
SSDI0016-7061(93)EOO8O-F
312 P.A. BURROUGH ET AL.
hguoht dseinhetth gwielinve s iylniatr etcon derahs yy bl,reanlouycrietvreap
yb srennal pdn anois iscreedkam ohw hsiw ot esu nloiiotsamro fsnai asisab
rof noisi.cgendikam
ehT ts ayltn eswrtae yevah nees ysneacmnav dnai eh tyroeht foaitaps l -ats
tistics, in technology for handling data and the availability of quantitative
atad os taht l iyotsilibaira vsi won hcum re tdtoeobtsred nnuaht ti desu oteb
.fc( retsbeW dna ,revilO ;0991 ,bguorruB 991 1 .)a lio Sytilibairav sahneeb
the subject of a huge research effort in recent year s ,hguorruB( 199 3 ) . The
mia f osriehp tasp ie doitv owafreepi iv ,f reteoeb rngteedah rettfrlsouwconk
d estanese rypber ne eh,gtgnniinteegea mWni smretfo
)a( eht yroeht fo lait,anpositairav
)b( snoitacilppa gnisu noitamrofni tuoba lios,ytilibairav
taotvoh(alecis )l able.
Wree vietwh espeo intsb,o tfho trh ceu rrensti tuationi,. et.h qeu estioonf
“What do we know at presen t ?“ , dna rof eht elbaeeserof ,erutuf .e.itahW“
should we know?“. In this paper we also identify some issues for future
investigation.
THE CURRENT STATE OF KNOWLEDGE ABOUT SOIL VARIABILITY
Theory
ehT deen ot ek attnuocca f oy tlialiit ba napgeisnhriwalvl eldioomgsnimrof
and environmental processes is now abundantly clear. The phenomenon of
lios ytilibairav sah neeb dehcaorppa yb l a,cniorietmeautcnaiifriasvsiatllcum
statistical methods, continuous (fuzzy) classification, geostatistics, fractal
,sdo hltaecmita myeghotlaomhprom dna soahc yroeht ,hguorruB( .)3991ehT
yroehot f Geostatistics, de ts aatrsobrbiafle y norehtaM ( 791 )1 d nnaeehdtam
accessible by Joumel and Huibregts ( ,)8791 av astk sadaanvsaiIrS ( ,)9891
Webster and Oliver ( ,)0991 Cressie ( 19 9 1 ,) Deutsch and Journel ( 1992)
and others, has been extremely useful in providing a suitable theoretical
krowemarf rof gniyduts l i,oystilibair advna rof gnidivorp a dnuloasciteroeht
sisab ro f,noita lloaprruettcnuir tssisylana dna rof eht ngised fo lamitpo-mas
gnilp.skrowten
Today it is clear that the estimation of the variance of a soil property has
little meaning unless it is expressed in terms of the size and kind of spatial
estwiamEsax tipwevrtrhdae ei.rlsffc iausoobhatnirre beiom idtnulsssi tt y
to georeferenced spatial units. It is also useful to distinguish soil properties
htiw dna tuoh tti cwle arecicidntacvaerlp edrna ot eton eht deen otenimreted
stpteaahmtnepicd oao rlva alr isatnrcmueuc ltotufir veasr iat e land qualities
emso orfhfot single characteristics (e.g. ,OAF.)6791
THE STATE OF THE ART IN PEDOMETRICS 313
Applications
Variability studies are now an integral part of soil science. Studies in the
tsal ytnewt sraey evah derolpxe eht melborp fo lios ytilibairav morfynam
stniop fo ,weiv dna ev adhetal e nreohntemon eo htspmelbor pftoneicilfifoes
use (e.g see Bouma, 1989). Soil variability is being linked to the concept of
retlhiea isbnoifiololfir tmya tmieoranes:lou ifra ebsi ilnictslytu adtee ments
tuoba niatrecnu srotcaf hcus sa laitaps ,ytilibairav atad ,ytilauq gnilacs-caf
tors, and simulation models. The reliability/uncertainty issue is becoming
man-by used are studies variability when especially important, increasingly
tnemega rof noisice.dgnikam
Current soil surveys provide some information on the internal variability
gf nositpip natumub ew od to nweohntkehw r characteristics
permanent soil
evah )erutxet .g.e( withdiinf fereonctc ur-
characteristic spatial structures
rences or delineations of the same soil series. Many soil properties are not
constant (e.g. level of nutrients, moisture, bulk density) and their spatial
structures are also a function of time and process. Also, if a mapped unit is
detaer ts usoaeneg onm ioghn isksa eme c-h,ont.roepi.sii(c erdof dnuorrgetaw
as-the coannsdi derabbel e ramvmiuaflyian cseatsrtheaiesbo sinmlsei ntty) ,
tnemss eysam eybls.udoeiwraelsf
erehT si won a daor bsusnesno c etvai htstattneermpe rtdeaettvnsiiredmorf
lios spam deen ot edulcni nnaois sle ar.np yoxftieoit lnlieibvoansiolCesrpam
are increasingly being supported with information about the variability of
deppam stinu dna ytilau qlortnoc ni lios yevrus si gnimoc eebnituor sa-pam
gnip sdohtem emoceb erom detamotua .g.e( ,tgerB.)9891
evitatitnauQ atad no lios ytilibairav era derots ni lacihpnaorigtoaemgrofni
:smetsys yeht era desu rof gnippam dna rof gnisimitpo lios yevrus,tgerB(
1989; Burrough , .)a1991 Digital databases and improved methods for data
noitcelloc dn alacitsit astissoyelgana naem taht deliated seiduts fo lios-airav
bilitaynt dhc eo nsequencetsh ereocfae na silbmyea deT.hc eo ntributioonf
soil variability to (a) errors in maps, (b) uncertainty in the results of quan-
evitatit sledom fo epac s,dsneaslsecorp dna )c( eht ytilibailer fo dnal-aulave
noit seiduts nac eb detamitse dna syevrus nac eb d.eyzligmniitdproocechaT
deen ot ekat tnuocca fo lyatiitlaipbsa inrea hvgwnilled olmi onsoitamrofdna
, sleast snheeccmuonsropri vsnae ffonu rdna l inoosiso reeD( ooR te ,.la)2991
si wo nyltnadn.urbaaelc
Tools
eh Tnoitacilbup fo elgni sretup msomcargorp rof gnisyl alnaaita-plsibairav
yti .g.e(i n has been complemented and im-
Computers and Geosciences)
proved upon by the provision of theoretical texts (Journel and Huijbregts,
197W8e;b staeOnrld i ve1r9,9 C0r;e ssi1e9,9 O1l;e 1a9,9 a1tbn)hyd e -ed
314 P.A. BURROUGH ET AL.
velopment of software packages for statistics and geostatistics (see Appen-
.)xid ,paehC lufrewop lanosrep sretupmoc evah edam scitsitatsoegelbaliava
otnam y people dna edveathalum ieths tgnihcaet fo eht sdohtem ni-isrevinu
seit ot lios ,stsitnei clsacis y,hsprehpa rsgtoseiggoloeg dna .stsigolordyhehT
metsys noitamrofni lacihpargoeg fo ytilibaliava s )SIG( asnod ii nlf ormation
smetsys )SIS( rof gnirots lios atad ni latigid ,mrof rof gnippam dna rof-etni
gnitarg lios atad h tniowitamrofn ino rehto stcepsa fo ehtnemnorivne t -ruB(
,hguor 991 1 )b sdaehtalu mkirtosw no eh tsmelbor pdna e hltacit-cialrpppa
snoitac fo yltiiolsi b.agi.rea(v xkO dn a,srepiuK91 9 I).
While tools in data analysis have improved, and laboratory methods of
chemical analysis have become more automated, there have been relatively
we fsecnavda ni eht dniopiatrcell ofco atad ni eht .gdnlieticfe llliooCs-mas
selp si llits evisnepxe dna emit ,gnimusno chguoht secnavda ni-atnemurtsni
tpieornrm aiptri edp,r oducimbelaes uremmpaoehnfnyy ts ipcraolp ertoifes
eht lios r e.gga.ret(nel lden ha,ceSlttiloo D991.)1
ACTION FOR IMPROVING KNOWLEDGE ABOUT SOIL VARIABILITY
Theory
haveprobably we area, research popular a remains geostatistics Although
sufficient theory for many practical purposes in soil science. However, the
elor fo lios gn ismersosfecorp n ignitare nlyeitgoislibair anvi ecaps dnaemit
is still generally only understood in qualitative terms. There is little under-
gnidnat sfo woh li ogssneismsreoc fonrapc tluser ni eh tsuoi rsadvnik fo-aps
tviaarli aFtsiihigoonnw n . 1. Mosst tu dsioovefias lr iabilihtabyve ee n
post
i.e. unknown patterns of distribution are sampled in an attempt to map
hoc,
the true variation by interpolation rather than by predicting the spatial or
lar onpomiettubirtsi dmorf a la cginsiydhnpatsrednu fo lios gnimrof dnalios
chanpgrioencqgefuh seTiyaswthvdre heareserlo t. eelo no tgrsiuo cnraolf f
reta wldenduoomrg ni l i,oescnei cds nhacraese rni siht aera si,dedeen
hguohtlA yllaicifrepus ,evitatitnauq ynam fo eht erom decnavda -pa
proaches to gnilledom lios ytilibairav hcus(a s slatcarf and chaos theory -
,hgu o)r3r9u9B1 era ero me v yi:lteupvr iitnrtacphsit ertdciserp yamreven
. e.g.
e lebbi sost o ypylat scwaoxhe a n nryeetvt iitfl gao inplbicia ioiyfsrniaacveps
aera stluser morf a ralucitra ptes fo rae.nsiels-sneocnorp
litnU now, s naicirt eemvoadhep diap tso mnoitnetta ot eht melborp fo-aps
tial variation. The time component is rarely included in geostatistical anal-
yses. Typically, the scientist is confronted either with spatially rich/tempo-
yllar roop ro yllaropmet yllaitaps/hcir roop .atad A a consequence, only
S
limited use can be made of the data. There is a lack of suitable theory for
describitvnhager iabiliity n time ocfr iticaslo iplr opertiessu camhso isture
dna cinagr orett a.mtnetnoc roF eht l alcaictispiyt taattsaodegtes , -rec
supply
315
THE STATE OF THE ART IN PEDOMETRICS
al - X )b X
1Z .-;-:.-.
c
X X
cl dJ
X n X
e/
.giF .1 lacitehtopyH sledom fo suoirav smrof foaitaps l noitairav tahtac n rucco ni .lios)a(
dezilaedI suonegomoh noitairav nihtiw pam stinu gnivah prahs seiradnuob taht era netfodesu
ot etamixorppa emos fo eht gniwollof laer sdnik .noitairavfo )b( suounitnoC htooms,noitairav
lacipyt fo emos .smrofdnal )c( tinu-nihtiW noitairav rellams naht neewteb tinu noitairav sanac
rucco nehw lios noitairav si detanimod yb secnereffid ni suoenegomoh lacigoloeg .stinu)d(
suounitnoC htooms noitairav htiw lacol esion taht si nommoc rof ynam lacigolordyhseitreporp
hcus sa retawdnuorg .slevel )e( yranoitats-noN noitairav gnidulcni a dnert ( 1), tpurbaegnahc
)2( dna regralaht n egareva tinu-nihtiw noitairav )3( taht srucco htiw ynam lios .setubirtta)f(
noitairaV erehw trohs egnar stceffe hcus sa laicalgirep features ro lacol slevel fo lisotsnatullop
nac pmaws lla rehto.slangis
tain question s nac eb derewsna ,tub fi eht etubirtta segnahc revo ,emit a lluf
elacs gnilpmas troffe si deriuqer ot etadpu eht .noitamrofni kroW nolaropmet
noitairav fo lios lliw ylbaborp eriuqer noitaroballoc htiw stsitneics ni rehto
senilpicsid hcus sa ygoloroetem dna.ygolordyh
nI etips fo a eguh hcraeser ,erutareti legdelwonkuoba t soil ytilibairav sillits
316 P.A. BURROUGH ET AL.
dispersed and not organized in such a way that there is a general theory or
elur esa b g .nryiott ficelliriideobehsarTip rsaiv a deen oetzina gdrnoa-etsys
e zeig tdra eumy lotnwiool n ilknbiiao ishrcauvs a ya wt ashrtes ufo l-iroosfni
mation unskilled in geostatistics and modelling can make the best possible
sno i ssrnieocdien tdu.iyd tnfnooic aetcrneOcn u eehgtdelw osnakh neeb-htag
dere ,ddneazi nnaeghrto ti yam e belbisne sot esu tr espmxeetsys ot pleheht
res uesoohc woh tseb ot lae.dy thntiiawtrecnu
For regional, continental and global studies we face the problem that the
spatial resolution of the application is often quite different from the spatial
noituloser ro( eht )troppus fo eht sno ietvaivtraetsnbeos e,rspeelri(forptniop
.e,)sssuenalocp demteBaips si nwo nytktaih ltli ibsoais inrea tvefgnoriahltiw
spatial units, such as soil associations used for regional studies, we need to
ask if it is sensible to use point data and detailed models to make regional
estimates of attributes such as expected crop yields (Bregt and Beemster,
.)9891 roF saera hcihw osla evah lios spam ta regral selacs ti yam eberom
s ts i e .neftr nu roa oei-eemef labghihdbrua Wtteirsros tseeteehntvkgeaaismew
avakianlloalwb lulesende eg ceteosb sea wriyl l ite ximsastpc lsaa lreg en o
ylb idsestoapl(uspacne ni na trepxe )metsys dna diova oduesp.ycarucca
Applications
Futuarpep licatiokonnfso wledsogofevi alr iabiliwtimyiblo neln itoring
(determining derived variables using pedo-transfer functions, remote sen-
sing, etc.), for predicting values of attributes that are too expensive to mea-
sduirreec camotnerblna eyos tud rierde cetfanlonvyrdi, r onmenta l -lledom
.gni ehT tsal y lstrinaalturcoiptmr iaspa yethntiatre cnniu led osmtluseryam
netfo eb eud ylegral ot s eeihttn idaetsrueaccnu yb laitaps dna laropme-tirav
abilibitonytt dhhae at tnamhd oe d pealr amete(rBso um1a9,8 H9e;u velink
te ,.la.)9891
yyntaiMl isbeaiidruatvs era edam ni alac i,gtoxleotdne opecrehw lios-ed
snoitpi recrsa desab no cs in.toseinntoeaz gcihirclouphspA sa dnnoailtaulave
studiessh ouladl scoo nsidetrh kei ndosvf a riatiotnh aatr ien ducewdi thian
nevig epyt fo lios yb lios .tnemeganam tnereffiD sepyt fo tnemeganamnac
netf oevah a ro jtacmapmi no , rleuisoouisav cayehebe hbttcef felariuotscurts
ro eht tnetnoc fo cina g.rroettam nI gniydut s,l yistotissliitbnadeilirucaosvhs
be more aware of this phenomenon and Stratification of soil data by land
tnemeganam rehtar naht yb lios epyt yam yllanoisacco eb elbatiforp,surB(
.)499 1s i sheeTlspimsaa xheephmte deen rof a l asciistyilracn afo eht-marap
yduts deilppa fo epyt ralucitrap yna rof tnaveler tsom era taht atad dna srete
.g.e( ,amuoB.)2991
noi tganliulmlieSdom syilgnisa egrncineib desu reovfitatit ndanuaql-lave
.noitau retaW dna etulo swolf si ydlelbaiu rsccuist e sndsiilneidmormeteydb
eht drahciR/ycraD noita uhyqcleit hiswceimlups mssialios otb e -enegomoh
EHTTATS E EHT FO TRA NISCIRTEMODEP 317
dn a.ciporto stisoM dleif slios era r eshutoieennegom orhon ciportosidna
ous
contain either contrasting soil horizons or macropores, such as cracks in
swelling soils and biopores in biologically active soils. Because many land
,seitilauq hcus sa erutsi oymtilibaliava ro ,ytilibaciffart era dessessa ybgnisu
noitalu msiesiduts taht ylticilp meimussa eht lios ot eb ,suoenegsotmlouhser
yam . genbi deareelhsTim si osla a ksir taht eg rlaalitaps r ol-alriobpamiertav
yti ni eht cis asbci tlsiiorset cfaor a,hecru tcxientag rroettam dna klub,ytisned
which are used as model inputs, may give incorrect assessments (Bouma,
991 .)1 f Inoita lsulmeidsom era os evitisnes o tsnoitaira vni tupni atad saot
yield unreliable results then their relevance and usefulness should be ques-
tioned. The interplay between soil variability and the sensitivity of mathe-
val-parameter and data in variatteimopnosr al and spatial to modelsm atical
ues should lead to the development of robuster models and to an improved
understanding of the limitations of current linear modeiling (De Roo et al.,
1992).
erutuF snoitacilppa ni erutlucirga dna latnemno rtinvenmeeganam lliw-er
quire detailed knowledge of soil variability in both space and time. For ex-
,el psmraezilitref nac eb deilppa er o,myltneicif fhetiw decsuedcenreuqesnoc
to the environment if the application to a crop can take account of levels of
rezilitref taht era ydaerla ni eht lios .g.e( ,ekniF .)3991 noitagirrI retawnac
osla eb deilppa ni caificeps -,eytaiws yb enro eightntairduitoavsa -rroevo-ni
fertila-pply whdiecvhe lopbeede n haves yPsrtoetmowsstau ytfpeferi .c ient
srezi ot sdlei fg n sirdrseeoutltula pochmricotlicnphopwca era dediug yb-gid
ital maps of the field variability. However, it is still unclear how well these
systems protect ground water from contamination. Data on soil variability
lliw eb desu ot eetcanre edsnilefegnvoecl no slneodiotmc itdaehrtp eradesu
yb srennalp dna noisi c.esdrekam ehT esu fo sledom dlnaacihpa-rrgoofengi
mastyisoivtstnnahoe craimodlitlnsaua tdbaeia w ldliiilltfolyfw e lraenndt
es usoiranecs ot eb .dyelreavpimtocceffe
Tools
scitsita tssaoheG devorp ot eb a yrev lufesu loot rgonfiyfit nlaiuoqs-airav
bility, though its use has raised many questions about numbers of samples,
-citrap erehw dna nehw dna ,atad yfitarts ot woh ,margoirav a ledom ot woh
ral useuqinhcet era t s.oemtairpo repspeahT seussi deen ot eb desserddadna
toolnse etdbom e a daev ailablteh apte rmiuts ertseo x plorteh esqeu estions
.y lsidsoahet eyM rfoota raotlaipdsxyelana s )ADE( l inkedt o -wodniwitlum
ing statistical programs on microcomputers (e.g . ,.la te ttelsaH
REGARD -
)0991 wolla eht resu ot erolpx ex eeltpamiorcavit lautmad stes ylisae dnaot
remoovuet liseotrrrs a ncgleu sterTwwshaih.eyni s c h ADE tsissa nac -soeg
lacitsitat sesylana deen ot eb .rdeehttarguiftsevni
ethnTempo lleav c efiedotrsaiwttaftoss oreogf gniwol lsaresu ot krowhtiw
318
P.A. BURROUGH ET AL.
g.e( atad evitatilauq . Bierkens aBnud r roug1h9,9 qo3ur)a ntitatidvaeait na
probabilistic way (e.g. Yates and Yates, 1988; Deutsch and Journel, 1992)
sdee n o.t dselg oaeeorbkTuiolcAnDeA M (ni lesseW g , kdnnialev9u1eH 9 )1
for analysing how errors in data affect the results of environmental models
need to be made widely available. In the United States, a recent National
ymedacA fo e ecdenetentiricem Scmhnoto Cicswdohte m rgonfisdsneusosrag
yt irdleeitsbasawerretn sleuhvt deen rof sdoht ehmcihw dle isytluser ni-borp
citsili b.asmret nI eh ts’eett inmomioncipo ylno siht epyt fo noitamrofnliliw
elb aenseu -sdrneaglanam ot eka md e,m srynoloflinasiiicceepds eni eht-serp
ecne . yfto nsidaothrte echMncuihw od t osne ietdiilvio bryapabmordpaelsim
eht resu ot nginiveile beht ledom tuptuo si.niatrec
eh Tg nn iiklacbmomlubt so t rseetitdeub t fsyoti llii bosasiir akvcal fo.atad
Methondesdbte eeodv elopfegodar t herignogdo adqt uai cklaylin,and r ge
amounts. There is a need to integrate modem remote sensing systems with
geographicianlf ormatisoyns teptmroso viddaewbt ieaatt htr eers olutiionn
space and time than is now usually possible. Geoelectrical and geophysical
smets yhscus rs eagg nadir nt t ,uarndeoraenlrtdlatgealtnreiehlpco9So1(D 9 )1
or electro-magnetic measurements (e.g. Brus et al., 1992) may be useful in
emos.secnatsmucric
tI si ygl ngtinnmiaostcareeobrpcmni iot wonk eht ltaccaixhepa-ragcooelg
stoooibifosl ne rvatoirrioetdnnloe sta ra ht ceecm u raltatenold ys cfaepae-
serut hcus sa ,y g,omlrooefgd nlaalcol feiler d n.ay gdolleohr-ddlynahabHolg
gninoi tsimseotpsys )SPG( taht ev ineocietramrof nmiorf a krowten foecaps
setille tearsa gnimoc otni esu rof.siht
,slooT hcus sa tre p,xsemetsy sdeen ot eb depoleved ot edivor psresuhtiw
up-to-date information on how to tackle soil variability and how it affects
issues such as crop yield estimation, environmental management etc. A re-
tn eeclpmaxe fo a luf etsrue pmxeetsys si ALES ,retissoR( .)9891
NOISSUCSID DNA :SNOISULCNOC EHT TNATROPMISEUSSI
Issues for soil survey
Current soil surveys provide some information on the internal variability
fo gnip psatminu tub ew od ton wonkehtehw r lios scitsiretcarahc
permanent
.g.e( )erutxet evah within different occur-
characteristic spatial structures
secner rsonoitaenil efdo eht emas lios .seires etoN taht ynam liosseitreporp
anrpoeet r mane(nntu trientmso,i sturbeu,dl ekn sitaytn)hd e sipra tisatlr uc-
serut era osla anoitcn uffo emit d.nsas eecroerhpT si a deen rofc iatametsys
spatial variability analysis of permanent properties in multiple delineations
fO lios.seires
tA mraf ,level lyitoislibair asvi won gdneiteebrpret nnii smret fo-anretla
sa e y r ttf atenios-n vel mbesirirgr umit e bono.seaffafifdgfoielairbendaiaVfm
THE STATE OF THE ART IN PEDOMETRICS 319
seen as a key attribute rather than just a nuisance. So far, attention has been
focused on soil fertility but moisture supply, egallit practices, planting and
seeding, and biocide applications will follow. We need to be able to define
evi tsceerjubdoecorp rof gnin isfaeedra-b unsihtiw sdleif taht tca saylevitaler
homogeneous management units. There is a need for procedures to assist
noitacifita rytbs 1aera yevrus ro yb etome r.gn insonietsalu msilSedomdluoc
be used to define variability over time when the underlying physics of the
system is known. Other methods are needed for defining the time-rate of
egnahc ni lyitoislibai rr aosvfeitre peorrephw eht scisyhp si ylegrnawlonknu
or misunderstood. Inclusions of different soil types in a mapped unit may
esuac e ryetvneisatre cnn eugh nweitnaiimrrpeotre pdspeasu rof .dnal roF-xe
,elpma n,ade tdreodpuelrcnnu ilios ,epyt neve fi t istneserper a llamsnoitrop
fo eht ,latot nac g neibtats aovte ddnuo rrge tyatwilauq fi seehittrep ofropeht
included soil enhance transport. These impurities are similar to fractures or
rehto larutcurts .serutaef sdohteM rof ,gnitae nginliezdiretcarahc dna-troper
gni si hntoitamrofn iera.dedeen
For regional, continental and global studies we face the problem that the
laita pnsoituloser fo eht noitacilppa si etiuq tnereffid morf eht laitaps-uloser
tion of the observations (representative profiles, point samples, pedons).
When soil variability is known to be large within the spatial units used for
lan osiegiedruts ti s iyrassece not wonk woh oetsila rtennieogp atadof r -om
delling potential crop yields and other difficult to measure properties. For
saera htiw lios spam ta regral ,selacs dnuos sdohtem rof gnliaknaomitroporp
s e detregaotamhrigetoivseaew f yt rseepuolrap vsrtoifnu -ebru.asdedeen
soil
erehW o nre gerlaa lcssp atmsixe ew tsum es uged lelbllawaloinakva e -issop(
y ldbetaluspacn eni na trepxe )metsys dna diova oduespycarucca . since
Also
,ssmees ls,b esodcnr nooprariupsciccoe dt as u, ossiedrloaahvct seemradedeen
which operate at these scales, that translate information from one scale to
rehtona dna edivorp e hyttniatrecn ufo gniod.os
Issues for modelling
Because of the effect of weather on soil behaviour, temporal variation is
also very important. We can model processes retrospectively and can cali-
brate and “validate” (or quasi-validate) the models. For land management
and planning we need to predict future conditions for alternative land use
.soirane ctsI lliw e blaitness eot wonk fi laer e mginti ldleekdcoemhc yblaer
em igtnirotino mdna muidem mret reh tsateswacerof si lufesu dn.aelbadroffa
It is necessary to know how the probable, large inaccuracies of long-term
weather forecasts can affect model predictions and therefore to know how
accurately soil characteristics must be measured or defined given the likely
egral laropmet dna lai tyatpislibairav fo rehtaew dna .etamilc ehTnoitcaretni
fo suo idreatevaslseercorp s sdeen ot deobotsre dfn i uegtnairlulcecldaloimw
320 P.A. BURROUGH ET AL.
reve eb .deveihca sihT semoceb erom tnatropmi sa seid ustssapmocnreegral
saera .g.e( eht labolg.)elacs
It is important to determine the uncertainty in the data as well as in the
predictive methods. Resource managers are quite dismayed at the current
slevel yfton itanterseecrnpu n ign i.lslterdoofmfe feIcned isfdnnoacb eraoot
large, then the methods are not helpful for practical decisions, regardless of
detail. As the size of the area to be managed increases, simpler approaches
mbaeyc ommouersn eeie faiscunt eld sad sbbteatelotro e ey r mitanhpee-
etairpor plevel fo liated fo sledom dna gn intoriotpapmursofn irof ynanevig
.esu tI sme eys lleak cisi ldttosahih tttdealmtusooceg eb desu oetnimreteehdt
leve ly tfioxelp maoc l e sddsolam upnomehovscing eeht level fo liated foeht
elbaliava .noitamrofni
Predicting soil attributes using a digital elevation model and terrain anal-
sesy yam evah y ns antmoniattarcoip fmrii omefavr igtnciildle,erydpnonmeJ(
491 691,1 .)1 si hhTcaor ptphagim eb dias ot ” y gtenibiltiecbciandiiersrapv“
the aim is to predict the spatial distribution of soil attributes from easy to
obtain, nondestructive, non-soil, high resolution data. If this type of an ap-
hcaorp nac ec ued tosarerptuacmciats efo eht naem dn aecnairav fo eht-birtta
ptarrtetsutdhulpauinemrbyritcenofe oneta da c-,irmecoe v alefseyl s iensg
elba ni ) yelhetvi traalee nr,(eru thugf usophitllihP (891 9 ) sdaehnr afwoeht
smelborp taht ytiraenil-non yam.gnirb
Issues for methods and procedures
weN sdohte mhcihw e cnuo di,eteracmn iaetirsrieauvqe rrewe fselpmasdna
nac esu ”tf onso“itamro fdnliuohs eb .degaru oscdnoehteM dluohs eb-leved
depo hcihw wo lnloaitamitse ni htob eht laitaps dna laropm entiamod-lumis
taneously. Methods should be developed that provide probability informa-
noit lufesu rof melbo r.pgnivlos weN sdohtem rof gnilpu olcaiyttaiplsibairav
ot sledo mdluohs eb.depoleved
One serious problem is the need for more and better data. A systematic,
deliated laitaps sisylana fo tnenamrep lsicoistsiretc adrlauhocw eb ,laeditub
yam ton .elbacitc aorTp od os dl ueorwiuqer ngeanviinsinae rtrtxoee(rwen
)gnirih fo lios yevr ulsennosrep dna eht tsoc g nfiotagi tdseepvpnaimerslios
polibteias cbnctaaocalstettmli plih(ayctesHeiy aato . bsiwealtce.te sv, . e r,
naem d n)aecnaira vfo scit s eidhrlteutoccara hecb dei ldpapeutssni fo aegnar
thdeeterminet oi mportanti s it Also,v a“ltuyep.i cal” a or val“uleisk ely” of
uncertaintitdhnyae wat esatial phnslre e dictimveet hodRse.s ourmcaen -
sr eygaa mton e belb ao ts deto saheuhtvt eaomh ohtgi.hy talneiva etflroecnu
efc Ind enedahib tfsnio co,oe tgnre ah sltedho thetrea mtlounf ergsonufikam
practical decisions, regardless of their level of sophistication. Methods are
dedeen oetnim ree tteaehi dtrlpeovreplpa fo liated rof sledom gdnniatroppus
noitamrofni ot eveihca ralucitrap.slaog