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Snow Surveying in Canada: A PerspectiveB.E. Goodison , J.E. Glynn , K.D. Harvey & J.E. SlaterPublished online: 23 Jan 2013.

To cite this article: B.E. Goodison , J.E. Glynn , K.D. Harvey & J.E. Slater (1987) Snow Surveyingin Canada: A Perspective , Canadian Water Resources Journal / Revue canadienne des ressourceshydriques, 12:2, 27-42, DOI: 10.4296/cwrj1202027

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Snow Surveying in Canada: A perspective

B.E. Goodisonl, J.E. Glynnz, K.D. Harveys and J.E. Slaters

Abstract:This paper presents a brief overview of snow surveying in Canada-its evolution,current trends and problems, and future possibilities. Th6 nitional snow survey networkis discussed, particularly with respect to the rore played by environment Canada. prob_lems associated with the measurement and analysis of conventionat snowtourse data,data publication, and data archiving are identified. Airborne g"rr"iiy ,now surveysare revlewed as one viable alternative in the future. Tne fealibillty of

'establisning inoperational gamma ray program in Canada is discussed. fne'potentrar tor usingpassive microwave and other remotely-sensed data from satellites to estrmate andmap snow parameters is_ assessed. Finally the need for a co-ordinated natronal snowsurvey program is identified.

Resume:ce document donne un bref apergu de r'6tabrissement des rev6s nivometriques aucanada, son 6vorution, ses tendances, ses probre,mes actuers et ses possibiritesfutures. ll traite du r6seau.nivom6trique national, et plus partlculie'rement du r0le jou6par Environnementcanada. lld6gage les proble'mes li6s a,la mesure et a,l'anaryse desdonn6es crassiques du cheminehent des rev6s de r,enneigement, a;la jubrication et a,I'archivage des donn6es. il examine res rev6s nivom6triqu6s adriens p"r riyonn"r"ntga.mma' m6thode qui pourrait constituer une solution acceptaore poui Liuenir. 16tudiela faisabilitd d'6tablir un programme d'exploitation des lev6s par rayonnement gamma.ll€value la possibilit6 d'utiliser les donndes obtenues par tes hyperfr6quences passiveset celles provenant de la t616ddtection par satellites pour esilmer. er'cartoirapnte1- tespararne'tres de la neige. Enfin, il 6tabrit la n6cessit6 o,un progiamme naiionat coo.donn6 d'6tablissement des lev6s nivom6triques.

IntroductionSnow courses have formed the basis of theCanadian snow survey network for over fiftvyears. However, recent advances in remotesensing technology offer the potential for signifi_cant changes in snow survey procedures inmany regions of Canada. A combination ofground-based, airborne and satellite informa_tron, or ultimately remote sensing methodsatone, may be the most effective and efficientmeans of snow survey data collection to meet avariety of user needs. These include streamflow/flood modelling and forecasting, water resourceplanning and management, irrigation and otheragricultural activities, wildlife management, acid

snowmelt shock potential assessment, recrea-tion, and building design. Although hydrologistshave historically been the principle users ofsnow data, many other fields are now benefit_ting from their availability.

Recently, there has been considerable dis-cussion about the future of snow survevino inCanada. We are in a period where resouiceconstraints are forcrng agencies to review care-lully their current programs and assess theirfuture plans. This paper is intended to providernformation on the cunent state of the snow sur-vey network, particularly that of EnvironmentCanada, and includes an overview of potentialproblems of measurement and analVsis associ_

1 Canadian Climate Centre, Atmospherlc Environment Service, Environment Canada, 4905 DufferinStreet, Downsview, Ontario, M3H 5T4.2 Natlonal Hydrology Research Institute, Environment Canada. Current address is Geological Surveyof canada, Department of Energy Mines & Resources, 601 Booth st., ottawa, ontario, K1A oEB.e Inland Waters/Lands, Conservation and Protection, Environment Canada, place vincent Massey,Hull, Quebec.

Revue canadienne desressources hydriques / Vol. 12,No. 2, 1987

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ated with these data. lt examines the status oT

the Canadian alrborne gamma ray snow surveyprogram and summarizes advances in satelliteremote sers'ng. includ'ng init'al research results

on snow cover determination on the CanadianPrairies usrng passive microwave sensorsErrors and problems witn these new methodsare also discussed,

National Snow Survey ProgramCanadian Snow SurveY NetworkTable 1 outlines the growth of the snow coursenetwork from 1963-64 to 1982-83' and ln-

cludes the totals for the only agencies operat-ing national snow survey programs, namely tne

Water Resources Branch (WRB) of Inland Waters

ano Lands Directorate and the AtmosphericEnvironment Service (AES).

Water Resources Branch has been collect-ng and publishing snow survey data since 1922(Water Survey of Canada, 1 968). By 1 964, ii wassurveying 1B percent of the riation's 674 snowcourses. At that time, AES (formerly Meteoro-logical Branch, Departnrent of Transport) had

only 11 snow courses, The latter's active part,cipation in snow course operattons began in

1 961 -62 f ollowing a decision to include regularsnow surveys at principal weather stations. It

was anticipated then that the data would bevaluable in estimating the spring runoff poten-

tial, agncultural productivity and fertilizer re-

quirements, water-fowl populations, livestockand wilcilife survival rates, snow loads and in

providing inforrnation on the physical characterof the snow. Today, it is recognized that thesedata are also useful for the analysis ol the

impact of climate change on snow resourcesand are extrernely valuable for the validation of

new remote sensing technlques.By 1973. 13.6 percent o+ all courses were

being operated by WRB, The number of WRB

snow courses peaked at 175 in 1976 8y the

winter of 1982-83, the nunrber of stationsreporting had dropped to g4 Substantial reduc-tions were made in 1984-85 by the AtlanticRegion of IWD with the retirement of all but 6snow courses, which are located in the Saint

John River Basrn and ccntrnue to be surveyedas part of Canada's ccmmitment to the FloodDarnage Reduction prcgram. In addition' in1984-85, the Winnipeg office eliminated the 13

snow courses it was operating within the Lake-

of-the-Woods watershed. As an alternative, the

Lake-of-the-Woods Control Board now use

snow water equivalent estimates based on

accumulated PreciPitation data,AES exoanded its srow course nelwork over

the last two decades and currently operates

130 courses. or 1O percent of the total letworkacross Canada.Atall stations observations are

made twice monthly; weekly observations are

made at many. Including courses operated by

Parks Canada, Environment Canada's natlonal

network currently represents less than 15 per-

cent of all snow coursesThe remainder of the snow survey networK

is operated by several other government

agencies-mainly provincial-and a number of

oivate companies involved in the hydro-electric

oower production. Table 2 shows the distribu-

iion by agency of the total network in Canada in

1982-83 (Atmospheric Environment Service,

1984), There is a wide variety of uses ot these

data, as noted earlier, butthe primary motrvalton

of most agencies is as stated by the British

Columbia Ministry of Environment, ie, "the

measurement of the water contained in the

snowpack prior to the commencement of melt,

is a oood indicator of subsequent streamflow,

whici in turn is of great benefit to those con-

cerned with hydro-electric power, flood control'

irrigation, and domestic and municipal water

su[pty' (British Columbia Ministry of Environ-

ment, 1986).

Snow Courses: Problems in Measure-ment and AnalYsisThe development of a snow survey networK and

the frequency and accuracy of associatedmeasurements must be relateo to its purpose

ln water resources, most snow courses are

established to obtain an index of snow water

equivalent over an area. For this purpose the

equipment, procedures and siting of the course

should remain consistent over time Unfor-

tunately, some or all of these factors may

change over the years; yet' the data contlnue to

be us-ed in the same manner, uncorrected' with

users ultimately questloning their validity Abso-

lute estimates of areal water equivalent can only

be obtained after allowance is made for instru-

mental, observational and siting blases ano

after the sampling network has been designed

to reflect areal snowcover variability

a) Instrument ErrorsOur knowledge of instrument errors asso-ciated with snow samplers used in North

America is now well documented (Work et ai '

1965; Goodison, 1978; Farnes et a/, 1983)'

The most important in deternining the abso-lute accuracy of a sampler is its ability to cut

and hold an accurate snow core This is assum-

ing. of course, that equipment is properly

maintained-tubes are waxed, cutters are

28 Canadian Water Resources Journal /Vol 12, No. 2' 1987

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29Revue canadienne des ressources hydriques /yol. 12, No. 2, j9B7

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TABLE 2: Distribution of Snow Gourses In Canada, 1982-83

1)

L.)

2\

4)

ql

6)

7)

8)

e)

r0)

11)

L2)

13)

1s)

16)

Operatlng AgencY

Ontarlo Hydro

Environment Canada, Inland WatersDirectorate

Abitlbl PaPer Co. Ltd.

Parks Canada

Ministry of Natural ResourcesQuebec Meteorological Service

Agriculture Canada

Soc16t6 d'6lectrolYse et dechimie Alcan Lt6e

Churchill FalLs (Labrador)Corporation Limlted

The New Brunswlck ElectrlcPower Commission

The Bowater Power Co. Ltd.

Ontario MinistrY of NaturalResources, ConservatlonAuthorities Branch

Indlan and Northern Affalrs Canada

Alberta Envlronment, TechnicalServices Division

Province of Manitoba, DePartmentof Natural Resources, WaterResources Branch

Saskatchewan Envlronment

Envlronment CanadaAtmospheric Envlronment SerVlce

B.C. MlntstrY of the Envlronrnent,Hater Management Branch

EnvLronment New Brunswlck

TgTAL

deternined from Snow Cover Data (Atmospheric Environrnent

Number ofSnow Courses

130

257

IT291

Percent of Total

7 .3%

0.4%

L.9%

1 n oo/

0.5%

L.4%

L.O%

2.4%

2.0%

L2.8%

6.4%

2.3%

9 .5y

6.4%

L9.9%

0.67"

T00-.0r,

94

5

2.1

141

ld

IJ

31

26

165

83

L22

83

30

14)

t7)

18)

Note: Totals nereService, 19E4)

30 Canadian Water Besources Journal / Vol 12, No 2, 1987

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Kept shafp, and spring balances are checkedregularly for accuracy (Atmospheric Environ-ment Service, 1973).

Farnes et a/ (1983) documentecl the fteldtests, meihods and results from stucjies onacouracy and design of existing ancj reconr-mended metric manual snow sampling equip-merit. Table 3 gives the mean measLl!'ementerrof for selected snow samplers, based onoa'a obtained by the Metrication Committee ofihe Western Snow Conference and other studieson snow sampler accuracy, These results showthat small diameter cutters (i,e., areas of 1 O- 1 2cm2) overmeasure by up to 1O percent whilemanv of the large diameter samplers measurevvithin 1 percent of the values,

Frgurre 1 shows the snow water equilrment(SWE) measured using the standard Fede'alsnow sampler, which is used in deep snow-packs in North America, compared to thereterence Glacier snow sampler. 'fhe Federalovermeasures by an average 1 O percent basedon samples taken in Ontario, Brrtish Columbia,Mo, ':arra and Calr'ornia (Farnes el a/., 1gB3). Todate, agencie-s have not corrected their data forthrs rreasurement bias, althouqh it is now

realrzed that it is significant, particularly in deepsnowpack regions.

A declsion on correcting historicalsnow coursedata tor instrument error has yet to be made, TheU.S. Soil Conservation Service and CaliforniaDepartment of Water Resources, for examole,propose to correct historical data files for sam-pier overmeasurement and convert to metricwhenever they might convert existing equipmentto metric. This decision is extremely important forusers, particularly those involved in flow forecast-ing, since forecast procedures wijl have to bead1usted to account for any change in snowmeasuremenl related to the change in equip-ment. This is particularly true for models whichuse snow survey data as an index. A 10 percentro'duction in measured snow water equivalentcaused by equipment changes could certainlyarfect model calibratron and, hence, the flowvolume forecast, Thrs problem could be accen-tuated even more if some agencies change theirequipment and others do not.

b) Metrication of Snow SamplersThe Western Snow Conference established aMetrrcation Committee in 1978 to review, test

TABLE s: overmeasurement of snow water Equivalent and correctionFactor. for Various $urow Samplers

\peOvermeasurement

Cutter Area, cm? (percent)CorrectionFactorr

Glacier

Standard FederalLeupoici anC StevensSharpened lederalBowmanMcCal IRos enUtah

1980 lletric198i Metric

ESC 30

AdircndackMSC

Aluminurn Tubing

81.9

77.2r\.27t .2TI .211. .211 .2LL.2

10.010.4

30.0

35.1lq 1

77.r

0

10"08.0o.z

4.0

3.8

-0. 3

0.1J.t0.6

1.00

0.91u.95o.94n aq

0.960.970. 95

0.960.96

1 .00

1.000.950.99

To obtain true SWE with various samplers, multiply measured StdE by thecorrection factor. (adapted from Farnes et" al.. 19g3)

tlevue canadtenne des ressources hydriques /yol.12, No.2, 1987 .)l

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FIGURE 1: Snow Water Equivalent (swE) for the Glacier snow sampler compared to the

Standard Federal Snow SamPler

*

g

and recommend equipment and procedures for

the metricatron of snow surveys and nranual

snow sampling equipment. Their report (Farnes

el a/., 1983)'ecornmended tvvo'netric sa'nplers-one for deep snowpacks, another for shallowsnowpacks. The 1981 metr,c snow sampler,with a cutter area of 10.6 cm2 and with scalestnat read rn true weight (i.e 1 gram welghtequars 1 mm water equivalent), is proposed for

deep snowpacks. The principles of design are

similar Lo ti'ose of the Federal sarnpler now inuse. For shallow snowpacks the ESC-30 sam-

oler is proposed. lt has a cutter area of 30 cm2

and uses clear plastic instead of aluminum forthe snow tube. For snow depths less than 1 m'

this sampler shows no significant overmeasure-ment, Detailed design information and testresults for both samplers are provided by Farnes

etal.(1982 and 1983),Tnree phases can be used to convert to riet-

ric units. First, a "soft" cc;nversion is applied todata obtained with existing equipmeni. AES

began doing this with the 1978-79 Snow CoverData publication, Secondly, existing equlpmentcan be modified by changing the marklngs on

the tube and scale to metric units British Colum-

bra Water Resources Serv'ce corverted their

Federal samplers in this manner in 1977 Chang-

ing the cutters on these samplers to metrlc ones

w6uld complete the conversion; this step has

not yet been taken. The final step in conversionwould be implementation and use of the new

metric equipment, In Canada, for shallow snow-pack sampling, the MSC sampler wourd be

replaced bY the ESC-30 samPler'AES has initiated the changeover oI Its equrp-

ment, Small diameter metric samplers ano

sp.ing balances l'ave been put Into operation at

siations requiring new equipment. The cutter is

strll that of the old Federal sa'npler: cutters will

be changed when other snow survey agencies

change theirs, The first ESC-30 samplers nave

been acquired and deployed as required lt

would be preferable to replace all MSC sam-

plers with ESC-30 samplers at the same tlnle so

ihat there is minimum disruption and confusion

in data acquisition, processing, archiving and

analysis. Other agencies must decide if they are

going to 'retrrcate their equipment

GLACIERvs

STAHDANO FEDERAL

Y.O.So9sxR2=O.99sgS.E.:1 7.5

STANDARO FEDERAL SwE. mm

oz Canadian Water Resources Journal /Vol 12, No 2' 1987

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c) Representativeness of Snow Surveyuala

There remajns the problem of us jnq snow coursedata to represent areat srow corie, conditions.Terrain, Iand use, and vegetative cover are impor-tant factors effecttng snowcover djstribution and,ultrrnately, snow melt. Are our snow coursesrealy representative of the surroundinq area?

It has been ctearly demonsr,ated ih;t accurare oastn snow cover estimates of depth, densitvand water equivarenr can De obtarned from asnow course network or survey sampling schemespecifically designed to represent local land_scape characteflstics, i.e., vegetation and terrainvanations (Steppuhn and Dyck, 1974; Adams,1976; Goodison, igBt; Woo et a/,, i9B3), Thisconcept is fundamental in the accurate deter_mination of basin snow storage. Snow samplingTor onty one type of land use or terrain condjtionresults in a biased estimate useful, at best, as anindex of regional snow cover, Unless one knowsthe site characteristics of snow courses used rnan analysis, it is difficult to develop climatolooicalor synoptic maps of snow cover water equivilent(Goodison, 1976). By using known vegetativeano pnysrographic parameters, techniques suchas multiple regression, trend surface or proximitvanarysis can then be tested for the devetopmentof basin maps of snow distribution (Trivett andWater.nan, 19BO),

Table 4 illustrates the difficulty rn making effec-tive use of standard snow survey data, lt com-pares data from three snow courses at SiouxLookout located at three different sites, each witha different number of sampling points, operated

by three different agencies, with each agencypossibly using different equrpment. Needless tosay, the measured water equivalent varies con-sid-erably Which is "right" or "wrong?,'Each mayin fact be correct for the land cover and terraincharacteristics that it represents.

It is important to elimrnate or minimize theerrors of measurement and to standardize themethods not only to assist current users ofthese data, but also to provrde the most accur-ate "ground truth" measurements possible fordeveloping algorithms for the determination ofsnow cover ustng remote sensing, The accuracyot snow data determined from satellite remotesensing will be closely related to the accuracvof tr's "trar.a truth" oata used fo. calrbraticn,

Data Publication and ArchivinqAtmospheric Environment Servi6e publishesSnow Cover Dafa, which is an annual summarvof snow course observations made bv i 9 aoenlcies (Table 2), To date no national digiialarc"hiveof these data exists, although individual agen-cres may nave thetr own data archives for theirspecific use. The lack of an easily accessiblenatronal digital archive has often hindered spa-tial and temporal analyses of snow data forsnowmelt modelling or development of satellitesnow cover a gorithms.

AES is currently implementing a change to themethod and format of publication following thesuggestions of Findlay and Goodison (1978), whorecommended the creation of a computer-basedarchive from which data could be retrieved direct-ly for pubiication. This permanent data storaqe

TABLE 4: comparison of snow course water Equivarent Measurements (mm)Sioux Lookout 1 925-1979

Harch(first week)

AESr %

(rr) changetOntario Hydro %

(mm) changezidRB %

(rr) changez

r97 5I97 6r977197BL9)9

-t6Jr34 -26%'II7 -1 ?9

154 +32%108 -30%

r0284 _18%

99 +I7%106 + 7%

76 _28%

13097 -2s%

II2 +I5%LTZ UQA -1 tol

LLh

Note: Means of surveyChange in water

on March 1

equiva 1 entand 8

from previous year

Revue canadienne des ressources hydriques /Vo|.12, No,2. 1987 33

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facility could be readlly accesseo ani.r \'vairi'-l

grow in usefulness, particulari,v flt' sia,i:ti";:'ranalyses, over a nuriber o'l -veats. ii -u"ci:it'l ;ro-vide a standardized format for di:ia c:rileci?lrby a variety of agencies arid woulti ia.cliiiai: lslrof the data over broad geocr J 'r - -

Finally, the proposed for.rna.t wcuii al c\j!' ic-r:-i-l

inclusion of additionai physrcal inliiriaiirn,such as snow crusts, ice layers, DrrY icilrilenialcharacteristics, sampler t"vpes, etc., ';i'h ch iiicrecorded by many agencies, l"rut rci :ee l.liaflv

published. This type of infcrnrattorr rs lril.oif rlirg

even more important tn olr lr',resiiqatiors ll'eknow stratigraphy is an lmpo{ilri iii..lI3i iiavalanche studies, so it rs carefullv mcnlio eC

However, stratigraphic infcrmaiir:ltr is inpoilari-tor the study of snow cover prci:le'-iles Lrs f !lmicrowave techniques and is L;seiil n ihl siilCt"

of acidic snowmelt sholk no1+niial. -iLiiiticir'ally, such information has not bee. i'ei,iai il llv;lll-able, precluding the full use of hilr.otical d;la ioialgorithm or model oeveloPrn?ri.

Future of the Snow eourgs ffiif.ii.'tl-r"lnln view of recent trends, it is possii:le tirii in!number of snow courses operari.ti:1 ;n [,:alactawill decline in the future. $ihai has ciiuiiecl iirtapparent decline of the sncr sLri't/e!/ ijfoqi;r.iilwithin Environment Canada's Siiite t [l*girrrcelBranch? The reductions in tle i-r.ii:rkler C;t 3ticorr

courses surveyed by !i FB in recenl )/9i:-r-i's aiilthe combined result o{ lncreas-d ies.JL!ace cJi'-straints, a diminishing profile of the sirci/v sr.riVi:r-!

program relative to ihe nation4 h\/,:iicmi:i.1c

data collection prograni, a iack o{ cl€liii)i d::!ltilied users and benefits cllhe ciata, arri uricei.-

tainty as to whether the cc,llecicrr oi siro,nt

survey data is withln the WFB rnanda.l: \.rLiiiill Ithe WRB, snow survey d3.ta have i"i:.':j:illi-rai 'rbeen collected as a secorcja;y ir)"(ji*fretf cparameter, with the surveys heirg Iilocl'poi'a.le(liinto normal operationa.l plans. flcwevsi i-rc il:i'-

mal commitment has ever fleer r'lairi to 'lhal

program and it has always beerr a clisctet ';ili.ii'yitem in the budget. -lhe drafting ci the iei:leial'provincial Water Quantitv Sr,irvey,4i;te:.lrr.Lcr-tt:; lir

1 975 reinforced the hydrometric.lerta c:oll3'.iiroir

role of the Branch, but did not lncl!c$ 5i'O\,r/ i-rr'ri-

vey data collection. Later, a natrot*iie srrl'vey

and subsequent report whlch reviered iirilnational hydrometrlc data cci ectlon !.oLli3r-l(Environment Canada, 1980) drd i'ol: {irir-'tlYaddress the collection of snorv d;lt:r' ili lr-t ; ;ri)

noteworthy that the inq'liry cn FeCi:;l !l'ltri''ir

Policy did not acidress ihts pic;iln elii-rr;;

(Pearse et a/., 1985)The Atmospheric Envlionrnerrt Se iv ce cl::irs

i-ro :ri*i-iif cant reduction in its snow course net-',rr; k at ifris iime, although reduction of the num-i-rr,:r ci ilanned cbserving stations can result in a, r{ ,-i o , rr'luture snow course observations'i tc sro rq aourse network, along with other sup-'- ii, rr?" l,imaioiogical networks is of courseL-.t.iC.i r.icntin,ous review by AES Regions as

lire,!' gtive iLa operate the most effective net-,rcik oossibie for the resources available toti.eir.. Ar-S is implementing the new recom-r'r 3:ic- 5no'"'J samprcrs in its network and is

iiri aiirrg the nat onai digital archive of snow

cor.:ise data. lt will continue to provide guidance

cii sncv/ SrJn'ey procedures as requlred.-irr'rr ?r? J':'cienc'es in the present decen-

" ri. i?l 3'y'ster oi snow data collection in

i..: ' .:dl Currently, agencres are independently

c5lerat ng sno\^/ courses across Canada. This

fragme nte<1 approach has led to some disparityi;r r.+tho*s ard procedures which, in turn, canvi+ll ei:ta cf or-iestionable comparability As

. . , , :,n.!iandard analytical pi'ocedures and

r', rlq9, .;cci io rela',e snow data to runoff

i;.:ltenti:rl, give rrrconsistent results lt in fact

i)ou c ce ;rrgLred that the lack of a more com-

l: :. . ^..: .'. n?rwcrk providing accurate esti-iiiiite s cf snovi prope(ies has inhibited progress

ii. basri: sncur related research, and in addition'f indered tire development of improved meas-

- cj^ ;( ". o ,,1 analysis techniques' and in the

|iir,-re ilxtensive scientifrc application of this

iiata rage.

.,.iii'i;crne Gamrrma Ray Snow Surveysr-)ne a ierna te sncw survey procedure is the air-

i:rlinl. gamma ray method. The airborne snow

sL:irrey i'neihcd is r:ased on the attenuation by ag;ri:wpack of garrrma radiation emitted byiraiurai rarlicactive ijecay in the ground. This

, crr, rt": nas ueen used in selected regions of

iana.cia crr an experimental basis since 1972.|n'ili) last thr"ee years, gamrna ray snow surveyslavo been performed over southern Sas-

l(a.tche\,van, the north shore of Lake Superior,

.ind the S;.r rLt ,lohn River Basin. These surveys

'" o ieJ 'i,, nq r1''g a rplanes, operated by the

fieclcgical llurve5r cf Canada (GSC) and the

Lr !;. i\iational \Aleaiher Service (NWS)' each with

ciiiereni l;rpes of spectrometers.

Ssxctl Atrbrtrne Ganma RaY,!r..iri'v Su,'ueYs in CanadaIn i'ei-rilar-v i982, a nraior snow survey experl-Tnsrri \,viis cclducted over southern Sas-

?, . D:'1aii; cf ll-re experrment are given

. , ,: -,-'r sJ'l el ai ( 1934). One of rts oblectiveswas io Drovtde a direct comparison of airbcrne

34 Lj:iir;rcjrair \i/akl,r llesources Journal /Yol. 12, No, 2, 1987

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gamma radration snow water egLji\.ral.e!-lI il-1ea:,.ured by the GSC system and the llWS syst;mwith each other and with grornd rlbsenratjor:r.Intensive ground snow surveys cn seieci!..!calibration lines were specifically desiqnr:ci ir.rbe representative of the areal land ijsi) sc ihalthe best estimate of ground snor,rr ccv,:r ccllclbe obtained using standard snow srjivevs,

A comparison of the two gamma ray svsi€ii:jwith each other and with ground oa ta *, , , , , _

cribed in Carroll et a/ (1983). The rv,'c sveteir[iagreed with each other w,th an frill.;; e.r-;" r.i4.5 mm, The GSC system agreed r,vith ail groi_r,;tdata to an RMS error of 4.6 mrn i4.0 ri-lir.1 cn ii-reprimary calibration line) and the NWS sVSte r-agreed with the ground cjata with an iiiris eri.r--iof 7.5 mm (6.0 mm on the primai.v c:rlitr;:icirline). These results were over lat .arr,li. r, r, ,;snow water equivalent (SWE) ranging fn:i.i. i0 il80 mm and they probably indicate rhe cltse_ripossible agreement of the gamma rav t.:cirI-que with ground based measurerne r..;

A problem encountered on the frrsi cay ci iii5:Survey was the extremely high levei ci r11i11;;-pheric radon gas. The calittratioil orccei-litrcmust filter out the effect of racJor b*ir,rie iresnow water equivalent can be Calcuiari_.ci.

-; ireGSC and NWS system correct 10r r.ajil,:,r.1 ii'r i.tir,ferent ways. The GSC flies the airciafi ,lvei irlake to measure the background aii.nlsi:heiicrradiatron and these results are sublr rc ui . a .- ,

the terrestrial flight line data to obtain rfr l:tgamma radiation from the ground, I his meiirci.lposes a problem in the prairies because fti;rcare very few lakes and radon concjitions rear alake may not be representative of ccndiitcnijnear the flight lines. The NWS systell pi:rce I aSmaller detection package above the i.i.iari..package so that the main detecticn nacl<acr:willshield the small one from ter.esl:ial ra.'l,oirl,rThe small package will then orly nireasurr:atmospheric radiation. A problern r,'vriir ri.r;tmethod is that the heavy radon gas cfierr i *sbelow the aircraft and it is therelore inr.'rsibio ir:the upward looking detector, Despite ihes* dirlerenceS, the snow water equir",aleni rneasr_tii:r-lby the two systems agreed cioseiy

In 1982 and 1983 GSC and Nl!4iS arrlroriresnow surveys were conductecj ovei' tlle r__aii,-:

Superior Basin and providecl vallabie exi:,rri.ence in flying over hilly, forest-cove.eC Iefiarnwith highly variable radicmetric qround oo.crir-trations. This type of envi;orine,ri o -,., .:many more sources oJ error thari the $ranes.most notable being the variab:ility in ine soiimoisture. Soil moisture absorbs p:ir , i t.naturat gamma ray signal in the grluric, fr:r.crrq

a.)rreatioi't iii ihe ai[borne data. The usualfirfilir0d .ii a:oifectioil is to take 20 to 40 soils;:,rili*s aitr..g several so-called "cailbration',lir'r:-.s, i.ie t*fin rre the rnean gravimetric moisturecai)t+i'ti, a[c ihei'] extrapolate these data to thelli.,.:r iiiglt liires. In r'egions where terrain plays an ralrr facior ir-r scil moisture variability, there are(:1ir't)r"s I'r lnii methcd. Anothef factor influencing'iils ;*si.rlt$ is liight line replication. The analysisol iire galrila ray ciata relies on a pre-snow sur-vii, io 'Jsrisit ici'background terrestrial radia-irti,. :ir ir'::;t wooded areas, the pilots must felv'r' . r 'c -, r,.tv Qi:tcnal ards, such as transmisln.ir irne., pip,3iine rights-of-way, winding roadsa:lrj 4lcca$toi^iaiiy, rivers and streams, This prob-iirr'1i r-i fiaqniiieci in the Lake Superior region.r'irl;i-e clr'aritic Outcrops cause high spatial';ltiaurtilii, ln the radioelernent conCentratiOns. Inadctrlicri lh;: radicnretric signal reaching the air-.iiiii 'iiie;ticmeter is weakened by the high3,',rI in ii:i.: ai'ea (up to 250 mm).

il :p,:e ri these problerns, the GSC systemiii':fr ila lri\,Y5 system agreed with the groundc:iie ,.iviiir a il rnm RMS error, and statistical4',1;,1; .,'li-rlltg irori tlre ground sampling pro-caa'j.ii:; ac;:LlLilrted for about half of this. The twoijlseirl ae f eed witr-r each other wtth a 4.5 mmfiir:ri oiror (Cai:thier el a/., 1983).

i:r|i ali',iariie !jamrna ray SUrvey was pef-'i.-,, ri:ij ir ir,':ai;h 1984 in the Saant John River:)ai-:tir c{.1\,i:i'iitE ite flight lines shown in Fig. 2.i.'it.-.isr\.'it EftLrnci snow and soil moisture sur,,.'ii'! ,r,ei.j aerited out along eight of these lines.A :;ofipe 't$o|l oi the GSC and ground measure-iTrcl.'s r'e\,-"'-.C an overall RMS error of 62 mm.-iiri.' iriql oiscrepancy was due to large errorsii (,-,rrq iri'ee lines, each having more thant.l,li) rril 51II wiih one ha'ring 460 mm SWE.-diirarr iiese tines were excluded from thei;ai,::t.ti::.ticirs tie lllv,lS error dropped to 20 mm.i-::,: l3;g; *rror ir deep snow pack areasaltc,ris tc be ihe result of systematic underes-tri..a;iroi' a--i Ine !i"cund based measurements bv

'i. Slre g.cssibte reasons for thiiruict)'rjstiifialion are outlined by Glynn e1 a/.i l:iii5).

:,:|tri/€vs pe ;i';r-r|ed in these three areas havernil aai.j4 ihai iha airborne gamma ray techni-aii-ra: ii\riis fei:eetariie and accurate estimatescl tic!,r i/'iaiei equivalent under a variety ofi._,.ffilii-r tvpss anc snow conditions. More worki'rirJsi i:r9 ,seficrmed in regions where the snowl...,al*i cturvaiert exceeds 300 mm. lt would bei.rr:i:rfiri io lest ihe accuracy of the method in ai-rrr-)|ritianou-c area in western Canada. althouohthi: wruia i,e expensive since a helicopier\Yiiiilfl be i-equirecl.

Revue canadienne des ressources hvirigLl{}s /,.lol. tp, \ro. 2, 1gg7 35

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Canadian Water Resources Journal /Yol. 12, No 2' 198736

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Feasibr,lity of a Canadian Gamma RaySnow Survey ProgramThe Natronal Hydrology Research Institute(NHRI) of Environment Canada conducted afeasibility study to determine the costs and userrnterest in an operational airborne gamma rayprogram in Canada (Glynn et a/,, 1985), Thisstudy outlined previous work on airborne snowsurveys in Canada and other countries and, inaddition, reported the results of a questionnaire,The questionnaire was circulated by NHRI toover 300 users and collectors of SWE data inCanada, Preliminary replies indicate wrde-spread user interest in the gamma ray techni-que. Of approximately IOO responses, over 30organrzattons indicated interest in providinofinancial support for surveys in their regions.

Several questions remain to be answeredregarding the future of the gamma ray method inCanada, The technique has been shown to grveaccurate results in different types of terrain andsnow conditions commonly found in easternCanada and r.r the Canadran prairres. Tnetechnique has moved from the research staqeto that of technology transfe.. at least for reqio.tswith a snow water equivalent less rhan 3OO mm.Snow surveys are usually used as indices inrunoff models and these models often requirelengihy records before the survey data can beused operationally. There is, therefore, the needto lustify a new program which might notDecome truly operational for several years.

Another malor question is the source of fund-ing for such a program, Cost recovery fromindividual users requires tbat an accountingprocedure would have to be devised to recovercosts on a proportional basis from small andlarge users of the data. In addition, a prioritvscheme would be needed, since it rs l:kely thatseveral users might want surveys performed atthe same time. Finally, there is the question ofeconomic benefits arisrng from improved esti-mation of snow water equivalent. Do improvedestimates lead to improved flood forecastest mates? lf so, is it possible to quantify theeconomic benefits of these improved estimates?At this time, quantitative studies have not beenperformed to answer these questions.

Satellite Remote Sensingof Snow CoverSatellite remote sensing of snow cover is notnew-it was one of the first applications ofsatellite data in the water sector. We should nowbe at the stage where it is possible to develoo,assess and Integrate new techniques for snowcover assessment, inciuding the acqursition of

point and areal snow measurements by remotesensors. Snow cover mapping in Canada wasciemcnstrated during the WMO Snow Studiesby Satellite Prolect, initiated in 1974. Analyseswere carried out on the Columbia. Souris. Lake-of-the-Woods and Saint John River Basins,using NOAA and Landsat imagery, Satellitesnowcover mapping has been continued in theSaint John Basin. A digital processing systemusing NOAA/TIROS multi-channel data wasdeveloped to dete.mine the areal extent ofsnowcover in this forested basin (Waterman eta/., 19BO) and an analogue/digital procedureusing NOAA or GOES data was recently report-ed (Johnstone and lshida, 1984). Both techni-ques only provide areal extent of snow cover, Inan effort to determine basin water equivalent,Power e1 a/. (1980) tested the use o'Landsatdigital data to delineate various vegetationcategories in a basin and then used concurrentsnow course data obtained withrn the givenvegetation category to distribute the snowwater equrvalent over areas within the basincontajnrng that category of vegetation. This isone possible method for combining satelliteand ground data for the determination of snowwater eourvalent.

In Canada it is difficult to use Landsat data foroperational snow cover mapping because the16 or 1B day period between successiveimages (or even half that if two satellrtes areoperatng) rs generally inadequate. The pre[-ability of cloud free coverage every 16 days islow and during that time interval the snowpackcord disappear entirely (Peteherych etal., '1 983).For 'arge basins. such as the Saint John, theincreased spatial resolution of Landsat meansthat passes on 4 or 5 successive days arereqtired fo. coverage o'the entire basin. Cloudcover is a problem in snowcover mapping bothfor obtaining coverage of the basin and in dis-tinguishing between cloud and snow. Dailycoverage of target areas by the weather satell-ites is more suitable for obtaining usable andtimely data.

Currently, only areal extent of snow cover isoperationally derived from satelltte data, andthere is no centralized national system for map-ping every basin tnat a user agency might.equire. Fo. each user to implernent his ownupstysis system woLld require the receipt ofsateilite data In near real-time and the develop-ment o' an objective interpretation systemwhich is affordable and transferable to "non-specialists". The River Forecast Centre ofAlberta Environment is co-operating with theAlbena Remote Sensing Centre to develop

Revue canadienne des ressources hydriques /yol.12, No.2, 1987 37

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such a system. Work is currently in progress formonitoring snowpack depletion in the moun-tains of Alberta and applying snow cover areastatistics to the SSAFR model (Ferner andSutherland, 1986).

A major challenge in the remote sensing ofsnowcover is the development of algorithmswhich determine snow depth, water equivalent'areal extent and liquid water content using sen-sors having all-weather capabilities. The mostimmediate promise in this area is the applicationof passive and active microwave data lo snow-cover problems. Research at the University ofKansas has been extremely important in ad-vancing our knowledge of active and passivemicrowave responses to different snowpackconditions (Stiles and Ulaby, 1980; Ulaby andStiles. 1980),

Goodison et a/. (1980) reported Initial results

on the use of airborne synthetic aperture radarimagery (X and L band)for snow cover monitor-ing, but at the moment, passlve microwave dataoffer the greatest prospect for the determina-tion of snow cover. Investigations (Goodison eta/., 1986; Kunzi el al., 1982; Chang ef al ' 1982'Fostereta/,, 1980; Rango etal,, 1979)using datalrom the Scanning Multichannel MicrowaveRadiometer (SMMR) on NIMBUS-7 and fromESMR on NIMBUS 5 and 6 have shown thatthere is a potential for using passive mlcrowavesensors to monitor snow cover, notably areal

extenl, depth, water equivalent and melt.

One objective of the malof snow surveyexperiment conducted in Saskatchewan in

1982 was to assess the utility of passive mic-rowave data for the mapping of prairie snowcover (Goodison et a/,, 1984). Research has

focussed on the derivation of algorithms toestimate snow water equivalenl using micro-wave radiometer data, Airborne microwavemeasurements (18 and 37 GHz, horizontallyand vertically polarized) were made with NASA's

multifrequency microwave radiometer alongthe same flight lines traversed by the airbornegamma aircraft. Airborne gamma rYleasure-

ments of SWE were used as one of the "ground

true" data sets against which the microwavedata were calibrated. The gamma and airbornemicrowave data were averaged over 20-25 km

segments, this resoluiion being similar to the 30

x 30 km resolution of the 37 GHz NIMBUS-7SMMR satellite data collected on the samedays.

Goodison ef ai, (1986) discuss the develop-ment of initial empirical airborne algorithms forderiving snow water equivalent estimates fromoassive microwave measurements. These

algorithrns have been tested on SMMFi aata to

deternrine the areal distrrbution of snow water

equivalent over southern prairie regions Figute

3 sho\/vs ihe derived estimate of SWE on Feb-

ruary 17, 1982 for southern Saskatchewan'Reqular snow course measurements of SWE

made independently of this investigation and

not usecl In any algorithm development are plot-

ted on the map for comparison Depending on

local terrain and land use. these measurementscan vary gre;atly over short distances; ihe sat-

ellite deriveci estimates are instead "smoothed"

over the 30 x 30 km area, and are oaseo on

37 GHz vertically polarized brightness iem-

Deratures.The SWE estimates in eastern Saskatchew-

an, soutlr of the tree line, are good comparecl to

the rndependent snow course measuremenlsand the gamma surveys; SWE estimates tn

vr'estern Saskatchewan are high. SWE esti-

mates north of the tree line have not been

validatecl, since there were no airborne flights

there. The region south-west of Regina, whcre

there are no contours of SWE, exhibited bright-

ness temperatures 2 241K, and correspondedto regions of wet or melting snow The abrupt

change rn 37 GHz brightness temperature

allowi one to distinguish beiween wet and dry

snow areas, but wet snow precludes deter-

rnination of snow depth or water equivalent'It should be noted that information on snow-

pack structure (stratig'6p6y, ice layers' grain

size, wetness, etc.) is very important in the inter-

preiation of lhe microwave data, but such infor-

mation generally is not readily available ln the

future, cbnsideration should be g'ven to record-ing sucfi in{ormation at selected snow coursesites.

There are many questions yet to be 3n5''vsred

in the use of passive microwave data for the

derivation of snowpack properties, but recentprogress has been positive and research should

continue to develop this technique Since pass-ive microwave resolutron from space is prse-

ently about 30 km, the technique is cilrrerrtly

applicable over large, relatively homogeneousregions, such as the Prairies. Use of these oatafor snow cover determination in mountaln or neav-

ilv rot"tt"O regions has yet to be de"nonst'atedTheoretical studies and field experiments involv-

ing scientists from different discrplines will be

necessary to advance the applicatron of this

technique. Co-operation among agencies will be

vital just as it was during the airborne gamrna

experiments. Currently, satellite microwave raolo-

meter data are available from NIMBUS-7, whtch

is a research satellite, but are not available in real-

38 Canadian Water Besources Journal /Yol. 12, No 2' 1987

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FIGURE 3: snow water Equivarent over southern_ggskatchewan, February 17, 1gg2derived from NTMBUS-7 SMMR Data (37 GHz Verticariv-p;raiizeot.Standard snow course point measurements of SWE collected independent ofthis study are shown for comparison. The right ttatchinto"-pi"t" the airbornegamma survey.network;_the heavy hatched line denotel the natural tree-line(map produced by phD Associatei under contract to enviionment canada).

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Revue canadienne des ressources hydriques /Vol.12, No. 2, 1987 39

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time. An operational satellite mlcrowave racllo-

meter (SSM/l) is planned for iaunch rn 1987 on a

U.S. Defence l"4eteorological satellite Plans to

obta n these data in near real-time for opera-tional demonsiration of snow cover and sea-iceapplications are being reviewed by Environ-

rnent Canada.

OutlookThis paper prcvides an overview of currenttrends in snow s';rveying in Canada. Our ground-

based technir;ues are belng standardized and

errors are being quantified But for vartous

reasons, the number of conventional snowcoui'ses wili probably decrease Airborne gamma

ray snow surveys offer a v able alternative formany regions of Canada. However, implemen-tation of an operational system in Canada is yet

to be achieved. In the future, sateilite data'noiably pass ve i'nicrowave, may provide the

basis for large scaie assessment of snow-cover propertles.

Yet, where are v.re tcday? AES, whlch now

operates the cnly nation-wide snow surveynetwork, publrshes the data collected byagenctes and provides dtrection on snow sur-vey eqeiipment and procedures N/any feelthatthls is not enough. A panel discussion at the.1 985 Eastern Snow Conference highlighted a

number cf problems and disadvantages of thecuirent arrangenrent (Eastern Snow Con-ference, 1985). lt may be that a more com-prehensive and co-ordtnated national progrann

is needed if we are to derive maximum benef its

from the measurement and analysis ot snowparameiers. Such a program snoulo ensurethe siandardizaiion of data coilection, analysisand d ssemination procedures, while at thesame time ensuring the introduction of moderntechniques, Such a program should be res-ponsive io the needs of the water resourcescommunity and other users lt should promote

the development of the necessary expenlse Ioapply knowledge, gained from basic research,to the analys s and interpretation of snow dataand thereby provide the information neededby water resources managers. The identlfica-tion ot all potential users ancj benefits of snowdata and arrangements for cost sharing anci/or cost recovery are considered essential tothe successful lmplementation of such a

program.

Acknowledgements1he authors wish to thank colleagues within

Atmospheric Etrvlronment Service and Inland

Waters/Lands who have provided comments

on this paper. Thanks are especially due to sup-

port staff and others who actively contributeci to

experiments noted in the paper' Finally, the con-

tinuing support of Environment Canada mana-

gers in conducting this work is acknowledgeo

ReferencesAdams, W.P. 1976 "Areal Differentiation ot

Snow Cover in East Central Ontario" Waler

Resour. Fes.,12. PP 1226-1234

Atmospheric EnvironmentService l9T3 Snow

Surveying: Manual ol Standards and Snow Sur-

veying Procedures. 2nd ed Downsview, Ontario

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Cover Data, Winter 1982-83 Minister of Supply

and Services Canada, Ottawa,

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Carroll, T.R., J,E. Glynn and B E Goodison l983"A Comparison of U.S and Canadian Gamma

Radiation Snow Water Equivalent Measure-

ments," Proc. Western Snow Conf .,51st Annual

Meeting, Vancouver, Washington, April 19-21

pp 27-37.

Chang, A.T.C,, J.L. Foster, M Owe, D Hall and A'

nango. lOeS. "Passive and Active Microwave

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R.P. Richards. lgB2 "Metrication of Manual

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Ferner S, and L sutherland. 1986. The Use ofNOAA Sateilite lmagery for River Forecasting inAl be rta. Progress Report. Internal Report AlbertaEnvironment, 30 p.

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,,snowpackMonitoring in North America and Eurasia UslngPassive Microwave Satellite Data]' Remot6Sensrng of Envrronment, Vol. 10. pp. 285-298.

Gauthier, R.1., T,R. Carroll and J.E. Glynn. 19E3."Airborne Gamma Radiation Data Used toAssess Snow Water Equivalent Over the LakeSuperior Basin." Proc. Seventeenth lnti. Symp.on Remote Sensing of Envr. EnvironmentalResearch lnstitute of Michigan, Ann Arbor, Ml.(t):415-424.

Glynn, J.E. and R.L. Grasty, 1980. ,,A Calibration

Procedure for Airborne Gamma Ray Snow Sur-veys." Proc. Western Snow Conf . April 15-17.Laramie, WY pp, pA-127.

Glynn, J.E., J. Haas, R.L. Grasty and p.B. Holman,1985. A Feasibility Study for an Operational Airpgrne Snow Survey program. lnternal Report.National Hydrology Research lnstitute, InlandWaters Directorate, Ottawa, Ontario,

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