Glacier Meltwater Contributions and Glaciometeorological...

Glacier Meltwater Contributions and GlaciometeorologicalRegime of the Illecillewaet River Basin, British Columbia,

Canada

J.M.R. Hirose* and S.J. Marshall

Department of Geography, University of Calgary, Calgary, Alberta, Canada

[Original manuscript received 3 March 2012; accepted 22 February 2013]

ABSTRACT This study characterizes the meteorological parameters influencing glacier runoff and quantifiesrecent glacier contributions to streamflow in the Illecillewaet River basin, British Columbia. The Illecillewaet isa glacierized catchment that feeds the Columbia River, with terrain, glacial cover, and topographic relief thatare typical of Columbia River headwaters basins in southwestern Canada. Meteorological and mass balancedata collected on Illecillewaet Glacier are used to develop and constrain a distributed model for glacier melt,based on temperature and absorbed solar radiation. The melt model is applied to all of the glaciers in theIllecillewaet River basin for the summers of 2009 to 2011. Modelled glacier runoff for the three years has anaverage value of 112 ± 12 × 106 m3, approximately 10% of Illecillewaet River yields for 2009 to 2011. Glacierscontributed 25% to August flows for the three years. On average, 66% of modelled glacial discharge is derivedfrom the seasonal snowpack, with the remaining 34% resulting from the melting of glacier ice and firn. For thelowest flow year in the basin, 2009, snow and ice melt from glaciers in the basin contributed 14% and 33%,respectively; 81% of the August glacier runoff is derived from glacier storage (ice and firn). Climate sensitivitystudies for Illecillewaet Glacier indicate that the glacier mass balance is strongly influenced by summertemperature, with a net balance change of −0.6 metres of water equivalent (m w.e.) under a 1°C warming. A30% increase in winter precipitation is needed to offset this. Our values are initial estimates, and long-termmonitoring is essential to characterize glacier and climate variability in the region better, to refine estimates ofglacier runoff, and to quantify the sensitivity of runoff to glacier retreat.

RÉSUMÉ [Traduit par la rédaction] La présente étude caractérise les paramètres météorologiques quiinfluencent le ruissellement des glaciers et quantifie les contributions récentes des glaciers à l’écoulementfluvial dans le bassin de la rivière Illecillewaet, en Colombie-Britannique. L’Illecillewaet est un bassinhydrographique englacé qui alimente le fleuve Columbia, avec un terrain, une couverture de glace et des élémentstopographiques caractéristiques des bassins du cours supérieur du fleuve Columbia dans le sud-ouest du Canada.Nous utilisons les données météorologiques et de bilan massique recueillies sur le glacier Illecillewaet pour mettreau point et contraindre un modèle distribué de fonte des glaciers, basé sur la température et le rayonnement solaireabsorbé. Le modèle de fonte est appliqué à tous les glaciers situés dans le bassin de la rivière Illecillewaet pour lesétés de 2009 à 2011. Le ruissellement modélisé des glaciers pour les trois années a une valeur moyenne de 112 ±12 × 106 m3, approximativement 10% de l’écoulement de la rivière Illecillewaet pour 2009 à 2011. Les glaciers ontcontribué pour 25% de l’écoulement en août les trois années. En moyenne, 66% du ruissellement modélisé desglaciers provient de l’accumulation saisonnière de neige, les 34% restant provenant de la fonte de glace deglacier et de névé. Pour l’année du plus faible écoulement fluvial dans le bassin, 2009, la fonte de neige et deglace de glacier dans le bassin a contribué pour 14% et 33%, respectivement; 81% du ruissellement des glaciersen août est dérivé du stockage des glaciers (glace et névé). Des études de sensibilité climatique pour le glacierIllecillewaet indiquent que le bilan massique du glacier est fortement influencé par la température en été, avecune variation nette de −0,6 mètre d’équivalent en eau dans le bilan pour un réchauffement de 1°C. Unaccroissement de 30% dans les précipitations hivernales est nécessaire pour annuler cet effet. Nos valeurs sontdes estimations préliminaires, et une surveillance à long terme est essentielle pour mieux caractériser la variabilitédes glaciers et du climat dans cette région, pour raffiner les estimations de ruissellement des glaciers et pourquantifier la sensibilité du ruissellement au retrait des glaciers.

KEYWORDS glacier; mass balance; glacier melt; glacier runoff; headwaters; Illecillewaet; Columbia River basin

*Corresponding author’s email: [email protected]

ATMOSPHERE-OCEAN iFirst article, 2013, 1–20 http://dx.doi.org/10.1080/07055900.2013.791614Canadian Meteorological and Oceanographic Society

Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

1 IntroductionThe Columbia River basin (CRB) is the sixth largest river basinin North America, with a total basin area of 671,300 km2.About 15% of the basin lies within Canada, including numer-ous high-elevation catchments. Approximately 1760 km2

(1.7%) of the Canadian CRB (CCRB) is glacierized, and itsupper headwaters receive high annual precipitation (e.g.,Cohen, Miller, Hamlet, & Avis, 2000; Hamlet, Mote, Clark,& Lettenmaier, 2005; Kite, 1997), with much of this accumu-lating in the mountain snowpack. An estimated 30–40% ofannual discharge in the Columbia River, as measured atThe Dalles, Oregon, is derived from the Canadian portion ofthe basin (Cohen et al., 2000; FCRPS, 2001; Hamlet &Lettenmaier, 1999). Glacier contributions to annual dischargeare unknown in the CRB.Glaciers are natural freshwater reservoirs on seasonal to

centennial time scales. The retreat and thinning of glaciersaffects both water availability and water temperature in gla-cierized catchments (Moore, 2006). Much of the long-termstorage (glacier ice) gets depleted in late summer and earlyfall (Fountain & Tangborn, 1985), and ice-melt runoff helpsto maintain streamflows after the seasonal snow has melted(e.g., Déry et al., 2009; Huss, Farinotti, Bauder, & Funk,2008; Moore & Demuth, 2001). Glacier melt also has acooling effect on streams because of the colder meltwaterand higher flows; this reduces the sensitivity to energyinputs and maintains habitat for cold-water species in down-stream rivers (Moore, 2006). There has been limited glaciolo-gical research in the CCRB, but modelling efforts in the Micasub-basin indicate that meltwater from glacier ice contributesup to 25–35% of streamflow in August and September (Jost,Moore, Menounos, & Wheate, 2012). This represents a vitalfreshwater resource to the Columbia River system, supportingmunicipalities, industry, hydroelectricity generation, irriga-tion, and ecosystems.Glacier contributions to streamflow have been assessed in

the southern Coast Mountains (e.g., Moore, 1993; Moore &Demuth, 2001) and on the eastern slopes of the CanadianRocky Mountains (Comeau, Pietroniro, & Demuth, 2009;Demuth et al., 2008; Hopkinson & Young, 1998; Marshallet al., 2011). Hopkinson and Young (1998) conclude thatice-melt from glaciers contributed 1.8% of the averageannual discharge in the Bow River in Banff from 1951 to1993, but as much as 15% of annual runoff and 50% ofAugust flow in 1970, an extremely negative mass balanceyear. Comeau et al. (2009) apply a hydrological model tothe glacierized headwater basins of the South and North Sas-katchewan River systems and find that more than 60% ofJuly to September streamflow is composed of glacial runoffin headwater catchments with over 10% glacier cover, butthis study does not distinguish between meltwater runoffderived from seasonal snow and glacier ice. This is difficultto separate in hydrographs (or isotopically), because glacierrunoff contains a mixture of these two sources, derived simul-taneously from a range of elevations on a glacier. However, itis possible to separate the contributions using field

observations and glacier mass balance models. Separation isimportant because runoff from the seasonal snowpack isintrinsically renewable and can be expected to persist, albeitreduced, as glaciers recede from the landscape. Meltwaterfrom glacier ice and firn, on the other hand, taps into a reser-voir that is diminishing with time. In this paper we defineglacier runoff to include all the meltwater that issues from gla-ciers, including snow, firn, and ice, but we report the runofffrom seasonal snow and that drawn from stored firn and iceseparately.

It is unclear whether glacier contributions to streamflowmeasured or modelled in other parts of western Canada arerepresentative of the CCRB. The eastern slopes of theRocky Mountains are in a more continental climate than arethe Columbia Mountains, with relatively sparse glaciercover. Rango, Martinec, and Roberts (2008) examine glaciercontributions to runoff in the Illecillewaet River basin, butwith limited observational constraints and with a simplifiedtreatment of glacier mass balance and melt processes. Jostet al. (2012) and Bürger, Schulla, and Werner (2011) applyhydrological models to nearby basins of the CCRB andprovide preliminary assessments of the importance andimpact of glacier runoff, but these models treat the glacierssimply and also lack direct observations to constrain massbalance gradients and high-elevation meteorologicalconditions in the region.

Here we present observational and modelling results ofglacier meteorological conditions, mass balance, and runoffin the relatively undisturbed Illecillewaet River sub-basin(IRB), a high-elevation headwater catchment of the CCRB.Our study has several objectives: i) to report direct massbalance and meteorological observations from field studiesat Illecillewaet Glacier; ii) to constrain mass balance gradientsand high-elevation meteorological conditions needed for gla-ciological and hydrological models; iii) to develop and vali-date a distributed melt model for Illecillewaet Glacier massbalance and meltwater runoff; iv) to explore the uncertaintiesand climate sensitivities of the model; and v) to estimate andpartition meltwater runoff contributions to IllecillewaetRiver from glacier snow and ice. This preliminary study pro-vides a snapshot of recent glacier-melt contributions in a head-waters catchment of the CCRB.

2 Study area

The climate regime of the CCRB is transitional between that ofthe maritime environment of the Coast Mountains and thecool, dry conditions of the eastern slopes of the CanadianRocky Mountains, two extensively glacierized regions inwestern Canada where mass balance records began in themid-1960s (e.g., Demuth et al., 2008; Moore & Demuth,2001; Moore et al., 2009). Glaciological information in theCCRB is too scarce to know whether mass balance in theupper catchments of the CCRB is correlated with eitherregion. Mass balance records from Peyto Glacier in theRocky Mountains have been taken as a proxy in CCRB

2 / J. M. R. Hirose and S. J. Marshall

ATMOSPHERE-OCEAN iFirst article, 2013, 1–20 http://dx.doi.org/10.1080/07055900.2013.791614La Société canadienne de météorologie et d’océanographie

Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

studies (e.g., Bürger et al., 2011). However, glaciers in theCCRB may be more sensitive to interannual precipitationvariability and North Pacific weather patterns than glacierson the eastern slopes of the Rocky Mountains (e.g., Bitz &Battisti, 1999).The IRB, in the CCRB, extends from Rogers Pass to Revel-

stoke and is located in the Columbia Mountains where thesnow climate is considered to be “transitional with a strongmaritime influence” (Hägeli & McClung, 2003). The IRBcovers 1150 km2 with an elevation range of 443 to 3284 m.Precipitation totals and orographic precipitation gradients arehigh. For the 30-year climate normal from 1971 to 2000,mean annual precipitation in Revelstoke (450 m) averaged618 mm, compared with 1547 mm at Rogers Pass (1340 m),with 933 mm falling as snow at Rogers Pass (EnvironmentCanada, 2012b). There are no long-term precipitationmeasurements on the glaciers of the IRB, but snowfall andprecipitation totals can be expected to exceed those atRogers Pass.The IRB is a headwaters catchment of the Columbia River

and is undisturbed by regulated flows. Other anthropogenicdisturbances are also minimal, because most of the basin lieswithin the boundaries of Mt. Revelstoke and Glacier NationalParks. This makes it an excellent study basin to compare glacierrunoff with seasonal flows at Illecillewaet River’s HydrometricStation in Greeley, 08ND013 (51°0′49′′N, 118°4′57′′W; Fig. 1).Glacier meltwater runs off into Illecillewaet River from 79 gla-ciers in the IRB (Table 1). Hydrometric data from IllecillewaetRiver have been gauged since 1963 and are available fromHYDAT, the database of the Water Survey of Canada. Illecille-waet River joins the Columbia River near Revelstoke, justdownstream of Greeley.

a Glacier Area and HypsometryThrough the Western Canadian Cryospheric Network(WC2N), Bolch, Menounos, and Wheate (2010) completedan inventory of glaciers in British Columbia and Alberta.This work provides the areal extents for the glaciers used inthis study, based on Landsat Thematic Mapper (TM5)imagery from 2004 to 2006. Glaciers are sub-divided intowatersheds based on a 25 m Digital Elevation Model(DEM). Total glacierized area in the Illecillewaet Riverbasin in 2005 was 56.0 km2, or 4.9% of the IRB. Glaciers inthe basin range from 0.05 to 5.94 km2. Most of the glaciersin the basin are less than 1 km2 and most of the glacier areais associated with the size class 1–2.99 km2 (Table 1). Illecil-lewaet Glacier is the largest ice mass in the basin, covering5.94 km2 and representing 11% of the total glacierized area.The glacier is the largest outlet of the Illecillewaet Icefield,draining northward into the IRB; other outlets of the icefielddrain into different hydrological catchments to the south andsouthwest. Illecillewaet Glacier is the one of the most accessi-ble glaciers in the basin and was used to collect mass balanceand meteorological data (see Section 3).

Glacier hypsometry in a basin provides baseline data forregional estimates of glacier mass balance and meteorologi-cal sensitivity (Marshall et al., 2011). A 20 m DEM wasobtained from Parks Canada to assess glacier hypsometryin the IRB. The DEM was derived from aerial photographs,acquired in approximately 1997 from Terrain ResourcesInformation Management (TRIM). The elevation range ofthe Illecillewaet Glacier is 1993 to 2911 m, while theelevation of the IRB glaciers ranges from 1592 to 2942 m(Fig. 2 and Table 2). The elevations of Illecillewaet Glacierare reasonably representative of IRB glaciers because thereis limited glacierized area below 2000 m, the lowestreaches of Illecillewaet Glacier (Fig. 2). The median glacierelevation for the IRB is 2385 m, 136 m below that ofIllecillewaet Glacier.

Given its close proximity to Rogers Pass, the CanadianPacific Railway line, and the TransCanada Highway passingthrough the area, Illecillewaet Glacier has been extensivelyphotographed and visited. It was the site of several early twen-tieth century investigations of glacier motion and glacierretreat, and historical changes in Illecillewaet Glacier terminusposition and area have been documented (Champoux &Ommanney, 1986; Sidjak & Wheate, 1999). Loukas, Vasi-liades, & Dalezios (2002) project future glacier-area evolutionin the IRB under different climate regimes, estimating aglacier cover of 51 km2 by 2080–2100, 5 km2 smaller thanits current area.

Glaciological projections and hydrological modelling in thebasin do not benefit from regional glaciological data, however.No mass balance measurements have been reported from Ille-cillewaet Glacier. The federal government carried out massbalance studies on nearby Woolsey Glacier from 1966 to1975, but these measurements were abandoned. Hence, thereis little knowledge of glacier mass balance, high-elevationsnowpack, and meteorological gradients in the IRB, or inother headwaters catchments of the CCRB.

3 Methodsa Mass Balance MeasurementsTo address the lack of essential glaciological data in theCCRB, we initiated mass balance studies on IllecillewaetGlacier in 2009. Mass balance measurements have sub-sequently been taken over by Parks Canada, in conjunctionwith the National Glaciology Program at Natural ResourcesCanada, with winter balance data available from 2009 to2012 and summer balance data from 2009 to 2011. Fromlate April until mid-September 2009, an intensive field studywas carried out on Illecillewaet Glacier to measure biweeklysnow accumulation, snow and ice melt, and meteorologicalconditions along a centre line transect on IllecillewaetGlacier (Fig. 3).

Point snowpack measurements were taken on 1 May 2009through a combination of probed snow depths and snowdensity measurements at several locations on the glacier, toderive snow water equivalent (w.e.) or SWE. Snow density

Glacier Meltwater Contributions to Streamflow in the Illecillewaet River Basin / 3


Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

was measured through a combination of snowpit profiling andsnow-core estimates. Snow w.e. on 1 May is taken to representthe winter accumulation (bw) on Illecillewaet Glacier, with

point measurements extrapolated to give the glacier-widewinter mass balance (m3 w.e. a−1). We express this as themean specific balance for the glacier, Bw (m w.e. a−1)through normalization by the glacier area. In interior regionsof western Canada, seasonal melting at the elevation of theglaciers typically begins in May and extends through Septem-ber. Stake measurements provide data on summer massbalance, with point values extrapolated to give glacier-widesurface mass balance, Bs. Combining the two measurementsdelivers the net balance, Bn = Bw + Bs. Any mass addedthrough summer snow events is implicitly included in Bs.

In 2009, a total of 13 stakes were drilled into the glacierevery 50 m in elevation along the centre line (NW–SE).

Table 1. Glacier area statistics for the glacierized portions of the IllecillewaetBasin. The estimated mapping error in glacier area is 3%.

Size Range(km2)

GlacierCount

GlacierCount (%)

Glacier Area(km2)

GlacierArea (%)

0.00–0.99 63 80 16.6 301.00–2.99 11 14 18.7 333.00–4.99 4 5 14.8 265.00–5.94 1 1 5.9 11Total 79 56.0

Fig. 1 Map of the Illecillewaet Basin with the Illecillewaet Glacier located to the northeast and the Greeley Hydrometric station located to the southwest (green dot).Glacier polygons from Tobias Bolch, UNBC and 20 m DEM from Parks Canada.



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

Seven additional stakes were established along two transverselines 200 m apart (Fig. 3). Winter balance (snow accumu-lation) was measured at all stake locations in early May.Beginning in 2010, mass balance surveys have been con-ducted by Parks Canada, with a total of seven stakes spacedapproximately every 100 m in elevation along the samecentre-line transect. Measured winter and summer balancesare regressed against elevation (Fig. 4) and linearly extrapo-lated to the entire glacier. Error analysis for mass balanceresults is based on the estimated error in glacier area andhypsometry (e.g., through non-contemporaneous imagery)and measurement errors for snow depth, snow density, andstake height.

b Meteorological MeasurementsMeteorological input data needed to model glacier melt werecollected from an automatic weather station (AWS) and sec-ondary weather stations positioned on and off the IllecillewaetGlacier from 1 May to 14 September 2009 (Fig. 3). Air temp-erature, humidity, and precipitation, were recorded by second-ary weather stations mounted on poles drilled into the ice andspaced every 100 m in elevation. The centre-line transect oftemperature loggers was used to measure temperature lapserates on the glacier.The AWS was mounted on a tripod at an elevation of 2435m

andwas configured to record temperature, humidity, precipitation,

wind speed and direction, air pressure, and incoming and out-going shortwave and longwave radiation. Measurements at theAWS were taken every 10 seconds, with average values storedevery 10 minutes on a Campbell Scientific datalogger(CR1000). Next to the AWS an ultrasonic ranger (SR50)was installed on a fixed pole to record snow or ice surfaceheight every 30 minutes.

To supplement the data gathered in summer 2009, we usehourly precipitation, humidity, and temperature data from anEnvironment Canada weather station at Rogers Pass, whichhas been operational since 1966. The station is at an elevationof 1340 m and is 9.3 km from the glacier AWS. Winter(September to May) precipitation at Rogers Pass averaged1278 mm from 1966 to 2011, while mean summer (June,July, August) temperature averaged 12.0°C over this period.For our study period, winter precipitation deviated from thelong-term mean by −18%, −16%, and +10% in 2008–09,2009–10, and 2010–11, respectively. Mean summer tempera-ture anomalies from 2009 to 2011 were 1.2°C, −0.1°C, and−0.7°C, respectively. Mass balance year 2008–09 was there-fore warm and dry, which should drive a more negativemass balance; 2009–10 was relatively normal, and 2010–11was cool and wet in the region, conducive to positive massbalance.

c Illecillewaet Glacier Melt ModelWe develop and calibrate a local melt model at the AWS siteand then apply it to Illecillewaet Glacier at 20 m resolution.Spatially distributed energy balance investigations arenecessary to understand and simulate glacier melt better(e.g., Hock, 1999; Wagnon, Ribstein, Kaser, & Berton,1999). Although a complete energy budget approach is theideal way to model glacial melt, it demands many obser-vations which are generally unavailable. Instead, tempera-ture-index models that are based on cumulative positivedegree days (PDD) have proven to be useful in glacio-hydro-logical studies. The “classical” degree-day temperature-index model captures seasonal patterns in runoff and islikely sufficient for long-term analyses (e.g., Braithwaite,1995), and it has been applied in a wide variety of regions(e.g., Jóhannesson, Sigurdsson, Laumann, & Kennett,1995; Rango et al., 2008).

However, PDD models do not capture daily and seasonalrunoff variability well (Hock, 1999), in part because degree-day factors can vary considerably in space and time (e.g.,Hock, 1999; Singh and Kumar, 1997). Modified degree-daymodels that include solar radiation (e.g., Hock, 1999; Pellic-ciotti et al., 2005) capture daily cycles better, as well asspatial variations in melt resulting from topographic influences(i.e., effects of shading, slope, and aspect). Temperature-indexmodels that incorporate treatments of potential direct incom-ing solar radiation are well established (e.g., Hock, 1999,2003; Moore, 1993; Pellicciotti et al., 2005; Shea, Moore, &Stahl, 2009), because potential direct solar radiation isreadily calculated.

Fig. 2 Percentage of glacierized area versus elevation for the IllecillewaetGlacier and in the Illecillewaet basin.

Table 2. Glacier area and elevation statistics for Illecillewaet Glacier andglaciers within the Illecillewaet River sub-basin (IRB), 2005.

GlaciersArea(km2)

Glacier cover in theIRB (%)

Elevations (m)

Min. Median Max.

Illecillewaet 5.94 1.0 1993 2521 2911Sub-basin 56.0 4.9 1592 2385 2942



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

1 MELT PARAMETERIZATION

Here we adapt the temperature-index melt models ofHock (1999) and Pellicciotti et al. (2005), using absorbedsolar radiation rather than potential direct solar radiation

in our melt model. Pellicciotti et al. (2005) alsoconsider absorbed solar radiation, in a bivariate relationwith PDD (i.e., two separate melt terms). Because absorbedsolar radiation and degree days are highly correlated, we

Fig. 3 Topographic contour map of the Illecillewaet Icefield study area, with an elevation contour interval of 50 m (100 m on the glaciers). The field instrumenta-tion from summer 2009 is also indicated. AWS; automatic weathers station; RP: Rogers Pass; T and RH: temperature and relative humidity stations,respectively.



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

take a different approach and combine these into a singleterm:

M = [TF+ SRF (1− α)I]DD, (1)

where M is the total daily melt (mm w.e. d−1); DD is thenumber of positive degrees in a day; α is the surfacealbedo, and I is the average daily shortwave radiation(W m−2) received at the site. TF and SRF are empiricalcoefficients, the temperature factor and shortwave radiationfactor, expressed in mm w.e. °C−1 d−1 and mm w.e. W−1

m2 d−1, respectively. We treat these as constants. Insteadof separate melt factors for snow and ice, which are typi-cally invoked in PDD models (e.g., Braithwaite, 1995;Hock, 1999; Jóhannesson et al., 1995), the solar radiationterm embeds an evolving surface albedo, which varies inspace and time.Equation (1) introduces additional complexity relative to

Hock (1999) because of the need for information on surfacealbedo and atmospheric cloud conditions. Temperature,albedo, and incoming solar radiation all need to be measuredor parameterized. Where AWS data are available, this canbe evaluated directly. We determine TF and SRF based onobservations at the Illecillewaet Glacier AWS site and fromour ablation stakes in summer 2009, using three-day averagedmelt data from the AWS ultrasonic depth gauge (SR50) andbiweekly melt data from stake ablation measurements. Toconvert SR50 and stake measurements to water equivalence,initial snowpack density was measured from four snowpits(2000, 2200, 2400, and 2600 m) in 2009 and three snowpits(2200, 2400, and 2600 m) in 2010 and 2011. Ice lenses andglacier ice are assumed to have a density of 917 kg m−3. Weneglect the effects of snow densification through thesummer. Half of the days from our study period, 1 May to14 September 2009, are used to calibrate the model, with theother days reserved for model evaluation. Once calibrated,the melt model can be applied to other points on the glacieras well as to other years.

2 TEMPERATURE INPUTS

For distributed modelling of snow and ice melt, hourly temp-erature is modelled as a function of elevation, using measuredlapse rates on the glacier. For 2009 this is based on hourlymean temperatures recorded at the AWS,

Tcell = TAWS + βT (zAWS − zcell), (2)

where zAWS and zcell are the AWS and grid cell elevations,respectively; TAWS is the AWS hourly temperature, βT is thesurface temperature lapse rate, and Tcell is the computed celltemperature. Daily DD values are calculated from hourlytemperatures, providing a measure of the heat energy availableover a day in excess of 0°C (i.e., available for melting). Forother years, we adapt Eq. (2) so that it is based on hourly temp-erature data from Rogers Pass (see Section 4b).

3 RADIATION AND TRANSMISSIVITY

Radiation and albedo data are available for the AWS site butmust be estimated elsewhere on the glacier. Potential directsolar radiation, Iϕ, is calculated for each glacierized grid cellby running hourly ArcGIS Area Solar Radiation, which incor-porates solar radiation at the top of the atmosphere, a specifiedclear-sky atmospheric transmissivity (τ), solar geometry, andtopographic characteristics (slope, aspect, and shading) (see,e.g., Oke, 1987). We find the optimal τ value by comparingmeasured daily incoming solar radiation for clear-sky dayswith modelled potential direct solar radiation. Diffuse pro-portions of incoming radiation are assumed to be 20%(Arnold, Willis, Sharp, Richards, & Lawson, 1996).

Cloud cover reduces the solar radiation that reaches thesurface, relative to the potential direct value. From the AWSdata, we calculate the fraction of daily mean radiation relativeto the potential direct radiation in order to derive a clear-skyindex: fcs = I/Iϕ. This is evaluated daily to provide an indexfcs[ [0,1], with fcs = 1 indicating clear-sky (cloud-free) con-ditions and fcs� 0 for overcast skies. Daily values of fcs areassumed to apply glacier-wide, allowing an estimate of incom-ing solar radiation I = fcs Iϕ to be applied in Eq. (1) for distrib-uted melt modelling. In years when we lack radiation data, fcsis parameterized as a function of temperature and humidityconditions at Rogers Pass (see below).

4 ALBEDO

Albedo also needs to be estimated at all points on the glacier.Snow albedo increases after a fresh snow event and declinesthrough the summer melt season as a result of grain recrystal-lization, liquid water content, and increasing concentrations ofaerosols and debris in a melting snowpack (e.g., Brock, Willis,Sharp, & Arnold, 2000; Klok & Oerlemans, 2004). Based onobservations at the AWS site, we parameterize the summersnow-albedo evolution, αs(t) as a function of cumulative posi-tive degree days, Σ DD (t), following a logarithmic fit:

αs(t) = a+ b ln [ΣDD(t)]. (3)

Parameters a and b are fit to the data and are assumed to applyat all locations on the glacier. Once the seasonal snowpack

Fig. 4 Vertical profiles of Illecillewaet Glacier for winter (long dashed lines),summer (short dashed lines), and net mass balances (solid lines) for2009 (black), 2010 (dark grey), and 2011 (light grey).



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

melts away, fixed albedo values for firn or ice are assigned,based on measurements of old snow and bare ice at theAWS site.Fresh snowfall events in the summer have a large effect on

the surface albedo, reducing summer melt (Brock et al., 2000;Oerlemans & Klok, 2004). These were measured in summer2009 by direct observations during biweekly site visits,SR50 snow-surface heights, and the AWS albedo data.Snow-water equivalence (SWE) is estimated for fresh snowevents based on the depth of the fresh snow and measurementsof snow density from summer snowfall events. When asummer snowfall occurs, surface albedo is reset to a freshsnow value until the fresh snow melts away, at which timethe previous underlying surface value, from Eq. (3) or forbare ice or firn, is restored. Snow events at the AWS sitemay correspond to rainfall at lower elevations. Based onobservations from the AWS site, we adopt a local (grid cell)DD threshold of 4°C d−1 to determine whether a summer pre-cipitation event manifests as snow or rain.

d Illecillewaet Basin ModelWinter mass balance for other glaciers in the IRB is estimatedthrough extrapolation from Illecillewaet Glacier, based on alinear regression of May bw against elevation on Illecillewaet.We therefore assume that the observed snowpack, its variationwith altitude, and their interannual variability are representa-tive of other glaciers in the basin.Application of the melt model to the IRB requires data for

temperature, lapse rates, cloud cover, and summer snowevents. This is available for Illecillewaet Glacier in 2009,but for 2010 and 2011 we use hourly weather data fromRogers Pass. This includes temperature data for DD estimates,lapsed to different elevations in the IRB, along with parame-terizations of cloud cover and summer snowfall based onRogers Pass temperature, humidity, and precipitation data.These adaptations to the melt model are explained below.The mass balance and runoff models are then extended to allthe glaciers in the IRB.The observed relation between hourly temperature at

Rogers Pass and the glacier AWS is used to extrapolatehigh-elevation temperatures. This is not a simple matter ofadopting a fixed lapse rate, because near-surface air tempera-tures are determined by local surface energy balance (i.e., heatabsorption in a forested versus glaciated environment) and bylocal air movements, such as cold air drainage patterns(see, e.g., Pepin & Losleben, 2002; Petersen & Pellicciotti,2011; Shea & Moore, 2010). As discussed in Section 4, weobserve a strong diurnal relation in the temperature differencebetween the Rogers Pass AWS and the glacier AWS and usethis as the basis for temperature extrapolation to the glaciers.Glaciers in the IRB occupy different aspects and experience

different degrees of topographic shading, so the radiation-based melt model is essential for basin-scale distributed mod-elling. Potential direct solar radiation is readily modelled overthe entire IRB. Effective daily cloud cover ( fcs) measured at

Illecillewaet Glacier cannot be expected to apply to thewhole basin, but it may be “statistically” reasonable over thecourse of a summer. That is, the number of clear-sky andheavily overcast days may be similar across the IRB,because these are generally dictated by synoptic weather pat-terns during the summer season. Furthermore, the subset ofglacierized IRB locations occupy a similar range of elevation,mostly above 2000 m, and are likely to experience commonsky conditions (e.g., similar transmissivity and immunity tovalley fogs).

Nevertheless, cloud conditions in summer 2009 are notnecessarily typical of other summers, so we develop a proxyfor the clear-sky index, fcs, based on observed diurnal tempera-ture patterns and atmospheric humidity. Bristow and Camp-bell (1984) parameterize mean daily cloud cover and/oratmospheric transmittance as a function of daily temperaturerange, Tr = Tmax – Tmin. Cloudy days reduce daytime tempera-ture maxima and increase the overnight minima, giving lowvalues of Tr. Other parameterizations relate transmittance tothe relative or absolute humidity, which are also roughproxies for cloud cover (e.g., Richardson & Reddy, 2004).We examine different combinations of temperature andhumidity variables to develop an empirical relation for fcs, cali-brated against observations from summer 2009.

Summer snowfall events are well characterized for 2009 butare not known for other years. We explore two approaches tomodelling summer snow events: (i) introducing summersnowfall as a stochastic variable and (ii) estimating summersnow events based on daily precipitation at Rogers Pass. Forthe stochastic approach, the number and frequency ofsummer snow events is specified, then randomly generatedin MATLAB to determine event timing and magnitude. Mag-nitudes are sampled from a uniform distribution between 1 and10 cm, based on observations in summer 2009. We introducethis approach as a way of including summer snow events inmass balance models where local station data are unavailable.

For the second method, summer precipitation at RogersPass is assumed to be representative of precipitation on theglaciers, and local grid-cell temperatures (daily DD totals)determine whether precipitation falls as snow or rain. Wemeasured vertical precipitation gradients in Illecillewaetvalley in summer 2009 and found no significant relationshipbetween precipitation totals and elevation. Hence, we do notapply a precipitation lapse rate. Note that this may be appropri-ate for summer precipitation events but is not expected to holdtrue in winter when orographic precipitation is the dominantmechanism of snow accumulation.

Meltwater runoff from the IRB glaciers is our primary inter-est in this study. Snowpack and melt models are applied toeach 20 m × 20 m grid cell to determine the distributed melt,and all meltwater is assumed to run off to the Greeley gaugeat the outlet of the basin. We do not apply a hydrologicalmodel to route the runoff. Our simplistic approach neglectsdelays and storage in the glaciers and the groundwatersystem but may be reasonable for total glacier discharge ona monthly and seasonal time scale.



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

e Sensitivity TestsWe assess model uncertainties by exploring the parameterspace. In particular, we examine the sensitivity of modelledglacier runoff to our assumptions about melt model par-ameters, cloud conditions, summer-snow frequencies, andinitial (1 May) snowpack. There is uncertainty about thewinter mass balance gradient and even greater uncertaintywith respect to snowpack estimates on other (unmeasured) gla-ciers in the IRB.In addition to numerical experiments to evaluate uncertain-

ties, we examine Illecillewaet Glacier’s sensitivity to climatevariability through systematic perturbations in temperature,precipitation, and the clear-sky index. Using the massbalance and meteorological measurements from 2009 as areference climatology, we explore the effects of temperatureperturbations from −3°C to +3°C, winter precipitation vari-ations from 20% to 220% of the observed 2009 snowpack,and clear-sky index ( fcs) variations from 0.65 to 0.90 onmass balance and glacier runoff.

4 Resultsa Mass Balance MeasurementsMay snowpack (bw) data are available from 2000 m to 2600 mon Illecillewaet Glacier. Linear regression of these data in2009, for which we have the most detailed snowpack infor-mation, gives a balance gradient of βP = 0.92 mm w.e. m−1

(R2 = 0.61; Fig. 4). Winter mass balance measurements fromMay 2010 to 2012 indicate a weaker elevation gradient,with a mean value of βP = 0.73 mm w.e. m−1 for 2009 to2012. These values are comparable to precipitation lapserates adopted in other studies (e.g., Stahl, Moore, Shea, Hutch-inson, & Cannon, 2008).Observations indicate that winter accumulation on Illecille-

waet Glacier increases approximately linearly with elevationup to the last measured stake at 2600 m, the altitude of themain icefield plateau. Above this elevation we assume thatwinter accumulation levels off at the value measured at2600 m. This may overestimate the snow at the higherelevations, because slopes above this tend to be steep andwind scoured. Winter balances at elevations below 2000 mand above 2600 m are uncertain because of the lack ofdirect measurements. The regression functions for bw(z)provide winter snowpack estimates that can be extrapolatedto all grid cells on Illecillewaet Glacier and for the IRB,providing Bw and the initial snowpack that is input to themelt model.

Table 3 summarizes the observed mass balance data onIllecillewaet Glacier from 2009 to 2011. Error estimates arebased on the combined uncertainty in measurements andinput datasets used to derive the glacier-wide mass balance.We assess these to be 22% for winter balance and 23% forsummer balance (Hirose, 2012). Average specific massbalances from 2009 to 2011 were Bw = 1.43, Bs = −1.91, andBn = −0.48 m w.e. a−1. All three years had negative net massbalances, with the most extensive melting and runoff in 2009.

b Meteorological MeasurementsMonthly mean meteorological data collected at the glacierAWS are summarized in Table 4 and calibrated parametervalues from field measurements are found in Table 5.

1 TEMPERATURE

A mean summer temperature lapse rate of βT = −0.0067°C m−1

(R2 = 0.94) was measured from the transect of temperaturestations on Illecillewaet Glacier, with high correlationsbetween all glacier stations. Temperatures at Rogers Passhave a complex relationship with those on the glacier,however. For 1 May to 14 September 2009, the mean tempera-ture difference between the glacier AWS and the AWS atRogers Pass, ΔTm, was −7.8°C. There is a strong diurnalpattern to the temperature differences (Fig. 5), with meanmidday and overnight differences of about −13°C and −3°C,respectively (i.e., a 10°C diurnal cycle about the mean temp-erature offset of −7.8°C). Daytime heating at Rogers Pass,

Table 3. Observed and modelled mass balance and glacier runoff, 2008 to2011 (m w.e.) of Illecillewaet (Ille) Glacier and Illecillewaet River Basin(IRB). Uncertainty estimates are discussed in the text.

Season 2008–09 2009–10 2010–11 Average

ObservationsWinter 1.48 ± 0.33 1.43 ± 0.31 1.39 ± 0.31 1.43 ± 0.18Summer −2.08 ± 0.48 −2.00 ± 0.46 −1.65 ± 0.38 −1.91 ± 0.25Net −0.61 ± 0.58 −0.57 ± 0.56 −0.26 ± 0.49 −0.48 ± 0.31Runoff (106 m3) 12.4 ± 2.8 11.9 ± 2.7 9.8 ± 1.9 11.3 ± 1.5

Model, Ille GlacierWinter 1.55 ± 0.23 1.38 ± 0.21 1.44 ± 0.22 1.46 ± 0.13Summer −2.32 ± 0.42 −1.60 ± 0.29 −1.18 ± 0.21 −1.70 ± 0.18Net −0.77 ± 0.48 −0.22 ± 0.35 0.26 ± 0.30 −0.24 ± 0.22Runoff (106 m3) 13.8 ± 2.5 9.5 ± 1.7 7.0 ± 1.3 10.1 ± 1.1

Model, IRBWinter 1.45 ± 0.36 1.30 ± 0.33 1.39 ± 0.35 1.38 ± 0.20Summer −2.68 ± 0.48 −1.91 ± 0.34 −1.43 ± 0.26 −2.01 ± 0.22Net −1.23 ± 0.60 −0.61 ± 0.47 −0.04 ± 0.43 −0.63 ± 0.29Runoff (106 m3) 150 ± 27 107 ± 19 80 ± 14 112 ± 12

Table 4. Monthly mean weather at the Illecillewaet Glacier AWS site, summer 2009.

Period Tmin (°C) �T (WC) Tmax (°C) PDD (°C d) RH (%) �I (Wm−2) �α fcs

May −12.7 −1.3 10.2 40 72 308 0.80 0.85June −6.6 2.4 10.4 93 71 312 0.70 0.79July −6.2 5.7 15.4 191 69 300 0.62 0.80August −2.4 5.5 14.8 181 71 232 0.40 0.771–14 Sept. −2.9 3.8 13.3 62 73 184 0.56 0.78Season −12.7 2.6 15.4 566 71 296 0.62 0.80



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

relative to the glacier, may be caused by the lower albedo inthe valley-floor environment, resulting in increased solarabsorption. Closure of the overnight temperature differenceis consistent with cold air drainage, driving weak or invertedovernight lapse rates. This systematic diurnal cycle meansthat a constant offset (i.e., static lapse rate adjustment) fromRogers Pass to the glaciers would give daytime temperaturesthat are too high, leading to excessive modelled melt.Based on these observations, we introduce a sinusoidal,

diurnal temperature correction to make Rogers Pass datamore representative of the glacier,

ΔTd = −A cos (2π (t − tlag)/24), (4)

where A is the half-amplitude of the temperature difference; t isthe hour of interest, and tlag is the time lag from local solar noon

and midnight for the peak temperature difference. Becausedaily DD totals are the essential variable of interest for glaciermelt modelling, we determine A and tlag based on the best fitto observed summer DD totals. Resulting values are A = 5.8°C and tlag = 2.8 hr, shown by the dashed line in Fig. 5.

Temperatures at Rogers Pass are then used to drive the meltmodel with a three-stage correction: (i) a uniform temperatureshift to the reference elevation of the glacier AWS site, ΔTm,(ii) a correction for the diurnal temperature pattern, ΔTd, and(iii) a lapse rate correction for the elevation of the glacier pos-ition of interest, after Eq. (2):

Tcell = TRP + ΔTm + ΔTd + βT (zAWS − zcell), (5)

where TRP is the hourly mean temperature at Rogers Pass. Thistemperature parameterization is used for basin-wide meltmodelling and for driving Illecillewaet Glacier mass balancemodels for 2010 and 2011.

2 SOLAR RADIATION

Measurements of average daily incoming solar radiation onclear-sky days, relative to modelled potential direct solar radi-ation, allow an estimate of atmospheric transmissivity for thesite. Fits to the data indicate a value for τ of 0.73 (R2 = 0.94),within the range of other studies which recommend values of0.6–0.9 (Hock, 1999; Oke, 1987). Radiation modelling for thebasin was carried out treating τ as a constant. Daily meanpotential solar radiation in the IRB averages 315 W m−2 forthe summer melt season, 1 May to 14 September, rangingfrom 22 W m−2 on a northern exposed slope to 433 W m−2

on a southern aspect.In summer 2009, clouds and atmospheric scattering reduced

solar radiation on the glacier by 20%, on average, a clear-skyfactor of fcs = 0.80. Daily values for fcs ranged from 0.28 to1.03. Monthly mean fcs values are relatively consistent,varying from 0.77 to 0.85 (Table 4). These mean valuescould be applied to melt modelling in other years for whichwe lack radiation data. Alternatively, we examine the relationbetween mean daily fcs values, daily temperature range, Tr, and

Table 5. Parameter values calibrated from field measurements.

Parameter Description Value Units

βP Winter snowpack lapse rate, 2009 0.92 mm w.e. m−1

Winter snowpack lapse rate, 2009–11 0.73 mm w.e. m−1

βT Temperature lapse rate −0.0067 °C m−1

TF Temperature factor 0.9308 mm w.e. °C−1 d−1

SRF Solar radiation factor 0.02974 mm w.e. m2 W−1 °C−1 d−1

τ Atmospheric transmissivity 0.73fcs Average summer clear-sky index 0.80αs Fresh snow albedo 0.86αi Ice albedo 0.20αf Firn albedo 0.40kdT Regression parameter for fcs 3.08 % °C−1

ke Regression parameter for fcs −2.07 % mbar−1

DDt Degree day threshold for snow 4.0 °C dA Half amplitude, diurnal ΔTd 5.8 °Ctlag Lag time, diurnal ΔTd 2.9 hr

Fig. 5 Hourly temperature differences between the Rogers Pass AWS andIllecillewaet Glacier AWS for all days, 1 May to 14 September2009 (asterisks), after correcting for the mean summer temperaturedifference between the sites (−7.8°C). The solid line shows theaverage temperature difference for each hour and the dashed lineshows the best-fit sine wave introduced to correct for this diurnalpattern.



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

humidity variables at Rogers Pass. Of several different combi-nations of variables, a bivariate combination of Tr and themean daily vapour pressure, ev, proves to be the strongest pre-dictor of the clear-sky index:

fcs = 0.646+ 0.0308Tr − 0.0297ev. (6)

This relation is statistically significant (R2 = 0.65), with astandard error in fcs of 0.01. This relation allows regionalcloud conditions to be parameterized from historicaltemperature and humidity data at Rogers Pass, or from near-surface temperature and humidity fields in climate modelprojections.

3 ALBEDO

Seasonal melt had not yet begun at the time of our initial snowsurveys and AWS setup in late April 2009. Measurements ofearly season and fresh summer snow indicate an albedoof 0.85 to 0.9 (Fig. 6). This is borne out by regressions ofsnow albedo against cumulative DD, which give the relation

αs = 0.86− 0.05668 ln∑

DD( )

. (7)

The mean measured albedo of ice at our site was 0.20. Fitsof the albedo model to the measured AWS albedo are good(Fig. 6), but the detailed fit is contingent on capturing thefresh-snow events, which briefly boost the albedo back tofresh-snow values. Snow-depth gauge and albedo measure-ments identify the timing of fresh-snow events, but theamount of snowfall and the altitude of the snowline (i.e.,where the glacier received snow rather than rain) in eachsnowfall event are less certain. We use a fresh-snowdensity of 145 kg m−3 for summer snow accumulations,based on measurements, and estimate SWE at the AWS

through a combination of SR50 records and fits to thealbedo data.

To apply this to the rest of the glacier in 2009, we assumethe same timing for snow events but determine an elevationthreshold where rain transitions to snow based on the localdaily DD total. Based on the fresh-snow and meteorologicalobservations at the AWS site, rain is assumed at locationswith a daily DD in excess of 4°C d−1; below this, precipitationis assumed to fall as snow.

The total amount of SWE contained in summer snowfall isrelatively minor, but its influence on albedo is important. Astochastic model of summer snowfall events is developedbased on the frequency of snow events (approximately 10per summer) and their observed magnitude (up to 10 cm ofsnow accumulation) in summer 2009. These parameters arevaried in sensitivity tests to explore their relative importanceto seasonal melt and runoff models. Alternatively, precipi-tation at Rogers Pass can be extrapolated to the glacier,along with temperature adjustments following Eq. (5), to esti-mate summer snowfalls. For summer 2009, this method givessimilar results to the melt model runs with observed snowfalland with stochastic (N = 10) snow events: Bs values of −2.32,−2.35, and −2.33 m w.e., respectively. Because this is readilyapplied to other seasons when we lack direct observations ofsummer snowfall, we adopt the Rogers Pass precipitationextrapolation as our “reference model” for 2010 to 2011 andfor basin-scale modelling.

c Illecillewaet Glacier Melt ModelUsing measured mass balance and AWS meteorological data,the melt model parameters are calibrated (Tables 2 and 4).Using multiple linear regression the melt model’s coefficientsare optimized with TF = 0.9308 mm w.e. °C−1 d−1 and SRF =0.02974 mm w.e. W−1 m2 °C−1 d−1 ((Eq.) 1), significant at the95% and 99.9% levels of confidence, respectively. Standarderrors for the two coefficients are 0.46 mm w.e. °C−1 d−1

and 0.0026 mm w.e. W−1 m2 °C−1 d−1, respectively. Themelt model is independently validated at a subset of the abla-tion stakes and selected biweekly periods of the SR50 data torepresent the seasonal, elevation, and surface variability. Forthe independent test data, R2 = 0.88 and the mean absoluteerror |ε| = 0.4mm w.e. (Fig. 7).

Driving the distributed model with these parameters andwith the temperature, radiation, and albedo models describedabove, glacier-wide melt can be modelled for the summersof 2009 to 2011. Distributed radiation and DD fields forJuly 2009 are illustrated in Fig. 8. Glacier melt can also be par-titioned into that associated with seasonal snow and thatcaused by melting of glacier ice and firn. Modelled massbalance and Illecillewaet Glacier runoff for 2009 to 2011 aregiven in Table 3. We discuss uncertainty estimates inSection 5b.

d Illecillewaet Basin Melt ModelBasin-wide glacier snow accumulation and melt from 2009 to2011 can be calculated by extension of the methods used for

Fig. 6 Observed (solid) and modelled (dashed) daily mean albedo at the Ille-cillewaet Glacier AWS (2450 m elevation).



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

Illecillewaet Glacier. Because glacier hypsometries and solarradiation fields differ between Illecillewaet Glacier and theIRB, different specific mass balances are predicted. To esti-mate Bw, we extrapolate from the observed IllecillewaetGlacier winter snowpack, based on the observed altitude gra-dient, βP, for each year. The melt model can be applied directlyto the basin. Model simulations indicate more negativesummer and annual mass balances for the IRB as a whole,relative to Illecillewaet Glacier (Table 3). For the 2008–09balance year, modelling of the IRB gives Bw = 1.45, Bs =−2.68, and Bn = −1.25 m w.e. Snow accumulation is 7% lessthan on Illecillewaet Glacier, and there is 16% more summermelt, with both factors contributing to the more negativemass balance. Modelled glacier runoff for the basin is150 × 106 m3 in 2009, with 45% of this derived from iceand firn melt.For the three-year composite, 2009 to 2011, IRB mass bal-

ances are Bw = 1.38, Bs = −2.01, and Bn = −0.63 m w.e. (Table3), and modelled glacier runoff averages 112 × 106 m3,of which 34% comes from glacial ice and firn. Differencesin annual mass balance are primarily driven by summertemperature and cloud cover, with winter snowpack havinga secondary influence for these years. Frequent summersnowfalls also contribute to the reduced melting and runoffin summer 2011.

5 Discussiona Observed and Modelled Mass BalanceHere we discuss the observed and modelled mass balance andtotal glacier runoff from Illecillewaet Glacier. There are noobservations to evaluate this on the scale of the IRB, but wediscuss basin-scale mass balance in the context of glacierdischarge in Section 5d.

Average Illecillewaet Glacier mass balance was negativefrom 2009 to 2011, but there is interesting interannual varia-bility in the seasonal balances and summer runoff. The2008–09 balance year was the most negative of the threeyears, 2009–10 was slightly negative, and mass balance in2010–11 was close to a state of balance (Table 3). Summerrunoff from the glaciers decreased in each of the three years.These results are consistent with available meteorologicalobservations at Rogers Pass, which indicate that summer2009 was warm relative to 2010 and 2011. Mean temperaturefrom 1May to 14 September 2009 was 10.4°C, compared withvalues of 9.3°C and 9.1°C in 2010 and 2011, respectively.Relative humidities for this period were 70.8, 73.6, and74.8% for 2009, 2010, and 2011, respectively. Precipitationwas recorded at Rogers Pass on 65 days in summer 2009, com-pared with 78 and 71 days in the two subsequent summers.This indicates relatively cool, overcast summer weather in2010 and 2011.

Regional snowpack was above normal in the La Niña winterof 2010–11 (Anslow & Roddenhuis, 2011). September throughApril precipitation at Rogers Pass was 1332 mm in 2010–11,10.4% above the 1965–2011 average of 1206 mm. In contrast,precipitation in 2008–09 and 2009–10 was below normal, with990 and 1042 mm of September–April precipitation, respect-ively. It is unlikely that Illecillewaet Glacier winter massbalance was as low as reported in 2010–11, Bw = 1390 mm;this is comparable to the winter precipitation at Rogers Passand less than the winter mass balance that was measured in2009. We suspect that high elevation snow depth measurementson the glacier may have been misread because of ice layers ordenser snow that was mistaken as firn.

Modelled winter balance in 2008–09 overestimates thebalance by 5% relative to the observations (Table 3). Thelinear accumulation gradient that we adopt oversimplifies the

Fig. 7 Observed versus modelled melt (m w.e.) at the AWS and ablation stakes during the calibration and verification periods.



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

snowpack variability. A portion of the glacier also lies above2600 m, where we do not have measurements. The higheststake data are assumed to apply to all elevations above2600 m. Winter balance data need to be measured at higherelevations to assess this assumption. These areas on the glacierare steep, avalanche prone, and heavily crevassed, however,making this difficult. These steep upper slopes may retain lesssnow accumulation, so that both our measured and modelledwinter balances overestimate bw at elevations above 2600 m.

The model overestimates summer mass balance by 12%compared with the observed stake data, when extrapolatedto the glacier area (Table 3). We suspect that the model maybe closer to the truth, because it parameterizes snow and icemelt based on energy constraints (i.e., solar variability,albedo, elevation, and aspect), while high-elevation ablationestimates in the “observed” mass balance are from thehighest stake data (2600 m). The stake data do not captureimportant differences in energy inputs on the upper glacier

Fig. 8 Modelled (a) positive degree days (°C d), (b) melt (m w.e.), (c) potential direct solar radiation (W m−2), and (d) absorbed solar radiation (W m−2) onIllecillewaet Glacier, July 2009.



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

slopes, which have southwest aspects. The highest elevationson the glacier therefore receive greater amounts of solarradiation (Fig. 8c), which will contribute to higher melt rates.In combination, observed and modelled 2008–09 net mass

balances are comparable and well within our uncertainties,at −0.61 and −0.77 m w.e. Discrepancies between observedand modelled net balance are also within the uncertainties in2009–10 and 2010–11 (Table 3), but the melt model underes-timates summer melt and annual mass losses in these years, incontrast with 2009. On average, for the three years, observedBn = −0.48 m w.e. and modelled Bn = −0.24 m w.e. Most of thedifference can be attributed to underestimated melt in themodel; mass balance observations from 2009 to 2011 indicatea mean summer runoff of 11.3 × 106 m3 compared with a meanmodelled runoff of 10.1 × 106 m3. Average Bs and runoff inthe model are 11% less than the observational estimate,although values fall within the uncertainties.

b Model UncertaintiesUncertainties in the model can be explored through pertur-bation experiments. We examine the sensitivity of modelledrunoff and mass balance to the melt model coefficients,clear-sky parameter, and summer snowfall. Additional uncer-tainties in albedo and temperature values can be considered tobe embedded in the melt model coefficients (i.e., they intro-duce errors similar to having higher or lower values of thecoefficients TF and SRF). We vary these parameters individu-ally and in combination, based on the standard error estimatesfor TF and SRF reported above. For the clear-sky index, fcs, weexamine the impact of assuming a constant value for thesummer, mean monthly values, or through varying the meansummer value of fcs by ±10%, from 0.72 to 0.88. Thisexceeds the range of mean monthly values observed at thesite. We also explore the importance and sensitivity ofmodelled runoff to summer snowfall by varying the numberof randomly selected snow events from 0 to 20.Results of these sensitivity tests for Illecillewaet Glacier are

compiled in Table 6. Sensitivity tests are reported for summer2009 and the reference model, with Bs = −2.32 m w.e., is basedon our optimized parameters and observed temperature, clear-sky index, and summer snow events. The most sensitive freeparameter in the melt model is the temperature melt factorTF, for which variation by ±1 standard error gives a rangein modelled Bs from −2.59 to −2.03 m w.e. (i.e., ±12%).Uncertainty in SRF gives a variation in summer balance of±9%, and the sensitivity of summer balance to the clear-skyindex is ±10% for fcs ranging from 0.72 to 0.88.We have observations of the timing and extent (water equiv-

alent) of summer snow events in 2009, but this needs to beparameterized for other years. Our two main methods forthis, randomly generated snow events and extrapolation ofdaily precipitation at Rogers Pass, give similar results for thesummer 2009 mass balance: Bs = −2.33 and −2.32 m w.e.,respectively. The sensitivity of Bs to summer snowfall is eval-uated by varying the number of summer snow events, relative

to our reference value of 10 snow events in summer 2009. Thisintroduces less uncertainty than the melt parameters, with Bs

varying from −2.43 to −2.25 m w.e. (+5 to −3%) for 0–20summer snowfall events, although it is important to emphasizethat summer snows have a non-negligible impact on summermass balance.

Taking uncertainties in TF, SRF, fcs, and summer snowfrequency as additive (using the root mean square error),modelled Bs = −2.32 ±0.42 m w.e. (±18%). Modelled summerrunoff from the glacier has the same uncertainty: Q = 13.9±2.5 × 106 m3.

Accurate estimates of the winter snowpack also represent amajor source of uncertainty in our model, particularly at thebasin scale. Experiments inwhichwe allow snow accumulationto increase with altitude above 2600m, rather than levelling outat this altitude, have only a small effect on Bw (+1%; Table 6).We also carry out experiments in which the accumulationgradient βP ranges from 0.5 to 1.3 mm w.e. m−1, relative tothe reference value of 0.92 mm w.e. m−1. This range ofvalues in the accumulation lapse rate brackets the interannualvariability observed from 2009 to 2012. Resulting winterbalance for 2009 ranges from 1.35 to 1.74 m w.e. (Table 6),13% of the reference model value. Based on these numericalexperiments, we adopt 15% as the uncertainty for modelledwinter balance (i.e., Bw = 1.55 ± 0.23 m w.e.).

Net balance, Bn, has a greater uncertainty because of thecompounding uncertainties in Bw and Bs. We assess Bn for2008–09 at −0.77 ± 0.48 m w.e., with an average value ofBn = −0.24 ± 0.22 m w.e. from 2009 to 2011. Our best esti-mates predict cumulative mass loss, with IllecillewaetGlacier near a state of balance in 2010–11. Within confidence

Table 6. Sensitivity of modelled Illecillewaet Glacier 2008–09 mass balanceand runoff to parameter uncertainties and climatic conditions. The finalcolumn is the percentage of glacier runoff associated with ice and firn melt asopposed to seasonal snow.

Experiment

Mass balance(m w.e.) Runoff (106 m3)

Bw Bs Bn Total Snow Ice Ice (%)

Reference (2009) 1.55 −2.32 −0.77 13.8 9.4 4.4 32TF −1 s.e. 1.55 −2.03 −0.48 12.0 9.2 2.8 23TF +1 s.e. 1.55 −2.59 −1.05 15.4 9.5 5.9 39SRF −1 s.e. 1.55 −2.11 −0.56 12.6 9.3 3.2 26SRF +1 s.e. 1.55 −2.52 −0.97 15.0 9.5 5.5 37TF, SRF −1 s.e. 1.55 −1.83 −0.28 10.9 9.0 1.9 17TF, SRF +1 s.e. 1.55 −2.80 −1.25 16.7 9.5 7.2 43fcs = 0.72 1.55 −2.07 −0.52 12.3 9.3 3.0 25fcs = 0.88 1.55 −2.52 −0.97 15.0 9.4 5.6 37No summer snow 1.55 −2.43 −0.88 14.4 9.1 5.3 37Random snows, N = 10 1.55 −2.33 −0.78 13.8 9.3 4.6 33Random snows, N = 20 1.55 −2.25 −0.70 13.3 9.4 3.9 29No Bw plateau 1.57 −2.30 −0.73 13.7 9.5 4.2 31βP = 0.5 mm w.e. m−1 1.35 −2.37 −1.02 14.1 8.3 5.8 41βP = 1.3 mm w.e. m−1 1.74 −2.27 −0.52 13.5 10.2 3.3 24

Climate perturbationsΔT = −2°C 1.55 −1.38 0.17 8.2 7.5 0.7 8ΔT = +2°C 1.55 −3.57 −2.02 21.2 9.4 11.8 56ΔP = −20% 1.24 −2.43 −1.19 14.4 7.6 6.8 47ΔP = +20% 1.86 −2.24 −0.38 13.3 10.8 2.5 19ΔT = +2°C, ΔP = +20% 1.86 −3.46 −1.60 20.6 11.3 9.3 45



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

limits, modelled mass balance is consistent with observationsfor this period.Our error estimates are conservative relative to those typi-

cally reported in the literature but are realistic given ourshort period of study at the site. Direct measurements ofstream discharge and additional summer albedo and meltobservations would improve the confidence in summer meltmodelling. Targeted observations and a more sophisticatedsnow-accumulation model are also needed to help reduce theuncertainty in Bw. Development of a detailed snow distributionmodel would be valuable (e.g., Dadic, Mott, Lehning, & Ber-lando, 2010) and is recommended for future study. Snowpackextent varies from year to year, but patterns of snow depositionon glaciers typically recur, because snow redistributionthrough processes such as avalanching and wind scouring isprimarily a function of the terrain. However, for the samereason, patterns of snow redistribution and measured altitudi-nal gradients on Illecillewaet Glacier are not necessarily repre-sentative of the broader IRB. We therefore increase ouruncertainty estimates in basin-scale estimates of Bw from 15to 25%, in order to bracket available snowpack measurementsat Rogers Pass and Mt. Fidelity.Basin-wide uncertainty in the melt model is also difficult to

assess because there is structural uncertainty associated withextrapolation of the Illecillewaet Glacier melt model andRogers Pass weather conditions to the entire basin. Weadopt the confidence limits derived for Illecillewaet Glacierto the IRB simulations (±18%) but acknowledge that thismay underestimate the model uncertainty. We have more con-fidence in the ability of our empirical melt model to be

extrapolated to the basin scale, because it is calibrated for arange of weather conditions, and the distributed pattern andintensity of incoming solar radiation are physically based.

Finally, the chosen DEM and glacier mask can also beexpected to influence our results. We reran the analysis usinga 95 m DEM available from the Shuttle Radar TopographyMission (SRTM; Farr et al., 2007). This represents theglacier topography and outlines in somewhat less detail,giving a glacierized area of 54.4 km2 in the IRB watershedcompared with 56.0 km2 using the 20 m DEM. ModelledIRB glacier runoff in 2009 with the SRTM topography is148 × 106 m3, compared with 150 × 106 m3 using the 20 mDEM—1.3% less, mostly explained by the reduced glaciercover. Specific discharge for the IRB is 1.5% higher with the95 m DEM; Bs = −2.72 m w.e. compared with −2.68 m w.e.for the 20 m DEM. Hence, there are some differences, butthese are not significant relative to our overall uncertainlylevel of approximately 20%.

c Climatic Sensitivity of Illecillewaet GlacierSensitivity of Illecillewaet Glacier mass balance toperturbations in temperature and precipitation is shown inFig. 9. This plots Bn and summer runoff for temperatureperturbations,ΔT, from −3 to +3°C, relative to observed temp-eratures in summer 2009 and for winter accumulation (Bw)scaled from 20 to 220% of the observed 2008–09 snowpack.Model parameters are set to the reference values for the2008–09 balance year. Simulated mass balance values andrunoff totals for illustrative experiments are given in Table 6.

Fig. 9 Sensitivity of modelled Illecillewaet Glacier runoff to perturbations in (a, c) summer temperature and (b, d) winter mass balance. (a, b). Winter (blue),summer (red), and net (black) mass balance, m w.e. (c, d). Glacier runoff (106 m3) from 1 May to 14 September for total runoff (black), snow melt(red), and ice melt (blue).



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

The strong sensitivity to summer temperature is consistentwith mass balance observations from 2009 to 2011. A linearfit to the Bn(T) curve in Fig. 9a gives a slope ∂Bn /∂T = −0.55m w.e. °C−1. A quadratic equation fits the Bn (T) curve better,with Bn = −0.7725 − 0.5458ΔT − 0.0374ΔT2. This gives atemperature sensitivity ∂Bn/∂T = −0.5458 − 0.0748ΔT, whichis equivalent to the linear line of best fit when evaluated atthe reference temperature (ΔT = 0). However, modelled temp-erature sensitivity increases with the extent of warming as aresult of the increasing exposure of low-albedo glacial ice.An increase in the summer temperature anomaly ΔT from0 to 1°C corresponds to ∂Bn/∂T = −0.58 m w.e. °C−1, whilewarming from ΔT = 1°C to ΔT = 2°C exhibits greatersensitivity: ∂Bn /∂T = −0.68 m w.e. °C−1. Hence, we can con-clude that the net balance impact of summer temperaturechange is about −0.6 m w.e. °C−1, with a non-linear increaseunder greater warming.Mountain glacier sensitivity to summer temperature gener-

ally exceeds that associated with variability in precipitation(Braithwaite, Zhang, & Raper, 2002; Oerlemans and Reichert,2000). For Illecillewaet Glacier, a linear fit to the Bn (P) curvein Fig. 9b gives a slope ∂Bn /∂P = +1.91 m w.e., indicating anet balance change of +0.19 m w.e. for a 10% increase in pre-cipitation. A quadratic fit to Bn (P) is again slightly stronger.For a 30% increase in accumulation relative to the 2008–09winter balance, dBn = +0.58 m w.e., Illecillewaet Glacierrequires a precipitation increase of 30% to offset a warmingof 1°C (i.e., to overcome a net balance loss of approximately0.58 m w.e.). This is consistent with the predictions ofOerlemans and Reichert (2000) for a continental, mid-latitude mountain glacier but contrary to the conclusions ofBürger et al. (2011) at an adjacent basin in theCCRB. Bürger et al. (2011) argue that a 10% increase inprecipitation could offset a 1°C warming in the region, butprecipitation in the IRB appears to be considerably less thanthey report (in excess of 3000 mm). Our estimated summertemperature sensitivity is also about twice that of Bürgeret al. (2011).We do not carry out future climate change assessments in

this analysis because our objective is to characterize the con-temporary basin, but Table 6 includes mass balance andrunoff estimates from Illecillewaet Glacier for projectedfuture climate conditions in the basin (PCIC, 2010), a 2°Csummer warming and increases in winter snowpack of up to20%. Summer balance is severely affected by the warming,with Bs = −3.46 m w.e. and Bn = −1.60 m w.e. for this scen-ario. Increased snow cover delays the transition to bare ice,but the effect is minor relative to the increase in meltenergy. Summer runoff is 20.6 × 106 m3 under this climatescenario, 49% higher than the reference model (Table 3),although the proportion of runoff associated with seasonalsnow is similar at 55%.

d Glacier Contributions to Discharge in Illecillewaet BasinTo compare modelled glacier runoff to Illecillewaet River dis-charge, monthly streamflows during the 2009–11 glacier melt

season were obtained from the Greeley gauging station(Environment Canada, 2012a). Mean annual discharge from1963 to 2011 at Greeley was 52.6 m3 s−1; mean annual dis-charge rates for 2009, 2010, and 2011 were 41.2, 44.8, and54.8 m3 s−1, respectively, corresponding to a total runoff of1300, 1412, and 1735 × 106 m3 a−1, respectively. Hence, dis-charge rates for 2009 and 2010 were below normal but slightlyabove normal for 2011, in good accord with the winter precipi-tation observations in this snowmelt-dominated catchment.The Greeley station records natural flows; we assume thatglacier meltwater will discharge through Greeley within themonth in order to compare monthly proportions of glacierrunoff to the river yield for each ablation year (Table 7).

We estimate that average glacier volume losses from 2009to 2011 were equivalent to 112 ± 12 × 106 m3, or 10% of thetotal May to September discharge in the Illecillewaet River.Glacier runoff contributions decreased from 2009 to 2011,accounting for 14, 11, and 6% of basin yield (Fig. 10). Thehighest discharges for 2009 and 2010 occurred in July, withsnowmelt being the primary contributor. As a result ofcooler temperatures, peak snowmelt did not occur untilAugust 2011. As a proportion of Illecillewaet River flows,glacier runoff contributes most heavily in August, constituting25% of basin yield from 2009 to 2011 and 33% in August2009. Glacier runoff derived from ice and firn melt represents16% of the total August yield in the basin.

Glacial runoff can be separated into the fraction derivedfrom melting of the seasonal snowpack and that associatedwith melting of glacier ice and firn. Seasonal snow runoffaccounts for 66% of the glacier runoff for the three years,

Table 7. Modelled glacier runoff, Qg, which includes meltwater from theseasonal snowpack on the glaciers,Qs, and meltwater from glacier ice and firn,Qi. IRB yield is the total basin discharge measured at the Greeley Hydrometricstation for the period of study. The proportions of basin yield resulting fromtotal glacier melt, snowmelt, and ice melt are expressed as percentages, fg, fs,and fi.

Period

Modelled Runoff(106 m3)

IRB yield(106 m3)

fg(%)

fs(%)

fi(%)Qi Qg Qs

2009 149.8 82.4 67.4 1037 14.4 7.9 6.5May 2.2 2.2 0.0 180 1.2 1.2 0.0June 23.3 23.1 0.2 364 6.4 6.3 0.1July 62.7 46.5 16.2 271 23.1 17.2 6.0August 54.0 10.2 43.8 166 32.5 6.1 26.4September 7.6 0.4 7.2 55 13.8 0.7 13.1



Average,2009–11

112.3 74.1 38.3 1143 10.3 6.6 3.6



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

while melting of glacier ice and firn makes up the remaining34%. The percentage of glacier runoff resulting from ice andfirn melt increases continually from May to September, aver-aging 0, 1, 20, 62, and 69%, in the respective months. Thisessentially tracks the depletion of the seasonal snowpackand exposure of glacial ice and emphasizes the importanceof August and September for the streamflow that is derivedfrom glacier storage.A heavy winter snowpack or cool summer can dramatically

reduce late-summer ice melt, as evidenced in 2011 (Table 7)and several of the sensitivity tests summarized in Table 6. Inthese cases, total runoff is reduced and the fraction of snow-melt to total glacier runoff increases. In contrast, a lowwinter snowpack or warm summer causes ice to be exposedearlier in the season, increasing meltwater runoff and glacierdepletion.Rango et al. (2008) assess glacier storage contributions to

the Illecillewaet River using a simplified hydrological model.They conclude that for a temperature increase of 4°C, glacierstorage (ice) will contribute 134 × 106 m3 a−1 to the IRB. Inthe warm, dry year of 2009, glaciers in the IRB generated150 × 106 m3 of runoff in our model, with 67 × 106 m3

derived from glacier ice. Sensitivity analysis indicates a rateof increase in total glacier discharge of 3.7 × 106 m3 °C−1 forIllecillewaet Glacier (Fig. 9c) or 27% °C−1. If warming isaccompanied by an increase in precipitation of 10% °C−1 thesensitivity is reduced to 3.4 × 106 m3 °C−1 or 24% °C−1. Apply-ing this temperature sensitivity to the basin, it is expected thatrunoff will approximately double under a warming of 4°C,equivalent to the results of Rango et al. (2008). Most of this

increase would come from ice melt, concentrated from July toSeptember.

Our comparison with IRB yields at Greeley station neglectsmeltwater losses to evaporation, delays that may be introducedby glacier or groundwater storage, and the potential ecologicalinfluences of the river’s downstream hydrological balance.Hydrological routing through the glacier and through thebasin can introduce delays from days to weeks (Willis,Arnold, & Brock, 2002), particularly during the early meltseason when runoff is delayed by the snowpack and the sub-glacial drainage system can be inefficient (Fountain &Walder, 1998). Our estimated proportions of glacier runoffto streamflow should, therefore, be treated cautiously withrespect to timing of meltwater delivery to the IllecillewaetRiver. Terrain in the IRB is steep and well drained, particularlyin the late summer when the seasonal snowpack has receded.We therefore expect that monthly and total summer runoffestimates are representative. However, daily dischargescannot be compared to basin values without a model of hydro-logical routing that considers delays and storage terms (e.g.,Moore, 1993; Stahl et al., 2008).

Our mass balance and runoff studies are short term, and wehave not sampled a full range of interannual variability in theIRB. The conditions during the three years assessed in thisstudy differed: dry, warm, and clear in 2009; cool andcloudy in 2010; wet, cool, and cloudy in 2011. Meteorologicalconditions from 2009 to 2011 were typical with respect to theclimate normals for Rogers Pass (within one standard devi-ation), the most proximal site with long-term meteorologicalobservations. Our results are likely to be representative of“normal years” in the basin, for the current glacier extentand hypsometry; past and future magnitudes of glacierrunoff will be sensitive to the evolution of the glacierizedarea in the basin.

e Modelling of Other Time Periods in Illecillewaet BasinFurther research is needed to extend the model to historicalrunoff reconstructions and future projections of glacier andhydrological change in the IRB. The distributed massbalance and runoff models can be driven by historical (e.g.,Rogers Pass) station data. This works well for summer massbalance in our study period, with results comparable todirect observations on Illecillewaet Glacier (statistically equiv-alent Bs and runoff estimates, within uncertainty bounds).Extrapolation of winter mass balance from historical stationrecords to high-elevation glacial environments is lesscertain, and methods for this need to be developed.

In general, the method of estimating summer snow eventsfrom Rogers Pass daily precipitation (with appropriate temp-erature adjustments to the glacier) is favourable because thisprovides a more deterministic treatment of the influence ofinterannual temperature and precipitation variability. It maynot be as helpful for future projections, however, wherestation data are unavailable and climate models are not gener-ally reliable with respect to precipitation frequency (e.g.,

Fig. 10 Modelled glacier runoff in the IRB, 1 May to 14 September, 2009 to2011, partitioned into snow (red), ice (blue), and total (black) runoff.



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

Bader et al., 2008). We recommend the random snow-eventparameterization where the mass balance model is driven byoutput from climate models.Ice thickness and volume also need to be known to simu-

late ice dynamics and glacier evolution. Slope-thickness andvolume-area scaling calculations can be used to estimate icevolume, but these are highly uncertain and not applicable forlocal ice thickness data (Clarke, Berthier, Schoof, & Jarosch,2009; Farinotti, Huss, Bauder, Funk, & Truffer, 2009). Toour knowledge, there are no measurements of glacier icethickness within the CCRB. As glacier area and volume aredepleted, glacier contributions to runoff will decline, whichwill be of particular importance in late summer. It isnecessary to quantify glacier area and volume changes tounderstand the regional impacts of diminishing glacierrunoff. We recommend that ice thickness characterizationbe part of a sustained monitoring program within the IRBor other headwaters catchments of the CCRB. Future workshould extend the mass balance and high-elevationmeteorological observations in the region and aim to refinethe snowmelt and accumulation models at the basinscale. Historical weather data are available in the region tocharacterize glacier runoff over the last several decades,but such an analysis requires a treatment of evolvingglacier geometry.

6 Conclusions

Through combined field and modelling studies, we examinethe meteorological and mass balance regime of IllecillewaetGlacier. Observations are used to develop and validate anempirical melt model to estimate glacier runoff contributionsto Illecillewaet basin, a headwaters catchment of the ColumbiaRiver. Required inputs for our model are a DEM, glacier mask,hourly temperature, and winter mass balance (initial Maysnowpack). Where available, daily humidity and precipitationdata can also be applied in estimation of daily cloud cover(incident solar radiation) and summer snowfall.We find little degradation in model performance for Illecil-

lewaet Glacier when we drive the melt model with nearbyvalley-bottom weather records from Rogers Pass, rather thanusing local AWS temperature and radiation data. This requiresa two-stage adjustment of Rogers Pass temperature data tomake it applicable on the glacier: (i) an elevation correctionand (ii) a diurnal temperature correction, to account fordaytime heating and overnight cold air drainage in thevalley bottom. This was accommodated by applying a sinusoi-dal temperature correction to Rogers Pass temperatures.Potential direct solar radiation is scaled through a clear-skyindex (fraction of transmitted radiation), which is calibratedfrom AWS data for summer 2009. Daily temperature ampli-tude and vapour pressure at Rogers Pass provide a goodproxy for the clear-sky index, and we use this to estimateincoming solar radiation in 2010 and 2011, when AWS dataare not available. The melt model is then applied to Illecille-waet Glacier and the IRB.

Average modelled mass balance from 2009 to 2011 forIllecillewaet Glacier is Bw = 1.46, Bs = −1.70, and Bn =−0.24 m w.e. a−1. This compares reasonably well withaverage observed mass balances of Bw = 1.43, Bs = −1.91,and Bn = −0.48 m w.e. a−1. A composite of our observedand modelled balances gives an average glacier runoff of10.9 ± 2.5 × 106 m3 for the three summers, with 24% of thisderived from glacier ice and firn. The remaining 76% of Illecil-lewaetGlacier runoff comes frommelting of the seasonal snow-pack, including a small contribution from summer snows.Extended to the basin scale, modelled mass balances arelower, specific discharges are higher, and the fraction of mod-elled glacier runoff derived from ice melt is higher, 34% onaverage. In a heavy melt year such as 2009, more than 45%of glacier runoff in the basin is attributed to ice and firn melt.

One of the largest uncertainties in our observations and ourmodel is associated with winter snowpack and its distributionto the basin scale. Our melt model is calibrated for a range ofweather conditions measured throughout the ablation season,improving our confidence in the summer mass balance esti-mates. Nevertheless, additional melt data (i.e., a repeat ofthe intensive observations conducted in summer 2009)would improve calibration and confidence in the melt modelparameters, reducing uncertainties in our mass balance andmelt model estimates.

Based on climate sensitivity analysis, we conclude that a 1°Cwarming on Illecillewaet Glacier requires an approximate 30%increase in winter precipitation, to overcome a net balance per-turbation of −0.58 m w.e. Under an increase in temperature of2°C accompanied by a precipitation increase of 20%, relative toour reference summer (2009), runoff increases by 49% whilenet mass balance declines from −0.77 to −1.60 m w.e. Futureprojections and climate change studies require a dynamic icemodel to assess the impacts of geometric and hypsometricchanges on glacier mass balance and runoff.

Our results provide preliminary estimates of glacier contri-butions to streamflow in the basin, broadly consistent withthe hydrological modelling results of Jost et al. (2012),which assess a neighbouring basin with similar glacierextent. Glacier contributions to Illecillewaet Basin averaged112 ± 12 × 106 m3 from 2009 to 2011, with 66% of thisfrom seasonal snow and 34% from glacier ice and firn. Thisrepresents 10% of the summer Illecillewaet River yield from2009 to 2011. The most significant glacier contributionsoccur in August, when glacier runoff constituted 25% of theIllecillewaet River from 2009 to 2011. Glacial runoffexceeded 32% of Illecillewaet River yield in August 2009,with more than 80% of this derived from glacier ice.

Winter precipitation and summer temperature conditions for2009 to 2011 fall within one standard deviation of the“normal” conditions for the region, based on records atRogers Pass that date to 1966. Hence, these years are represen-tative of the past 46 years. The IRB is a typical headwaterscatchment of the CCRB with respect to its terrain, glaciercover, and climate regime. Our results emphasize the impor-tance of glacier contributions to late-summer streamflow in



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

the region and the need to characterize the sensitivity of thiswater resource to ongoing climate change and glacier retreat.

Acknowledgements

We thank the Natural Sciences and Engineering ResearchCouncil (NSERC) of Canada and Parks Canada for supportof the Illecillewaet Glacier fieldwork. The University ofCalgary and the Canadian Institute for Advanced Researchprovided additional support. Ongoing hydrological and

meteorological data collection by Environment Canada hasbeen essential to this study. The Western Canadian Cryo-spheric Network, funded by the Canadian Foundation forClimate and Atmospheric Sciences, created a comprehensiveglacier inventory of western Canada and sponsored work-shops that enabled networking and collaboration. RogerWheate provided additional assistance. Mt. Revelstoke andGlacier National Parks and the glaciology group at NaturalResources Canada have been instrumental in taking on Illecil-lewaet Glacier as a long-term mass balance monitoring site.

ReferencesAnslow, F. S., & Roddenhuis, D. (2011). Whywas this spring and early summerso cool in British Columbia. PCIC Update. Retrieved from http://pacificclimate.org/sites/default/files/publications/PCIC.UpdateSpecial.12Sep2011.pdf

Arnold, N. S., Willis, I. C., Sharp, M. J., Richards, K. S., & Lawson, W. J.(1996). A distributed surface energy-balance model for a small valleyglacier. I. Development and testing for Haut Glacier d’Arolla, Valais,Switzerland. Journal of Glaciology, 42(140), 77–89.

Bader, D. C., Covey, C., Gutowski, W. J., Held, I. M., Kunkel, K. E., Miller,R. L.,… Zhang, M. H. (2008). Climate models: An assessment of strengthsand limitations. Synthesis and Assessment Product 3.1, U.S. ClimateChange Science Program. Department of Energy, Washington, DC.

Bitz, C. M., & Battisti, D. (1999). Interannual to decadal variability in climateand the glacier mass balance in Washington, western Canada and Alaska.Journal of Climate, 12, 3181–3196.

Bolch, T., Menounos, B., & Wheate, R. (2010). Landsat-based inventory ofglaciers in western Canada, 1985–2005. Remote Sensing of Environment,114, 127–137.

Braithwaite, R. J. (1995). Positive degree-day factors for ablation on theGreenland ice sheet studied by energy-balance modeling. Journal ofGlaciology, 41(137), 153–160.

Braithwaite, R. J., Zhang, Y., & Raper, S. C. B. (2002). Temperature sensi-tivity of the mass balance of mountain glaciers and ice caps as a climatolo-gical characteristic. Zeitschrift fur Gletscherkunde und Glazialgeologie, 38(1), 35–61.

Bristow, K., & Campbell, G. S. (1984). On the relationship between incomingsolar radiation and daily maximum and minimum temperature. Agricultureand Forest Meteorology, 31(2), 159–166.

Brock, B. W., Willis, I. C., Sharp, M. J., & Arnold, N. S. (2000). Modellingseasonal and spatial variations in the surface energy balance of Haut Glacierd’Arolla, Switzerland. Annals of Glaciology, 36, 53–62.

Bürger, G., Schulla, J., & Werner, A. T. (2011). Estimates of future flow,including extremes, of the Columbia River headwaters. Water ResourcesResearch, 47, W10520. doi:10.1029/2010WR009716

Champoux, A., & Ommanney, C. S. L. (1986). Evolution of theIllecillewaet Glacier, Glacier National Park, B.C., using historical data,aerial photography and satellite image analysis. Annals of Glaciology,8, 31–33.

Clarke, G. K. C., Berthier, E., Schoof, C. G., & Jarosch, A. H. (2009). Neuralnetworks applied to estimating subglacial topography and glacier volume.Journal of Climate, 22, 2146–2160.

Cohen, S. J., Miller, K. A., Hamlet, A., & Avis, W. (2000). Climate changeand resource management in the Columbia River Basin. WaterInternational, 25(2), 253–272.

Comeau, L. E. L., Pietroniro, A., & Demuth, M. N. (2009). Glacier contri-bution to the North and South Saskatchewan Rivers. HydrologicalProcesses, 23, 2640–2653.

Dadic, R., Mott, R., Lehning, M., & Berlando, P. (2010). Wind influence onsnow depth distribution and accumulation over glaciers. Journal ofGeophysical Research, 115, F01012. doi:10.1029/2009JF001261

Demuth, M., Pinard, V., Pietroniro, A., Luckman, B., Hopkinson, C., Dornes,P., & Comeau, L. (2008). Recent and past-century variations in the glacierresources of the Canadian Rocky Mountains: Nelson River system. SpecialIssue: Mountain glaciers and climate changes of the last century. TerraGlacialis, 11, 27–52.

Déry, S. J., Stahl, K., Moore, R. D., Whitfield, P. H., Menounos, B., &Burford, J. E. (2009). Detection of runoff timing changes in pluvial, nivaland glacial rivers of western Canada. Water Resources Research, 45,W04426. 1–11.

Environment Canada. (2012a) Water Survey of Canada HYDAT data.Retrieved from http://www.wsc.ec.gc.ca/products

Environment Canada. (2012b) National climate data and information archive.Retrieved from http://www.climate.weatheroffice.gc.ca/ClimateData

Farinotti, D., Huss, M., Bauder, A., Funk, M., & Truffer, M. (2009). A methodto estimate ice volume and ice thickness distribution of alpine glaciers.Journal of Glaciology, 55(191), 422–430.

Farr, T. G., Rosen, A. P., Caro, E., Crippen, R., Duren, R., Hensley, S., …Alsdorf, D. (2007). The Shuttle Radar Topography Mission. Reviews ofGeophysics, 45, RG2004. doi:10.1029/2005RG000183

FCRPS (Federal Columbia River Power System). 2001. The Columbia Riversystem inside story. Retrieved from http://www.bpa.gov/power/pg/columbia_river_inside_story.pdf

Fountain, A. G., & Tangborn, W. V. (1985). The effect of glaciers on stream-flow variations. Water Resources Research, 21(4), 579–586.

Fountain, A. G., & Walder, J. S. (1998). Water flow through temperate gla-ciers. Reviews of Geophysics, 36, 299–328.

Hägeli, P., & McClung, D. M. (2003). Avalanche characteristics of a transi-tional snow climate—Columbia Mountains, British Columbia, Canada.Cold Regions Science and Technology, 37, 255–276.

Hamlet, A. F., & Lettenmaier, D. P. (1999). Effects of climate change onhydrology and water resources in the Columbia River Basin. Journal ofthe American Water Resources Association, 35, 1597–1623.

Hamlet, A. F., Mote, P. W., Clark, M. P., & Lettenmaier, D. P. (2005). Effectsof temperature and precipitation variability on snowpack trends in thewestern United States. Journal of Climate, 18, 4545–4561.

Hirose, J. M. R. (2012). Glacier meltwater contributions and glaciometeoro-logical regime of the Illecillewaet River Basin, a headwaters catchment ofthe Upper Columbia River Basin, British Columbia, Canada. (M.Sc.thesis). University of Calgary, Alberta, Canada.

Hock, R. (1999). A distributed temperature-index ice- and snowmelt modelincluding potential direct solar radiation. Journal of Glaciology, 45(149),101–111.

Hock, R. (2003). Temperature index melt modeling in mountain areas.Journal of Hydrology, 282(1–4), 104–115.

Hopkinson, C., & Young, G. J. (1998). The effect of glacier wastage on theflow of the Bow River at Banff, Alberta. Hydrological Processes, 12,1745–1762.

Huss, M., Farinotti, D., Bauder, A., & Funk, M. (2008). Modelling runofffrom highly glacierized alpine drainage basins in a changing climate.Hydrological Processes, 22, 3888–3902.



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

http://pacificclimate.org/sites/default/files/publications/PCIC.UpdateSpecial.12Sep2011.pdf



http://www.wsc.ec.gc.ca/products

http://www.climate.weatheroffice.gc.ca/ClimateData

http://www.bpa.gov/power/pg/columbia_river_inside_story.pdf

http://www.bpa.gov/power/pg/columbia_river_inside_story.pdf

Jóhannesson, T., Sigurdsson, O., Laumann, T., & Kennett, M. (1995).Degree-day glacier mass-balance modelling with applications to glaciersin Iceland, Norway and Greenland. Journal of Glaciology, 41(138),345–358.

Jost, G., Moore, R. D., Menounos, B., & Wheate, R. (2012). Quantifying thecontribution of glacier runoff to streamflow in the upper Columbia Riverbasin, Canada. Hydrology and Earth System Sciences, 16, 849–860.

Kite, G. W. (1997). Simulating Columbia River flows with data from regional-scale climate models. Water Resources Research, 33(6), 1275–1285.

Klok, E. J., & Oerlemans, J. (2004). Modelled climate sensitivity of the massbalance of Morteratschgletscher and its dependence on albedo parameteri-zation. International Journal of Climatology, 24, 231–245.

Loukas, A., Vasiliades, L., & Dalezios, N. R. (2002). Climatic impacts on therunoff generation processes in British Columbia, Canada. Hydrology ofEarth System Sciences, 6(2), 211–227.

Marshall, S. J., White, E. C., Demuth, M. N., Bolch, T., Wheate, R.,Menounos, B., … Shea, J. M. (2011). Glacier water resources on theeastern slopes of the Canadian Rocky Mountains. Canadian WaterResources Journal, 36(2), 109–133.

Moore, R. D. (1993). Application of a conceptual streamflow model in aglacierized drainage basin. Journal of Hydrology, 150, 151–168.

Moore, R. D. (2006). Stream temperature patterns in British Columbia,Canada, based on routine spot measurements. Canadian Water ResourcesJournal, 31, 41–56.

Moore, R. D., & Demuth, M. N. (2001). Mass balance and streamflow varia-bility at Place Glacier, Canada, in relation to recent climate fluctuations.Hydrological Processes, 15, 3473–3486.

Moore, R. D., Fleming, S. W., Menounos, B., Wheate, R., Fountain, A., Stahl,K., … Jakob, M. (2009). Glacier change in western North America:Implications for hydrology, geomorphic hazards and water quality.Hydrological Processes, 23, 42–61.

Oerlemans, J., & Klok, E. J. (2004). Effect of summer snowfall on glaciermass balance. Annals of Glaciology, 38, 97–100.

Oerlemans, J., & Reichert, B. K. (2000). Relating glacier mass balance tometeorological data by using a seasonal sensitivity characteristic. Journalof Glaciology, 46(152), 1–6.

Oke, T. R. (1987). Boundary layer climates (2nd ed.). London: RoutledgePress.

PCIC (Pacific Climate Impacts Consortium). (2010). Summary of climatechange for Columbia-Shuswap in the 2050s. Retrieved from http://www.plan2adapt.ca/tools/planners?pr=8&ts=8&toy=16

Pellicciotti, F., Brock, B., Strasser, U., Burlando, P., Funk, M., & Corripio, J.(2005). An enhanced temperature-index glacier melt model including theshortwave radiation balance: Development and testing for Haut Glacierd’Arolla, Switzerland. Journal of Glaciology, 51(175), 573–587.

Pepin, N., & Losleben, M. (2002). Climate change in the Colorado RockyMountains: Free air versus surface temperature trends. InternationalJournal of Climatology, 22, 311–329.

Petersen, L., & Pellicciotti, F. (2011). Spatial and temporal variability of airtemperature on a melting glacier: Atmospheric controls, extrapolationmethods and their effect on melt modeling, Juncal Norte Glacier, Chile.Journal of Geophysical Research, 116, D23109. doi:10.1029/2011JD015842

Rango, A., Martinec, J., & Roberts, R. (2008). Relative importance of glaciercontributions to water supply in a changing climate. World ResourceReview, 20, 487–503.

Richardson, A. G., & Reddy, K. R. (2004). Assessment of solar radiationmodels and temporal averaging schemes in predicting radiation and cottonproduction in the southern United States. Climate Research, 27, 85–103.

Shea, J. M., & Moore, R. D. (2010). Prediction of spatially distributedregional-scale fields of air temperature and vapour pressure over mountainglaciers. Journal of Geophysical Research–Atmospheres, 115, D23107.doi:10.1029/2010JD014351

Shea, J. M., Moore, R. D., & Stahl, K. (2009). Derivation of melt factors fromglacier mass-balance records in western Canada. Journal of Glaciology, 55(189), 123–130.

Sidjak, R. W., & Wheate, R. D. (1999). Glacier mapping of the Illecillewaetice field, British Columbia, Canada, using Landsat TM and digital elevationdata. International Journal of Remote Sensing, 20(2), 273–284.

Singh, P., & Kumar, N. (1997). Impact assessment of climate change on thehydrological response of a snow and glacier melt runoff dominatedHimalayan river. Journal of Hydrology, 193, 316–350.

Stahl, K., Moore, R. D., Shea, J. M., Hutchinson, D. G., & Cannon, A. (2008).Coupled modeling of glacier and streamflow response to future climatescenarios. Water Resources Research, 44, W02422. doi:10.1029/2007WR005956

Wagnon, P., Ribstein, P., Kaser, G., & Berton, P. (1999). Energy balance andrunoff seasonality of a Bolivian glacier. Global and Planetary Change, 22,49–58.

Willis, I., Arnold, N., & Brock, B. (2002). Effect of snowpack removal onenergy balance, melt and runoff in a small supraglacial catchment.Hydrological Processes, 16, 2721–2749.



Dow

nloa

ded

by [

Uni

vers

ity o

f V

icto

ria]

at 1

0:12

07

May

201

3

http://www.plan2adapt.ca/tools/planners?pr=8&ts=8&toy=16

http://www.plan2adapt.ca/tools/planners?pr=8&ts=8&toy=16

Glacier Meltwater Contributions and Glaciometeorological...

Documents

Transcript of Glacier Meltwater Contributions and Glaciometeorological...