Spatial and seasonal variability of polygonal tundra water balance: Lena River Delta, northern Siberia (Russia)

Spatial and seasonal variability of polygonal tundra water balance:Lena River Delta, northern Siberia (Russia)

Manuel Helbig & Julia Boike & Moritz Langer &

Peter Schreiber & Benjamin R. K. Runkle &

Lars Kutzbach

Abstract The summer water balance of a typical Siberianpolygonal tundra catchment is investigated in order toidentify the spatial and temporal dynamics of its mainhydrological processes. The results show that, besidesprecipitation and evapotranspiration, lateral flow consid-erably influences the site-specific hydrological conditions.The prominent microtopography of the polygonal tundrastrongly controls lateral flow and storage behaviour of theinvestigated catchment. Intact rims of low-centred poly-gons build hydrological barriers, which release storagewater later in summer than polygons with degraded rimsand troughs above degraded ice wedges. The barrierfunction of rims is strongly controlled by soil thaw, whichopens new subsurface flow paths and increases subsurfacehydrological connectivity. Therefore, soil thaw dynamicsdetermine the magnitude and timing of subsurface outflowand the redistribution of storage within the catchment.Hydraulic conductivities in the elevated polygonal rimssharply decrease with the transition from organic tomineral layers. This interface causes a rapid shallowsubsurface drainage of rainwater towards the depressedpolygon centres and troughs. The re-release of storagewater from the centres through deeper and less conductivelayers helps maintain a high water table in the surfacedrainage network of troughs throughout the summer.

Keywords Water balance . Permafrost . Heterogeneity .Wetlands . Russia

Introduction

The arctic freshwater system has undergone considerablechange in recent decades, and impacts caused by climatechange in high latitudes are diverse and complex (White etal. 2007). Hydrological conditions and fluxes in arcticwatersheds underlain by permafrost control a variety ofenvironmental processes such as soil thaw (e.g. Guan etal. 2010; Jorgenson et al. 2010), vertical and lateraltransport processes of carbon and nutrients (e.g. Limpenset al. 2008; Petrone et al. 2006; Townsend-Small et al.2011; Zona et al. 2011), or plant growth and peataccumulation (Woo and Young 2006). Thus, alteredhydrology is likely to change the overall functioning ofarctic ecosystems. At the same time, hydrological pro-cesses in the Arctic are not adequately understood in orderto predict future modifications of these processes (Woo etal. 2008).

Wetlands are a common feature of permafrost environ-ments in the Arctic. Their characteristics differ from otherarctic landscapes due to their reliable water supplythroughout the summer (Woo and Young 2006). Soilcarbon stored in arctic wetlands contributes a considerableamount to the global soil carbon pool (Schuur et al. 2008),and they favour permafrost aggradation due to theinsulating peat and moss layers (Hinzman et al. 1991;Blok et al. 2011). Polygon mires are typical arcticwetlands and cover ca. 250,000 km2 of the circumarcticregion (Minke et al. 2007). In contrast to their flatmacrorelief, their microtopography is distinctly pro-nounced. However, despite their widespread occurrencein the Arctic, studies addressing specific hydrologicalprocesses of these landscapes related to their pronouncedmicrotopography are still rare (i.e. Boike et al. 2008;Liljedahl et al. 2012). Lateral subsurface flows and theproduction of runoff in watersheds underlain by perma-frost largely depend on the thickness of the active layer(Hinzman et al. 1991). Thus, a thorough understanding ofthe linkages among surface microtopography, soil thaw

Received: 1 May 2012 /Accepted: 8 November 2012Published online: 3 January 2013

* Springer-Verlag Berlin Heidelberg 2012

Published in the theme issue “Hydrogeology of Cold Regions”

M. Helbig ()) : P. Schreiber :B. R. K. Runkle : L. KutzbachInstitute of Soil Science,University of Hamburg,Allende-Platz 2, 20146 Hamburg, Germanye-mail: [email protected].: +49-40-428384041Fax: +49-40-428382024

J. Boike :M. LangerAlfred Wegener Institute for Marine and Polar Research,P.O. Box 60 01 49( 14401 Potsdam, Germany

Hydrogeology Journal (2013) 21: 133–147 DOI 10.1007/s10040-012-0933-4

and hydrological fluxes (Quinton and Carey 2008) isnecessary to fully grasp the hydrological system ofpolygonal tundra.

In contrast to numerous studies on the interactions ofpermafrost and hydrology in Alaska and the CanadianArctic (e.g. Hinzman et al. 1991; Quinton and Marsh1999; Bowling et al. 2003; Woo and Guan 2006; Guan etal. 2010), remote permafrost catchments in Siberia haveexperienced scarce research attention. In order to narrowthis gap, this study focuses on the water balances of keylandscape units of a small polygonal tundra catchment inthe Lena River Delta, northern Siberia. The objectives are(1) to assess the spatial and temporal heterogeneity ofwater balances of key landscape units, (2) to explain thehydrological processes behind the spatial and temporalvariability, and (3) to understand the redistribution ofwater storages via lateral surface and subsurface flowswithin the catchment and its relation to runoff production.This study aims to improve our knowledge of the mainhydrological processes of a typical Siberian tundralandscape, which is a prerequisite for the understanding ofother ecosystem processes such as the carbon cycle or thethermal regime of permafrost.

Study site

The study area is a small catchment of about 0.6 km2

situated on Samoylov Island, which features a totalsurface area of about 5 km2. The island is situated at oneof the main streams of the Lena River Delta in northernSiberia (72°22′ N, 126°30′E) and is characterised bycontinuous permafrost measuring depths of 500–600 m(Grigoriev 1960). The catchment is situated on the higherlate-Holocene river terrace forming the eastern part of theisland (Fig. 1). The western part of Samoylov Islandconsists of a lower modern floodplain that is partlyflooded every year during the spring flood (Kutzbach2006). Low slope gradients (< 0.2 %) toward the modernfloodplain are dominant in the catchment (Boike et al.2008). At the confined outflow to the modern floodplain,the slope is considerably steeper (∼2 %). The catchmentlandscape is characterised by wet tundra typical for thecircumpolar lowland tundra. Water-saturated low-centredice-wedge polygons, typically 50–100 m2 in size, andraised surrounding rims of 0.2–1.0 m height (Fig. 2) shapethe micro-relief (Kutzbach 2006; Langer et al. 2011;Muster et al. 2012). Large parts of the catchment consistof polygons with degraded rims, water-filled troughsabove degraded ice wedges, and thermokarst lakes. Thesurface drainage network of the catchment consistspredominately of connected troughs interspersed withponds and lakes. It is most pronounced in the thermokarstdepression extending from the catchment outflow south-east to the meteorological station (Fig. 1c). Deeppercolation is strongly impeded by the waterlogged ice-rich permafrost.

The climate at the study site is arctic-continental(Kutzbach 2006). A mean annual air temperature

of −13.5 °C and total annual precipitation of323 mm have been measured at the meteorologicalstation in Tiksi, 110 km south-east of the study site,for the period 1961–1990 (ROSHYDROMET 2012).Approximately half of the precipitation falls as snowduring the long winter (Kutzbach 2006). The accu-mulated snow water equivalent is released duringsnow melt typically in the beginning of June.Compared to other arctic sites, the permafrost surfacetemperature is much colder with a mean annual temperatureof −10.1 °C (Boike et al. 2008). The maximum thawdepth of the active layer is reached early in Septemberwith depths ranging between 30 to 50 cm (Kutzbach 2006;Boike et al. 2008).

A distinct microtopographical gradient between wetpolygon centres with organic-rich Typic Historthels andelevated rims with Typic Aquiturbels (Soil Survey Staff2010) featuring lower organic matter contents governs theisland’s vegetation distribution. Total vegetation coverageis high with a moss/lichen layer covering 95 % of thesurface. Vascular plants cover only 30 % and aredominated by the sedge Carex aquatilis. Hydrophyteslike C. aquatilis and the mosses Limprichtia revolvens andMeesia longiseta are abundant in the centres, whereasadditional mesophytes like the dwarf shrub Dryas octo-petala and the mosses Hyclomium splendens and Timmiaaustriaca are frequently found at the rim sites (Kutzbachet al. 2004).

Materials and methods

Experimental setupWater table relative to the vegetation surface and watertemperature were measured by pressure sensors (Mini-Diver, Schlumberger Water Services, Netherlands) every2 min and averaged over 30-min intervals at eight sites inpolygon centres with intact and degraded rims and inwater-filled troughs above degraded ice wedges between22 May and 19 August 2011. In order to preventsedimentation, the water table was measured insideperforated PVC tubes. Total pressure measurements werecorrected for atmospheric pressure (CS100, CampbellScientific, USA) measured at the meteorological stationsituated in the middle of the late-Holocene terrace (Fig. 1).Total catchment runoff (Q) was calculated for the twooutflows to the modern floodplain between 4 July and 18August 2011 using measurements of water level fluctua-tions at two sharp-crested V-notch (α060°) weirs. Thecalculations were based on a well-established stage–discharge relationship (Kulin and Compton 1975). Stagewas measured with a vented pressure transducer(BTEM6100, SensorTechnics, Germany) every 2 minand averaged over 30-min intervals. All pressure measure-ments were corrected for water-temperature effects. Anautomated tipping-bucket rain gauge (Model 52203, R.M.Young, USA) continuously measured precipitation next tothe meteorological station. The precipitation data were

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corrected based on measurements of wind speed and rainintensity (Førland 1996; Rubel and Hantel 1999).

Soil temperatures (Model 109 Temperature Probe,Campbell Scientific, USA) at depths of 2, 5, 10, and15 cm and liquid soil volumetric water content (VWC;CS616, Campbell Scientific, USA) at 10 cm weremeasured in a nearby rim. Surface temperatures are

derived from outgoing longwave-radiation measurements(NR01, Campbell Scientific, USA) based on the Stephan-Boltzmann law assuming a surface emissivity close tounity.

The eddy covariance method was applied to measurethe turbulent land–atmosphere water flux, which isassociated with landscape-scale evapotranspiration (ET).

Fig. 1 a Location of the study site within the Russian Federation (as indicated by the orange rectangle), b location of the study catchmenton the island, and c location of water level measurement sites, the meteorological station, and direct runoff measurement sites on SamoylovIsland. A true-colour aerial picture is shown as background in b and c (data from Muster et al. 2012)

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The eddy covariance system was installed at the meteo-rological station consisting of a sonic anemometer(CSAT3, Campbell Scientific, USA) and an open pathCO2/H2O gas analyser (LI-7500, LI-COR, USA). Mea-surement height was 4.15 m above the average moss layersurface. In addition relative humidity, air temperature(HMP45C, Campbell Scientific, USA), and horizontalwind speed (WindSonic, Gill Instruments, UK) weremeasured at the same site.

The eddy covariance system measured H2O concen-trations and the wind velocity components at 20 Hzand was connected to a CR-3000 data logger (Camp-bell Scientific, USA). The gas analyser was tilted by10° to avoid forming water drops. The analyser wascalibrated for zero offset using pure nitrogen gas (OJSCLinde Gas) and span offset using a dew point generator (LI-610, LI-COR, USA) 2 weeks prior to the measurementperiod and for zero offset once again during the measure-ment period.

ET fluxes were calculated for 30-min intervals usingEdiRe Data Software (version 1.5.0.10, University ofEdinburgh). Two coordinate rotations were applied to thewind vector measurements (McMillen 1988). Transferfunctions were applied to the calculated fluxes to accountfor sensor separation, spectral response of the gas analyser(Moore 1986), and air density effects (Webb et al. 1980;Leuning 2007). ET fluxes during very humid conditionssuch as rain and fog as well as during periods of poorlydeveloped turbulence (Foken and Wichura 1996) werediscarded. Unrealistic spikes were identified and excludedby a moving window filter (i.e. 3-h moving average ±three standard deviations), which led to a total reductionof 21.1 % of the original data set. Small data gaps (< 2consecutive hours) were filled using linear interpolation.For larger gaps, a multi-linear regression model wasapplied, based on measurements of net radiation andvapour pressure deficit (Alavi et al. 2006). The model wasfitted to the quality-controlled ET flux data with a rootmean square error of less than 0.025 mmh−1 (N03,562).

The field-saturated hydraulic conductivities of unfrozentundra soils were estimated using the single-ring falling-

head infiltration method (Nimmo et al. 2009). Themeasurements were performed at different depths (2–23 cm below the moss surface) in the rims of threepolygons (INT2, INT3, DEG1).

Site water-balance calculationsIn order to examine the main processes governinghydrological fluxes, the water balances of the keylandscape units of polygonal tundra (i.e. polygons withdegraded and intact rims, troughs above degraded icewedges) were analysed (McGlynn et al. 2004). Waterbalances for eight sites in the study catchment werecalculated for the period between 22 May 2011 and 19August 2011. The site DEG1 is situated in a polygoncentre surrounded by degraded rims featuring a troughconnecting the polygon centre to the network of troughsabove degraded ice wedges (Fig. 2a). Intact rims surroundINT1, INT2, and INT3, which are also situated in polygoncentres (Fig. 2b and c). The locations named TRO1,TRO2, and TRO3 (Fig. 2a) are representative water-filledtroughs above degraded ice wedges. TRO1 was relocatedto TRO2 in a nearby trough on 4 June 2011 because thebottom of the PVC well tube became unstable due toenhanced thawing in the water-filled trough. The siteOUT1 was installed in the outflow channel to thefloodplain in the beginning of July (Fig. 1).

The water balances for these sites were assessed for30-min intervals as follows:

P � ET� OUT� INð Þ ¼ P � ET� NLF ¼ ΔS ð1Þwhere P (mm) is precipitation, ET (mm) is evapotranspi-ration, NLF (mm) is the net lateral flow, which is thedifference between outflow from (OUT) and inflow to(IN) the site, and ΔS is the change in site water storage(mm). Due to the presence of continuous permafrost,suprapermafrost groundwater infiltration or subpermafrostgroundwater intrusion is impeded and NLF representsonly lateral surface and subsurface flow in the active layer.For water-table fluctuations above the vegetation surface,

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Fig. 2 Surface microtopographies of four study sites: a a polygon with degraded rims and surrounding troughs (DEG1, TRO3), b apolygon with low intact rims (INT1), and c a polygon with high intact rims (INT3)

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ΔS is the observed change in water table ΔWTobs (mm).Specific yield (Sy) is to be considered when the water tabledrops below the surface. Sy is the volumetric fraction ofwater that is drained by gravity from saturated soil. Basedon measurements of VWC of saturated soils and dry soilsby Langer et al. (2011) Sy was estimated to be 0.7.Following Boudreau and Rouse (1995), ΔS is thendetermined as:

ΔS ¼ ΔWTobsSy ð2ÞThe changes of VWC in the drier polygon rims were

not included in the calculations since only the site waterstorages in the centres and the troughs were analysed.

Roulet and Woo (1986a) and Muster et al. (2012)showed that average ET is almost similar for lake andwetland surfaces in arctic lowland catchments under-lain by continuous permafrost. Hence, ET calculationsfrom the eddy covariance tower are assumed to bevalid for all investigated sites that are situated in wetlandscape units; P is similarly treated as representativethroughout the study area. Thus, NLF of the differentsites was calculated based on these measurements asthe residual of the water balance.

Water balances for periods with distinct meteorologicalcharacteristics were calculated separately. The first period(22 May–2 June 2011) represents the post-melt periodwhich is still influenced by the large snow melt inputsduring spring and starts with the onset of topsoil thaw

(Fig. 3). 3–4 June 2011 was excluded from the analysesdue to the relocation of TRO1–TRO2. The early summerperiod (5 June–31 July 2011) is characterised by airtemperatures constantly above 0 °C and intermediateprecipitation amounts. The last period consists of the latesummer period (1 August–19 August 2011), which wasdominated by a heavy rainfall event at the beginning ofAugust followed by two weeks without precipitation.Based on the different landscape units and seasonalperiods, the spatial and temporal variability of water-balance terms during the thaw period were examined.

Error estimatesErrors in the water-balance calculations can arise fromvarious sources including measurement inaccuracies,errors due to wrong model parameterisation, as well asinappropriate assumptions. The aggregated error (i.e., ofthe calculated NLF rates) tends to be a composition ofrandom and potentially systematic errors. Since theprobability density functions of these errors cannot beexplicitly defined, the uncertainty of the NLF calculationscan only be assessed as maximum error bounds. There-fore, linear error propagation is applied to estimate themaximum possible errors in NLF. All uncertainty intervalsindicated in the text and in the figures represent thesemaximum error bounds, which can be considered asconservative.

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Fig. 3 a Air temperature at 2 m above ground level, b precipitation and liquid soil volumetric water content (VWC) at 10-cm depth, and csoil temperatures in a polygon rim close to the meteorological station, measured May–August 2011. Liquid volumetric water content earlyin the study period is low due to frozen soil conditions. The white line in c indicates the 0 °C-isoline. The measurement interval for all datais 30 min. Vertical dashed lines separate individual study periods: post-melt (I), early summer (II, III, IV), and late summer period (V)

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Precipitation measurements by rain gauges are knownto be affected by wind-induced undercatch, wetting losses,trace amount of precipitation, and spatial variability withinthe investigated catchment. Wind-induced undercatchrepresents the biggest error that is reported to be of theorder of about 10 % (Yang et al. 2005). The appliedprecipitation correction accounts for this undercatch(Førland 1996; Rubel and Hantel 1999). Hence, themaximum possible residual error to be ±10 % is assumed,following other precipitation studies in northern regions(Yang et al. 2005).

Evapotranspiration rates can be spatially heterogeneouswithin the footprint of the eddy covariance measurements(Langer et al. 2011; Muster et al. 2012). The maximumpossible error due to this heterogeneity is assumed to beless than 20 % (Muster et al. 2012). In addition touncertainties in the high-frequency measurements of watervapor and wind speed, the accuracy of the eddycovariance method itself is known to be limited. Severalassumptions used for the calculation of turbulent transport(e.g. stationarity and homogeneity) are often violatedunder complex terrain conditions (Inagaki et al. 2006;Foken 2008). The potential errors can be larger than 25 %of the measured heat fluxes (Wilson et al. 2002).However, a thorough quality assessment was appliedwhich also includes tests on the turbulence characteristics(cf. section Experimental setup). Studies using similarquality criteria assume measurement accuracies of about10 % (Mauder et al. 2006). Maximum possible errorbounds for site-specific evapotranspiration rates, thus, areassumed to lie within ±20 % of the water fluxes measuredby the eddy covariance system.

Further errors in the water balance are induced due touncertainties in the storage calculations. In addition tomeasurement uncertainties of the water level sensors, thelargest error sources are due to uncertainties in theestimated specific yield. Water tables at the study sitesnever dropped 15 cm below the vegetation surface duringthe study period. Thus, a maximum possible error rangeof ±10 % for Sy is assumed, which covers a large fractionof highly porous upper moss and peat layers (Andersen2003; Petrone et al. 2008).

Results

Meteorological and soil conditionsAn overview of the seasonal changes of meteorologicalconditions during the study period is given in the following(Fig. 3). The end of May was still characterised by airtemperatures fluctuating around 0 °C. Air temperaturesbetween 0 and 10 °C marked the beginning of the vegetationperiod in June. July was characterised by warm periods withair temperatures up to 25 °C intermitted by cold spells withair temperatures below 10 °C. Late arctic summer airtemperatures in August ranged between 23 °C in thebeginning of August and 5 °C in the middle of August.

Seasonal changes of liquid soil VWC in the unsaturat-ed organic layer of the polygon rims were small and did

not substantially contribute to changes in water storage ofthe polygons. The liquid VWC at 10 cm soil depth in thepolygon rim was below 10 % when frozen. A sharpincrease in VWC indicated thawing at 10 cm around 10June 2011. The rain event on 14 June 2011 contributed tothe highest VWC peak until the end of July 2011 but wascharacterised by a shorter return time to pre-event levelscompared to rain events later in the season. At that time,the thaw depth was just a few centimetres below the VWCmeasurement depth. Mean VWC for the subsequentthawed period was 41 %. A 4 % decrease in soil moisturewas observed from the middle of June to its late-Julyminimum of 40 % just prior to the heavy rain event in thebeginning of August. This rain event caused a sharpincrease in VWC to 46 % but returned to 41 % within2 weeks.

Surface soil thaw began at the end of May 2011coinciding with a short warm spell and air temperaturesabove 10 °C for approximately 5 days. Subsequent coolingimpeded further thawing, and the thaw front remained at10 cm soil depth in the rim. The next phase of thawingstarted on 11 June 2011, and a thaw depth of 15 cm wasreached by 17 June 2011. Warm periods during summer ledto maximum surface temperatures of 25 °C. Maximum soiltemperatures were observed at the beginning of August withtemperatures above 5 °C at 15 cm depth. The thaw depth(depth of the 0 °C-isoline) remained below 15 cm until theend of the measurement period (Fig. 3).

Total precipitation for the study period (22 May–19August 2011) was 108.6 mm. The post-melt period betweenthe end of May 2011 and the middle of June 2011 wascharacterised by low precipitation. The first significant rainevent took place on 14 June 2011 with 10 mmday−1 (Fig. 4).Total precipitation from the beginning of the measurementperiod until the end of June amounted to 30 mm. Frequentrain events accounted for 46 mm precipitation in July.Precipitation in August was dominated by a heavy rainfallevent on 1 and 2 August 2011 (total 39 mm). The periodbetween this event and the end of the study period wasalmost without rain (total 0.1 mm).

Total ET between 22 May and 19 August 2011 was137.9 mm. Highest ET rates around 3.0 mmday–1 wereexperienced early in the summer in the middle of Junewith air temperatures around 10 °C but with daily peaks ofnet radiation of 500 Wm−2 (data not shown). Later in theseason, ET rates were smaller. Only warm days with airtemperatures above 20 °C in July and August showedsimilar ET rates, which peaked at 2.9 mmday−1 on 26 July2011. Extended periods with ET rates below 1.5 mmday−1

characterised the end of May, the end of June, and themiddle of August (Fig. 4).

Catchment runoff (Q) to the modern floodplain wasmeasured between 4 July and 18 August 2011. Rain eventsin July caused only small increases in baseflow, and totalrunoff ranged between 0.5 and 3 Ls−1. However, the heavyrain event at the beginning of August caused a sudden sharpincrease in total runoff that peaked at 14 Ls−1; increasedrunoff rates were observed for the following 2weeks, and pre-event runoff was not reached before the middle of August.

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Field-saturated hydraulic conductivities in the polygonrim ranged between 40 mday−1 for living moss layers and0.03 mday−1 for the deeper mineral layers below 0.1 m. Asharp decline in the hydraulic conductivity is observedwith the transition from organic to mineral layers between0.05 and 0.15 m. Hydraulic conductivities decreased from17 mday−1 in the upper organic layer to 0.2 mday−1 in theupper mineral layer (Fig. 5).

Site water balancesEvapotranspiration exceeded precipitation by 29.3 mm forthe study period. However, the dynamics of water-storagechanges for distinct sites differ from these meteorologicaldynamics due to lateral surface and subsurface flowamong sites.

The post-melt period between 22 May and 2 June 2011was characterised by dry conditions with only 0.5 mm ofP. At the same time, ET largely exceeded P with 16.4 mm.However, high net outflow rates occurred and representedthe largest term of the water balance for this period for alllandscape units. Considerable differences among meandaily NLF rates of the study sites were evident. Netoutflow from the polygon with intact rims (INT1) wassmallest with 2.0±0.3 mmday−1, net outflow from thepolygon with degraded rims (DEG1) amounted to 5.3±0.3 mmday−1, and net outflow from the water-filledtrough above a degraded ice wedge (TRO1) was highestduring the post-melt period with 8.3±0.3 mmday−1. Netoutflow at DEG1 showed the same pattern as INT1 priorto 26 May 2011 but then exhibited an increased outflowfrom the site. High net outflow rates were observed atTRO1 from the beginning of the post-melt period, butwere intermitted by a short period of net inflow at 27 and28 May 2011. Small P, enhanced ET, and a high netoutflow led to an overall storage loss for the post-meltperiod (Fig. 6). Extended surface flooding and a highconnectivity of the network of troughs are visible on thephotograph taken on 1 June 2011 from the meteorologicaltower (Fig. 7a).

In the subsequent early summer period, water tableswere considerably lowered and the extent of surfaceflooding was reduced. This change is also visible in thephotograph taken 1 year later on 23 July 2012 whenhydrological conditions were similar (Fig. 7b). NLFdynamics were markedly different during this period(Fig. 8). Between 5 June and 31 July 2011, a total of68.8 mm P was received. ET exceeded P for that periodby 23.7 mm and amounted to 92.5 mm. Mean daily NLFrates were reduced compared to the post-melt period andranged between a net outflow of 3.2±1.0 mmday−1 atINT2 (17 July–31 July 2011) and a net inflow of 0.9±0.5 mmday−1 at INT2 (5 June–18 June 2011). Net outflowat the trough above a degraded ice wedge (TRO2) washighest for the period 5–18 June 2011 with 2.3±0.5 mmday−1, whereas NLF for all other sites ranged between a

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net outflow of 0.4±0.5 mmday−1 (INT3) and a net inflowof 0.9±0.5 mmday−1 (INT2). Between 18 June and 16July 2011, small NLF rates ranging between 0.0±0.4 mmday−1 (TRO2) and a net inflow of 0.6±0.4 mmday−1

(TRO3) were observed for all sites except for INT1. INT1showed a small net outflow of 0.4±0.5 mmday−1. A

shift of lateral flow dynamics was observed in thefollowing period (17 July–31 August 2011) with en-hanced net outflow from sites with intact polygon rims. Netoutflow from these sites ranged between 3.2±1.0 mmday−1

(INT2) and 2.5±0.5 mmday−1 (INT3). Net outflow rates forTRO2 and TRO3 were smallest with 1.5±0.5 and 1.1±

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Fig. 6 a Cumulative net lateral flow (NLF), evapotranspiration (ET), and precipitation (P) and b mean daily NLF rates, during the post-melt period at three study sites: INT1 represents a polygon with intact rims, DEG1 a polygon with degraded rims, and TRO1 a trough abovea degraded ice wedge. The error bars indicate estimates of maximum error bounds of NLF

Fig. 7 View from the meteorological tower toward the outflow to the floodplain a on 1 June 2011 and b on 23 July 2012. The traverse inthe right side of picture in part b has a width of 15 m

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0.5 mmday−1 respectively. DEG1 showed intermediate netoutflow rates of 1.8±0.5 mmday−1. Rapid net inflows thatrecharged the site storages were observed at all sites shortlyafter rain events. This response to rain events was mostpronounced for INT1, INT2, DEG1, and TRO3. Followingthe inflow peak, a slow release of this increased storage dueto net outflow was observed. A considerably delayedresponse to rain events was observed at TRO2 situated inthe centre of the catchment where lateral flow from elevatedareas converged (Fig. 8). Total catchment runoff (Q) wassmall and averaged 1.6 Ls−1 (data not shown) between4 July and 31 July 2011. Homogenously distributed Pduring the early summer period allows the assumptionthat mean Q was also reasonably representative for therest of the early summer period. Specific runoff for thisperiod equalled 13.1 mm and was 19 % of P.

The late summer period (1–19 August 2011) wasdominated by a heavy rain event accounting for39.2 mm in the beginning of August 2011 andsubsequent high total catchment runoff peaking at14.2 Ls−1. The rest of the study period featured norain while ET added up to 24.7 mm at the end of thelate summer period. Hence, this period represented theonly period where P exceeded ET (Fig. 9). Subsequentto the rain event, all sites showed a rapid increase instorage due to net inflow. Time to peak inflow variedconsiderably among the sites and ranged between13.5 h (INT2) and 64.5 h (OUT1). Also, the amplitudeof peak inflow showed large differences. The highestnet inflow amounted to 62.3±8.8 mm at INT1 and thelowest accounted for 42.5±5.0 mm at OUT1. The netoutflow following the inflow peak was highest at INT3with 87.9±4.3 mm and lowest at OUT1 with 37.9±3.8 mm. NLF reacted considerably differently to therain event among the sites. Polygons with intact rimsshowed the largest reduction in storage water due to

net outflows ranging between 44.7±8.9 mm (INT3)and 18.8±10.0 mm (INT1) for the entirety of the latesummer period. The polygon with degraded rims(DEG1) featured a slightly smaller storage loss dueto net outflow accounting for 11.0±8.9 mm. Incontrast, the troughs above degraded ice wedges andthe outflow site showed net inflows accounting for4.5±8.9 mm (TRO2), 8.5±8.9 mm (TRO3), and 8.4±8.9 mm (OUT1), respectively, at the end of the studyperiod. Subsequent to the rain event, directly measuredQ at the outflow of the study catchment increased from0.8 to 14.2 Ls−1, and specific runoff totalled 16.3 mmfor the period 1–19 August 2011. This specific runoffsuggests that despite the low topographic gradient, aconsiderable amount of P left the catchment as Q duringthis period. Accounting for the loss due to evapotrans-piration overall catchment storage was not increased bythe heavy rain event (Fig. 9).

The site-specific water balances for the whole studyperiod (Table 1) show that high net outflows characterisedall study sites and that they were of the same order ofmagnitude as precipitation and evapotranspiration. NLF atTRO1/2 considerably exceeded the NLF at all other siteswith 167.4±38.5 mm due to the high outflow rates in thepost-melt period; TRO3 instead featured the lowest NLF.Observations of the surface drainage network downstreamof TRO3 indicated that the site was disconnected earlyfrom the network and later received inflow from thesurrounding rims and polygon centres. Consequently thissite showed the lowest NLF with 60.9±38.5 mm. INT1,INT3, and DEG1 were characterised by intermediate NLFduring the study period ranging between 90.3±38.5 and107.9±45.7 mm for DEG1 and INT1, respectively. Thisoutflow occurred mainly during the post-melt period forDEG1, and during the early and late summer period forINT1 and INT3. NLF rates at the time of snow melt are

a

b

c

Fig. 8 a–b Cumulative net lateral flow (NLF), evapotranspiration (ET), and precipitation (P) and c mean daily NLF rates for thesubperiods 5–18 June 2011 (II), 19 June to 16 July 2011 (III), and 17 to 31 July 2011 (IV) during the early summer period at six study sites;for comparison, P and ET are shown both in a and b. INT1, INT2, and INT3 represent polygons with intact rims, DEG1 a polygon withdegraded rims, and TRO2 and TRO3 water-filled troughs above degraded ice wedges. The error bars indicate estimates of maximum errorbounds of NLF

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not included since the measurements started only severalweeks after the main snow melt took place.

Discussion

Earlier studies on precipitation (Boike et al. 2008) andevapotranspiration (Boike et al. 2008; Langer et al. 2011;Muster et al. 2012) at the same study site showed that theclimatic conditions and seasonal patterns of P and ETduring the study period presented here are representativefor this site and do not represent an outlier year. Heavyrain events exceeding 30 mmday−1, as reported in thisstudy, were also stated for other arctic environments inAlaska (McNamara et al. 2008). Hence, such intense rainevents do not seem to be unusual events in the Arctic.Likewise Liljedahl et al. (2011) found similar patterns ofET for a polygonal tundra site in Alaska. The study periodthus can be considered suitable for analyses of typicalprocesses of polygonal tundra governing lateral surfaceand subsurface flows. The spatially explicit measurementsof the dynamics of water balances of the key landscapeunits provide a robust basis for these analyses (McGlynnet al. 2004; Spence 2010).

Vertical and lateral water fluxesET exceeded P only slightly at the end of the study period,but a large depletion of ΔS was observed at various sites.At the same time, baseflow at the catchment outlet wasmaintained during the whole study period. Both processes

can only be explained by the lateral release of storagewater via either surface flow in open water tracks orsubsurface flow through the polygon rims. This storagewater was accumulated prior to snow melt. It mayoriginate from saturated soil moisture conditions duringfreezing in the preceding year and from accumulated snowduring winter and spring (Bowling et al. 2003). Rovanseket al. (1996) and Woo and Guan (2006) found overlandflow following snow melt in spring to be the main driverof recharge of pond water in the Alaskan and Canadiantundra. Similar extensive surface flooding following snowmelt within the study catchment (Fig. 7a) coincided withmaximum catchment storage conditions during the studyperiod (Fig. 10).

High water tables throughout the catchment caused ahigh hydrological connectivity of the surface drainagenetwork (Fig. 7a). Hence, during the post-melt period,high outflow rates originated primarily from trough sites(TRO1) and from hydrologically connected polygonswith degraded rims (DEG1). The temporary net inflow atTRO1 observed between 26 and 27 May 2011 mostlikely originated from a late-lying snow bank at thewestern edge of the study catchment. In contrast, theintact and still frozen rims of INT1 prevented storagewater from being released to the drainage network and ahigher water table was maintained during the post-meltperiod (Fig. 10).

By the middle of June, equilibrium conditions werereached at TRO2, and inflow and outflow were balanced(Fig. 8). Due to rapidly falling water tables in the troughsbetween the middle of May and the middle of June, some

Table 1 Cumulative precipitation (P), evapotranspiration (ET), and site-specific net lateral flow (NLF) for the study period 22 May to 19August 2011. Corresponding maximum error bounds are reported together with all fluxes

P (mm) ET (mm) NLFINT1 (mm) NLFINT3 (mm) NLFDEG1 (mm) NLFTRO1/2 (mm) NLFTRO3 (mm)

108.6±10.9 137.9±27.6 107.9±45.7 84.8±38.5 90.3±38.5 167.4±38.5 60.9±38.5

Fig. 9 a–b Cumulative net lateral flow (NLF) at the study sites, evapotranspiration (ET), precipitation (P), and directly measured specific(Qsp) and c total runoff (Qtot) at the outflow to the floodplain for the late summer period (1–19 August 2011); for comparison, P and ET areboth shown (a–b). TRO2 and TRO3 represent water-filled troughs above degraded ice wedges and OUT1 is situated in the outflow channelto the floodplain. INT1, INT2, and INT3 represent polygons with intact rims and DEG1 represents a polygon with degraded rims

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parts of the surface drainage network became disconnect-ed (Fig. 7b). A decrease in hydrological connectivity thenprevented rapid drainage of the catchment (Bowling et al.2003; Phillips et al. 2011). At the same time, increasing airtemperatures indicated enhanced soil thaw, which poten-tially opens new subsurface flow paths. Thus, subsurfacehydrological connectivity increased during the summer.Late summer hydrological subsurface connectivity of low-centred polygons in Siberia was also reported by Minke etal. (2009) based on topographic surveys and thaw depthmeasurements. At the end of July, enhanced subsurfaceoutflow through the recently thawed soils of the rims wasobserved and led to a more rapid decrease of storage waterin the polygons with intact rims (INT1, INT2, INT3) thanin the troughs (TRO2, TRO3) and in the polygons withdegraded rims (DEG1; Fig. 8). Early in the summer, ice-rich frozen soil in the rims blocked the water movementand helped maintain different water tables in the centresand the surrounding troughs (Fig. 10). This barriergradually thawed and led to a decrease of the polygon’sstorage capacity (Wright et al. 2009). With active layerdepths between 30 and 50 cm, thaw rates in the rims werefaster, compared to the drop of the water table in thecentre. Hence, once the lowest position of the frost table inthe surrounding rim fell below the polygon’s water table,

subsurface outflow to the drainage network occurred. It isimportant to note that subsurface water flow has thepotential to further increase the thaw depth along the flowpath due to lateral heat advection (Wright et al. 2009).Such positive feedback mechanisms on the hydrologicalconnectivity of permafrost catchments are reported by e.g.Young and Abnizova (2011) who observed an increasedsubsurface flow caused by the expansion of flow paths forpond drainage. Ice-wedge cracks receive the outflow fromthe polygons and convey it through the drainage networkto lower areas rather than transmitting water betweenadjacent polygons (Woo and Guan 2006). Also Boike etal. (2008) found surface and subsurface flow to contributesignificantly to the summer water balance of the polygonaltundra in the same study area. They estimated net outflowsof 1.1 mmday−1 at an intact polygon for the period 1June–31 August 1999 and of 1.7 mmday−1 for the period14 July–31 August 2003. These values are comparable tothe daily net outflow rates found in this study.

Also, the distinct surface topography of the polygonsand its intact rims determine their lateral flow dynamics.For instance, INT2 showed enhanced lateral flow alreadyby 16 July 2011, while INT3 with the most pronouncedrims (Fig. 2c) and the highest elevation of all study sitesstarted to drain slowly only by 22 July 2011. As a

Fig. 10 Conceptual model of seasonal water balances of key landscape units of polygonal tundra. Representative data are shown forpolygons with degraded (DEG1) and intact (INT1) rims and for a trough above a degraded ice wedge (TRO1/2). Data are shown for thepost-melt period (22 May–2 June 2011, I), the early summer period (5–18 June 2011, II; 19 June–16 July 2011, III; 17–31 July 2011, IV),and the late summer period (1–19 August 2011, V). Arrows of P, ET, and NLF are scaled according to their magnitude

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response to the rain event in August 2011, INT3 showedthe largest outflow of all study sites (Fig. 9). Despite thehigh hydraulic gradient between the wet centre of INT3and the trough network, the water table in the polygoncentre was characterised by relatively stable conditionswith only small outflow rates prior to the rain event. Onlythe large input of precipitation in August 2011 seemed tohave led to considerable subsurface drainage at the site.Similar drainage events following increased summerrainfalls have also been observed by MacDonald et al.(2012) for larger spatial scales.

The described processes have large implications for theredistribution of storage water within polygonal tundracatchments. With enhanced thaw rates during the arcticsummer, polygons with intact rims lose storage water viasubsurface drainage and move faster toward drier con-ditions, whereas lower parts of the catchment gain waterfrom these areas via subsurface inflow and can sustainhigher water tables. Hence, during the summer, storagewater from ponds situated in polygons with intact rims andfrom thawing soil is slowly released. This storage releasehelps sustain baseflow from the catchment even duringperiods of little precipitation (Bowling et al. 2003) asmeasured at the outflow to the floodplain. Boudreau andRouse (1995) had similar findings for a wetland in theCanadian High Subarctic where drainage water from theuplands preserved saturated conditions of the lower peat-lands. ET exceeded P at the lower peatland, but inflow fromthe uplands could balance these losses. The studied terrainunits, however, were considerably larger (0.46–5.37 km2)than the landscape units in this study that exhibit the largestdifferences at the microtopographical level. This sustainedprovision of baseflow is in contrast to the hydrologicalbehaviour of continuous permafrost wetlands withoutmicrotopographic features such as polygons. There, signif-icant subsurface flow does not occur during summer due tothe missing storage capacities (Roulet and Woo 1986b).

The large rain event in the beginning of August tookplace in a time of the year when the thaw front had alreadypenetrated into deeper soil layers (Fig. 10) and storagecapacities of all landscape units were small. The rain eventproduced a distinct peak of total catchment runoff (Q) thatexceeded the previous baseflow more than ten times. Suchrain-generated floods in late summer can reach snow meltdischarge levels in arctic catchments as stated byMcNamara et al. (2008) for a permafrost-underlaincatchment in Alaska. The storage capacities of mostcatchment parts were exceeded due to the sharp increasesof the water tables after the rain event, which resulted inthe expansion of areas contributing to catchment runoff(Bowling et al. 2003). A strong increase in the hydrolog-ical connectivity then led to a considerable and prolongedrunoff response (Meerveld and McDonnell 2006). Withinthe period 1–19 August 2011, the specific runoff to thefloodplain was 16.3 mm, which is about 40 % of theprecipitation input in the same period. In general, suchhigh runoff ratios during summer indicate a low storagecapacity. Similar rainfall runoff ratios were also found fora low gradient catchment in Alaska (Kane et al. 2008).

The time lags between the peak of the large rain eventand the peaks of inflow increase from the polygons overthe troughs to the outflow channel (Fig. 9). Also, netoutflows were observed in the polygon centres, whereasnet inflows characterised the troughs and the outflowchannel in the late summer period. Both observationsillustrate the convergence of slow subsurface outflowsfrom the polygons in the surface drainage network andeventually at the outlet of the catchment. Hence, thecatchment shows a typical cascading behaviour withinwhich different downstream storage capacities (e.g. poly-gons, troughs, outflow channel) need to be filled beforesignificant runoff occurs at the outlet (Spence and Woo2003).

However, the lateral fluxes at the study sites were notonly characterised by surface and subsurface outflow. Netinflow was also observed at all study sites shortly afterrain events. The unsaturated peat soil layers on top of thepolygon rims showed only small fluctuations of soilvolumetric water content (Fig. 3) and, thus, were of littleimportance for storage-water changes in the catchment.The hydraulic conductivity in the rims was reduced bytwo orders of magnitude at the transition zone of thehighly porous near-surface layers and the less porousmineral layers (Fig. 5). These soil properties promoterapid lateral flow of rainwater in the shallow surfacehorizon above this interface (Chappell et al. 1990;McDonnell et al. 1991; Brown et al. 1999; Quinton andMarsh 1999). Hence, the rainfall inputs on the rims wererapidly transmitted through these unsaturated moss andpeat layers along the topographic gradient to the centresand troughs. A sharp increase of the volumetric watercontent and a rapid return to pre-event conditions in theorganic horizon of the rim (Fig. 3) indicate the presence ofsuch fast responding flow paths (Brown et al. 1999). Earlyin the season, when the thaw front is above this interface(Fig. 10), water flow occurs on top of the frost table.Subsequently, the accumulated storage water in thepolygon centres is slowly drained through the saturatedlower organic or mineral layers with considerably smallerhydraulic conductivities (Quinton and Marsh 1999; Careyand Woo 2001; Quinton et al. 2008) when the thaw depthis below the water table as described in the preceding.This behaviour indicates a two-layer flow system (Careyand Woo 2001) where the unsaturated highly conductiveupper organic layer is characterised by fast flow, whereasslow suprapermafrost groundwater flow occurs in the lessconductive saturated lower organic and mineral layers. Itis important to note that the flows in the different soillayers can have different directions (Fig. 10).

Storage thresholds and hydrological connectivityThis study shows that the pronounced microtopography ofthe surface and of the frost table results in spatiallyheterogeneous water balances and storage capacitieswithin a polygonal tundra catchment. The resultingdifferences of storage thresholds of the key landscapeunits and their surface and subsurface hydrological

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connectivity largely control the lateral hydrological fluxesof polygonal tundra catchments, a situation typical of afill-and-spill runoff system (e.g. Spence and Woo 2003;Meerveld and McDonnell 2006). The importance ofstorage thresholds and hydrological connectivity for theunderstanding of hydrological processes on a range ofdifferent scales were highlighted in recent literature (e.g.Metcalfe and Buttle 2001; Spence and Woo 2003;Meerveld and McDonnell 2006; Wright et al. 2009;Spence 2010). However, the presence of continuouspermafrost adds another controlling variable. The storagethresholds of key landscape units of polygonal tundra andthe dominant subsurface flow paths are not fixed param-eters but instead shift with changing frost tables (Quintonand Carey 2008; Wright et al. 2009) and, hence, reachtheir minimum in late summer. As a consequence, filling-up and release of storage water of different landscape unitsis a result of the dynamic interaction of soil thaw anddrawdown or rise of water table due to precipitation andevapotranspiration.

Conclusion

The water balances of key landscape units within thestudy catchment were found to feature a high spatial andtemporal variability. Their dynamics gave useful informa-tion on the dominant hydrological processes of polygonaltundra catchments:

& Although evapotranspiration exceeds precipitationduring the summer, lateral outflow of water is of thesame order of magnitude. The related storage decreasethroughout the catchment highlights the importance ofthe wintertime snow cover for refilling the waterstorages and balancing the annual water budget.

& Lateral surface and subsurface water fluxes are found tostrongly control the redistribution of storage (snow melt)water during the summer period. These lateral fluxes aresubject to high spatial and temporal variations, which arelargely related to the microtopography and the thawdynamics of the polygonal tundra. In the course of thesummer, the thaw depth increases, which opens newpathways for subsurface water flow and decreases thestorage capacity of the catchment. Due to this relation,catchment runoff is maintained during the whole summerperiod even under conditions where evapotranspirationexceeds precipitation, while runoff responses to rainevents in late summer increase due to increasedsubsurface hydrological connectivity.

& The elevated polygon rims are covered by living mossand organic soil layers, which constitute fast pathwaysfor shallow subsurface drainage of rainwater due totheir high hydraulic conductivities. They conveyrainwater along the topographic gradient toward thedepressed polygon centres and the troughs and cause arapid increase in storage water in the centres after rainevents. The re-release of this storage water through

deeper soil layers with lower hydraulic conductivitiesis considerably slower.

& The concept of fill-and-spill systems is particularlyapplicable to polygonal tundra catchments due to theirabundant depression storages and their pronouncedmicrotopography. However, soil thaw during summerchanges storage capacities and lowers threshold levelsfor spill processes. Lateral subsurface flows within thecatchment are, therefore, a result of the dynamicinteractions of soil thaw rates and water-table changescaused by precipitation and evapotranspiration.

Acknowledgements The authors gratefully acknowledge the finan-cial support of M. Helbig, P. Schreiber, B. R. K. Runkle, and L.Kutzbach through the Cluster of Excellence “CliSAP” (EXC177),University of Hamburg, funded by the German Research Founda-tion (DFG), and the support of J. Boike and M. Langer through agrant (VH-NG 203) awarded to Julia Boike, funded by theHelmholtz Association. The support of the Friedrich EbertFoundation (FES) which supported M. Helbig through a travelstipend is appreciated. The authors also acknowledge the financialsupport by the European Union FP7-ENVIRONMENT projectPAGE21 under contract no. GA282700. Special thanks are due toGünter Stoof, Waldemar Schneider, and Karoline Wischnewski fortheir support during field data collection and to Niko Bornemann forinspiring discussions.

References

Alavi N, Warland JS, Berg AA (2006) Filling gaps in evapotrans-piration measurements for water budget studies: evaluation of aKalman filtering approach. Agr Forest Meteorol 141(1):57–66

Andersen HE (2003) Hydrology, Nutrient processes and vegetationin floodplain wetlands. PhD Thesis, National EnvironmentalResearch Institute, Silkeborg, Denmark

Blok D, Heijmans MMPD, Schaepman-Strub G et al (2011) Thecooling capacity of mosses: controls on water and energy fluxesin a Siberian tundra site. Ecosyst 14(7):1055–1065

Boike J, Wille C, Abnizova A (2008) Climatology and summerenergy and water balance of polygonal tundra in the Lena RiverDelta, Siberia. J Geophys Res 113:G03025. doi:10.1029/2007JG000540

Boudreau L, Rouse W (1995) The role of individual terrain units inthe water balance of wetland tundra. Clim Res 5(1):31–47

Bowling L, Kane DL, Gieck R et al (2003) The role of surfacestorage in a low-gradient arctic watershed. Water Resour Res 39(4):1087. doi:10.1029/2002WR001466

Brown VA, McDonnell JJ, Burns DA et al (1999) The role of eventwater, a rapid shallow flow component, and catchment size insummer stormflow. J Hydrol 217(3):171–190

Carey SK, Woo MK (2001) Slope runoff processes and flowgeneration in a subarctic, subalpine catchment. J Hydrol253:110–129

Chappell NA, Ternan JL, Williams AG et al (1990) Preliminaryanalysis of water and solute movement beneath a coniferoushillslope in Mid-Wales, U.K. J Hydrol 116:201–215

Foken T (2008) The energy balance closure problem: an overview.Ecol Appl 18(6):1351–1367

Foken T, Wichura B (1996) Tools for quality assessment of surface-based flux measurements. Agr Forest Meteorol 78:83–105

Førland EJ (1996) Manual for operational correction of Nordicprecipitation data. Norwegian Meteorological Institute, Oslo,Norway

Grigoriev N (1960) The temperature of permafrost in the Lena deltabasin: deposit conditions and properties of the permafrost inYakutia. Yakutsk 2:97–101

145


http://dx.doi.org/10.1029/2007JG000540

http://dx.doi.org/10.1029/2007JG000540

http://dx.doi.org/10.1029/2002WR001466

Guan XJ, Spence C, Westbrook CJ (2010) Shallow soil moisture–ground thaw interactions and controls, part 2: influences ofwater and energy fluxes. Hydrol Earth Syst Sci 14(7):1387–1400

Hinzman LD, Kane DL, Gieck R et al (1991) Hydrologic andthermal properties of the active layer in the Alaskan Arctic.Cold Regions Sci Tech 19(2):95–110

Inagaki A, Letzel MO, Raasch S et al (2006) Impact of surfaceheterogeneity on energy imbalance: a study using LES. JMeteorol Soc Jpn 84(1):187–198

Jorgenson T, Romanovsky V, Harden J et al (2010) Resilience andvulnerability of permafrost to climate change. Can J Forest Res40(7):1219–1236

Kane DL, Gieck R, Boudreau L (2008) Water balance for a lowgradient watershed in northern Alaska. In: Kane DL, HinkelKM (eds) Proceedings of the Ninth International Conference onPermafrost, University of Alaska, Institute of Northern Engi-neering, Fairbanks, AK, pp 883–888

Kulin G, Compton PR (1975) A guide to methods and standards forthe measurement of water flow. US Dept. of Commerce,National Bureau of Standards, Washington, DC

Kutzbach L (2006) The exchange of energy, water and carbondioxide between wet arctic tundra and the atmosphere at theLena River Delta, Northern Siberia. Alfred Wegener Institutefor Polar and Marine Research, Bremerhaven, Germany

Kutzbach L, Wagner D, Pfeiffer E-M (2004) Effect of microreliefand vegetation on methane emission from wet polygonal tundra,Lena Delta, Northern Siberia. Biogeochem 69(3):341–362

Langer M, Westermann S, Muster S et al (2011) The surface energybalance of a polygonal tundra site in northern Siberia, part 1:spring to fall. Cryosphere 5(1):151–171

Leuning R (2007) The correct form of the Webb, Pearman andLeuning equation for eddy fluxes of trace gases in steady andnon-steady state, horizontally homogeneous flows. Bound-LayMeteorol 123(2):263–267

Liljedahl A, Boudreau L, Harazono Y et al (2011) Nonlinearcontrols on evapotranspiration in arctic coastal wetlands.Biogeosciences 8(11):3375–3389

Liljedahl AK, Hinzman LD, Schulla J (2012) Ice-wedge polygontype controls low-gradient watershed scale hydrology. In:Hinkel KM (ed) Proceedings of the Tenth InternationalConference on Permafrost, vol 1: International contributions.The Northern Publisher, Salehard, Russia, pp 231–236

Limpens J, Berendse F, Blodau C et al (2008) Peatlands and thecarbon cycle: from local processes to global implications asynthesis. Biogeosciences 5:1475–1491

MacDonald LA, Turner KW, Balasubramaniam AM et al (2012)Tracking hydrological responses of a thermokarst lake in theOld Crow Flats (Yukon Territory, Canada) to recent climatevariability using aerial photographs and paleolimnologicalmethods. Hydrol Process 26(1):117–129

Mauder M, Liebethal C, Göckede M et al (2006) Processing andquality control of flux data during LITFASS-2003. Bound-LayMeteorol 121(1):67–88

McDonnell JJ, Owens IF, Stewart MK (1991) A case study ofshallow flow paths in a steep zero-order basin. J AmWater ResourAssoc 27(4):679–685

McGlynn BL, McDonnell JJ, Seibert J et al (2004) Scale effects onheadwater catchment runoff timing, flow sources, and ground-water–streamflow relations. Water Resour Res 40(7):W07504.doi:10.1029/2003WR002494

McMillen RT (1988) An eddy correlation technique with extendedapplicability to non-simple terrain. Bound-Lay Meteorol 43(3):231–245

McNamara JP, Oatley JA, Kane DL et al (2008) Case study of alarge summer flood on the North Slope of Alaska: bedloadtransport. Hydrol Res 39(4):299–308

Meerveld HJT, McDonnell JJ (2006) Threshold relations insubsurface stormflow: 2. the fill and spill hypothesis. WaterResour Res 42(2):W02411. doi:10.1029/2004WR003800

Metcalfe RA, Buttle JM (2001) Soil partitioning and surface storecontrols on spring runoff from a boreal forest peatland basin in

north-central Manitoba, Canada. Hydrol Process 15(12):2305–2324

Minke M, Donner N, Karpov NS et al (2007) Distribution, diversity,development and dynamics of polygon mires: examples fromNortheast Yakutia (Siberia). Peatlands Int 1:36–40

Minke M, Donner N, Karpov NS et al (2009) Patterns in vegetationcomposition, surface height and thaw depth in polygon mires inthe Yakutian Arctic (NE Siberia): a microtopographical character-isation of the active layer. Permafr Periglac Process 20(4):357–368

Moore CJ (1986) Frequency response corrections for eddycorrelation systems. Bound-Lay Meteorol 37(1):17–35

Muster S, Langer M, Heim B et al (2012) Subpixel heterogeneity ofice-wedge polygonal tundra: a multi-scale analysis of land coverand evapotranspiration in the Lena River Delta, Siberia. TellusB 64. doi:10.3402/tellusb.v64i0.17301

Nimmo JR, Schmidt KM, Perkins KS et al (2009) Rapidmeasurement of field-saturated hydraulic conductivity for arealcharacterization. Vadose Zone J 8(1):142–149

Petrone KC, Jones JB, Hinzman LD et al (2006) Seasonal export ofcarbon, nitrogen, and major solutes from Alaskan catchmentswith discontinuous permafrost. J Geophys Res 111:G02020.doi:10.1029/2005JG000055

Petrone RM, Devito KJ, Silins U et al (2008) Transient peatproperties in two pond-peatland complexes in the sub-humidWestern Boreal Plain, Canada. Mires Peat 3:1–13

Phillips RW, Spence C, Pomeroy JW (2011) Connectivity andrunoff dynamics in heterogeneous basins. Hydrol Process 25(19):3061–3075

Quinton W, Carey S (2008) Towards an energy-based runoffgeneration theory for tundra landscapes. Hydrol Process 22(23):4649–4653

Quinton W, Marsh P (1999) A conceptual framework for runoffgeneration in a permafrost environment. Hydrol Process 13(16):2563–2581

Quinton W, Hayashi M, Carey S (2008) Peat hydraulic conductivityin cold regions and its relation to pore size and geometry.Hydrol Process 22(15):2829–2837

ROSHYDROMET (2012) Weather Information for Tiksi. RussianFederal Service for Hydrometeorology and EnvironmentalMonitoring, Moscow. Available at http://www.worldweather.org/107/c01040.htm. Accessed 1 August 2012

Roulet NT, Woo MK (1986a) Wetland and lake evaporation in thelow Arctic. Arct Alp Res 195–200

Roulet NT, Woo MK (1986b) Hydrology of a wetland in thecontinuous permafrost region. J Hydrol 89:73–91

Rovansek R, Hinzman LD, Kane DL (1996) Hydrology of a tundrawetland complex on the Alaskan Arctic coastal plain, U.S.A.Arct Alp Res 28(3):311–317

Rubel F, Hantel M (1999) Correction of daily rain gauge measurementsin the Baltic Sea drainage basin. Nord Hydrol 30(3):191–208

Schuur EA, Bockheim J, Canadell JG et al (2008) Vulnerability ofpermafrost carbon to climate change: implications for the globalcarbon cycle. BioSci 58(8):701–714

Soil Survey Staff (2010) Keys to soil taxonomy, 11th edn. USDA,Natural Resources Conservation Service, Washington, DC

Spence C (2010) A paradigm shift in hydrology: storage thresholdsacross scales influence catchment runoff generation. GeogrCompass 4(7):819–833

Spence C, Woo MK (2003) Hydrology of subarctic Canadianshield: soil-filled valleys. J Hydrol 279:151–166

Townsend-Small A, McClelland J, Max Holmes R et al (2011)Seasonal and hydrologic drivers of dissolved organic matter andnutrients in the upper Kuparuk River, Alaskan Arctic. Bio-geochem 103(1):109–124

Webb EK, Pearman GI, Leuning R (1980) Correction of fluxmeasurements for density effects due to heat and water vapourtransfer. Q J Roy Meteorol Soc 106(447):85–100

White D, Hinzman LD, Alessa L et al (2007) The arctic freshwatersystem: changes and impacts. J Geophys Res 112:G04S54.doi:10.1029/2006JG000353

Wilson K, Goldstein A, Falge E et al (2002) Energy balance closureat FLUXNET sites. Agr Forest Meteorol 113(1–4):223–243

146


http://dx.doi.org/10.1029/2003WR002494

http://dx.doi.org/10.1029/2004WR003800

http://dx.doi.org/10.3402/tellusb.v64i0.17301

http://dx.doi.org/10.1029/2005JG000055

http://www.worldweather.org/107/c01040.htm

http://www.worldweather.org/107/c01040.htm

http://dx.doi.org/10.1029/2006JG000353

Woo MK, Guan XJ (2006) Hydrological connectivity andseasonal storage change of tundra ponds in a polar oasisenvironment, Canadian High Arctic. Permafr Periglac Process 17(4):309–323

Woo MK, Young KL (2006) High arctic wetlands: their occurrence,hydrological characteristics and sustainability. J Hydrol320:432–450

Woo MK, Kane DL, Carey S et al (2008) Progress in permafrosthydrology in the new millennium. Permafr Periglac Process 19(2):237–254

Wright N, Hayashi M, Quinton WL (2009) Spatial and temporalvariations in active layer thawing and their implication on

runoff generation in peat-covered permafrost terrain. WaterResour Res 45:W05414. doi:10.1029/2008WR006880

Yang D, Kane DL, Zhang Z et al (2005) Bias corrections of long-term (1973–2004) daily precipitation data over the northernregions. Geophys Res Lett 32(19):L19501. doi:10.1029/2005GL024057

Young KL, Abnizova A (2011) Hydrologic thresholds of ponds in apolar desert wetland environment, Somerset Island, Nunavut,Canada. Wetl 31(3):535–549

Zona D, Lipson DA, Zulueta RC et al (2011) Microtopographiccontrols on ecosystem functioning in the Arctic Coastal Plain. JGeophys Res 116:G00108. doi:10.1029/2009JG001241

147


http://dx.doi.org/10.1029/2008WR006880

http://dx.doi.org/10.1029/2005GL024057

http://dx.doi.org/10.1029/2005GL024057

http://dx.doi.org/10.1029/2009JG001241

Documents

Spatial and seasonal variability of polygonal tundra water balance: Lena River Delta, northern Siberia (Russia)