Permafrost, Phillips, Springman & Arenson (eds)© 2003 Swets & Zeitlinger, Lisse, ISBN 90 5809 582 7

Spatial and temporal variation in thaw depth in Siberian tundra near Tiksi
K. Watanabe & H. Kiyosawa
Faculty of Bioresources, Mie University, Tsu, JapanK. Fukumura
Department of Environmental Engineering, Utsunomiya University, Utsunomiya, JapanT. Ezaki
Fujita Corporation, Tokyo, Japan

M. Mizoguchi
Department of Biological and Environmental Engineering, The University of Tokyo, Tokyo, Japan

ABSTRACT: Siberian tundra is characterised by permafrost overlaid with an active layer. The spatial and temporalvariation in the thaw depth in the active layer may play an important role in biological and hydrological processes.
In this study, we carried out field investigations of flat tundra and a hillslope in a watershed near Tiksi, Siberia, atvarious scales, from 1997 to 2000. The ground started to thaw in early June and refroze in mid September. The
progress in the ground thaw was proportional to the square root of the thawing index. The maximum thaw, which
was observed at the end of August, ranged from 1.2 to 0.2 m and averaged 0.4 m. The spatial variation was
analysed using a variogram method. The ground thaw had a fractal dimension (1.8) at each scale. While there
was no anisotropy in the thaw depth in the flat area, the thaw depth on the hillslope periodically fluctuated perpendicular to direction of maximum slope.

primary goal of this study was to describe the spatial
and temporal variation of thaw depth in the active
layer of a Siberian tundra watershed. Such information forms an important component of any strategy
attempting to integrate observations into a regional
overview.

1 INTRODUCTION
Siberian tundra is characterised by permafrost overlaid by a thin layer that freezes and thaws annually,
the active layer. Almost all the biological and hydrological processes in the tundra occur on or within
the active layer (Hinzman et al. 1991, 1998). In tundra
regions, the flux of greenhouse gases, such as CO2
and CH4, are related to the thaw depth and moisture
condition of the active layer (Kane et al. 1991,
Vourlitis et al. 1993). The thaw and freeze dynamics
of the active layer influence the hydrology, hydrogeology, and geomorphology of the tundra (Hinzman et al.
1991, Hinzman & Kane 1997, Watanabe et al. 2001).
Monitoring variation in the active layer thaw is necessary for assessing changes in the environment.
The thaw depth in the active layer can vary substantially over short distances and time periods because
heat transfer in soils that are subject to freezing andthawing reflects the interaction of a large number ofhighly localised factors, including vegetation type,snow cover, organic layer thickness, soil thermal
properties, soil moisture, microtopography, and theoperation of nonconductive heat-transfer processes(Washburn 1980, Outcalt et al. 1990). To measurethaw depth with maximum effectiveness, the spatial
representation and optimal interval of measurementsites must be considered. It is important to obtain
quantitative estimates of the variability in the thaw
depth in the active layer. Few examples of such work
are available for the Siberian tundra however. The

2 STUDY AREA
The study area was located in a typical tundra watershed (Walker et al. 1998), situated 5 km southwest ofTiksi, Russia (latitude 71°38N, longitude 128°52E)(Fig. 1). The topography of this watershed consists ofrolling hills, with gently sloping hillslopes and elevations of 200–300 m. Marshy wetlands develop at thebottom of these slopes. The vegetation mainly consists of water-tolerant plants, such as sedges (Carex
sp. and Eriophorum sp.) and mosses (Sphagnum sp.,Aulacomnium sp., Calliergon sp., Dicranum sp., andPolytrichum sp.), accompanied by lichens (Cetraria sp.,
Alectoria sp., and Dryas sp.) and low shrubs (Salix sp.).
The soil is a multi-layered system that consists of
0–0.2 m of live and accumulated organic material on
0.05–0.3 m of partially decomposed organic matter,
which overlies a mineral silt above the bedrock(Watanabe et al. 2000). The hydraulic conductivity ofthe organic soils is 10 to 100 times greater than that of
the silt.
The live-plant layer of moss has a very highconductivity.
1211

The thermal conductivity increases with depth fromthe live-plant layer through the organic soil to the silt
(Watanabe et al. 2000). The hilltops are covered byshale, with some lichens (Umbilicaria sp., Rhizocarpon
sp., Dryas sp., Festuca sp., and Luzula sp.). The permafrost is estimated to be over 500 m thick (Fartyshev
1993). A network of ice-wedge polygons with diameters of about 7 m occur in the tundra. A field of thesepolygons was studded with non-sorted circles (frost
boils) about 0.5 m in diameter (Washburn 1980).
This survey was carried out between 1997 and 2000.
The average air temperature was 13.5°C, with a maximum recorded temperature of 32.6°C and a minimumof 53.6°C. The air temperature remained below 0°C
from mid September to mid May. The average annual
precipitation was 345 mm. Compared to the groundthaw season in 1997, there was less precipitation in1998 and relatively warmer temperatures in 1999 and2000. The prevailing winds were northeasterly insummer and southwesterly in winter (Kodama 1998).
Due to relatively high wind speeds (mean of 5 m/s),
less than 0.1 m of snow accumulated in the wetlands
and it piled into drifts (2–20 m thick) in the valleys
during winter. The drifted snow remained until
August, and supplied water for the wetlands.

3 METHODS

Figure 1. Study area. (10 m contour interval.)

An area of 1000 m 1000 m, consisting of a networkof 121 precisely located permanent stakes, driven into
the permafrost at 100 m horizontal intervals (F100G),
was established in a tundra flat (Hinzman 1997).
Nested (hierarchical) square grids with intervals of 10,
5, and 1 m were fitted inside the southeast end of thearea (F10G, F5G, F1G) (Fig. 1). A meteorological station was located 100 m south of the area. Parts of thearea were covered by a mat of moss forming a
0.03–0.2 m layer of live plants. Likewise, an area of
100 m  100 m was chosen on a hillslope (average
gradient 2°), and nested grids with intervals of 10, 5,
and 1 m were set up in the area (S10G, S5G, S1G).
The thaw depth of the ground was measured monthly
at each grid intersection from June to September using
a steel rod, calibrated in centimetres and pushed vertically into the ground. Since it was difficult to recognise
the ground surface where it was covered by a thickmat of moss, we placed a wooden panel (0.2 m  0.2 m,
weight 500 g) on the plants and set this as the groundsurface. Mackay (1995) discusses some potential
sources of error associated with this methodology.
Soil temperatures were measured at depths of 0.1 and
0.2 m using a thermistor, and the thaw depth waschecked every August. In August, the ground surface
level, ground water level, gradient, soil type, and soil
moisture were also investigated at each intersection.

Additionally, the vegetation cover in each 10 m squaregrid was classified by the dominant species observed(Watanabe et al. 2001).

4 RESULTS AND DISCUSSION
4.1

Temporal variation in thaw depth

4.1.1 Difference by year
Table 1 lists the thaw depth in each grid during the
maximum thaw season between 1997–2000 (i.e. active
layer thickness). The average thaw was 0.40  0.15 m
and the maximum and minimum values were 1.05 m
and 0.15 m, respectively. Compared with 1997, theground thaw was shallower in 1998, as a result of adry summer, and deeper in 1999 and 2000, which were
warmer summers. A similar trend was not seen in the
maximum and minimum values of thaw depth however(Table 1).
Ground thaw is strongly influenced by the propertiesof vegetation and soil (Nelson et al. 1997, 1999, Hinkel
et al. 2000). In this watershed, thaw depth varies withvegetation type, the vegetation cover ratio and microundulations, which induce water runoff (Watanabe et al.
2001). Figures 2a–c map the thaw depth in F10G in
1212

depth was close to 1 m. The thaw depth was locallydeeper at or near water-filled depressions and near
non-sorted circles. It was shallower in moss-covered
areas. The locations of points at which the ground thaw
was deeper were similar in all three years, as were thedepth of thaw, despite the year-to-year spatial variationin the thaw and mean thaw depth.

1997, 1998, and 1999, respectively. The groundthawed to a deeper level in the northwestern part of
the grid than in the southeastern part. At some points
near the northwestern midpoint of the grid, the thaw
Table 1. Active-layer thickness in the observation grid.
year

day

N

Avg
(cm)

max

Std
min (cm)

Cov (%)

10 m  10 m, 1 m interval (F1G)
1997 8/15 625 35.1
48 25
1998 8/17 625 55.4
72 35

4.79 13.65
7.29 13.16

100 m  100 m, 10 m interval (F10G)
1997 8/16 121 56.1 105 27
1998 8/15 121 49.9 100 25
1999 8/19 121 60.7 102 29

15.90 28.34
14.93 29.91
15.69 25.85

1000 m  1000 m, 100 m interval (F100G)
1997 8/22 121 40.6
84 18 13.02
1998 9/12 121 40.2
81 25 10.01
1999 9/18 121 41.6
79 15 11.07
2000 8/26 121 45.2
75 26 10.74

4.1.2 Seasonal change
The soil in the observation area started to thaw in mid
June, reaching a maximum depth in late August to early
September, before refreezing after mid September.
Several previous studies have addressed the correlation
between thaw depth and air temperature records (e.g.
Gray et al. 1988, Jorgenson & Kreig 1988). Figure 2
shows the seasonal change in the average thaw depth
and the standard deviation at F10G and S10G in 1998.
The thawing index is a time-temperature integral,calculated by summing the mean daily temperatures
above 0°C (Harlan & Nixon, 1978). In both observation
grids, the ground thaw progressed as the thawing index
increased, and reached its maximum depth in lateAugust. The average thickness of the active layer was

32.07
24.90
26.61
23.78

N indicates number of samples; Avg, Std and Cov are average,
standard deviation and coefficient of variance.

Figure 2. Maps of thaw depth in the 100 m  100 m observation area on flat tundra, F10G (a–c), and hillslope, S10G (d).
(a) August 16, 1997; (b) August 15, 1998; (c) August 19, 1999; (d) August 20, 1998. The solid lines are the thaw depth contour with a 5 cm interval.
1213

JULY

(
S10G (

40

AUGUST

direction
All
N-S
NE-SW
E-W
NW-SE

80

40
semivariance,

thaw depth, Z (cm)

F10G

mean
艑
std
mean
艑
std

(
(

JUNE

60

20

(b)

0
Contour direction
Slope direction

80

‹
0

0

200
Thawing index, DD (degree day)400
40

Figure 3. Seasonal change in thaw depth in the
100 m  100 m observation area on the flat tundra (F10G)
and hillslope (S10G) in 1998.

(d)
0

20
lag, h (m)Figure 4. Semivariogram for F10G (b) and S10G (d).

53.5 cm in F10G (range 33 to 83 cm) and 32.6 cm in
S10G (range 16 to 60 cm). The standard deviation
increased with increasing thaw depth, indicating thatvariation increased as the ground thawed.
The relationship between thaw depth, Z, and thethawing index, DD, was ZF10G  1.9 DD0.54 (R2  0.99)
for F10G and ZS10G 2.0 DD0.53 8.5 (R2  0.99) for
S10G (shown as solid lines in Fig. 3). In both areas, theground thaw was roughly proportional to the squareroot of the thawing index, indicating that the trend in
the seasonal change in thaw depth in this watershed isprimarily homogeneous. These relationships agreewith the form of the Stefan solution, which has beenused in studies of active layer thickness (e.g. Hinkel &Nicholas 1995, Nelson et al. 1997). The active layeron the hillslope was shallower than that on the tundra
flat, despite similar air temperatures and vegetation.
This was presumably due to differences in slope aspect
and the existence of a snow patch just above the hillslope, which continually supplied flowing cold waterto S10G during the ground-thaw season.
4.2

10

seen in the thaw-depth map. By contrast, no non-sorted
circles were observed in S10G. Numerous water tracks
developed into gullies in the hillslope. In some places,
the active layer in these gullies was deeper than that on
the tundra flat.
The spatial correlation in thaw depth variation was
calculated by semivariogram,   0.5 var{z(s h)  z(s)}, where z is the thaw depth at point s, and his the spatial lag. The spatial variation increases with .
If anisotropy were present,  has a different form
(Mizoguchi et al. 1998, Gomersall & Hinkel 2001).
Figures 4b and 4d show  for F10G and S10G, respectively, associated with each lag distance. In F10G, flattens at a lag of about 10 m (range ⬇10 m), indicatingthat sampling of thaw depth at intervals over 10 m are
independent observations. No difference in  wasobserved in any direction. There appears to be no
anisotropy in the thaw depth in the tundra flat. Likewise, no periodicity of  was detected for the slope
direction in S10G. By contrast,  for the contour direction in S10G had local minima with a periodicity of 7 m(arrows in Fig. 4d). Water tracks meandered through thesurface of ice wedges that formed at an angle aroundthe polygons, and some of the water tracks developed
into gullies. Although the ground thaw is mainly
dependent on the vegetation and the thermal properties
of soil (Nelson et al. 1997, 1999, Hinkel et al. 2000,
Watanabe et al. 2001),  observed in the contour
direction may be attributed to the water tracks. The
drop in periodicity in the direction of the slope can be
explained in terms of movement of the subsurface soil
by solifluction.

Spatial variation in thaw depth

4.2.1 Topography
The depth of thaw differed between the tundra flat andhillslope, although the trend in ground thaw progression
was similar at the two sites (Fig. 3). We analysed thespatial variability in both observation grids (F10G &S10G). Figures 2b and 2d map the thaw depth in
F10G and S10G respectively, in the maximum thaw
season of 1998. S10G was oriented in the direction of
the slope. The average thaw depth was deeper in F10G
than in S10G. In F10G, locally deep thaws wereobserved near non-sorted circles, which consisted ofsilt with a high thermal conductivity. This factor wascompounded by the lack of vegetation on their surface
and a reduced albedo. Dense contour lines are therefore

4.2.2 Scale
The values of thaw depth, such as average and maximum thaw, differed when a different grid interval was1214

show that an interval of 100 m or greater is adequate for
capturing the primary scale of the variability in groundthaw for this watershed. This interval fails however toresolve some of the minor variability related to localised
phenomena. At the scale of hydrological processes
associated with cryogenic topography such as gully erosion and solifluction, sampling at less than 10 m intervals is useful, as shown in Figure 4. Alternatively, toconsider the specific mechanism of ground thaw at
one point, we may need to determine the soils’ thermal
properties, surface conditions, and vegetation cover at
a spatial interval that is at least the same as that used
for the maximum thaw depth (i.e. 1 m or less for thiswatershed) (Watanabe et al. 2001).

3

log

2

22AUG'97
1

F1G
F5G
F10G
F100G

0

1

F 100G
97804
97822
97907
98709
98912
2
log h (m)

99625
99725
99918
00826
00916
3

Figure 5. Variogram for each scale.
JUN

JUL

AUG

SPT

5 CONCLUSION

fractal dimension, Di

2

1.9
F100G

year
1997
1998
1999
2000

1.8
160

Variability in thaw depth occurred at different temporaland spatial scales in a tundra watershed near Tiksi,
Siberia. The ground began to thaw in early June andrefroze in mid September. The progression of groundthaw was proportional to the square root of the thawing
index. The maximum thaw, which was observed at theend of August, ranged from 1.2–0.2 m and averaged
0.4 m. While there was no anisotropy in the varianceof thaw depth in the tundra flat, the thaw depth on thehillslope periodically fluctuated perpendicular to thegradient. The ground thaw had a similar fractal dimension (⬇1.8) that was independent of the samplinginterval. Although temporal and spatial variations inthaw depth are important for understanding biologicaland hydrological interactions, it is difficult to identify
the variation in a large watershed over a short time.
Our results have significant implications for designingeffective strategies for the sampling and constructionof regional estimates of thaw depth and closely related
phenomena.

200

( 1 )
( 10 )
(F5G)
day

240

280

Figure 6. Fractal dimension for each observation area onflat tundra.

selected (Table 1). The difference between the maximum and minimum thaw depth decreased, and detailed
variation in thaw depth was obscured by increasing
the grid interval. Here, we compare the spatial variability for each grid size. Figure 5 shows the relationship between variogram, , and the lag, h, for eachscale (F1G, F5G, F10G, & F100G) in the maximum
thaw season of 1997, and for F100G during the 1997–
2000 thaw seasons. There are no fundamental differences in the variability of thaw depth at each gridscale, which have similar fractal dimensions, Di (4–2
Di   log / log h ⬇ 0.33; Di  1.8) (Burrough1981, Zhang et al. 2001). Figure 6 shows the seasonalchange in the fractal dimension observed in Figure 5.
The fractal dimension decreased with ground thaw,
reached a minimum value during the maximum
ground thaw period, and then increased with groundfreezing, presumably because ground thaw progressed
irregularly during the first stage, becoming smooth as
it progressed. A similar trend was observed in all
observation years. Although the Di value is high, itwould seem worthwhile to use the Di value as a guideto further mapping and observation.
These results suggest the optimal sampling interval
for field observations in this watershed. Figures 5 and 6

ACKNOWLEDGMENT
This work was supported by the Japanese GAME
Siberia Program.
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