Influence of soil moisture content and infiltration on ground temperature and active

Department of Physical Geography
Influence of soil moisture
content and infiltration on
ground temperature and active
layer depth in a river terrace in
Adventdalen, Svalbard
Carina Schuh
Master’s thesis
Physical Geography and Quaternary Geology, 45 Credits
NKA 131
2015
Preface
This Master’s thesis is Carina Schuh’s degree project in Physical Geography and Quaternary
Geology at the Department of Physical Geography, Stockholm University. The Master’s
thesis comprises 45 credits (one and a half term of full-time studies).
Supervisor has been Andrew Frampton at the Department of Physical Geography, Stockholm
University. Examiner has been Steve Lyon at the Department of Physical Geography,
Stockholm University.
The author is responsible for the contents of this thesis.
Stockholm, 1 October 2015
Steffen Holzkämper
Director of studies
Acknowledgements
I would like to express my gratitude to my supervisor Andrew Frampton for his valuable guidance and support throughout my Master thesis. You were right, the learning curve was steep!
I am also very grateful to Romain Pannetier, Ylva Sjöberg and Ethan Coon for their continuous
help and encouragement, especially using the newly developed ATS simulation code. Thanks
Benoît Dessirier and Norris Lam for patiently assisting me with one or the other technical difficulty in Linux and Matlab.
Furthermore, I would like to thank Hanne H. Christiansen and Sarah Strand at the University
Centre in Svalbard (UNIS) for providing me with high-quality field data and additional information which improved my work fundamentally.
Many thanks go to Nicola Colombo, Sandra Fischer, Bettina Matti and Emily Voytek for proofreading and commenting my thesis.
Cover: View into Adventdalen, central Svalbard, with its braided river system of Adventelva at
the end of June 2015. Special thanks to my friend and colleague Åsa Wallin for sharing this
beautiful photo with me.
The permafrost domain still encompasses many scientifically uncharted territories with innumerable hydrologic features yet to be discerned, many processes to be understood and pertinent
new concepts to evolve. The excitement of discovery will continue to entice future investigators.
Ming-ko Woo (2012), Permafrost Hydrology, preface
Abstract
The active layer constitutes an important subsystem of permafrost environments. Thermal and
hydrological processes in the active layer determine local phenomena such as erosion, hydrological and ecosystem changes, and can have implications for the global carbon-climate feedback.
Despite their importance for environmental and climate change, active layer dynamics are still
only poorly understood. The importance of hydrology for active layer processes is generally
well acknowledged on a conceptual level, but the physical interdependencies between soil moisture, subsurface water flows and active layer depth are largely unresolved. This thesis used
state-of-the-art numerical modeling to study the influence of ground surface temperature, soil
moisture content and advective heat flow on near-surface permafrost temperatures and active
layer depths. The investigation was performed for a dry, loess-covered river terrace in central
Adventdalen, Svalbard, and fed by high-resolution hydro-climatic field data for the period
2000-2014. Nine scenarios were considered in order to independently test the influence of
different initial soil moisture contents (6%, 12%, and 19%) and infiltration patterns (no infiltration, constant infiltration, and early summer peak infiltration). Results indicated that the permafrost-hydrological system at the study site is largely influenced by cryosuction processes due to
strong capillarity of the highly unsaturated soil. Zones of increased ice content developed
primarily near the permafrost table, creating a ‘transition zone’ between the lower part of the
active layer and the upper permafrost. Infiltration based on snow melt and summer precipitation
was found to be negligible for the seasonal active layer development. The active layer depth
generally decreased with increasing initial soil moisture content due to a higher consumption of
latent heat. However, cryosuction into the permafrost table and water percolation could potentially counterbalance latent heat effects, at least in systems characterized by higher soil moisture
contents. Both model simulations and field observations showed a clear tendency of increasing
active layer depth during the study period, whereas inter-annual variations in active layer depth
were comparably small. Given the moisture migration into the ‘transition zone’, the model
results further suggested that the site might be capable to buffer thaw and thus obscure increasing ground surface temperatures to a certain degree. This could have implications for the suitability of active layer depth as a proper indicator for climate change.
Keywords: active layer, permafrost hydrology, numerical modeling, cryosuction, transition
zone, Adventdalen, CALM.
Content
1 Introduction ......................................................................................................................................... 1
1.1 Background .................................................................................................................................. 1
1.2 State of research ........................................................................................................................... 2
1.3 Aim of this thesis ......................................................................................................................... 4
2 Regional setting................................................................................................................................... 5
3 Methods .............................................................................................................................................. 9
3.1 Numerical modeling ..................................................................................................................... 9
3.2 Data input and processing .......................................................................................................... 11
3.3 Model set-up .............................................................................................................................. 12
3.3.1 Basic model configuration ................................................................................................... 12
3.3.2 Modeling strategy ................................................................................................................ 12
3.3.3 Scenario analysis................................................................................................................. 14
4 Results ............................................................................................................................................... 17
4.1 Subsurface temperature and active layer depth........................................................................... 17
4.2 Phase saturations ........................................................................................................................ 19
4.3 Soil moisture content in the active layer ..................................................................................... 21
4.4 Darcy flow.................................................................................................................................. 22
5 Discussion ......................................................................................................................................... 24
5.1 Soil moisture and ground ice distribution ................................................................................... 24
5.2 Infiltration, water flow and advective heat transport .................................................................. 26
5.3 Active layer dynamics and permafrost development .................................................................. 29
6 Summary and conclusion .................................................................................................................. 32
Appendix .............................................................................................................................................. IV
References ......................................................................................................................................... VIII
I
Figures
Figure 1:
a) map of the lower Adventdalen in central Spitsbergen including the location of the
UNISCALM site and the meteorological station Svalbard Airport; b) close-up of the river
terrace including the UNISCALM site and adjacent boreholes. ............................................. 5
Figure 2:
UNISCALM study site during summer (07.08.2001) looking northwest (downstream)
towards the Old Auroral Station 2 and Isdammen water reservoir. ........................................ 6
Figure 3:
Mean monthly subsurface temperatures [°C] ('trumpet curve') for the period 2009-2013.. ..... 7
Figure 4:
Mean annual precipitation [mm yr -1] (blue bars) and air temperature [°C] (cyan line)
at Svalbard airport weather station between 2000 and 2014. .................................................. 8
Figure 5:
Schematic representation of modeling steps 1-4. ................................................................. 13
Figure 6:
Schematic representation of infiltration scenarios with a) constant infiltration,
and b) peak infiltration ....................................................................................................... 16
Figure 7:
Modeled daily subsurface temperature [°C] in the upper 2 m of the model domain for
base scenarios a) DRY, b) MED, and c) WET during the study period. ............................... 17
Figure 8:
Modeled daily subsurface temperature [°C] at 1.1 m depth for scenarios a) MED and
b) MED-cinfil (both dashed red) as compared to field data (black) ..................................... 18
Figure 9:
Modeled daily permafrost temperatures [°C] for scenarios DRY (pink), MED (red)
and WET (blue) plotted against observations at borehole ASB-2 (black) ............................. 18
Figure 10: Modeled daily liquid and ice saturation [-] for base scenarios a) DRY, b) MED, and
c) WET during the study period. ......................................................................................... 20
Figure 11: Modeled daily liquid and ice saturation [-] for scenarios including constant infiltration
a) DRY-cinfil, b) MED-cinfil, and c) WET-cinfil during the study period. .......................... 20
Figure 12: Compilation of a) infiltration model input, b) ground surface temperature model input,
and c) soil moisture content as modeled (black) and observed (red) at 10 cm depth
for year 2011 ..................................................................................................................... 21
Figure 13: Darcy flow [m s-1] in vertical direction during the period 05/2010 and 08/2014 for the
scenarios including constant infiltration a) DRY-cinfil, b) MED-cinfil, and c) WET-cinfil. . 22
Figure 14: Darcy flow [m s-1] in horizontal direction during the period 05/2010 and 08/2014 for the
scenarios including const. infiltr. a) DRY-cinfil, b) MED-cinfil, and c) WET-cinfil. ........... 23
Figure 15: Relationship between water saturation and capillary pressure (‘retention curves’) as used
in base scenarios DRY (black), MED (red) and WET (blue) ............................................... 24
Figure 16: Subsurface temperature [°C] during the active layer freeze-back 2011 for base scenarios
a) DRY and b) WET ........................................................................................................... 25
Figure 17: Active layer thaw as observed at the UNISCALM site in spring/summer 2011.................... 27
Figure 18: Active layer depth [cm] as derived from physical probing (grey) (Data: UNIS)
and model scenario WET (white) during the study period. .................................................. 30
Figure 19: Daily ground surface temperature [°C] as recorded at the UNISCALM site between
09/2000 and 08/2014........................................................................................................... 31
II
Tables
Table 1:
Mean monthly and annual temperature [°C] and precipitation [mm] at Svalbard airport
during the study period 2000-2014 ........................................................................................ 8
Table 2:
Available field data used as model input and for model evaluation. ..................................... 11
Table 3:
Physical and thermal subsurface properties used in the model simulations as derived
from literature. .................................................................................................................... 14
Table 4:
Overview of tested scenarios including their denotations. .................................................... 15
Table 5:
Active layer depth [cm] as derived from physical probing (Data: UNIS)
and model scenario WET during the study period. .............................................................. 30
III
1 Introduction
1 Introduction
1.1 Background
Permafrost is present in about one quarter of the Northern Hemisphere’s land area (Zhang et al.,
2000). Given its influence on energy exchange, hydrological processes, carbon budgets and
natural hazards, permafrost has been identified as one of the key components of the global climate system (Riseborough et al., 2008). In the northern circumpolar region, permafrost degradation has already been observed, and in some parts, significant amounts of permafrost are
expected to thaw out this century. The thawing of permafrost will proceed at different rates,
since ground thermal regimes and ground ice content vary considerably among different physiographic settings (Kuhry et al., 2010).
With regard to hydrology, ecology and mass movements, the active layer is an important subsystem of permafrost environments. It determines gas fluxes, groundwater flow regimes, soil
formation and the conditions for plant growth (Boike et al., 1998). The permafrost beneath the
active layer limits percolation and subsurface water storage, allowing wet soils and ponding at
the surface even in dry climates (Vörösmarty et al., 2001). The thermal and hydrological processes in the active layer are key to local or regional phenomena like erosion, hydrological and
ecosystem changes (Weismüller et al., 2011). Furthermore, given the large amount of carbon
stored in permafrost (Tarnocai et al., 2009), active layer dynamics have additional implications
for the global carbon-climate feedback. Research in arctic hydrology has primarily been driven
by the climate change debate. Hydrology has come into focus because changes in the hydrological cycle can indicate ongoing permafrost change (e.g. Lyon et al., 2009; Sjöberg et al., 2013)
and because permafrost change can in turn have a large impact on hydrology. Examples include
permafrost warming, increased active-layer thickness, shorter snow cover periods, and increased
shrub vegetation (Woo et al., 2008). Active layer thickening in particular is expected to alter
groundwater flow rates, flow paths, and discharge into surface water. In this context, growing
concern arises from the associated transport of carbon and nutrients and the shift in biogeochemical composition of surface waters (Walvoord and Striegl, 2007).
In Svalbard, long-term records indicate an increase in mean annual air temperature of 0.23°C
per decade since the beginning of the 20th century (Humlum et al., 2011). There is also evidence
that permafrost temperatures in Svalbard, already highest in the Arctic, have been rising during
this period. Since the turn of the century, a considerable and accelerated permafrost warming
has been detected down to a depth of 60 m (Isaksen et al., 2007). Permafrost degradation usually starts with a deepening of the active layer, followed by the formation of a talik and the subsequent thawing of the remaining permafrost. Therefore, increasing active layer depths might be
regarded as an ‘early warning system’ for permafrost degradation (Westermann et al., 2010).
Active layer development in Svalbard has been observed through the Circumpolar Active Layer
Monitoring (CALM) network. The CALM program, designed to observe the spatial and
temporal variability of the near-surface permafrost, is the world’s primary source of information
about the active layer (Shiklomanov et al., 2008). UNISCALM, the monitoring site in
Adventdalen, was established in summer 2000 and has been probed regularly ever since (Christiansen and Humlum, 2008).
1
Carina Schuh
So far, active layer dynamics in Svalbard have primarily been studied based on the analysis of
monitoring data. Roth and Boike (2001) quantified the soil thermal properties and conductive
heat fluxes for an experimental site near Ny-Ålesund based on subsurface temperature data and
soil moisture measurements. Åkerman (2005) monitored active layer depths over several decades in the Kapp Linné area with regard to periglacial slope processes. Isaksen et al. (2007)
evaluated thermal monitoring data for a 100 m deep borehole in central Adventdalen over a
period of six years. For the period 2000-2007, Christiansen and Humlum (2008) used a combined consideration of thermal monitoring data and active layer depth measurements to derive
information on active layer development at the UNISCALM study site. More recently, two studies went beyond the analysis of monitoring data to explore active layer dynamics at sites close
to Ny-Ålesund. Westermann et al. (2010) used ground penetrating radar (GPR) to identify soil
moisture content and thaw depths. The study by Weismüller et al. (2011) involved the application of a one-dimensional coupled thermo-hydrological model to quantify key processes controlling active layer dynamics.
Despite their importance for environmental and climate change, active layer dynamics are still
only poorly understood. The importance of hydrology for active layer processes is generally
well acknowledged on a conceptual level, but the physical interdependencies between soil moisture, subsurface water flows and active layer behavior are largely unresolved. Here, physicallybased modeling can serve as an excellent tool to test hypotheses, investigate processes and improve the overall system understanding.
1.2 State of research
Advances in permafrost modeling within the last few decades have been substantial. Models of
varying complexity have been developed to investigate the thermal response of permafrost to
(hydro-) climatic conditions (Riseborough et al., 2008; Karra et al., 2014). Permafrost modeling
started out as the modeling of a sole process, thermal conduction, and has increasingly been
improved by adding further physical components and processes. Research on the freeze/thaw
mechanism of arctic soils was boosted during the 1970s and 1980s in light of increased oil and
gas exploitations in Alaska and Canada (Hansson et al., 2004). The necessity to couple thermal
and moisture regimes to account for phase changes in thawing and freezing soils became widely
recognized and incorporated into permafrost models during this time (e.g. Nakano and Brown,
1971; Harlan, 1973; Guymon and Luthin, 1974; Jame and Norum, 1980). Heat transfer through
convection was commonly neglected, first due to the absence of suitable mathematical solutions, and then because it was considered irrelevant for permafrost research (e.g. Nixon, 1975;
Fuchs et al., 1978; Lachenbruch and Marshall, 1986). Up until today, the pure interplay of
thermal conduction and latent heat has been considered an adequate conceptualization to describe permafrost dynamics and active layer processes in a multitude of studies (e.g. Kane et al.,
1991; Hinzman et al., 1998; Shiklomanov and Nelson, 1999; Roth and Boike, 2001; Ling and
Zhang, 2004; Bolton et al., 2008; Zhang et al., 2008; Smith and Riseborough, 2010; Etzelmüller
et al., 2011; Jafarov et al., 2012). Widely used algorithms for the estimation of active layer
depth in these studies are the Stefan and the Kudryavtsev models. They allow for the calculation
of the temperature field and the position of the freezing/thawing front given soil thermal proper2
1 Introduction
ties and latent heat (Riseborough et al., 2008). A less physical but more functional model for
active layer characterization was proposed by Smith and Riseborough (1996). The so-called
TTOP model links air, surface and permafrost temperature through seasonal surface transfer
functions and subsurface thermal properties. It has been utilized and tested against other types
of models in a variety of studies ever since (e.g. Wright et al., 2003; Juliussen and Humlum,
2007; Duchesne et al., 2008; Ednie et al., 2008; Janke et al., 2012; Luo et al., 2014).
The investigation of convection as a means of heat transfer in permafrost resumed about the turn
of the century. The first efforts in modeling coupled heat and mass movements in freezing soil
were mostly generic in nature and have generally been evaluated using laboratory simulations of
freezing soil columns. They usually concentrated on small spatial scales in the range of centimeters and aimed at exploring the physical processes ongoing in permafrost. For instance, Zhao et
al. (1997) investigated the interaction between simultaneous heat transfer, liquid water flow,
and phase change in unsaturated frozen soil while applying infiltration; or Lu et al. (2001) emphasized moisture migration and ice segregation processes occurring along the freezing front.
Increasing process understanding has continuously been readopted and developed further by
subsequent studies, all driven by the wish to represent thermo-hydrological processes as comprehensively as possible (Hansson et al., 2004; Akbari et al., 2009; Thomas et al., 2009; Zhou
and Zhou, 2010; Dall’Amico et al., 2011; Sheshukov and Nieber, 2011; Weismüller et al., 2011).
Major advances in permafrost-hydrological modeling have only been made recently, when fully
coupled two- or three-dimensional models were developed. They cover a range of spatial scales
and time frames to conform to the nature of cold-region hydrology (Karra et al., 2014). The
modeling studies carried out so far addressed either entirely generic settings or problems inspired by a specific regional setting. The MarsFlo code (Painter, 2011) has been applied by
Frampton et al. (2011, 2013) to simulate water flows in a generic permafrost system under seasonal temperature variability and climate change. Grenier et al. (2013) used the Cast3M simulation platform to estimate the impact of permafrost development on groundwater flow patterns in
a generic two-dimensional river plain. McKenzie and Voss (2013) simulated permafrost thaw in
a generically-designed nested groundwater system using a modified version of the SUTRA
groundwater simulator. Karra et al. (2014) tested the PFLOTRAN-ICE code for projecting the
hydrological response of degrading permafrost by reproducing a previously conducted laboratory experiment. The studies involving example applications to specific field sites all considered
fully-saturated flow. McKenzie et al. (2007) and Ge et al. (2011) used SUTRA-ICE to model
groundwater systems as found in North American peat bogs and on the Tibet Plateau, respectively. Rowland et al. (2011) used ARCHY to model a sub-lake talik similar to those observed
at Seward Peninsula, Alaska. FlexPDE has been applied in numerous studies to investigate permafrost degradation and glacially-driven groundwater systems either for generic or specific
regional settings (Bense and Person, 2008; Bense et al., 2009; Bense et al., 2012; Scheidegger
et al., 2012; Scheidegger and Bense, 2014). The Arctic Terrestrial Simulator ATS (Coon et al.,
in review) is a recently developed surface/subsurface code for permafrost-hydrological modeling. Atchley et al. (2015) used field data from Barrow, Alaska, for model calibration, whereas
Sjöberg et al. (in review) investigated groundwater flows through subarctic fens using the ATS
in conjunction with field data from Northern Sweden.
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Carina Schuh
1.3 Aim of this thesis
This thesis built on the latest developments in permafrost-hydrological modeling and made use
of the Arctic Terrestrial Simulator ATS to explore active layer dynamics. In contrast to previous
modeling studies, this thesis considered permafrost hydrology in a dry arctic setting. The investigation was not only inspired by, but based on high-resolution hydro-climatic field information
for the UNISCALM site in Adventdalen, Svalbard. For a 14-years study period (09/200008/2014), the influence of soil moisture content and advective heat flow on active layer depths
and permafrost temperatures was tested. To evaluate different hypotheses regarding the site
conditions and dominating processes, a scenario analysis was performed by altering the assumptions made in the numerical model. Results of the model simulations were compared to ground
temperature and soil moisture records at the study site and discussed in the context of relevant
research previously performed at the study site or in comparable settings.
The thesis aimed at improving the process understanding of active layer dynamics and permafrost temperatures with regard to hydrological influencing factors. In order to do so, it addressed
the following research questions:
In a dry arctic permafrost environment 
What is the effect of soil moisture on ground temperature development and active layer
depth?

How does infiltration and the associated heat flow through moisture movement affect
active layer dynamics?
4
2 Regional setting
2 Regional setting
Adventdalen is one of the largest valleys in Svalbard and located in the central part of the archipelago. During about four months of summer, mostly between June and September, the braided
river system of Adventelva drains the valley and discharges into Adventfjorden close to the
village of Longyearbyen (Fig.1). During the rest of the year, the river is frozen and does not
produce any discharge into the fjord (Bryant, 1982; Killingtveit et al., 2003).
Figure 1: a) map of the lower Adventdalen in central Spitsbergen including the location of the UNISCALM site and the
meteorological station Svalbard Airport; b) close-up of the river terrace including the UNISCALM site and adjacent
boreholes (Data: Norwegian Polar Institute).
Adventdalen is a typical U-shaped valley that dissects a landscape characterized by peaks,
ridges and plateaus. It is mainly covered by unconsolidated glacial, colluvial, alluvial, marine
and aeolian deposits. The tributary streams draining to Adventelva have built up large alluvial
fans on both sides of the valley (Oliva et al., 2014). Moreover, several river terraces have been
described that confine the braided channel system of Adventelva and can extend up to several
meters above river elevation (Bryant, 1982). The UNISCALM site (78°12’ N, 15°45’ E) is located on one of these terraces on the southern bank of Adventelva at an elevation of 10 m a.s.l.
(Fig. 1). The upper 1.3 m of sediment has been described as horizontally layered loess, i.e. siltdominated aeolian sediment (Christiansen and Humlum, 2008). Information from adjacent
5
Carina Schuh
boreholes and a study site about 3 km upstream supports this classification and provides evidence of fine-grained, silt-dominated sediment with interbedded clay and sand down to a depth
of 60 m (Gilbert, 2014; Oliva et al., 2014; Cable et al., in review). From his extensive study on
the sedimentation history of Adventdalen, Gilbert (2014) concluded that the aeolian sedimentation and permafrost aggradation at the UNISCALM site began about 3,000 years ago when the
ground was exposed subaerally. Today, the site is covered by typical arctic tundra vegetation
consisting of mosses and low vascular plants like Salix herbacea and sedges (Fig. 2) (Bryant,
1982; Cable et al., in review).
Figure 2: UNISCALM study site during summer (07.08.2001) looking northwest (downstream) towards the Old
Auroral Station 2 and Isdammen water reservoir; Adventelva is located outside the picture to the right (photo credit:
H. H. Christiansen).
The periglacial environment, which accounts for the glacier-free parts of Svalbard (about 40%),
is characterized by geomorphic permafrost features such as pingos, ice wedges, and sorted
circles (Humlum et al., 2003). Permafrost is continuous in Svalbard, i.e. more than 90% of the
ice-free, terrestrial surface is believed to be underlain by perennially frozen ground. Permafrost
in the high mountains can be up to 500 m thick, whereas in the valley bottoms such as in
Adventdalen permafrost thickness is estimated to be about 100 m (Listøl, 1977; Humlum, 2005).
Information from the 1 km deep CO2 borehole close to the UNISCALM site (Fig. 1b) provides
evidence for a sub-permafrost groundwater table at around 150-250 m depth (Braathen et al.,
2012).
Fig. 3 summarizes the thermal characteristics for the 10 m deep ASB-2 borehole in close proximity to the UNISCALM site (Fig. 1b). Based on recordings between 2009 and 2013, the mean
annual ground surface temperature (MAGST) ranged from -13.1°C in March to +9.8°C in July.
Zero annual amplitude, i.e. the depth where the annual change of ground temperature is < 0.1°C
(Woo, 2012), can be observed at -9.85 m. Here, the mean annual ground temperature (MAGT)
6
2 Regional setting
was -5.5°C, but shows an average increase of 0.05°C yr-1 during the period of records. According to the temperature envelope (‘trumpet curve’), the active layer develops during four months
of summer, i.e. from June to September, and reaches its maximum thickness of about 0.95 m in
August.
Figure 3: Mean monthly subsurface temperatures [°C] ('trumpet curve') for the period 2009-2013; data is obtained
from records at borehole ASB-2 approx. 80 m northwest of the UNISCALM site (Data: Geological Survey of Norway).
Svalbard is categorized as polar tundra according to the Köppen-Geiger climate classification.
Despite its location in the High Arctic, it exhibits a comparatively mild climate which can be
ascribed to the North Atlantic Current. However, these warm air masses compete with northeasterly winds transporting cold air from the Siberian High to the Svalbard region. High temperature fluctuations, especially during winter, are a result of the alternating pressure conditions
in the Northern Hemisphere and a common phenomenon in Svalbard. Here, variations in monthly mean temperature of up to 25°C have been observed during winter (Førland et al., 1997).
Svalbard airport is the nearest meteorological station to the UNISCALM site. Fig. 1 shows its
location at about 8 km northwest of the study site, but closer to the shoreline and at a slightly
higher elevation (28 m a.s.l.) than UNISCALM. Based on records from Svalbard airport, as
summarized in Tab. 1, annual mean air temperature during the study period was -3.6°C and
mean annual precipitation was 195 mm. Comparison to the latest climate normal 1981-2010
shows that annual mean air temperature was noticeably higher during the study period. Precipitation occurred mainly during winter so that about two thirds of annual precipitation (125 mm)
fell as snow. April, May and June were the driest months. Over the course of the study period,
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Carina Schuh
both precipitation and mean air temperature were subject to considerable inter-annual variations, as depicted by Fig. 4. With regard to the snow cover, several studies report snowmelt in
Adventdalen to occur within a couple of weeks only, primarily between May and June (Gerland
et al., 1999; Humlum, 2002; Killingtveit et al., 2003; Moreno and Cañadas, 2013).
Table 1: Mean monthly and annual temperature [°C] and precipitation [mm] at Svalbard airport during the study
period 2000-2014; statistics for the latest climate normal 1981-2010 are included for comparison (Data: Norwegian
Meteorological Institute).
19812010
2000-2014
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
T [°C]
-9.5
-10.0
-12.9
-8.7
-1.8
+3.7
+7.0
+6.2
+2.1
-3.5
-6.7
-8.5
Ø -3.6
Ø -5.1
P [mm]
20
12
15
9
8
7
21
20
22
21
19
22
Σ 195
Σ 187
-1
Figure 4: Mean annual precipitation [mm yr ] (blue bars) and air temperature [°C] (cyan line) at Svalbard airport
weather station between 2000 and 2014 (Data: Norwegian Meteorological Institute).
8
3 Methods
3 Methods
3.1 Numerical modeling
Modeling permafrost hydrology is a challenging endeavor due to the inherent complex interactions between thermal, hydrological, hydrogeological, and mechanical stress effects (Frampton
et al., 2013; Painter et al., 2013). Even a superficial consideration of active layer behavior
reveals a multitude of ongoing processes, several of them interconnected with each other and
highly nonlinear (Weismüller et al., 2011). According to Atchley et al. (2015), soil thermal conductivity alone is highly intricate as it depends on a variety of factors like volumetric water content, mineral composition, porosity, density, and temperature. Furthermore, the simulation of
arctic hydrology can require a strong coupling between surface and subsurface water flows
including the surface-atmosphere interrelation (Woo et al., 2008). Modeling studies might also
need to consider the freeze/thaw cycle of possibly ice rich soil, snow cover dynamics, biogeochemical processes or the evolution of the microtopography due to degrading ground ice in the
subsurface (Garimella et al., 2014).
For the present thesis, the simulation of permafrost hydrology is restricted to subsurface thermal
hydrological processes including thermal conduction, subsurface water flow, advective heat
transport through the movement of water, vapor diffusion and the partitioning between the ice,
liquid, and vapor phase. Models for water movement in freezing porous media usually combine
conservation equations for energy and water mass. The ATS computes the mass and energy
balances for water in a porous media, where water can exist in the liquid, gas, and/or ice phase.
The mass and energy conservation equations are (Karra et al., 2014)
(Eq. 1)
(Eq. 2)
where Qw is a mass source of water [mol m-3 s-1] and Qe is a heat source [J m-3 s-1]; the subscripts l, g, and i denote the liquid, gas, and ice phases respectively; is porosity [-]; sα (α = l, g,
i) is the saturation index of the α-th phase [-]; ηα (α = l, g, i) is the molar density of the α-th
phase [mol m-3];
(α = l, g, i) is the mole fraction of water in the α-th phase [-];
is the
tortuosity of the gas phase [-]; Dg is the diffusion coefficient in the gas phase [m² s-1]; T is temperature [K]; cr is the specific heat of the soil [J kg-1 K-1];
is the density of the soil [kg m-³];
Uα (α = l, g, i) is the molar internal energy of the α-th phase [J mol-1]; Hα (α = l, g, i) is the molar
enthalpy of the α-th phase [J mol-1]; is thermal conductivity [W m-1 K-1];
is the gradient
operator and
is the divergence operator.
The Darcy flow for the liquid phase q [m s-1] is given as
(Eq. 3)
where is the absolute permeability [m²];
is relative permeability [-]; μl is viscosity [Pa∙s];
pl is partial pressure [Pa]; ρl is mass density [kg m-3]; g is acceleration due to gravity [m s-2] and
z is the vertical distance from a reference datum [m]; the subscript l denotes the liquid phase.
9
Carina Schuh
In addition to the conservation equations described above, the simulation of non-isothermal,
multi-phase flow of water requires certain constitutive relations. In the ATS, these additional
sets of equations describe relations for the mole fraction of water vapor, saturations of the various phases, relative permeability, thermal conductivity, and water vapor diffusion (Karra et al.,
2014).
Regarding saturations, the ATS uses the approach by Painter and Karra (2014) to calculate the
partitioning of ice, liquid, and vapor phases. The model addresses two critical constitutive relationships among temperature, liquid pressure and total water content and solves them simultaneously for sl and si (Karra et al., 2014):
(Eq. 4a)
(Eq. 4b)
where
is the retention curve for unfrozen liquid-gas phases;
pressure [Pa];
of ice [kg m-3];
is the liquid-gas capillary
is the ratio of ice-liquid to liquid-air surface tensions [-]; ρi is the mass density
is the heat of fusion of ice at 273.15 K [J kg-1];
[-] and T0 = 273.15
K. The Heaviside function H is used to make Eq. 4b applicable to both frozen and unfrozen
conditions. The first relation (Eq. 4a) is derived assuming that ice can be treated as a solid in
order to relate capillary pressure and phase saturations, so that the remaining pore space is divided into vapor and liquid phases using the retention curve for unfrozen liquid-vapor. The second relation (Eq. 4b) describes liquid saturation as a function of total water content. The first
term in square brackets is the capillary pressure between ice-liquid phases when gas is absent
(saturated conditions), and the second term is the addition to the ice-liquid capillary pressure
when gas is present (unsaturated conditions).
For the retention curve for unfrozen liquid-gas phases
Genuchten, 1980)
,
,
the van Genuchten model (van
if
(Eq. 5a)
if
(Eq. 5b)
is used together with the Mualem model (Mualem, 1976) for the relative permeability of liquid
water:
(Eq. 6)
where
is the residual saturation [-];
is capillary pressure [Pa];
; and α [Pa-1]
and n [-] are parameters (Painter and Karra, 2014).
For a more detailed derivation of the conservation equations and full information on all the constitutive relations considered in the ATS see Painter (2011) and Karra et al. (2014).
10
3 Methods
3.2 Data input and processing
This thesis makes use of high-resolution field site data consisting of ground temperature, precipitation, soil moisture, and active layer depth records (Tab. 2). Except for precipitation, all
datasets were made available by the University Centre in Svalbard (UNIS) and the Geological
Survey of Norway (NGU). High-resolution ground temperature data was available from a highprecision Tinytag logger at the center of the UNISCALM grid and from the ASB-2 borehole
located around 80 m northwest (Fig. 1b). At the UNISCALM site, temperature has been recorded hourly during a period of 14 years at five different depths within the active layer. At borehole
ASB-2 hourly temperature records exist for five and a half years at 10 different depths both
within the active layer and the permafrost. Precipitation data from the Svalbard airport meteorological station was obtained as a complete daily time series from the Norwegian Meteorological
Institute. The soil moisture time series encompasses 3-hourly information on volumetric water
content recorded in close proximity to the ASB-2 borehole. It is available for six depths within
the active layer. Information on active layer depth derived from repeated physical probing during summer has been provided for the UNISCALM monitoring site. The annual active layer
depth has been defined as the maximum active layer depth at the grid center measured each
summer. Except for the information on active layer depth, all other datasets have been converted into daily averages to agree with the model set-up.
Table 2: Available field data used as model input and for model evaluation.
Source
Method
Dataset
Period
UNISCALM logger
(UNIS)
Automatic logger
(Tinytag)
Ground surface temperature (0.0 m)
Subsurface temperature (-0.1, -0.2, -0.5, -1.1 m)
01.09.200031.08.2014
ASB-2 borehole
(NGU)
Automatic logger
(GeoPrecision)
Ground surface temperature (0.0 m)
Subsurface temperature (-0.25, -0.5, -0.75, -1.0, -2.0,
-3.0, -5.0, -7.0, -9.85 m)
17.09.200814.04.2014
Svalbard airport
meteorol. station
(Norw. Met. Inst.)
n/a
Precipitation
01.09.200031.08.2014
ASB-2 logger
(UNIS)
Automatic logger
(DL6)
Soil moisture (-0.1, -0.2, -0.3, -0.4, -0.6, -1.0 m)
20.10.200831.08.2014
UNISCALM grid
(UNIS)
Physical probing
Active layer depth
01.09.200031.08.2014
The subsurface temperature datasets showed minor data gaps (<1% of data) and were corrected
for a few clear outliers in subsurface temperature. Since the time series for ground surface temperature (0 m) was used as top boundary condition for the model domain, two periods of missing data (Aug 31-Sep 26, 2001 and Apr 26-Oct 17, 2004) needed to be amended. In order to
ensure the actual temperature pattern to the greatest possible extent, absent data was replaced
using information from the next closest sensor at 0.1 m depth. The data correction approach was
taken from previous work done by Leander and Buishand (2007) and Terink et al. (2009). They
used a statistical approach to fit downscaled temperature data from a regional climate model to
11
Carina Schuh
local observations in a catchment. Following their work, the missing ground surface temperature data was estimated as
(Eq. 7)
where
is the estimated daily ground surface temperature;
is the available daily
temperature at 0.1 m depth;
and
denote the mean temperature at 0 m and 0.1 m
depth, and σ0m and σ-0.1m denote the standard deviation at 0 m and 0.1 m depth, respectively (all
[°C]). Both statistical characteristics were computed for the respective data gap period and
based on the fully available time series 2001-2013.
Since the UNISCALM temperature logger does not provide information below a depth of 1.1 m,
existing data records from the ASB-2 borehole were used to evaluate the simulated permafrost
temperatures for the second half of the study period.
3.3 Model set-up
3.3.1 Basic model configuration
The model domain was chosen to be 10 m deep because subsurface temperature information
was available to a maximum depth of 9.85 m from the ASB-2 borehole. Also, the almost constant temperature at that depth (zero annual amplitude) could be used as an adequate lowermost
boundary condition. As mentioned earlier, the temperature at -9.85 m was increasing on average
by 0.05°C yr-1 between 2008 and 2014. This tendency is assumed to be a long-term phenomenon and was therefore extrapolated to the year 2000. The temperature input at the bottom of the
model domain was thus a linear function increasing from -6.05°C (09/2000) to -5.4°C
(08/2014).
The model domain was split up into equally spaced cells of 0.1 m height, except for the topmost
and lowermost cells which measure only 0.05 m. This was done to ensure that temperatures
were computed at exactly those depths where observations exist, e.g. 0.1 m, in order to facilitate
an adequate comparison. Since some scenarios involve infiltration (see below) and thus potential lateral water flow, a two-dimensional model configuration was required. Following the
layout of the UNISCALM active layer probing grid, the model domain was established as five
columns at 10 m length each. The first column on the left can be regarded as being the grid center and location of the temperature logger. The evaluation of model results was performed for
this column only.
3.3.2 Modeling strategy
The modeling process included four successive steps for every scenario, as illustrated by Fig. 5.
As a first step, the site was modeled under isothermal, unfrozen conditions, i.e. a constant temperature of +2°C was applied to the entire domain. No external energy flows were considered
either at the surface or the bottom of the column (no flow boundaries). A hydrostatic equilibrium was assumed by assigning a constant pressure boundary condition at the surface and applying a gradient of +9,830 Pa m-1 (specific weight of water) down to the bottom of the column.
12
3 Methods
The groundwater table was assumed to be at a depth of 150 m so that the corresponding pressure at the ground surface was determined to be -1.5 MPa using
(Eq. 8)
where
is ground surface pressure [Pa],
-3
water density [kg m ],
2013).
is the pressure at the water table [Pa],
-2
is gravity [m s ], and
is
is groundwater table depth [m] (Szymkiewicz,
Figure 5: Schematic representation of modeling steps 1-4 including the respective boundary conditions (BC) (not to
scale); grey color denotes a pressure BC, hatched areas a temperature BC, and dotted areas a mass flow BC; the
remaining non-emphasized boundaries are no flow boundaries. The vertical delineation of cells (0.1 m) is not shown.
The second modeling step used temperature and pressure as computed in step 1 as initial conditions. In this step, the model domain was frozen from the bottom by applying a constant negative temperature of -6°C (representing the approximate temperature at the depth of zero annual
amplitude) as bottom boundary condition. All other boundaries were no flow boundaries. The
model was run until a thermal equilibrium was reached.
Modeling step 3 was the preparing spin-up for the final model run. It used temperature and pressure from step 2 as initial conditions. The constant temperature as bottom boundary condition
remained unchanged. In this step, a periodic steady state was achieved by applying a simplified
annual temperature variation to the surface and running the model for 100 years. The spin-up
period necessary to achieve a periodic steady state was determined by quantifying the interannual differences in soil temperature at the end of every year, and the condition that the
13
Carina Schuh
maximum difference over the entire model domain shall not exceed 0.1°C. This is considered a
reasonable threshold with regard to other sources of error and reflects the UNISCALM logger
precision. For those scenarios involving infiltration, a mass flow was applied as top boundary
condition to the first column on the left. To allow lateral subsurface flow, the upper 1 m of the
domain’s right face was changed into a suction face. It was assigned the same value as the initial surface pressure, i.e. -1.5 MPa, to ensure that potential excess water could flow out.
The last modeling step consisted of running a transient model using the UNISCALM daily
ground surface temperature dataset (0 m) as top boundary condition. In addition, the constant
temperature input at the bottom of the domain was replaced by the linear function reflecting the
observed increasing temperature trend at the depth of zero annual amplitude. Where required,
infiltration and suction were applied to the respective faces equivalent to step 3.
3.3.3 Scenario analysis
The UNISCALM site represents an excellent testing ground for hydrological modeling due to
its relative homogeneity in sediment composition. By assuming the entire model domain to be
made up of homogeneous (sandy) silt with the respective physical and thermal properties (Tab.
3), the particular effect of soil water content and infiltration was brought into focus.
Table 3: Physical and thermal subsurface properties used in the model simulations as derived from literature.
Parameter
Porosity
Value
Unit
0.4
-
-14
Permeability
10
Density
2650
Source
e.g. Schwartz and Zhang (2003), Fitts (2013)
e.g. Freeze and Cherry (1979), Kirsch and Yaramanci (2006),
Wesley (2010)
2
m
kg m
-3
e.g. Andersland and Ladanyi (1994), Huang et al. (2012)
-5
2∙10
-6
6∙10
-6
2.5∙10
Pa
Van Genuchten m
0.35
-
UNSODA database (Leij et al., 1996),
in Ghanbarian-Alavijeh et al. (2010)
Van Genuchten Sr
0.0
-
-
Heat capacity
850
J kg K
1.7
Wm K
0.27
Wm K
Van Genuchten alpha
Thermal conductivity
(saturated)
Thermal conductivity
(dry)
UNSODA database (Leij et al., 1996),
in Ghanbarian-Alavijeh et al. (2010)
-1
-1
-1
e.g. Andersland and Ladanyi (1994), Ochsner et al. (2001),
Fitts (2013)
-1
-1
Woo (2012)
-1
-1
Woo (2012)
A total of nine scenarios were considered in order to allow an independent testing of both soil
water content and infiltration regarding their respective relevance for active layer dynamics.
Three base scenarios were created representing different soil water retention properties which
were run either without or with infiltration input (Tab. 4).
14
3 Methods
Table 4: Overview of tested scenarios including their denotations.
Base scenario
6%
15%
-1
2∙10e-5 Pa
12%
30%
-1
6∙10e-6 Pa
19%
47%
-1
2.5∙10e-6 Pa
DRY
MED
WET
Constant infiltration
DRY-cinfil
MED-cinfil
WET-cinfil
Peak infiltration
DRY-pinfil
MED-pinfil
WET-pinfil
Initial soil moisture content
Initial liquid saturation
Van Genuchten alpha
No infiltration
The initial soil water content in the model is a function of the soil water retention curve as computed according to the van Genuchten model, i.e. the relationship between liquid saturation and
capillary pressure (see Eq. 5a). Aside from the hydrostatic pressure in the subsurface as defined
by the location of the groundwater table (see Eq. 8), the van Genuchten model parameters α, m,
and Sr affect the water retention capacity and hence moisture content of a soil. Assuming a
stable groundwater table at 150 m depth, the initial soil water content for the different scenarios
was determined by making adjustments to the van Genuchten parameters (Tab. 3 and 4). For
simplicity, residual saturation was assumed to be zero, and m, controlling the relative permeability of the soil, was kept at a constant value. Consequently, the differences in soil water retention amongst the scenarios were ascribed to the α-parameter alone. For the present base scenarios, α-values of 2∙10-5, 6∙10-6, and 2.5∙10-6 Pa-1 resulted in initial soil water contents of approximately 6%, 12%, and 19%. Given a porosity of 0.4, this corresponds to a liquid saturation of
15%, 30%, and 47%.
The initial soil water contents to be tested in the simulations were inspired by the available soil
moisture dataset (Fig. A20, Appendix). Accordingly, 6% soil moisture represents potentially
very dry conditions in the active layer during winter, 12% can be regarded as the average
liquid saturation in the active layer during summer, and 19% as a potential upper limit of soil
moisture content in the active layer. In addition, irrespective of the targeted soil moisture
content, all three variations of the α-value are within an acceptable range for silt/sand soils
according to the UNSODA unsaturated soil hydraulic database (Leij et al., 1996, in:
Ghanbarian-Alavijeh, 2010).
Beyond the sole effect of soil water content on active layer development, the importance of
infiltration was tested on all base scenarios. In order to isolate the effects of infiltration volume
and infiltration timing, the scenarios distinguish two infiltration patterns (constant and peak)
whereas the amount of infiltration is kept stable. The infiltration volume was quantified based
on the estimation of 1) snow melt, and 2) monthly mean summer precipitation reduced by evapotranspiration. First, the volume of snow melt (snow water equivalent) was primarily derived
from the soil moisture records between 2011 and 2014. Based on the measured peaks in soil
moisture in the upper 10-20 cm of the soil, snow melt corresponds to about 0.5 mm d -1 of infiltration during a period of approximately 14 days. Total infiltration through snow melt was thus
assumed to be 7 mm per summer. Second, monthly mean summer precipitation as taken from
the Svalbard airport meteorological station was reduced by 80% to account for evapotranspira15
Carina Schuh
tion. Evapotranspiration in Svalbard has previously been quantified as ranging around 50% of
annual rainfall (Killingtveit et al., 2003; Hodgkins et al., 2009). However, since there is minor
evapotranspiration during the polar night, the rate during summer is presumably higher due to
the intense light conditions. The fact that Adventdalen is exposed to strong winds (Førland and
Hanssen-Bauer, 2003) further supports this assumption.
Infiltration was applied while the ground surface was unfrozen. Infiltration started in spring
(around mid/end of May) when the ground surface temperature became positive and would not
drop below zero again until the freeze-back in autumn. Infiltration stopped one day before the
ground surface temperature became negative (around mid of September). This way, the length
of the infiltration period varied between 14 and 19 weeks.
Fig. 6 illustrates the different assumptions on infiltration timing. In the constant infiltration
scenario, the total infiltration volume (i.e. snow water equivalent and 20% mean summer precipitation) was distributed equally over the infiltration period. In the scenario involving peak
infiltration, snow melt was assumed to occur during the first two weeks of the infiltration period
only, followed by 20% monthly mean precipitation. Using a stable infiltration volume, this
approach allowed the isolated consideration of the respective infiltration pattern, whereas it
ignored the inter-annual variability in snow water equivalent and precipitation.
Figure 6: Schematic representation of infiltration scenarios with a) constant infiltration, and b) peak infiltration (not
to scale); infiltration is composed of 7 mm snow water equivalent (SWE) and mean monthly precipitation reduced by
80% evapotranspiration; the total infiltration volume per summer remains approximately equal in both cases.
16
4 Results
4 Results
4.1 Subsurface temperature and active layer depth
Model results for the base scenarios DRY, MED, and WET show that the different assumptions
regarding initial soil water content had a considerable impact on the computed subsurface temperatures. As depicted in Fig. 7, the scenario with lowest soil moisture content (6%), DRY,
estimated the active layer depth (here assumed to equal the location of the 0°C-isotherm) to vary
from ca. 1.40 m to 1.90 m. Increasing the initial soil moisture content to 12% in scenario MED
led to a decrease in active layer depth to around 1.10-1.40 m. Another increase in soil moisture
(19%) in scenario WET did not reduce the thaw depth much further, but led to active layer
depths similar to scenario MED. Further tests performed outside this thesis confirmed these
findings. They showed that the highest reductions in active layer depth through increased initial
soil moisture were achieved in very dry systems (2% and 4% initial soil moisture content,
respectively).
Accordingly, when infiltration was added, the scenarios showed different magnitudes in subsurface temperature response. Active layer depths decreased most (by ca. 0.5 m) in the driest scenario DRY, followed by a small decrease in scenario MED (by ca. 0.1 m). In the scenario with
highest initial soil moisture, WET, active layer depths stayed approximately equal (not shown).
The particular infiltration pattern (constant vs. peak) did not yield noticeable differences in subsurface temperatures both in the active layer and the permafrost.
Figure 7: Modeled daily subsurface temperature [°C] in the upper 2 m of the model domain for base scenarios
a) DRY, b) MED, and c) WET during the study period. The black contour line indicates the 0°C-isotherm.
17
Carina Schuh
Compared to the UNISCALM active layer logger data, model results showed that those scenarios that mimicked measured summer temperatures best tended to underestimate winter temperatures, and vice versa (Fig. 8). In the permafrost, base scenarios MED and WET matched observations best during summer, whereas DRY mimicked winter temperatures best. Discrepancies
between the base scenarios decreased however with depth (Fig. 9). Scenarios including infiltration generally overestimated the annual temperature oscillation in the permafrost. Here, winter
temperatures were notably underestimated in particular by those infiltration scenarios based on
a low initial soil moisture content (not shown).
Figure 8: Modeled daily subsurface temperature [°C] at 1.1 m depth for scenarios a) MED and b) MED-cinfil (both
dashed red) as compared to field data (black) during the study period.
Figure 9: Modeled daily permafrost temperatures [°C] for scenarios DRY (pink), MED (red) and WET (blue) plotted
against observations at borehole ASB-2 (black) for the period 09/2008 to 04/2014; shown are the depths of a) 2 m,
b) 3 m, c) 5 m, and d) 7 m.
18
4 Results
4.2 Phase saturations
Regardless of initial soil moisture or infiltration assumptions, all scenarios showed different
degrees of saturation within the model domain. Starting from equally distributed soil moisture
content, the
repeated freeze/thaw cycle applied in the model resulted in a distinct soil moisture redistribution. Fig. 10 depicts saturation as a result of differences in initial soil moisture
content. In scenario DRY, liquid saturation in the thawed active layer corresponded exactly to its
initial value (15%), whereas in scenarios MED and WET, liquid saturation (23% and 30%) was
lower than their initial values (30% and 47%). Liquid saturation was generally highest in summer at the bottom of the respective active layer, whereas ice saturation was highest in winter at
the top of the permafrost table. Furthermore, results showed that lower initial soil moisture contents led to a more defined pattern of moisture accumulation whereas higher initial soil moisture contents resulted in a more diffuse moisture accumulation pattern.
In all scenarios, infiltration reinforced the characteristic saturation pattern by adding to the areas
of moisture accumulation at the bottom of the active layer and the top of the permafrost table
(Fig. 11). In addition, infiltration led to the formation of an ice-rich zone in the upper active
layer. The increase in soil moisture was most pronounced in the driest case, DRY, where infiltration increased total saturation by up to 60%. The particular infiltration pattern (constant vs.
peak) did not have any considerable effect on either degree or distribution of saturation.
19
Carina Schuh
Figure 10: Modeled daily liquid and ice saturation [-] for base scenarios a) DRY, b) MED, and c) WET during the study
period.
Figure 11: Modeled daily liquid and ice saturation [-] for scenarios including constant infiltration a) DRY-cinfil,
b) MED-cinfil, and c) WET-cinfil during the study period.
20
4 Results
4.3 Soil moisture content in the active layer
For comparison with available field data the soil moisture content was derived from modeled
liquid saturation using porosity ( = 0.4) for the upper 1 m of the model domain. Firstly, results
confirmed the findings on modeled saturation as described in section 4.2. As shown in Fig. A21
(Appendix), modeled soil moisture in the active layer generally increased with higher initial soil
moisture content. Adding infiltration resulted in increased soil moisture content in all scenarios,
however most pronounced in the driest scenario DRY. Again, there was no noteworthy difference between the constant and peak infiltration scenarios. The amount of unfrozen water during
winter was equal irrespective of whether infiltration was considered, and mimicked observed
variations over time.
Results for 0.1 m depth showed that the seasonal peak in soil moisture occurred simultaneously
for scenarios with and without infiltration. As shown for year 2011 (Fig. 12), it coincided with
the onset of active layer thaw in spring. Soil moisture increased during the zero curtain period,
stayed high during summer, and decreased sharply with the beginning of the active layer
freeze-back.
Figure 12: Compilation of a) infiltration model input, b) ground surface temperature model input, and c) soil moisture content as modeled (black) and observed (red) at 10 cm depth for the year 2011. Soil moisture is shown for
scenario MED without infiltration (black solid line), with constant infiltration (black dashed line), and with peak
infiltration (black dash-dotted line). A frame is inserted for orientation indicating the duration of the zero curtain (ZC)
effect and the modeled infiltration period.
21
Carina Schuh
4.4 Darcy flow
Results of all model simulations showed a periodic vertical flow of moisture within the active
layer, where water percolates down when thawing and moves up again when freezing (Fig. 13).
The magnitude of Darcy flows describing the vertical moisture movement increased with higher
initial soil moisture content. Amongst the scenarios excluding infiltration, Darcy flows were
found to range over almost three orders of magnitude with WET showing the highest values of
up to 3∙10-9 m s-1. Lateral moisture movement was negligible in the base scenarios. As soon as
infiltration was introduced, Darcy flows in vertical direction increased up to 10 -8 m s-1,
regardless of the particular initial soil moisture content. However, water percolation tended to
be more constant in the wetter systems and reached deeper into the active layer than in drier
systems (Fig. 13). A considerable effect of infiltration pattern (constant vs. peak) on Darcy
flows in vertical direction was not observed.
-1
Figure 13: Darcy flow [m s ] in vertical direction during the period 05/2010 and 08/2014 for the scenarios including
constant infiltration a) DRY-cinfil, b) MED-cinfil, and c) WET-cinfil. Shown are the upper 2 m of the model domain.
Negative values indicate a downward flow, positive values an upward flow (see arrows).
As far as the Darcy flow in horizontal direction is concerned, all scenarios showed a
considerable increase in lateral water movement after the introduction of infiltration. Since a
suction pressure was assigned at the right face of the model domain, lateral water movement
occurred exclusively to the right. The base scenarios responded in different ways to the input of
infiltration. Highest Darcy flows in horizontal direction (up to 12∙10-10 m s-1) were observed in
the drier scenarios DRY and MED, whereas scenario WET showed maximum values of only half
the size (6∙10-10 m s-1). Furthermore, results showed differences in the spatial flow pattern, as
22
4 Results
exemplified for the constant infiltration scenarios in Fig. 14. Hence, in scenario DRY-cinfil,
lateral water movement originated predominantly from the bottom of the active layer. In
scenario MED-cinfil, water flow was most pronounced right beneath the ground surface, and
partly at the bottom of the active layer. In the wettest scenario, WET-cinfil, no distinct pattern
could be observed.
-1
Figure 14: Darcy flow [m s ] in horizontal direction during the period 05/2010 and 08/2014 for the scenarios including constant infiltration a) DRY-cinfil, b) MED-cinfil, and c) WET-cinfil. Shown are the upper 2 m of the model domain.
23
Carina Schuh
5 Discussion
5.1 Soil moisture and ground ice distribution
The water retention parameters selected for the different base scenarios explain both the amount
of liquid water in the active layer and the degree of ice saturation in the frozen ground. In the
thawed active layer, in the absence of external flow, soil moisture is exclusively determined by
the hydrostatic pressure as derived from the location of the groundwater table, and the resulting
capillarity. Since the active layer undergoes a freeze/thaw cycle, soil moisture is furthermore
subject to a redistribution driven by changes in the pressure field. Fig. 15 shows the specific
water retention curves for the three base scenarios and the corresponding liquid saturation in
permanently thawed ground (as after modeling step 1, unfrozen hydrostatic equilibrium).
Through repeated active layer thawing and re-freezing, liquid saturation increases and decreases, thus altering the capillary pressure at the freezing/thawing front. When thawing, capillary
pressure decreases in the pores, such that water can percolate. As soon as the active layer
refreezes, liquid saturation in the ground decreases which causes capillary pressure to increase,
and soil moisture to move towards the freezing front (“cryosuction”). The distribution of liquid
saturation and ground ice is determined by the shape of the particular water retention curve. The
increase in capillary pressure is highest for the dry scenario because of the retention curve’s
high non-linearity at low saturations. This way, even if there is only little water available, water
is sucked into the freezing front. The higher the change in capillary pressure, the more defined
the ice-rich regions and the higher the increase in ice saturation with infiltration.
Figure 15: Relationship between water saturation and capillary pressure (‘retention curves’) as used in base scenarios DRY (black), MED (red) and WET (blue). Red dots indicate the respective initial liquid saturation as after modeling
step 1.
Active layer re-freezing in the model occurs both from the ground surface and the permafrost
table, so that water moves both up and down, creating a dry middle active layer (Fig. 16). Twosided freezing is most visible in the scenarios with higher soil moisture content. As exemplified
for the year 2011, active layer re-freezing in the wetter scenario WET (here: 19% soil moisture)
occurs in about equal parts from the ground surface and the permafrost table, whereas in scenario DRY (here: 6% soil moisture), the re-freezing is dominated by the downward moving freezing
24
5 Discussion
front. Furthermore, the example shows that, even if the onset of thaw coincides in both scenarios (15.09.2011), it takes three days longer for the active layer to re-freeze under dry conditions.
Both the imbalance in freezing direction and the delay in complete active layer re-freezing are
directly related to the prevailing soil moisture content. Hence, when refreezing, the dry scenario
impedes an efficient heat release from the active layer up and out of the ground due to the high
gas saturation. Air-filled pores conduct heat more than 20 times less than water-filled pores
(Woo, 2012), thus making the cooling of highly unsaturated ground more difficult. With regard
to latent heat effects, the higher thermal conductivity in scenario WET seems to outweigh the
comparably higher heat production through the phase change from liquid water to ice.
Figure 16: Subsurface temperature [°C] during the active layer freeze-back 2011 for base scenarios a) DRY and b)
WET. Shown are the upper 2 m of the model domain. The black contour line indicates the 0°C-isotherm. The dashed
lines mark the depth of maximum thaw at the onset of re-freezing (15.09.2011) and the day where freeze-back is
completed (08.10 and 05.10., respectively). Black arrows indicate the movement of the freezing fronts, and blue
arrows illustrate the corresponding movement of water through cryosuction.
Field evidence for two-sided freezing is usually provided by the existence of segregated ice, i.e.
ground ice which grows due to the migration of pore water along a certain soil water gradient
(French, 2007). An augmented amount of ice lenses at the top of the permafrost is usually interpreted as ice segregation through upward freezing from the permafrost table (Mackay, 1972;
Cheng, 1983), whereas ice lenses in the upper active layer can be found where downward freezing from the ground surface occurs (French, 2007). At the UNISCALM site, lenticular
cryostructures at the top of the permafrost have been described by Gilbert (2014) and Cable et
al. (in review). Independent field work performed with UNIS in March 2015 provided further
evidence for both downward and upward freezing. Here, sediment core retrieval on a river terrace opposite of the UNISCALM site showed increased ice lenses in the upper active layer and
at the top of the permafrost, whereas the middle active layer was comparably dry. Boike et al.
(1998) identified two-sided freezing at a comparable study site in Siberia using frost probing
and water content information.
Upward freezing and the accumulation of ice at the top of the permafrost is often related to sediment accretion processes, the accumulation of organic material or climate change (Mackay,
1972). Moreover, Cheng (1983) suggested cryosuction and moisture migration into the permafrost table as an alternative explanation. Model scenarios MED and WET provide evidence to
support this hypothesis. Soil moisture in the thawed active layer was lower than its respective
25
Carina Schuh
initial value before the application of a freeze/thaw cycle. Given that the system is otherwise
closed, soil moisture must have been incorporated from the active layer into the permafrost.
Shur et al. (2005) described this zone of high ice content in the uppermost permafrost as the
transition zone. In contrast to the active layer, the transition zone undergoes the freeze/thaw
cycle at lower frequencies. It accumulates ice through ice segregation processes and melt water
percolation with subsequent refreezing, and thus changes properties over time. Because of latent
heat effects, the transition zone can buffer thaw and increase the thermal stability in the deeper
permafrost (Shur et al., 2005).
Soil moisture and ground ice distribution are key to subsurface temperature dynamics because
thermal conductivities of air, water, and ice differ considerably (~ 0.025, 0.57, 2.2 W m -1 K-1;
respectively; Woo, 2012). The simulation of subsurface temperatures showed that doubling the
initial soil moisture from 6% to 12% decreased active layer depths. Here, latent heat consumption increased because of the higher amount of ground ice to be melted during thaw, resulting in
less efficient heat propagation into the ground. When initial soil moisture was increased further
to 19%, no more decrease in active layer depth was observed. This is related to the soil moisture
redistribution pattern described above. Since in scenarios MED and WET, water was incorporated into the permafrost, initial differences in soil moisture content in the active layer were
leveled out. WET counterbalanced the initially high soil water content of 19% by a comparatively higher cryosuction through enhanced two-sided freezing. The eventual active layer soil moisture content in scenarios MED and WET (~9% and ~12%) did not notably affect the simulated
active layer depths.
For the permafrost temperatures down to 7 m depth, model results indicated that the wetter scenarios MED and WET simulate observed temperature variations best, so that a total saturation of
about
20-50% in the permafrost seems to be a fair assumption. However, regions of
increased ice content in the permafrost have been modeled near the permafrost table only,
whereas field data points to high ice contents over large parts of the permafrost. From their drilling in January 2012, Cable et al. (in review) found that the ice content in the permafrost body
was considerably higher than in the active layer, and that almost the entire loess accumulation
below the active layer was interspersed with ice lenses. This is a cryostratigraphic pattern typically observed where long-term aeolian sedimentation and permafrost aggradation occurred
(Gilbert, 2014; Cable et al., in review). The modeling approach in this thesis did not consider
Holocene sediment accretion processes. Therefore, the representation of ice content and temperature development in the deeper permafrost might be less reliable.
5.2 Infiltration, water flow and advective heat transport
Two-sided freezing and the freeze/thaw cycle in general lead to a circulation of moisture within
the subsurface which is independent of additional water input. Though the turnover of water
within the active layer is highest in those scenarios including infiltration, the water movement
depends on the existing soil moisture rather than the water inflow. In all cases, the infiltration
volume is too small to considerably affect water flows compared to the available amount of soil
water and ground ice. During the 100-year model spin-up, a total of 16 m³ of infiltration was
inserted into the model domain (left column; 40 m³ total void space) which led to a distinct
26
5 Discussion
increase in total saturation. This way, when infiltration was applied in the transient model, it
accounted for only a very small part of the total soil moisture. For instance, in scenario MEDpinfil, peak infiltration of 0.5 mm d-1 represents only about 3% of the already existing soil moisture. Consequently, the model did not show a distinct response to the different infiltration patterns (constant vs. peak). The visible increase in soil moisture during summer as computed for
all scenarios is therefore interpreted as melting ground ice rather than being caused by water
inflow.
The soil moisture data obtained for the UNISCALM site allows two different interpretations
with regard to the source of water, namely infiltration from the surface and melting of ground
ice. In spring, a distinct peak in soil moisture content is visible at all sensor depths in the active
layer (Fig. A20, Appendix). Since the peak in the upper active layer is well-defined and lasts for
a few days only, it can be regarded as melt water input which subsequently percolates down.
A corresponding delay in peak timing with depth can be observed in the data set. Alternatively,
the peak in soil moisture could be caused by active layer thaw and corresponding ground ice
melting, as simulated by the model. Water could then in the same way percolate down, accumulate above the permafrost table, and migrate back up when refreezing. The combined consideration of soil moisture and subsurface temperature observations at the UNISCALM site supports
this assumption. As shown in Fig. 17, the peak in soil moisture at a certain depth corresponds
largely to the concurrent thaw depth. It has to be noted however that the UNISCALM dataset is
linearly interpolated and might therefore not represent accurate temperatures, especially between 0.5 m and 1.1 m depth.
Figure 17: Active layer thaw as observed at the UNISCALM site in spring/summer 2011. Shown are a) soil moisture
[m³ m ³] at three depths -0.1 m, -0.6 m, and -1.0 m, and b) subsurface temperature [°C] linearly interpolated from
logger data for the upper 1.1 m of the ground. The black contour line indicates the approximate location of the 0°Cisotherm. Red dots mark the depth of the soil moisture measurements shown in the upper plot (Data: UNIS).
27
Carina Schuh
The fact that ground ice melt produces a distinct increase in soil moisture does not eliminate the
idea of a potential snow melt infiltration into the ground. While ground ice has been shown to
exist in the active layer (Cable et al., in review), information is sparse on snow cover thickness
and related snow melt volume. There is evidence that the winter snow cover at the UNISCALM
site does not exceed 20-30 cm (Christiansen and Humlum, 2008; Farnsworth, 2013; Moreno
and Cañadas, 2013). In addition, the typical snow cover structure in conjunction with high wind
speeds in Adventdalen suggests that the infiltration volume from snow melt is less than the
snow water equivalent resulting from 20-30 cm snow cover. Moreno and Cañadas (2013) describe the snow cover in Adventdalen to consist of an unstable top layer that is prone to wind
erosion, and an icy, long-lasting base layer. Hence, given the wind exposure of the UNISCALM
site, a considerable amount of snow might be removed by wind before the start of the melt season. The remaining snow might melt, percolate through the snow cover and freeze onto the ice
layer at the ground surface, and melt eventually. An indicator of such an ice layer could be the
duration of the zero curtain effect, required to melt the ice, seen in ground surface temperature
data (Fig. 12, section 4.3). Regardless of snow redistribution or snowpack dynamics, the infiltration volume might in any case be reduced by evapotranspiration and sublimation. For their
study site in west Greenland, Johansson et al. (2015) found that sublimation from snow
(0.63 mm d-1) was an important hydro-climatic process to consider, especially on clear and
windy days in late winter, and constituted about half of the evaporation rate during summer.
Furthermore, manual monitoring of thaw progression at the UNISCALM site revealed that active layer thaw did not start before the snow cover had entirely disappeared (Christiansen and
Humlum, 2008). Ultimately, the observed peak in soil moisture after the onset of active layer
thaw might be caused by both melt water infiltration and ground ice melt. Based on the model
findings, ground ice melt seems to outweigh infiltration. However, neither of the components
has been sufficiently quantified so that a final model evaluation is not possible in this regard.
The modeled soil moisture increase in summer resembles a plateau rather than a peak, thus
questioning the effectiveness of percolation. For instance, percolation in scenario WET-cinfil
accounts for only about 5% of the available soil moisture content (here: 18%). Besides the
hydraulic gradient, Darcy flow is controlled by the parameters of permeability and relative permeability (Eq. 3). Permeability, here 10-14 m², is assumed to be representative for the range
commonly used for unconsolidated (loess) sediment (Freeze and Cherry, 1979; Kirsch and
Yaramanci, 2006; Bense et al., 2012). Relative permeability, i.e. permeability as a function of
liquid saturation, is defined through parameter m (here: 0.35) as used in the van Genuchten and
Mualem models (see Eqs. 5a and 6). The parameter value is derived from the UNSODA unsaturated soil hydraulic database (Leij et al., 1996) and assumed to represent sandy silt to a fair
degree. However, given the low saturation of the active layer, relative permeability approaches
very low values and thus severely inhibits the flow of water (Fig. A22, Appendix). More pronounced percolation of water could only be achieved where saturation is (temporarily) higher.
The available soil moisture records at the UNISCALM site (Fig. A20, Appendix) show that the
peak in soil moisture is most pronounced at the upper sensor depths (-0.1 m and -0.2 m), so that
highest percolation might occur right beneath the ground surface. This, in turn, might point to a
temporary strong increase in soil moisture through snow melt infiltration.
28
5 Discussion
Despite the site’s comparable dryness and low relative permeability, the movement of water and
the corresponding transport of advective heat cannot be entirely disregarded. Results for the
wetter scenario WET showed that the application of infiltration increased the amount of soil
moisture in the active layer, but did not decrease active layer depths. The simulated increase in
soil moisture from 12% (WET) to 17% (WET-cinfil) is assumed to impede summer heat propagation into the ground and thus to reduce the thaw depth. However, the higher soil moisture in
WET-cinfil facilitates the flow of water. Darcy flows in vertical direction were highest and flow
paths reached far into the active layer and the diffuse ground ice body in the transient zone.
Hence, advective heat transported through percolating water, even if of small amount, seems to
level out the increased latent heat consumption in the active layer. Similar findings resulted
from the GPR-survey carried out by Westermann et al. (2010) where thaw depths at a comparable study site close to Ny-Ålesund, Svalbard, remained stable even if soil moisture content in
the active layer increased. In contrast, Weismüller et al. (2011) reject the idea of active layer
deepening through water percolation. According to their modeling study at the Bayelva site
close to Ny-Ålesund, infiltrating snow melt water is not able to increase the thaw depth because
it freezes as soon as it reaches the freezing front due to its low temperature (0°C). Based on this,
one can deduct that in the present modeling study, the advective heat flow provoked by melting
ground ice and infiltration transports sufficient energy to boost the thawing process.
As far as lateral water flows are concerned, the simulations showed that they are most pronounced where the saturation at the onset of thaw was highest. The more saturated the ice layer,
the more lateral runoff occurred. Still, since Darcy velocities in lateral direction were one order
of magnitude smaller than those in vertical direction, lateral flow of water is assumed to have a
negligible effect on the permafrost hydrology at the UNISCALM site.
5.3 Active layer dynamics and permafrost development
As discussed above, permafrost temperatures matched observations best in scenarios MED and
WET. The best fit in active layer temperatures was achieved by model scenarios WET both with
and without infiltration. For the evaluation of active layer depths, the UNISCALM subsurface
temperature logger does not provide reliable information because of unfavorable sensor spacing.
While the upper active layer is well covered with sensors at 0 m, 0.1 m, and 0.2 m depth, the
middle and lower parts are monitored by only two sensors at 0.5 m and 1.1 m depth. This way,
the logger is not able to capture the temperature variations required to appropriately describe
active layer dynamics.
For the discussion of active layer depths, model results are compared to the data set on active
layer thaw depths as derived from physical probing during summer (Tab. 5 and Fig. 18). For the
year 2005, the data set contains a distinct outlier value (79 cm) with unclear probing date such
that it is excluded from further analyses. Based on the remaining time series, active layer depths
ranged from 99 cm to 116 cm with an average of 105 cm. Model scenario WET matches field
observations best by estimating active layer depths to range between 110 cm and 140 cm with
an average of 121 cm. Still, the model overestimates mean active layer depth by 16 cm and inter-annual variation in active layer depth by 13 cm. For the period 2000-2007, active layer dy29
Carina Schuh
namics at the UNISCALM site have been analyzed by Christiansen and Humlum (2008) regarding their response to a variety of meteorological factors. The authors found a good correlation
between active layer depth and solar radiation. In contrast, no correlation was found between
active layer depth and summer precipitation. Also, Westermann et al. (2010) concluded from
precipitation and evapotranspiration measurements in Ny-Ålesund, Svalbard, that late-summer
infiltration into the active layer was negligible. This supports the hypothesis of ground ice being
a more important source for soil moisture than infiltration in this particular setting.
Table 5: Active layer depth [cm] as derived from physical probing (Data: UNIS) and model scenario WET during the
study period. The day of measurement/maximum active layer depth is given in italic. The measurement in 2005 is
disregarded due to possible bias.
2000
2001
2002
2003
2004
2005 2006
2007
2008
2009
2010
2011
2012
2013
2014
UNIS physical probing
100
102
100
99
99
22.8.
4.9.
15.9.
2.10.
21.8
(79)
110
130
120
110
120
110
17.9.
31.8.
25.8.
25.8.
11.8.
2.9.
104
106
116
106
110
104
107
111
110
24.8.
11.9.
16.9.
2.9.
14.8.
23.8.
17.9.
31.8.
26.8.
Model scenario WET
130
120
110
20.8.
20.8.
29.8.
120
120
130
120
130
140
29.8.
15.8.
15.9.
21.8.
2.9.
26.8.
Figure 18: Active layer depth [cm] as derived from physical probing (grey) (Data: UNIS) and model scenario WET
(white) during the study period.
Disregarding the active layer depth measurement in 2005, the UNISCALM site shows a comparatively small inter-annual variation (Tab. 5 and Fig. 18). Years of extreme mean air temperatures are not reflected in summer thaw depth. Year 2006 was the warmest year on a 100-year
record, followed by 2007, with mean annual air temperatures of -1.7°C and -2.5°C, respectively,
compared to the long-term mean of -6°C (Eckerstorfer and Christiansen, 2011). The summer of
2000 was the coldest summer (June, July, and August) in the period 2000-2007 (Christiansen
and Humlum, 2008). The missing correlation between air temperature and thaw depth is an important factor to consider when interpreting the direct effect of climatic variations to active layer
development. Furthermore, it highlights the importance of applying ground surface temperature
as upper temperature boundary condition in the model. In any case, the separate consideration
of summer and winter temperatures is recommended for two reasons. First, temperature fluctuations during winter seem to be the decisive factor for the observed variations in annual air temperature in the 20th century in Svalbard (Humlum et al., 2003). According to records from the
UNISCALM site, this holds true also for ground surface temperature fluctuations (Fig. 19).
Second, not only summer temperatures should be considered when investigating active layer
dynamics. The mere winter temperature can have a large effect on the active layer since
30
5 Discussion
increased winter temperatures can result in enhanced thaw during the subsequent summer
(Burn, 2012).
Figure 19: Daily ground surface temperature [°C] as recorded at the UNISCALM site between 09/2000 and 08/2014.
Note that the periods from 31/08-26/09/2001 and 26/04-17/10/2004 have been reconstructed according to Eq. 7.
-1
The red solid line represents the linear trend of 0.26°C yr (p < 0.01 at a 0.05 significance level).
Although neither field data nor model results reflect the inter-annual variability in air temperature, they both show a noticeable tendency of increasing active layer depth over the course of
the study period. This coincides with the increase in ground surface temperature of 0.26°C yr-1
(p < 0.01 at a 0.05 significance level; Fig. 19). Active layer deepening has been described for
several other sites in Svalbard. Isaksen et al. (2007) reported rising permafrost temperatures
with accompanying increases in active layer depths for the Janssonhaugen site in central
Adventdalen. Åkerman (2005) found active layer deepening at Kapp Linné to correlate well
with increases in air temperature, and in the Ny-Ålesund area, the studies by Roth and Boike
(2001) and Westermann et al. (2010) indicate an increase in active layer depth of more than half
a meter within a decade.
The general climate trends in the Arctic and the findings from this modeling study allow the
suggestion that the permafrost-hydrological system at the UNISCALM site might be in a form
of ‘twofold’ transient state. On the one hand, the system is likely subject to long-term climate
change, including changes in temperature, snow cover, solar radiation etc. On the other hand,
the high importance of cryosuction for the UNISCALM site might lead to persistent moisture
migration into the permafrost, provided that there is a certain amount of infiltration. Not only
would that lead to an increasing ice content in the transition zone, but also might the system be
able to buffer increases in temperature to a certain degree. This possible ‘twofold’ transient state
should be considered when using active layer depth as an ‘early warning system’ for a warming
climate and degrading permafrost.
31
Carina Schuh
6 Summary and conclusion
The numerical model ATS was used to investigate the physical processes controlling nearsurface permafrost temperatures and active layer depths at the UNISCALM site in Svalbard. To
do so, the effect of ground surface temperature was tested in conjunction with different initial
soil moisture contents, and constant and peak infiltration was applied to identify potentially
relevant correlations. The main findings pertaining to the particular study site are summarized in
the following:

Soil moisture redistribution is driven by the freeze/thaw cycle alone and does not
require any external water input; zones of high ice content in the subsurface are more
defined the drier the system

Active layer depth decreases with increasing soil moisture content, but only to a certain
degree; differences in initial soil moisture content can be leveled out through intensified
cryosuction into the permafrost and advective heat flow through percolation

Two-sided active layer freezing occurs and is most pronounced in settings with higher
soil moisture; it leads to water migration into the upper active layer and the top of the
permafrost (‘transition zone’)

Infiltration is too small to have a considerable effect on inter-annual active layer
dynamics compared to the existing ground ice volume; however, infiltration increases
the amount of ground ice and thus alters permafrost (thermal) properties in the long run

Model simulations and field observations show a clear tendency of increasing active
layer depths during the study period; inter-annual variations in active layer depth were
comparably small

Due to ongoing climate change and persistent soil moisture migration into the
‘transition zone’, the UNISCALM site might be in a form of ‘twofold’ transient state;
ice enrichment in the ‘transition zone’ could buffer thaw and thus obscure increasing
ground surface temperatures; this could have implications for the suitability of active
layer depths as a proper indicator for climate change
The investigations performed in this thesis are based on substantial simplifications and numerous assumptions made to the best of knowledge. Additional uncertainty originates from the
measurement and processing of field data. Consequently, the investigations bear the risk of inaccurately representing the specific cryohydrological system at the UNISCALM site. Nevertheless, given that permafrost hydrology is still in its infancy, numerical modeling is considered to
be a valuable tool to investigate the physical functioning of a specific permafrost system. The
usage of high-quality field data in conjunction with state-of-the-art numerical modeling is an
excellent opportunity to advance permafrost-hydrological research and should be pursued further. In this context, research efforts should be undertaken to improve the estimation of infiltration volume and pattern, and, where required, to couple snowmelt dynamics to the subsurface
numerical model. Besides, the concept of a ‘transition zone’ in dry permafrost environments
should be explored further. The effect of soil moisture redistribution and cryosuction into the
permafrost, especially in dry settings, might be underestimated despite its function as a stabilizer for permafrost temperatures.
32
Appendix
Figure A20
Soil moisture [m³ m-3] as recorded at the UNISCALM site during 10/2008 and 08/2014 (Data:
UNIS). The dashed lines indicate the soil moisture content as assumed for the three base scenarios.
Figure A21
Modeled daily soil moisture [m³ m-3] for base scenarios 1) DRY, 2) MED, and 3) WET (all red)
compared to field observations (black). Solid lines indicate model runs without infiltration,
dashed lines scenarios with constant infiltration, and dash-dotted lines scenarios with peak infiltration. Subplots show results for a) 0.1 m depth, and b) 1.0 m depth.
Figure A22
Relationship between liquid saturation [-] and relative permeability [-] applied in all model scenarios. The function is computed according to Eq. 6 using m = 0.35.
IV
-
Figure A20: Soil moisture [m³ m ³] as recorded at the UNISCALM site between 10/2008 and 08/2014 (Data: UNIS).
The dashed lines indicate the soil moisture content as assumed for the three base scenarios.
V
-
Figure A21: Modeled daily soil moisture [m³ m ³] for base scenarios 1) DRY, 2) MED, and 3) WET (all red) compared
to field observations (black). Solid lines indicate model runs without infiltration, dashed lines scenarios with constant
infiltration, and dash-dotted lines scenarios with peak infiltration. Subplots show results for a) 0.1 m depth, and b)
1.0 m depth.
VI
Figure A22: Relationship between liquid saturation [-] and relative permeability [-] applied in all model scenarios.
The function is computed according to Eq. 6 using m = 0.35.
VII
References
Akbari, G.; Basirat Tabrizi, H. and Damangir, E. (2009): Numerical and experimental investigation of variable phase transformation number effect in porous media during freezing process.
Heat Mass Transfer 45 (4), pp. 407–416.
Åkerman, H. (2005): Relations between slow slope processes and active layer thickness 1972–
2002, Kapp Linné, Svalbard. Norsk Geogr. Tidsskr. 59, pp.116–128.
Andersland, O.B. and Ladanyi, B. (1994): An introduction to frozen ground engineering. Dordrecht (Springer), ISBN: 978-1-4757-2290-1.
Atchley, A.L.; Painter, S.L.; Harp, D.R.; Coon, E.T.; Wilson, C.J.; Liljedahl, A.K. and
Romanovsky, V.E. (2015): Using field observations to inform thermal hydrology models at
the Barrow Environmental Observatory, Alaska. Geoscientific Model Development 8, pp.
2701–2722.
Bense, V.F.; Ferguson, G. and Kooi, H. (2009): Evolution of shallow groundwater flow systems
in areas of degrading permafrost. Geophys. Res. Lett. 36 (22).
Bense, V.F.; Kooi, H.; Ferguson, G. and Read, T. (2012): Permafrost degradation as a control
on hydrogeological regime shifts in a warming climate. J. Geophys. Res. 117 (F3).
Bense, V.F. and Person, M.A. (2008): Transient hydrodynamics within intercratonic sedimentary basins during glacial cycles. J. Geophys. Res. 113 (F4).
Boike, J.; Roth, K. and Overduin, P.P. (1998): Thermal and hydrologic dynamics of the active
layer at a continuous permafrost site Taymyr Peninsula, Siberia. Water Resour. Res. 34 (3),
pp. 355–363.
Bolton, W.R., Boike, J. and Overduin, P.P. (2008): Estimation of hydraulic properties in permafrost-affected soils using a two-directional freeze-thaw algorithm. In: Kane, D.L. and Hinkel,
K.M. (eds.), Proceedings of the Ninth International Conference on Permafrost, University of
Alaska Fairbanks, June 29 - July 3, 2008.
Braathen, A.; Bælum, K.; Christiansen, H.H.; Dahl, T.; Eiken, O.; Elvebakk, H.; Hansen, F. et
al. (2012): The Longyearbyen CO2 Lab of Svalbard, Norway: initial assessment of the geological conditions for CO2 sequestration. Norwegian Journal of Geology 92, pp. 353-376.
Bryant, I.D. (1982): Loess deposits in lower Adventdalen, Spitsbergen. Polar Research 2, pp.
93–103.
Burn, C. (2012): Permafrost distribution and stability. In: French, H. and Slaymaker, O. (eds.),
Changing cold environments: a Canadian perspective. Hoboken (Wiley), ISBN:
9780470699683.
Cable, S.; Christiansen, H.H.; Gilbert, G.L. and Elberling, B. (in review): Cryostratigraphy and
geochemistry of active layer and permafrost in the Adventdalen valley, Svalbard.
Cheng, G. (1983): The mechanism of repeated-segregation for the formation of layered ground
ice. Cold Regions Science and Technology 8, pp. 57-66.
Christiansen, H.H. and Humlum, O. (2008): Interannual variations in active layer thickness in
Svalbard. In: Kane, D.L. and Hinkel, K.M. (eds.), Proceedings of the Ninth International
Conference on Permafrost, University of Alaska Fairbanks, June 29 - July 3, 2008.
VIII
Coon, E.T.; Moulton, J.D.; Painter, S.L. (in review): Managing complexity in simulations of
land surface and near-surface processes, Environmental Modelling and Software.
Dall'Amico, M.; Endrizzi, S.; Gruber, S. and Rigon, R. (2011): A robust and energy-conserving
model of freezing variably-saturated soil. The Cryosphere 5 (2), pp. 469–484.
Duchesne, C., Wright, J.F. and Ednie, M. (2008): High-Resolution Numerical Modeling of Climate Change Impacts to Permafrost in the Vicinities of Inuvik, Norman Wells, and Fort
Simpson, NT, Canada. In: Kane, D.L. and Hinkel, K.M. (eds.), Proceedings of the Ninth International Conference on Permafrost, University of Alaska Fairbanks, June 29 - July 3,
2008.
Eckerstorfer, M. and Christiansen, H.H. (2011): Topographical and meteorological control on
snow avalanching in the Longyearbyen area, central Svalbard 2006–2009. Geomorphology
134 (3-4), pp. 186–196.
Ednie, M., Wright, J.F. and Duchesne, C. (2008): Establishing Initial Conditions for Transient
Ground Thermal Modeling in the Mackenzie Valley: A Paleo-Climatic Reconstruction Approach. In: Kane, D.L. and Hinkel, K.M. (eds.), Proceedings of the Ninth International Conference on Permafrost, University of Alaska Fairbanks, June 29 - July 3, 2008.
Etzelmüller, B.; Schuler, T.V.; Isaksen, K.; Christiansen, H.H.; Farbrot, H. and Benestad, R.
(2011): Modeling the temperature evolution of Svalbard permafrost during the 20th and 21st
century. The Cryosphere 5 (1), pp. 67–79.
Farnsworth, W.R. (2013): The topographical and meteorological influence on snow distribution
in central Svalbard: how the spatial variability of snow influences slope-scale stability, permafrost landscape dynamics and regional distribution trends. Master Thesis. University of
Oslo, Department of Geosciences. Available online at http://www.duo.uio.no.
Fitts, C. (2013): Groundwater science. 2nd edition, Oxford (Elsevier), doi: 10.1016/B978-0-12384705-8.00016-9.
Førland, E. and Hanssen-Bauer, I. (2003): Climate variations and implications for precipitation
types in the Norwegian Arctic. Edited by the Norwegian Meteorological Institute, Oslo.
Førland, E.; Hanssen-Bauer, I. and Nordli, P. (1997): Climate statistics and longterm series of
temperature and precipitation at Svalbard and Jan Mayen. Edited by the Norwegian Meteorological Institute, Oslo.
Frampton, A.; Painter, S.L. and Destouni, G. (2013): Permafrost degradation and subsurfaceflow changes caused by surface warming trends. Hydrogeol J. 21 (1), pp. 271–280.
Frampton, A.; Painter, S.L.; Lyon, S.W. and Destouni, G. (2011): Non-isothermal, three-phase
simulations of near-surface flows in a model permafrost system under seasonal variability
and climate change. Journal of Hydrology 403 (3-4), pp. 352–359.
Freeze, R.A. and Cherry, J.A. (1979): Groundwater. Hemel Hempstead (Prentice), ISBN: 9780133653120.
French, H.M. (2007): The periglacial environment. 3rd edition, Chichester (Wiley), ISBN: 9780-470-86588-0.
Fuchs, M.; Campbell, G.S. and Papendick, R.I. (1978): An Analysis of sensible and latent heat
flow in a partially frozen unsaturated soil. Soil Science Society of America J 42 (3), p. 379.
IX
Garimella, R.V.; Perkins, W.A.; Buksas, M.W.; Berndt, M.; Lipnikov, K.; Coon, E. et al.
(2014): Mesh infrastructure for coupled multiprocess geophysical simulations. Procedia Engineering 82, pp. 34–45.
Ge, S.; McKenzie, J.; Voss, C. and Wu, Q. (2011): Exchange of groundwater and surface-water
mediated by permafrost response to seasonal and long term air temperature variation.
Geophys. Res. Lett. 38 (14).
Gerland, S.; Winther, J.-G.; Ørbæk, J.; Liston, G.; Øritsland, N.; Blanco, A. and Ivanov, B.
(1999): Physical and optical properties of snow covering Arctic tundra on Svalbard. Hydrol.
Process. 13, pp. 2331–2343.
Ghanbarian-Alavijeh, B.; Liaghat, A.; Huang, G.H. and Van Genuchten, M.T. (2010): Estimation of the van Genuchten soil water retention properties from soil textural data. Pedosphere
20 (4), pp. 456–465.
Gilbert, G.L. (2014): Sedimentology and geocryology of an Arctic fjord head delta
(Adventdalen, Svalbard). Master Thesis. University of Oslo, Department of Geosciences.
Available online at http://www.duo.uio.no.
Grenier, C.; Régnier, D.; Mouche, E.; Benabderrahmane, H.; Costard, F. and Davy, P. (2013):
Impact of permafrost development on groundwater flow patterns: a numerical study considering freezing cycles on a two-dimensional vertical cut through a generic river-plain system.
Hydrogeol J 21 (1), pp. 257–270.
Guymon, G.L. and Luthin, J.N. (1974): A coupled heat and moisture transport model for Arctic
soils. Water Resour. Res. 10 (5), pp. 995–1001.
Hansson, K.; Simunek, J.; Mizoguchi, M.; Lundin, L.-C. and van Genuchten, M.T. (2004): Water flow and heat transport in frozen soil: numerical solution and freeze-thaw applications.
Vadose Zone Journal (3), pp. 693–704.
Harlan, R.L. (1973): Analysis of coupled heat-fluid transport in partially frozen soil. Water
Resour. Res. 9 (5), pp. 1314–1323.
Hinzman, L.D.; Goering, D.J. and Kane, D.L. (1998): A distributed thermal model for calculating soil temperature profiles and depth of thaw in permafrost regions. Journal of Geophysical Research 103 (D22), pp. 28975–28991.
Hodgkins, R.; Cooper, R.; Wadham, J. and Tranter, M. (2009): The hydrology of the proglacial
zone of a high-Arctic glacier (Finsterwalderbreen, Svalbard): Atmospheric and surface water
fluxes. Journal of Hydrology 378 (1-2), pp. 150–160.
Huang, P.M.; Li, Y. and Sumner, M.E. (eds.) (2012): Handbook of soil sciences – properties
and processes. 2nd edition, Boca Raton (Taylor & Francis), ISBN: 978-1-4398-0305-9.
Humlum, O. (2002): Modelling late 20th-century precipitation in Nordenskiöld Land, Svalbard,
by geomorphic means. Norsk Geografisk Tidsskrift 56, pp. 96–103, ISSN 0029-1951.
Humlum O. (2005): Holocene permafrost aggradation in Svalbard. In: Harris, C. and Murton,
J.B. (eds.), Cryospheric systems: Glaciers and Permafrost, Geological Society, London, Special Publications 242: 119-130.
Humlum, O.; Instanes, A. and Sollid, J.L. (2003): Permafrost in Svalbard: a review of research
history, climatic background and engineering challenges. Polar Research 22 (2), pp. 191–
215.
X
Humlum, O.; Solheim, J.-E. and Stordahl, K. (2011): Identifying natural contributions to late
Holocene climate change. Global and Planetary Change 79 (1-2), pp. 145–156.
Isaksen, K.; Sollid, J.L.; Holmlund, P. and Harris, C. (2007): Recent warming of mountain permafrost in Svalbard and Scandinavia. J. Geophys. Res. 112 (F2).
Jafarov, E.E.; Marchenko, S.S. and Romanovsky, V.E. (2012): Numerical modeling of permafrost dynamics in Alaska using a high spatial resolution dataset. The Cryosphere 6 (3), pp.
613–624.
Jame, Y.-W. and Norum, D.I. (1980): Heat and mass transfer in a freezing unsaturated porous
medium. Water Resour. Res. 16 (4), pp. 811–819.
Janke, J.R.; Williams, M.W. and Evans, A. (2012): A comparison of permafrost prediction
models along a section of Trail Ridge Road, Rocky Mountain National Park, Colorado,
USA. Geomorphology 138 (1), pp. 111–120.
Johansson, E.; Berglund, S.; Lindborg, T.; Petrone, J.; van As, D.; Gustafsson, L.-G. et al.
(2015): Hydrological and meteorological investigations in a periglacial lake catchment near
Kangerlussuaq, west Greenland – presentation of a new multi-parameter data set. Earth Syst.
Sci. Data 7 (1), pp. 93–108.
Juliussen, H. and Humlum, O. (2007): Towards a TTOP ground temperature model for mountainous terrain in central-eastern Norway. Permafrost Periglac. Process. 18 (2), pp. 161–
184.
Kane, D.L.; Hinzman, L.D. and Zarling, J.P. (1991): Thermal response of the active layer to
climatic warming in a permafrost environment. Cold Regions Science and Technology 19,
pp. 111–122.
Karra, S.; Painter, S.L. and Lichtner, P.C. (2014): Three-phase numerical model for subsurface
hydrology in permafrost-affected regions (PFLOTRAN-ICE v1.0). The Cryosphere 8 (5), pp.
1935–1950.
Killingtveit, A.; Pettersson, L.-E. and Sand, K. (2003): Water balance investigations in Svalbard. Polar Research 22 (2), pp. 161–174.
Kirsch, R. and Yaramanci, U. (2006): Geophysical characterization of aquifers. In: Kirsch, R.
(ed.), Groundwater geophysics - a tool for hydrogeology. Berlin (Springer), pp. 439-457,
ISBN: 978-3-540-29383-5.
Kuhry, P.; Dorrepaal, E.; Hugelius, G.; Schuur, E.A.G. and Tarnocai, C. (2010): Potential remobilization of belowground permafrost carbon under future global warming. Permafrost
Periglac. Process. 21 (2), pp. 208–214.
Lachenbruch, A.H. and Marshall, B.V. (1986): Changing climate: geothermal evidence from
permafrost in the Alaskan Arctic. Science 234 (4777), pp. 689–696.
Leander, R. and Buishand, T.A. (2007): Resampling of regional climate model output for the
simulation of extreme river flows. Journal of Hydrology 332 (3-4), pp. 487–496.
Leij, F.J.; Alves, W.J., Van Genuchten, M.T. and Williams, J.R. (1996): The UNSODA Unsaturated Soil Hydraulic Database. U.S. Environmental Protection Agency, Washington DC.
Ling, F. and Zhang, T. (2004): A numerical model for surface energy balance and thermal regime of the active layer and permafrost containing unfrozen water. Cold Regions Science
and Technology 38 (1), pp. 1–15.
XI
Listøl, O. (1977): Pingos, springs, and permafrost in Spitsbergen. Edited by Norsk Polarinstitutt.
Oslo.
Lu, T.-J.; Du, J.-H.; Lei, S. and Wang, B.-X. (2001): Heat and mass transfer in unsaturated porous media with solid-liquid change. Heat and Mass Transfer 37, pp. 237–242.
Luo, D.L.; Jin, H.J..; Marchenko, S. and Romanovsky, V. (2014): Distribution and changes of
active layer thickness (ALT) and soil temperature (TTOP) in the source area of the Yellow
River using the GIPL model. Sci. China Earth Sci. 57 (8), pp. 1834–1845.
Lyon, S.W.; Destouni, G; Giesler, R.; Humborg, C.; Mörth, M.; Seibert, J.; Karlsson, J. and
Troch, P.A. (2009): Estimation of permafrost thawing rates in a sub-arctic catchment using
recession flow analysis. Hydrol. Earth Syst. Sci. 13, pp. 595-604.
Mackay, J.R. (1972): The world of underground ice. Annals of the Association of American
Geographers 62, pp. 1-22.
McKenzie, J.M. and Voss, C.I. (2013): Permafrost thaw in a nested groundwater-flow system.
Hydrogeology Journal 21(1), pp. 299-316.
McKenzie, J.M.; Voss, C.I. and Siegel, D.I. (2007): Groundwater flow with energy transport
and water–ice phase change: Numerical simulations, benchmarks, and application to freezing
in peat bogs. Advances in Water Resources 30 (4), pp. 966–983.
Moreno, R.M. and Cañadas, E.S. (2013): Snow cover evolution in the High Arctic,
Nordenskiöldland (Spitsbergen, Svalbard). Boletín de la Asociación de Geógrafos Españoles
61, ISSN 0212-9426.
Mualem, Y. (1976): A new model for predicting the hydraulic conductivity of unsaturated porous media. Water Resour. Res. 12, pp. 513–322.
Nakano, Y. and Brown, J. (1971): Effect of a freezing zone of finite width on the thermal regime of soils. Water Resour. Res. 7 (5), pp. 1226–1233.
Nixon, J.F. (1975): The role of convective heat transport in the thawing of frozen soils. Canadian Geotechnical Journal 12, pp. 425–429.
Ochsner, T.E.; Horton, R. and Ren, T. (2001): A new perspective on soil thermal properties.
Soil Sci. Soc. Am. J. 65, pp. 1641–1647.
Oliva, M.; Vieira, G.; Pina, P.; Pereira, P.; Neves, M. and Freitas, M.C. (2014):
Sedimentological characteristics of ice-wedge polygon terrain in Adventdalen (Svalbard):
environmental and climatic implications for the late Holocene. Solid Earth 5 (2), pp. 901–
914.
Painter, S.L. (2011): Three-phase numerical model of water migration in partially frozen geological media: model formulation, validation, and applications. Comput Geosci 15 (1), pp.
69–85.
Painter, S.L. and Karra, S. (2014): Constitutive model for unfrozen water content in subfreezing
unsaturated soils. Vadose Zone Journal 13 (4).
Painter, S.L.; Moulton, J.D. and Wilson, C.J. (2013): Modeling challenges for predicting hydrologic response to degrading permafrost. Hydrogeol J 21, pp. 221-224.
Riseborough, D.; Shiklomanov, N.; Etzelmüller, B.; Gruber, S. and Marchenko, S. (2008): Recent advances in permafrost modelling. Permafrost Periglac. Process. 19 (2), pp. 137–156.
XII
Roth, K. and Boike, J. (2001): Quantifying the thermal dynamics of a permafrost site near NyÅlesund, Svalbard. Water Resour. Res. 37 (12), pp. 2901–2914.
Rowland, J.C.; Travis, B.J. and Wilson, C.J. (2011): The role of advective heat transport in talik
development beneath lakes and ponds in discontinuous permafrost. Geophys. Res. Lett. 38
(17).
Scheidegger, J.M. and Bense, V.F. (2014): Impacts of glacially recharged groundwater flow
systems on talik evolution. J. Geophys. Res. Earth Surf. 119 (4), pp. 758–778.
Scheidegger, J.M.; Bense, V.F. and Grasby, S.E. (2012): Transient nature of Arctic spring systems driven by subglacial meltwater. Geophys. Res. Lett. 39 (12).
Schwartz, F.W. and Zhang, H. (2003): Fundamentals of ground water. New York (Wiley),
ISBN: 978-0-471-13785-6.
Sheshukov, A.Y. and Nieber, J.L. (2011): One-dimensional freezing of nonheaving unsaturated
soils: model formulation and similarity solution. Water Resour. Res. 47 (11).
Shiklomanov, N. and Nelson, F. (1999): Analytic representation of the active layer thickness
field, Kuparuk River Basin, Alaska. Ecological Modelling 123, pp. 105–125.
Shiklomanov, N.I., Nelson, F.E.; Streletskiy, D.A.; Hinkel, K.M. and Brown, J. (2008): The
circumpolar active layer monitoring (CALM) program: data collection, management, and
dissemination strategies, In: Kane, D.L. and Hinkel, K.M. (eds.), Proceedings of the Ninth
International Conference on Permafrost, University of Alaska Fairbanks, June 29 - July 3,
2008.
Shur, Y.; Hinkel, K.M. and Nelson, F.E. (2005): The transient layer: implications for
geocryology and climate-change science. Permafrost Periglac. Process. 16 (1), pp. 5–17.
Sjöberg, Y.; Coon, E.T.; Sannel, A.B.K.; Pannetier, R; Harp, D.; Frampton, A.; Painter, S.L.
and Lyon, S.W. (in review): Thermal effects of groundwater flow through subarctic fens: a
case study based on field observations and numerical modeling.
Sjöberg, Y.; Frampton, A. and Lyon, S.W. (2013): Using streamflow characteristics to explore
permafrost thawing in northern Swedish catchments. Hydrogeol J. 21, pp. 121-131.
Smith, M. and Riseborough, D.W. (1996): Permafrost monitoring and detection of climate
change. Permafrost and Periglacial Processes 7, pp. 301–309.
Smith, S.L. and Riseborough, D.W. (2010): Modelling the thermal response of permafrost terrain to right-of-way disturbance and climate warming. Cold Regions Science and Technology
60 (1), pp. 92–103.
Szymkiewicz, A. (2013): Mathematical models of flow in porous media. In: Szymkiewicz, A.
(ed.): Modelling Water Flow in Unsaturated Porous Media. Berlin (Springer), pp. 9–47.
Tarnocai, C.; Canadell, J.G.; Schuur, E.A.G.; Kuhry, P.; Mazhitova, G. and Zimov, S. (2009):
Soil organic carbon pools in the northern circumpolar permafrost region. Global
Biogeochem. Cycles 23 (2).
Terink, W.; Hurkmans, R.T.W.L.; Torfs, P.J.J.F. and Uijlenhoet, R. (2009): Bias correction of
temperature and precipitation data for regional climate model application to the Rhine basin.
Hydrol. Earth Syst. Sci. Discuss. 6 (4), pp. 5377–5413.
XIII
Thomas, H.R.; Cleall, P.; Li, Y.-C.; Harris, C. and Kern-Luetschg, M. (2009): Modelling of
cryogenic processes in permafrost and seasonally frozen soils. Géotechnique 59 (3), pp. 173–
184.
van Genuchten, M.T. (1980): A closed-form equation for predicting the hydraulic conductivity
of unsaturated soils. Soil Sci. Soc. Am. J. 44, pp. 892–898.
Vörösmarty, C.; Hinzman, L.D.; Peterson, B.; Bromwich, D.; Hamilton, L.; Morison, J. et al.
(2001): The hydrologic cycle and its role in arctic and global environmental change: a rationale and strategy for synthesis study. Arctic Research Consortium of the U.S. Fairbanks,
Alaska.
Walvoord, M.A. and Striegl, R.G. (2007): Increased groundwater to stream discharge from
permafrost thawing in the Yukon River basin: potential impacts on lateral export of carbon
and nitrogen. Geophys. Res. Lett. 34, L12402.
Weismüller, J.; Wollschläger, U.; Boike, J.; Pan, X.; Yu, Q. and Roth, K. (2011): Modeling the
thermal dynamics of the active layer at two contrasting permafrost sites on Svalbard and on
the Tibetan Plateau. The Cryosphere 5 (3), pp. 741–757.
Wesley, L.D. (2010): Fundamentals of soil mechanics for sedimentary and residual soils. Hoboken (Wiley), ISBN: 978-0-470-37626-3.
Westermann, S.; Wollschläger, U. and Boike, J. (2010): Monitoring of active layer dynamics at
a permafrost site on Svalbard using multi-channel ground-penetrating radar. The Cryosphere
4 (4), pp. 475–487.
Woo, Ming-Ko (2012): Permafrost Hydrology. 1 st edition. Berlin (Springer).
Woo, M.-K.; Kane, D.L.; Carey, S.K. and Yang, D. (2008): Progress in permafrost hydrology in
the new millennium. Permafrost Periglac. Process. 19 (2), pp. 237–254.
Wright, J.F.; Duchesne, C. and Côté, M.M. (2003): Regional-scale permafrost mapping using
the TTOP ground temperature model. Permafrost and Periglacial Processes, pp. 1241–1246.
Zhang, T.; Heginbottom, J.A.; Barry, R.G. and Brown, J. (2000): Further statistics on the distribution of permafrost and ground ice in the Northern Hemisphere. Polar Geography 24 (2),
pp. 126–131.
Zhang, Y.; Carey, S.K. and Quinton, W.L. (2008): Evaluation of the algorithms and parameterizations for ground thawing and freezing simulation in permafrost regions. J. Geophys. Res.
113 (D17).
Zhao, L.; Gray, D.M. and Male, D.H. (1997): Numerical analysis of simultaneous heat and mass
transfer during infiltration into frozen ground. Journal of Hydrology 200, pp. 345–363.
Zhou, Y. and Zhou, G. (2010): Numerical simulation of coupled heat-fluid transport in freezing
soils using finite volume method. Heat Mass Transfer 46 (8-9), pp. 989–998.
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