Introduction
Arctic environments are warming at a faster rate than any other region
on earth. This warming is causing concentrated, rapid hydrological
changes such as increased freshwater discharge, earlier spring peak
flows, increased precipitation and thawing permafrost (Walvoord &
Kurylyk, 2016). Climate change influences almost every characteristic of
an Arctic watershed snow and rainfall precipitation distributions;
vegetation coverage; groundwater storage; permafrost and thawing depth
(Hinzman, Bettez, et al., 2005). Permafrost is defined as soil, rock or
other natural material that has been frozen for two or more consecutive
years (van Everdingen & Association, 1998). We refer to soils that are
frozen for less than two years or that thaw every summer, as seasonally
frozen soils. Permafrost has been reported to redirect the flow of
groundwater (Hinzman, Johnson, Kane, Farris, & Light, 2000). In this
context, the role of permafrost connecting and disconnecting groundwater
flow and river flow is especially vulnerable to climate change. Apart
from permafrost, seasonally frozen soil will likely impact these
connections as well. Understanding the effects of seasonally thawing
soils on river discharge could provide valuable insights into long-term
changes across transitions from permafrost to non-permafrost regions.
Moreover as 55-60% of the land surface in the northern hemisphere is
currently frozen during winter (Niu & Yang, 2006), with 23.9% of the
exposed land area underlain with permafrost (T. Zhang, Barry, Knowles,
Heginbottom, & Brown, 2008), understanding how seasonally frozen soils
affect the flow of water is crucial to predict hydrological responses to
a changed climate.
Based on a synthesis of multiple arctic terrestrial studies examining
arctic freshwater processes across different hydrophysiographical
regions, Bring et al., (2016) concluded that warming-induced increases
in the active layer thickness will likely lead to changes in the storage
capacity of groundwater thereby altering river flow dynamics. Walvoord
& Kurylyk, (2016) reviewed multiple arctic water flow models and showed
that while groundwater exchange and subsurface connectivity is predicted
to increase locally, these models are inconclusive on how surface
connectivity and river flow dynamics will change at basin scales.
Hinzman, Yoshikawa, & Kane, (2005) suggest that evapotranspiration in
the Arctic will increase as temperatures increase, leading to dryer
soils and lower river flows. Prowse et al., (2015) put forward that the
ecological transition, from tundra to boreal, is strongly hydrologically
mediated. All of these studies show there is no single dominant
permafrost thaw effect on the hydrologic cycle; instead several
interacting changes that exacerbate other changes to create complex
responses, which differ by region and are typically hard to predict.
Predicting such complex and interacting changes in the Arctic is one of
the key challenges in hydrology (Peel & Blöschl, 2011; Tetzlaff, Carey,
McNamara, Laudon, & Soulsby, 2017). Therefore, observation based
approaches are crucial to reveal the ongoing change trajectories,
identify dominant processes and build reliable models that can project
change trajectories into the future. Although still considered sparse,
river discharge is the most commonly available observation throughout
the Arctic (Laudon & A. Sponseller, 2017) and contains integrated
signals of watershed processes affected by Arctic warming (Bring et al.,
2016). In this study, we aim to quantify long-term trends in how
watersheds release water (i.e. trends in watershed storage-discharge
relationships) throughout Northern Sweden and evaluate if these trends
can be attributed to changes in the spatial extent and timing of frozen
soils.
Several studies have previously investigated long-term trends in
storage-discharge relationships in the Arctic (Bogaart, Van Der Velde,
Lyon, & Dekker, 2016; Brutsaert, 2008; Lyon & Destouni, 2010; Lyon et
al., 2009; Sjöberg, Frampton, & Lyon, 2013; Watson, Kooi, & Bense,
2013). Typically, these studies assumed linear storage-discharge
relationships during winter baseflow conditions and found that
groundwater flows more easily (i.e. resistance to flow reduces) into
rivers with more pronounced Arctic warming. Lyon et al. (2009) related
such changes to an increased active aquifer depth of between 0.7-1.3
cm/y in Northern Sweden. Still, under non-base flow conditions (i.e.
following a rainfall or snowmelt event) the relationship between river
discharge and water storage is typically nonlinear (Brutsaert & Nieber,
1977; Kirchner, 2009; Wittenberg & Sivapalan, 1999), and cannot easily
be related to active flow depths (Bense, Ferguson, & Kooi, 2009).
However, under wetter conditions even more pronounced effects of frozen
soils on river discharge are expected as seasonal frost hampers
infiltration of melt and rainwater into the deeper groundwater, and
impacts groundwater outflow into rivers (Ploum et al, 2019; Walvoord &
Kurylyk, 2016). Frozen soils are expected to seasonally alter the
hydrological connectivity within watersheds by redirecting water
dominantly through shallow (above the frozen layer) and deep flow routes
(below the frozen layer) towards rivers (Ploum et al., 2019). A change
in hydrological connectivity typically alters the functional form of the
storage-discharge relationship (i.e. degree of non-linearity) (Lyon &
Destouni, 2010).
How does the hydrologic response of Arctic and sub-Arctic watersheds
change as the climate warms and the extent of frozen soils recedes?
Following up on the study of Ploum et al., (2019), we expect that under
thawed conditions deep groundwater, shallow groundwater and overland
flow paths all contribute to discharge, while under frozen top soil
conditions, shallow flow paths are dominant, although deep groundwater
can still contribute. This increase in flow path diversity is expected
to occur over both the long-term as permafrost thaws and summer active
layer increases with a warming climate, as well as on a seasonal
timescale when seasonal frozen soil thaw starts earlier as spring occurs
earlier. Previous studies have shown when catchments become wet and the
diversity of flow routes increases, increasingly non-linear storage
discharge relations are observed (Brutsaert & Nieber, 1977).
Based on these studies, our hypothesis is that as seasonally frozen
soils thaw and recede, flow path diversity and thus hydrologic
connectivity increases, thereby increasing the non-linearity of the
storage-discharge relationship. In this current study, our objective is
to test and expand on this hypothesis by quantifying trends and
spatio-temporal differences in storage-discharge relationships for
sixteen watersheds within Northern Sweden throughout the years of 1950
and 2018. Northern Sweden, has had strong temperatures increases from
the start of the 1800’s to the 2000’s of almost 0.1°C/decade, with a
cooling period occurring between 1940’s to 1970’s (Klingbjer & Moberg,
2003). Multiple proxies for seasonal and intra-annual differences in
extent and depth of frozen soils are used to test whether the observed
trends and patterns in storage-discharge relationships can be related to
thawing soils.
Methods
Concepts: Recession analysis, storage-discharge relationships, and
frozen soils.
Recession analysis is a well-established hydrologic method to examine
storage-discharge relationships of watersheds and also offers the
advantage of being relatively insensitive to meteorological forcing
(Tallaksen, 1995). Recession analysis relates the rate of decline of
river discharge to the absolute river discharge (recession curve). Under
the assumption of a unique relationship between storage, discharge and a
closed water balance, recession curves quantify the storage-discharge
relationship (Brutsaert, 2008; Kirchner, 2009). Therefore recession
curves can be used to better understand the watershed storage-discharge
relationship’s response to climate change, connecting changes in
subsurface groundwater flow with changes in surface flows (Ploum et al.,
2019; Shaw & Riha, 2012; Wrona et al., 2016).
Recession curves are typically quantified by fitting a nonlinear
storage-discharge relationship to hydrograph recessions during periods
when changes in discharge reflect changes in catchment water storage
(Brutsaert & Nieber, 1977; Kirchner, 2009; Ploum et al., 2019).
\(\frac{\text{dQ}}{\text{dt}}=-Q\frac{\text{dQ}}{\text{dS}}\approx-\alpha Q^{\beta}\)(1)
Here, we extend eq. 1 to alleviate the constrains of no-rain and
no-evapotranspiration conditions, which allows us to include and account
for periods with small amounts of precipitation and evapotranspiration
relative to discharge.
\(\log\left(-\frac{\text{dQ}}{\text{dt}}\right)-\log\left(1+\frac{E}{Q}-\frac{P}{Q}\right)=\log\left(\alpha\right)+\beta\ log(Q)\)(2)
Q is discharge of the river [mm/d], dQ/dt is the rate
of discharge decline during the recession [mm/d/d], P is
precipitation [mm/d] and E is evapotranspiration [mm/d].dQ/dS is the sensitivity of discharge [d-1]
(Kirchner, 2009). In recession analysis, the hydrograph recession is
typically plotted in a recession plot with\(\log\left(-\frac{\text{dQ}}{\text{dt}}\right)-\log\left(1+\frac{E}{Q}-\frac{P}{Q}\right)\ \)against\(\ \log\left(Q\right)\) (Equation 2). When Eq.2 is fitted to
the data in this log-log plot, \(\alpha\) represents the intercept\({[mm}^{1-\beta}d^{\beta-2}]\), and \(\beta\) is the
slope of the recession curve [-]. This technique has been applied to
many regions to further understanding of the groundwater and river
discharge relationship (Brauer, Teuling, Torfs, & Uijlenhoet, 2013;
Dralle, Karst, Charalampous, Veenstra, & Thompson, 2017; Lyon et al.,
2015).
Watershed scale recession slopes of rivers can be conceptually
interpreted as a measure of hydrologic connectivity as illustrated by a
series of buckets (Figure 1). A watershed with one dominant flow path
where discharge increases linearly with storage behaves similar to a
bucket with a single spigot representing a linear reservoir (\(\beta\) ≈
1) (Figure 1). Observed examples are watersheds with a deeply incised
river during baseflow conditions, a confined aquifer below permafrost,
or shallow water flow above a frozen soil (Brutsaert & Hiyama, 2012;
Lyon & Destouni, 2010; Ploum et al., 2019). In a drained unconfined
aquifer both the pressure as well as the saturated thickness control
flow (Troch et al., 2013). Such a system can be represented by a bucket
with multiple evenly distributed equally sized spigots (flow paths):
flow not only depends on the pressure exerted by storage on the spigots
but also by the number of spigots. Such a bucket behaves as a nonlinear
reservoir with β = 1.5. A bucket with increasing number of
spigots or increasing size of spigots towards the surface will haveβ > 1.5. Examples are found in (Kirchner,
2009), (Karlsen et al., 2019) and (Brauer et al., 2013). A special case
is when the resistance of the spigots decreases exponentially towards
the surface yielding an exponential reservoir (\(\beta\ \)= 2). This is
frequently observed in relatively flat catchments (e.g. Bogaart et al.,
2016; Brauer et al., 2013). Reservoirs where the resistance declines
hyperbolically towards the surface yield β > 2.
Several examples are found in literature (Brutsaert & Nieber, 1977;
Kirchner, 2009; Troch et al., 2013).
Figure 1
Recession analysis has been used to examine the rate of thawing
permafrost, (Brutsaert, 2008; Lyon & Destouni, 2010; Lyon et al.,
2009). Brutsaert (2008) focused on baseflow winter (i.e. frozen)
conditions when the recession slope (β) can be assumed 1 (linear
reservoir). Lyon & Destouni, 2010 used coefficient α (assuming β = 1)
to infer aquifer thickness during late summer, when the active layer
extend is maximum in permafrost soils. However, under spring and early
summer conditions, we expect that the spatial heterogeneity of actively
thickness and hydrological connectivity between aquifers challenges the
assumption of linear reservoir behavior (β = 1). Therefore, we focus on
temporal changes in recession slope (β ) during spring and summer,
which we relate to changes in hydrological connectivity using the
interpretation of Figure 1. The spring and summer periods are later
separated in order to untangle effects of seasonal soil frost and
permafrost on river recessions, with spring period having potential
seasonal soil frost and summer as the period with the greatest active
layer and without/less seasonal soil frost.
Study Sites and data
Our study sites are situated in Northern Sweden. The sixteen watersheds
were chosen because of expected presence of regions with permafrost in
the past and present (Brown et al., 1997; Gisnås et al., 2017; Zhang et
al., 1999), widespread occurrence of seasonal frozen soils and no
current or past known obstruction of the waterways by human intervention
following Sjöberg et al. (2013).