Hydrological processes are widely understood to be
sensitive to changes in climate, but the effects of concomitant changes in
vegetation and soils have seldom been considered in snow-dominated mountain
basins. The response of mountain hydrology to vegetation/soil changes in the
present and a future climate was modeled in three snowmelt-dominated
mountain basins in the North American Cordillera. The models developed for each basin using the Cold Regions Hydrological Modeling platform employed current and expected changes to
vegetation and soil parameters and were driven with recent and perturbed high-altitude meteorological observations. Monthly perturbations were calculated
using the differences in outputs between the present- and a future-climate
scenario from 11 regional climate models. In the three basins, future
climate change alone decreased the modeled peak snow water equivalent (SWE)
by 11 %–47 % and increased the modeled evapotranspiration by 14 %–20 %.
However, including future changes in vegetation and soil for each basin
changed or reversed these climate change outcomes. In Wolf Creek in the
Yukon Territory, Canada, a statistically insignificant increase in SWE due to
vegetation increase in the alpine zone was found to offset the statistically
significant decrease in SWE due to climate change. In Marmot Creek in the
Canadian Rockies, the increase in annual runoff due to the combined effect
of soil and climate change was statistically significant, whereas their
individual effects were not. In the relatively warmer Reynolds Mountain in
Idaho, USA, vegetation change alone decreased the annual runoff volume by 8 %,
but changes in soil, climate, or both did not affect runoff. At high
elevations in Wolf and Marmot creeks, the model results indicated that
vegetation/soil changes moderated the impact of climate change on peak SWE,
the timing of peak SWE, evapotranspiration, and the annual runoff volume.
However, at medium elevations, these changes intensified the impact of
climate change, further decreasing peak SWE and sublimation. The
hydrological impacts of changes in climate, vegetation, and soil in mountain
environments were similar in magnitude but not consistent in direction for
all biomes; in some combinations, this resulted in enhanced impacts at lower
elevations and latitudes and moderated impacts at higher elevations and
latitudes.
Introduction
Under warmer, less snowy climates, vegetation and soil properties are
expected to change, which will result in evapotranspiration increases
(Beniston, 2003) and shifts in runoff patterns (Neilson and Marks, 1994).
Vegetation response to warming varies with climate (Stow et al., 2004).
Deforestation, afforestation, and disturbance to the vegetation composition
are other mechanisms that have widely changed the vegetation cover,
especially in mountainous environments. Bosch and Hewlett (1982) reviewed
the impacts of deforestation and afforestation on water yield in forested
landscapes and concluded that water yield increases in coniferous forests
(e.g., pine), deciduous hardwood forests, and shrubs with a reduction in
cover. Studies have also shown that the growth rates of trees have increased
(Innes, 1991), the forest composition (e.g., in the Pacific Northwest) has
changed (Dale and Franklin, 1989), and the treeline has moved vertically and
northward in the last century (Hansell et al., 1971). The major drivers of
vegetation change in western North America are climate, mountain pine
beetle, logging, and wildfires (Macias-Fauria and Johnson, 2009; Halofsky et
al., 2018).
At northern latitudes, where the air temperature is low, the growing season
is short, cloud cover is persistent, and the solar angle is small, the
vegetation composition responds quickly to changes in climate and nutrient
availability; with warming, rapid changes in thawing and freezing processes
(Zhang et al., 2008; Walvoord and Kurylyk, 2016), snowmelt rates, and soil
moisture (Bales et al., 2011) are expected. One example of how the
interaction between climate and vegetation can change ecosystems is the
expansion of shrubs in northern latitudes (Martin et al., 2017; Myers-Smith
and Hik, 2018). Warming degrades permafrost in northern mountains and leads
to shrub tundra expansion (Tape et al., 2006; Hallinger et al., 2010).
Increased shrub coverage traps more windblown snow, increases snowmelt
volumes, lowers spring albedo, and alters melt rates (Pomeroy et al., 2006;
Krogh and Pomeroy, 2018). Warming has also resulted in increases in the
height of the tundra community (Bjorkman et al., 2018). Many mountain plants
begin growth at near-freezing temperatures when snowpacks start to melt
(Billings and Bliss, 1959), and snow depth and snowmelt rates affect
vegetation composition (Billings and Bliss, 1959; Stanton et al., 1994). In
a warmer climate, the abundance of cold-adapted species decreases and
warmth-demanding vegetation expands into higher elevations (Lamprecht et
al., 2018); thus, plant communities shift to more northern latitudes (Alberta
Natural Regions Committee, 2006; Schneider et al., 2009; Mann et al., 2012;
Schneider, 2013; Myers-Smith and Hik, 2018).
Changes in vegetation can lead to changes in soil properties and important
local and global feedbacks in ecohydrological processes and energy budgets
(Osterkamp et al., 2009; Rawlins et al., 2009). Soil development, however,
may not occur as quickly as vegetation change (Innes, 1991), and soil
properties may vary from the initial phase of the colonization of the bare
surface to the establishment of a forest (Crocker and Major, 1955). In cold
regions in general, and mountains in particular, the amount and timing of
snowmelt affects vegetation type, soil moisture, nutrient transport, soil
and leaf temperature, surface microclimate, and growing season (Billings and
Bliss, 1959; Walker et al., 1993; Stanton et al., 1994; Callaghan et al.,
2011). Potential changes in soil, especially changes in the organic matter
content, can have just as important effects on soil moisture, permafrost,
infiltration, groundwater recharge, and runoff processes as climate,
hydrology, and vegetation change (DeBano, 1991; DeFries and Eshleman, 2004;
Osterkamp et al., 2009). Deforestation increases soil bulk density and
decreases soil porosity, both of which alter infiltration, percolation,
aeration, and erodibility (Reiners et al., 1994). Increased active layer
thickness over permafrost, as a result of the warming climate, allows more
subsurface water storage, higher nutrient transport, and a deeper root zone,
which is favorable for shrub expansion (Sturm et al., 2005). Because they
are interrelated but have an uncertain timing, it is important to consider – both separately and in combination –
the climate, vegetation, and soil changes that may
occur in future.
Simulations of future hydrological conditions in mountains are challenging
due to the large biases between climate model outputs and locally
observed hydroclimatic conditions as well as the seasonal nature of snow
accumulation and depletion (Fowler et al., 2007; Bennett et al., 2012). In
the climate perturbation method, also known as the delta change factor
method, (e.g., Rasouli et al., 2014, 2015), observations are perturbed using
the difference (delta) between modeled present and future climates. This
method avoids the computational cost of dynamical downscaling and
maintains consistency in relationships of the atmospheric fields, which may
be distorted in statistical methods if the interaction of the variables is
not considered (Hijmans et al., 2005; Gutmann et al., 2016). Unlike the direct use of regional climate model
(RCM) outputs, the perturbation approach produces spatial and
seasonal precipitation patterns based on observations, with the changes due
to differences between present and future simulated climate (Hay et al.,
2000; Kay et al., 2009; Sunyer et al., 2012). This represents weather with
reasonable accuracy and also represents observed extremes such as dry
periods and storms. Of particular importance for mountain hydrology is the realistic representation of
the dynamics of precipitation, its phase, and its increase with elevation. Limitations of applying monthly
climatological change factors to perturb the climate are that any future
changes in large-scale weather patterns and their impact on extremes, and
sequences of wet or dry spans are not adequately represented. This is
similar to the assumption of stationarity in the relationships between
large-scale circulations and locally observed data that are made in
statistical downscaling. Changes in synoptic dynamics of the atmosphere
cannot be captured by the climate perturbation method, nor can RCMs capture
local-scale processes in mountainous regions (Rasouli, 2017).
There have been many studies on the impact of climate change on hydrology
and some on mountain hydrology (e.g. Link et al., 2004; Flerchinger et al., 2012; Fang et al., 2013; Pomeroy et al., 2003, 2012, 2015; Rasouli et
al., 2014; Williams et al., 2015). The present study builds on the recent
understanding of the impact of climate perturbations on three headwater
basins in the North American Cordillera where future reduced snowfall
amounts are offset by reduced losses due to snow sublimation and increased
rainfall amounts are offset by increased evapotranspiration, together
leading to insignificant changes in annual runoff (Rasouli et al., 2019a).
However, there are fewer studies that focus on the impacts of land surface
changes on mountain hydrology. In most impact studies, changes in
vegetation, soil, and land surface are not well represented, and there is
limited knowledge about how the combination of climate, vegetation, and soil
changes impacts hydrological processes and basin-level discharge (Brown et
al., 2005).
Interactions between climate, vegetation, and soils are complex
(Rodriguez-Iturbe, 2000) and the time lag between vegetation response to
climate changes and soil response to climate and vegetation changes is
unclear (Innes, 1991). In a warmer climate, with a longer snow-free season,
and increased precipitation in northern latitudes, vegetation is expected to
increase where adequate soil moisture and nutrients permit. Therefore,
assuming there will be no change in vegetation in future climates introduces
uncertainty and possible errors in hydrological impact studies of climate
change. Modeling climate change effects on hydrology with and without
vegetation and soil changes can help to understand the separate and combined
effects of climate, vegetation, and soil changes in mountainous headwater
basins. Rasouli et al. (2019a) show that future climates are warmer and
wetter, especially in the northern latitudes, and that temperature and
precipitation changes have complex effects in snow-dominated watersheds.
Warmer and wetter future conditions are expected to drive vegetation, soil,
and hydrological changes, but such changes have not been thoroughly studied.
The objective of this study is to investigate the hydrological changes due
to climate perturbations, building on Rasouli et al. (2019a), and plausible
concomitant soil and vegetation changes, adapted from Alberta Natural
Regions Committee (2006), Schneider et al. (2009), and Myers-Smith and Hik (2018) for three instrumented headwater basins ranging from middle to high
latitudes in the North American Cordillera.
MethodsStudy sites and data sources
Three mountain basins ranging from middle to high latitudes in the North
American Cordillera are examined: a subarctic basin (Wolf Creek Research
Basin ∼61∘ N, Yukon Territory, Canada), a headwater
catchment in the Canadian Rockies (Marmot Creek Research Basin,
∼51∘ N, Alberta, Canada), and a small catchment
with a cool montane climate (Reynolds Mountain East catchment, hereafter
called Reynolds Mountain, ∼43∘,N, Idaho, USA) (Fig. 2). All three basins are located in transition climate zones based on the Köppen
climate classification (Köppen 1936). Wolf Creek has the shortest
distance to the Pacific Ocean (Fig. 1), the lowest average elevation, the coldest
climate, and the lowest annual precipitation amongst the three basins. Marmot
Creek has the highest elevation, the largest elevation range, and the highest annual
precipitation and wind speed. Reynolds Mountain has the smallest drainage
area, the highest average elevation, and the lowest wind speed (Table 1).
Vegetation, hydrography, topography, and meteorological
stations of the three headwater study basins: (a) Wolf Creek
Research Basin, Yukon Territory, Canada; (b) Marmot Creek Research
Basin, Alberta, Canada; and (c) Reynolds Mountain within the Reynolds
Creek Experimental Watershed, Idaho, USA.
Comparison of physiography and climatology amongst the
three basins. UC denotes the “Upper Clearing” meteorological station in the Marmot
Creek Research Basin.
Characteristics Wolf CreekMarmot CreekReynolds MountainLatitude 60∘36′ N50∘57′ N43∘11′ NLongitude 134∘57′ W115∘09′ W116∘47′ WDrainage area (km2) 1799.40.38Elevation range (m) 660–20801600–28252028–2137Record period 1993–20112005–20141983–2008Dominant vegetation cover High elevationTundra mossRock and grassGrass and sageMiddle elevationShrub tundraSpruce and firFirLow elevationSpruceLodgepole pineAspen and willowClimate zone Cordillera andCordillera, prairie,Cordillera, continentalsubarcticand borealand MediterraneanElevation bands 331Temperature (∘C) High elevation-3.4-1.85.0Middle elevation-2.01.0 (UC)–Low elevation-1.52.9–Number of freezing days High elevation224217120Middle elevation203166 (UC)Low elevation179128Precipitation (mm) 3801011858Wind speed (m s-1) 3.75.81.9Relative humidity (%) 746961Number of subbasins & HRUs 5 & 294 & 361 & 12HRU area range (km2) 0.92–25.40.01–1.370.01–0.07
Jack pine, spruce, and aspen forests are the dominant vegetation types at low
elevations in Wolf Creek (Francis et al., 1998), and 65 % of the basin area
above the forest biome is covered with birch and willow shrub tundra with
heights ranging between 30 cm and 2 m. Alpine tundra with short moss, grass,
and bare rock covers high elevations in Wolf Creek. Engelmann spruce and
subalpine fir cover high elevations and lodgepole pine stands cover low
elevations in Marmot Creek (Kirby and Ogilvie, 1969). Areas adjacent to the
treeline in Marmot Creek are covered with shrubs and alpine larch. The
alpine zone is composed of grass, moss, and large areas of bare rock. The
spatial variability of vegetation is large within the Reynolds Mountain area
(Seyfried et al., 2009; Winstral and Marks, 2014), and grass, mountain
sagebrush, riparian willow, aspen, and coniferous trees are the dominant
vegetation types in this basin. Almost 43 % of Wolf Creek is covered by
continuous and discontinuous permafrost (Lewkowicz and Ednie, 2004). Soils
do not freeze in Reynolds Mountain and freeze seasonally in Marmot Creek.
Precipitation was measured using a tipping-bucket rain gauge, an unshielded “BC-style standpipe”, and Nipher-shielded storage gauges in Wolf Creek, using an
Alter-shielded Geonor storage gauge in Marmot Creek, and using shielded and
unshielded storage gauges in Reynolds Mountain. Snowfall observations were
adjusted using wind undercatch correction equations (Goodison et al., 1998;
Smith, 2009) based on wind-shield and wind speeds measured at gauge height.
Air temperature, humidity, wind speed, shortwave radiation, and streamflow
were measured and stored at hourly time steps for each basin. Suitable
driving meteorological time series from these observations were available
for 1993–2011 in Wolf Creek, 2005–2014 in Marmot Creek, and 1983–2008 in
Reynolds Mountain. Long-term datasets and descriptions of the variables for
each basin were published by Reba et al. (2011), Fang et al. (2019), and
Rasouli et al. (2019b).
Modeling strategy
As described in Rasouli et al. (2019a), a distinctive distributed
hydrological model for each basin was developed on the Cold Regions
Hydrological Modeling platform (CRHM; Pomeroy et al., 2007). The models
represent the major hydrological mechanisms in cold regions and those found in
these basins, including snow transport and redistribution by wind, snow
interception, snow sublimation, sub-canopy radiation, energy balance
snowmelt, mass and energy balance evapotranspiration, infiltration, and
runoff over frozen and unfrozen soils (e.g., Pomeroy et al., 1999; MacDonald
et al., 2009). Parameters for modeling each hydrological process were
obtained from field measurements in the basins or similar basins following
the deduction–induction–abduction approach outlined by Pomeroy et al. (2013). The models were discretized into hydrological response units (HRUs)
that are spatially segregated based on hydrological function and parameter
as defined by vegetation type, elevation, slope and aspect, soil depth, soil
layers, hydrography, and the variability of basin attributes. The CRHM
models were run at hourly time steps (Table 1). Details on model
parametrization and performance are available in Rasouli et al. (2014, 2015)
and Rasouli (2017).
Schematic illustration of the vegetation cover under the base
case and future climate, vegetation, and soil (ΔCVS) in the Wolf Creek
Research Basin, the Marmot Creek Research Basin, and Reynolds Mountain. Dark
shading indicates areas where changes to the soil are expected in future. The
numbers show the areal percentage of the alpine, forest, shrub tundra,
grassland, and forest clearing biomes. ΔT, ΔP, and ΔSWE are from Rasouli et al. (2019a).
Description of the eight cases of change in climate,
vegetation, and soils.
ClimateVegetation and soil caseNotation usedActual changein textPresentPresent vegetation and present soilBaseNo changePresentFuture vegetation and present soilΔVOnly vegetationPresentPresent vegetation and future soilΔSOnly soilPresentFuture vegetation and future soilΔVSBoth vegetation and soilFuturePresent vegetation and present soilΔCOnly climateFutureFuture vegetation and present soilΔCVBoth vegetation and climateFuturePresent vegetation and future soilΔCSBoth soil and climateFutureFuture vegetation and future soilΔCVSClimate, vegetation, and soil
Eight change cases were used to differentiate the individual and combined
effects of changes in climate (ΔC), vegetation (ΔV), and
soils (ΔS) from the present conditions (base case). The vegetation
and soil changes applied are conceptualized in Fig. 2 and summarized in
Table 2. The effects of vegetation and soil changes on snow regimes and
hydrological variables were evaluated under conditions in which: (1) climate
does not change, but vegetation and/or soil changes occur (ΔVS), (2) climatic conditions change but no changes in future vegetation and/or soil
occur (ΔC), and (3) changes in future climate will be accompanied by
vegetation and soil changes (ΔCV, ΔCS, and ΔCVS).
Porosity and soil depth are expected to change as a result of vegetation and
climate change. The specific vegetation and soil changes applied in each
watershed were different based upon the current understanding of likely
future terrestrial ecosystems in each of these three basins. In Wolf Creek,
the vegetation changes were an upslope movement of the treeline and
expansion of shrub tundra into former sparse tundra in response to a warmer
and wetter climate (Fig. 2a). In Marmot Creek, the changes were an upward
movement of the treeline, afforestation of areas harvested in the 1970s and
1980s, and deforestation of the lower elevations due to fire and disease in
a warmer climate (Fig. 2b). In Reynolds Mountain, the changes were
deforestation of all trees (aspen, fir, and willow) and expansion of mountain
sage due to a warmer climate with persistent water deficits. Other
combinations of these vegetation changes in the three basins were explored
to examine hydrological uncertainty due to various terrestrial ecosystem
trajectories; they produced similar results and are not presented here.
Changes in the organic layer of soils following vegetation changes can alter
the soil characteristics, including soil macropores and, hence, alter
snowmelt and rainfall infiltration, thawing and freezing processes, recharge into groundwater, and runoff mechanisms. The soil porosity in different soil
layers and soil depth were two soil model parameters that were altered to
bring the changed soil characteristics in line with those currently
associated with vegetation and land cover types (Fig. 2).
Hydrological model parameters that represented the current vegetation cover
and soil characteristics in forest, shrub tundra, grass, sage, and alpine
tundra were determined using field measurements in each basin. To represent
soil change and vegetation conversion from one type to another in the model,
the area being converted was added to or subtracted from an existing HRU
with that vegetation and soil type, or parameters (vegetation, soil, or both)
were modified in the converted HRUs. HRUs were altered to represent three
different changes (i) vegetation change only, (ii) soil change only, and
(iii) both vegetation and soil change.
Perturbed observations
Monthly perturbed climates were constructed from a downscaling method
applying delta changes in monthly climatology to base case hourly
meteorological observations from various elevations in the research basins;
see Rasouli et al. (2019a) for details. The monthly perturbation was
determined from the results of 11 regional climate models from the North
American Regional Climate Change Assessment Program (NARCCAP), which are
driven by outputs from multiple global climate models (GCMs) for the SRES A2
emission scenario (Mearns et al., 2007). Using observed data modified by the
monthly delta gives an estimate of the potential climate change impacts on
these driving forces consistent with large-scale atmospheric
circulations. The deltas used were the difference between the simulated
current monthly 30-year climatology (1971–2000) and the future (2041–2070)
monthly 30-year climatology (2041–2070) for 11 RCMs (Rasouli et al.,
2019a).
Significance testing
Significant changes and differences in water balance components, snow
characteristics, and their timing (initiation date, peak SWE date, snow-free
date, and duration of snow cover season) between simulations under the
present period (base case) and simulations under different cases of changes
in climate (ΔC), vegetation (ΔV), and soil (ΔS) were
assessed using a nonparametric Mann–Whitney U test (Wilcoxon, 1945; Mann
and Whitney, 1947). The differences between simulated distributions in the
modeled present period for n years (x1:11×nc, 11×n
values) and the simulated distributions in the modeled future periods,
obtained for 11 RCMs (x1:11×nf, 11×n years),
were determined (18 for Wolf Creek, 8 for Marmot Creek, and 25 for Reynolds
Mountain). Assessment of the changes in the hourly SWE distribution due to
vegetation changes was carried out using a nonparametric two-sample
Kolmogorov–Smirnov test (Massey, 1951). This test evaluates the difference
between the cumulative density functions of the hourly SWE in the present
period and a climate or vegetation alternative. The confidence interval in the plots is based upon the standard deviation of the results for the 11 RCMs
and the years of observations in each watershed.
The Tukey honestly significant difference test
An analysis of variance (ANOVA) was used to determine if there was a case
that was different from the others. This test, however, does not provide
information on the pattern of differences between the means of the eight
cases (Table 2). The Tukey honestly significant difference (HSD) test (Tukey, 1991) is a
widely used test to analyze the pattern of difference between means using
pairwise comparisons. In the pairwise comparisons, the significant
difference between a pair of means is determined using a statistical
distribution that gives the exact sampling distribution of the largest
difference between a set of means originating from the same population (Abdi
and Williams, 2010). In this test, groups that are statistically different
based upon paired comparison are labeled “a”, “b”, and so on, and are ordered by
mean from lowest to highest. Using an analysis of variance on
the annual differences between the modeled future and the modeled base
case and the Tukey HSD test for each basin,
differences in snow and runoff under the four groups of the eight cases were
determined (Table 2).
ResultsSynergic effects of climate, vegetation, and soil changes on
snow and runoff regimes
Changes in simulated peak SWE and annual runoff volume due to vegetation,
soil, and their interaction in the present climate (ΔV, ΔS,
and ΔVS) were compared with the modeled present (base case; no
changes in climate, vegetation, and soil) to determine the effect of
individual or combined changes. Similarly, changes in simulated peak SWE and
runoff due to changes in vegetation, soil, and their interaction in the
future climate were compared with future-climate change as well as the
present climate. In total, four cases under the present climate and four
cases under the future climate were studied and statistical differences,
based on the Tukey HSD test, were
distinguished from the modeled present; all cases were then classified into
multiple groups for each variable (Figs. 3, 4, 5).
Differences in peak snow water equivalent (SWE) and
annual runoff volume under seven combinations of changes in climate,
vegetation, and soil in the Wolf Creek Research Basin relative to present
climate, present vegetation, and present soil with no change (base). Lower
case letters from the Tukey HSD test indicate groups that are significantly
different from each other. The unshaded cases on the left-hand side of the
plot demonstrate changes under modeled present climate, and the shaded
cases on the right-hand side of the plot demonstrate vegetation and soil
changes under modeled future-climate cases.
In Wolf Creek (Fig. 3), the peak SWE declined significantly with ΔC (group “a”) in the alpine biome (Fig. 3a), and increased
insignificantly with ΔV and ΔVS in the present climate. Peak
SWE decreased significantly with ΔC, ΔCV, ΔCS, and
ΔCVS (groups “a” and “b”) in the shrub tundra biome (Fig. 3b),
and did not change significantly with any combination of vegetation change and
climate change in the forest biome (all eight cases are in group “a”)
(Fig. 3c). In the alpine biome within Wolf Creek, the effect of increasing
alpine vegetation on increasing peak SWE (Fig. 3a) is not statistically
significant by itself, but it was sufficient to offset the significant decrease
in SWE from climate change. In contrast to the forest biome SWE in Wolf
Creek, which is not affected by any changes (Fig. 3c), and to the alpine
biome, where combined changes counteracted each other, the decrease in peak
SWE in the shrub tundra biome due to climate change is intensified with
concomitant vegetation change (Fig. 3b). Soil changes do not affect peak SWE
in Wolf Creek. The annual runoff volume in Wolf Creek decreases
significantly with ΔV, ΔS, and ΔVS change cases in
the present climate and increases significantly for the future climate
ΔC, and ΔCS cases (Fig. 3d). The decrease in annual runoff
with soil and vegetation changes (ΔV, ΔS, and ΔVS) in
the present climate (groups “a” and “b”) is offset by the increases in
runoff with climate change (group “d”), such that the combined effects of
climate, vegetation, and soil change (ΔCV and ΔCVS) on runoff
in Wolf Creek are not different from the base case of current conditions.
Differences in peak snow water equivalent (SWE) and
annual runoff volume under seven combinations of changes in climate,
vegetation, and soil in the Marmot Creek Research Basin relative to present
climate, present vegetation, and present soil with no change (base). Lower
case letters from the Tukey HSD test indicate groups that are significantly
different from each other. The unshaded cases on the left-hand side of the
plot demonstrate changes under modeled present climate, and the shaded
cases on the right-hand side of the plot demonstrate vegetation and soil
changes under modeled future climate.
In Marmot Creek (Fig. 4), the high-elevation alpine biome peak SWE showed
no significant response to vegetation and/or climate changes (all eight
cases are in group “a”, Fig. 4a). In the forest biome, peak SWE declines
with climate change (ΔC; group “a” vs. base case group “b”,
Fig. 4b). In the forest clearing and treeline biomes (Fig. 4d, e),
there are significant decreases in peak SWE under ΔV and ΔVS;
in the forest clearing, these significant decreases are also seen with climate changes and all case
combinations (groups “a” and b”, Fig. 4c and d). Soil changes alone
(ΔS) do not affect peak SWE in Marmot Creek. The annual runoff
volume in Marmot Creek decreases with ΔV and ΔVS and
increases with ΔCS (Fig. 4e). This counteracting behavior is evident
in the response of annual runoff to ΔC and ΔCVS, which is
not significantly different from the base case (all are in group “b”). In
contrast, the combined effect of climate and soil change (ΔCS –
“c” in Fig. 4e) is magnified from that of climate alone. Therefore,
soil–climate interactions (ΔCS) are more important in changing
annual runoff in Marmot Creek than the individual effects of soil and
climate and are counteracted by concomitantly changing vegetation.
Differences in peak snow water equivalent (SWE) and
annual runoff volume under seven combinations of changes in climate,
vegetation, and soil in the Reynolds Mountain area relative to present climate,
present vegetation, and present soil with no change (base case). Lower case
letters from the Tukey HSD test indicate groups that are significantly
different from each other. The unshaded cases on the left-hand side of the
plot demonstrate changes under modeled present climate, and the shaded
cases on the right-hand side of the plot demonstrate vegetation and soil
changes under modeled future climate.
In Reynolds Mountain (Fig. 5), the alpine biome peak SWE decreases
significantly under climate change (ΔC; group “a”, Fig. 5a).
Significant decreases in peak SWE occur with both vegetation and climate
change (groups “a” and “b”) in the respective forest biome (Fig. 5b), the
blowing wind sheltered zone (Fig. 5c), and the blowing snow sink zone (Fig. 5d). The peak SWE in all of the biomes in Reynolds Mountain shows
significant decreases under climate, vegetation, and under a combination of
the two (Fig. 5), except for the alpine biome, which shows a significant
decrease only due to climate change (Fig. 5a). Similar to the other two
basins, soil changes do not affect peak SWE in Reynolds Mountain. Climate change
(ΔC) and soil change (ΔCS) do not affect the annual runoff
volume, whereas vegetation change and combined vegetation and soil change
(ΔV and ΔVS, respectively) significantly decrease annual runoff (Fig. 5e).
Although the individual effect of soil change on runoff is not
statistically significant, its combined effect can enhance the effect of the
vegetation change in diminishing annual runoff from this basin (Fig. 5e).
Snow characteristics
Basin-scale snow regime characteristics including peak SWE, length of the
snow season, snow initiation date, mean annual peak SWE, and timing of
snow-free date were simulated for current and future climate, vegetation,
and soils in the three basins. Under the current climate, soil changes did
not affect snow regime characteristics, and vegetation changes only
decreased peak SWE in Marmot Creek (Table 3). Despite the decrease in the peak
SWE at the basin scale in Marmot Creek and for certain biomes in all basins,
the timing of the basin-scale snow season was found to be insensitive to
vegetation and soil changes under present climate in all basins (Table 3).
Soil modules do not affect snow calculations in the CRHM models, and so soil
changes do not affect snow regimes (Table 3, compare columns 2 and 3 as well as 4 and 5). The
basin-scale peak SWE is affected by both climate and vegetation changes, and
the changes are statistically significant based on the Mann–Whitney U test
(p values ≤0.05).
Simulated basin-scale snow characteristics under current
climate and future vegetation and soil for the three basins. Values in italic font denote significant changes with p values of less than 0.1. Changes
relative to current climate/vegetation/soil and are given in parentheses.
VariableCurrent climate,Current climateCurrent climateCurrent climate andcurrent vegetation,and Δsoiland ΔvegetationΔsoil and vegetationand current soil(1) Wolf Creek Peak SWE (mm)133133118–133 (-11 to 0)118–133 (-11 to 0)Initiation (date)555 (0)5 (0)Peak SWE (date)186186182–185 (-4 to -1)182–185 (-4 to -1)Snow-free (date)250250250–252 (0 to 2)250–252 (0 to 2)Season length (day)224224224–226 (0 to 2)224–226 (0 to 2)(2) Marmot Creek Peak SWE (mm)183183136–168 (–26 to –8)136–168 (–26 to –8)Initiation (date)999 (0)9 (0)Peak SWE (date)210210211 (1)211 (1)Snow-free (date)294294294–296 (0 to 2)294–296 (0 to 2)Season length (day)283283283–284 (0 to 1)283–284 (0 to 1)(3) Reynolds Mountain Peak SWE (mm)368368326–375 (-11 to 2)326–375 (-11 to 2)Initiation (date)353535 (0)35 (0)Peak SWE (date)161161162–168 (1 to 7)162–168 (1 to 7)Snow-free (date)246246247 (1)247 (1)Season length (day)211211212–213 (1 to 2)212–213 (1 to 2)First day ofOctNovDecJanFebMarAprMayJunJulAugSepDay of water year1326293124152183213244274305336
Simulated snowpack accumulation and ablation under
current climate and vegetation (base scenario) and changes due to climate
and vegetation changes at different elevation levels and in current biomes in
the Wolf Creek Research Basin, the Marmot Creek Research Basin, and Reynolds
Mountain. Reynolds Mountain only has one elevation band but multiple blowing
snow regimes. The 95 % confidence intervals shown by the shaded areas
indicate the interannual variability. The three vertical lines denote the first
days of March, April, and May, respectively.
Simulated snow characteristics under current and monthly
perturbed climate and future vegetation and soil in the three basins. Bold
and italic values denote significant changes with p values of less than 0.05
and 0.1, respectively. Changes, relative to current
climate/vegetation/soil, are given in parentheses. Dates are given in water
year days.
VariableBaseΔClimate, ΔClimate and ΔClimate and ΔClimate, current vegetation, and soil Δsoil Δvegetation Δsoil, and Δvegetation Mean5 %Mean95 %5 %Mean95 %5 %Mean95 %5 %Mean95 %(1) Wolf Creek Peak SWE (mm)13373118 (-11)15373118 (-11)15364107 (–20)14264107 (–20)142Initiation (date)507 (2)4707 (2)4707 (2)4507 (2)45Peak SWE (date)186143164 (–22)178143164 (–22)178148164 (–22)170148164 (–22)170Snow-free (date)250213235 (–15)248213235 (–15)248216236 (–14)249216236 (–14)249Season length (day)224160208 (–16)242160208 (–16)242164215 (–9)251164215 (–9)251(2) Marmot Creek Peak SWE (mm)183102141 (–23)170102141 (–23)17074106 (–42)13074106 (–42)130Initiation (date)9424 (15)62424 (15)62424 (15)63424 (15)63Peak SWE (date)210175200 (–10)216175200 (–10)216177205 (-5)223177205 (-5)223Snow-free (date)294257281 (–13)295257281 (–13)295257283 (–11)299257283 (–11)299Season length (day)283204248 (–35)277204248 (–35)277200246 (–37)276200246 (–37)276(3) Reynolds Mountain Peak SWE (mm)368105196 (–47)277105196 (–47)27791168 (–54)23791168 (–54)237Initiation (date)352050 (15)852050 (15)851949 (14)831949 (14)83Peak SWE (date)161102129 (–33)148102129 (–33)14896127 (–34)14996127 (–34)149Snow-free (date)246184213 (–33)232184213 (–33)232195220 (–26)236195220 (–26)236Season length (day)211113161 (–50)197113161 (–50)197129171 (–40)200129171 (–40)200First day ofOctNovDecJanFebMarAprMayJunJulAugSepDay of water year1326293124152183213244274305336
The difference between times series and their spread of the present and
future peak SWE modeled using driving meteorology from 11 regional
climate models (11×n values) for n=18 years for Wolf Creek, 9 years for Marmot Creek, and 25 years for Reynolds Mountain are shown in
Fig. 6 and Table 4. Peak SWE decreases from 133 mm under the current
climate to 118 mm (11 % decrease) under climate change and to 107 mm
(20 %) when vegetation change is considered in combination with climate
change in Wolf Creek. In Marmot Creek, peak SWE declines from the current
climate value of 183 to 141 mm (23 % decrease) under climate change and
to 106 mm (42 % decrease) under combined climate and vegetation change. An
increase in precipitation under climate change in the north and a large
vegetation change in Marmot Creek as well as its effect on accumulated snow lead to
similar future peak snowpacks in Marmot Creek and Wolf Creek. The peak SWE
in Reynolds Mountain decreases from 368 mm in the current climate to 196 mm
(47 % decrease) under climate change and to 168 mm (54 % decrease) under
combined climate and vegetation change. Considering only vegetation changes
under the current climate, the peak SWE decreases more in Marmot Creek
(26 %) than in Wolf Creek and Reynolds Mountain (11 %). Therefore, under
the combined climate and vegetation change studied in this research, the
maximum accumulated SWE is the most stable in Wolf Creek and most sensitive
in Reynolds Mountain.
The significant responses to vegetation change (ΔV in Figs. 3–5)
shows that vegetation change in all three basins has an important effect on
snow and runoff regimes, except for the snow regimes in the alpine and
forest biomes in Marmot Creek. Figure 6 shows the snowpack regimes in
various current biomes and at various elevations for the three basins under current (base),
changed climate (ΔC), changed vegetation (ΔV), and both changed
climate and vegetation (ΔCV) cases with shading to reflect interannual
variability. The simulated snowpack regimes for ΔC, ΔV, and
ΔCV are significantly (p value ≤0.05) different from the base
case in each biome shown in Fig. 6 (Kolmogorov–Smirnov test); however,
there are important variations in how they differ. With ΔV, SWE in
Wolf Creek develops a greater peak and ablates more slowly, and the
snow cover season becomes longer (Fig. 6a). This is mostly due to shrub
expansion into higher elevations under ΔV, which reduces blowing
snow transport and subsequent sublimation of blowing snow and also slows
snowmelt rates (Pomeroy et al., 2006). Changes in the rate of snowmelt can
be assessed by comparison of the slope of the curve during the ablation
period in Fig. 6. There is no change in the slope between the base case
and ΔCV in the alpine and forested biomes of Wolf Creek (Fig. 6a–c) or
in the alpine biomes of Marmot Creek (Fig. 6d); however, these slopes
decrease under ΔCV at the middle elevations in Wolf Creek, the lower
elevations in Marmot Creek, and at all elevations in Reynolds Mountain
(Fig. 6e–k), indicating a slower melt rate. Under ΔCV, the effect
of climate change on the alpine snowpack is moderated by the impact of the
shrub tundra expansion into high-elevation alpine tundra. However, at middle
elevations, shrubs are expected to be replaced by forest; therefore, under
ΔCV, the peak snowpack decreases from 156 to 127 mm (19 %
decrease, Fig. 6b). Vegetation change is expected to be negligible at low
elevations in Wolf Creek; therefore, the snowpack is only disturbed by
climate change impacts in these simulations (Fig. 6c).
In Marmot Creek, the anticipated advance of trees into alpine tundra causes a
small increase in the simulated peak SWE and slower ablation rates at high
elevations under the ΔV scenario (Fig. 6d). In contrast to greater
snowpacks with upward movement of the treeline (ΔV), climate change
alone (ΔC) slightly decreases peak SWE in the alpine biome. The treeline
acts as an important sink for blowing snow transport and accumulates deep
snowdrifts; thus, the effect of treeline movement out of the upper middle
elevations (ΔV) on reducing snowpacks is even greater than that of
climate change (ΔC; Fig. 6e). This is due to the suppression of
snow redistribution to the former treeline with afforestation and subsequent
sublimation of intercepted snow in newly forested needleleaf canopies, which
is enhanced by climate change (ΔCV). At low elevations, snow
accumulation decreases from 87 to 39 mm (48 mm) under combined climate
change and conversion of forest to shrub and grass (Fig. 6f). Forest
clearings currently store deep snowpacks; however, with regrowth of
harvested forest, the peak snow will decrease as intercepted snow
sublimation increases (Fig. 6g). Climate change has less impact than forest
regrowth in these harvested clearings. In Marmot Creek, the impact of
vegetation change on peak snowpack timing offsets the impact of climate
change. The date of the peak SWE is delayed with only ΔV and
advanced with only ΔC (Table 3).
In Reynolds Mountain, all blowing snow regimes except for the depressions
and valley bottom (Fig. 6i) will receive a more uniform SWE under ΔV
as the forest canopy disappears. Despite the small impact of vegetation
change in the alpine biome which is covered with grass and short mountain sages, the
impact of ΔC on the snowpack in this biome is large (Fig. 6h). The
forest biome in the Reynolds Mountain area is most sensitive to ΔCV, based on
a large decrease in the peak snowpack (Fig. 6j). The interannual variability
of SWE, which is expressed as 95 % confidence intervals in Fig. 6, becomes
smaller in all of the biomes within the three basins under climate
perturbation because the snowpack becomes shallower under ΔCV and
variability of the shallow snowpack becomes smaller. This can occur despite
an increased variability of precipitation under future climate
conditions. The interannual variability of SWE does not change in the alpine
biome under ΔV.
Snow regimes are the most resilient to ΔCV at high elevations in
Wolf Creek and Marmot Creek and low elevations in Wolf Creek, with less than a 10 % decrease in peak SWE. In contrast, snow regimes in the forest
clearings in Marmot Creek and in the forest and sheltered sites in Reynolds
Mountain are very sensitive to ΔCV, with 80 % and 68 %
decreases, respectively, due to the role of canopy changes enhancing climate
change impacts with respect to reducing SWE. Under ΔV, peak SWE drops from 87
to 46 mm (a 47 % decrease) at low elevations in Marmot Creek with the
conversion of forest into grassland. Impacts of ΔC on snow regimes
can be enhanced or dampened by the impact of ΔV. Shrub tundra
expansion into the higher elevations in Wolf Creek can substantially dampen
the impact of climate change on the snowpack because it suppresses blowing snow
transport and sublimation. However, forest expansion above the current treelines
or into forest clearings enhances ΔC impacts on the snowpack by
introducing the sublimation of intercepted snow. Therefore, the impact of
shrubification or afforestation on the snowpack can be as important as the
impact of climate change.
Precipitation phase
With warmer air temperatures and increased precipitation, snowfall events
become less frequent as the precipitation phase shifts from snowfall to
rainfall (Fig. 7). For the three basins (Fig. 7), and their biomes
(Fig. 8), the portion of total precipitation that is rainfall increases in
all of the basins under climate changes (vegetation change does not affect the
precipitation phase). Furthermore, annual rainfall rises to 238 mm from the
413 mm of annual precipitation (a rainfall ratio of 0.58) in Wolf Creek, 550 mm
from 1027 mm (a rainfall ratio of 0.54) in Marmot Creek, and 473 mm from
866 mm (a rainfall ratio 0.55) in Reynolds Mountain. For all of the
basins, the currently snowfall-dominated elevations, ranging between 650
and 2500 m, are expected to become more rainfall-dominated under climate
change.
Mean modeled water fluxes, in the (three) liquid,
vapor, and snow states, under current climate and current vegetation (base), future
climate and current vegetation (ΔC), current climate and future
vegetation (ΔV), and future climate and future vegetation (ΔVC) in the Wolf Creek Research Basin, the Marmot Creek Research Basin, and Reynolds
Mountain. Statistically significant differences in the climatological mean
of the simulated variables with p values of less than 0.05 are represented using bold and black values.
Mean modeled water fluxes, in the (three) liquid,
vapor, and snow states, on an elevation/vegetation basis under current climate and
current vegetation (base), current climate and future vegetation (ΔV), future climate and current vegetation (ΔC), and future climate
and future vegetation (ΔVC) in the Wolf Creek Research Basin, the Marmot
Creek Research Basin, and Reynolds Mountain. Statistically significant
differences in the climatological mean of the simulated variables with
p values of less than 0.05 are represented using bold and black values.
Snow transport and redistribution
The modeled snow redistribution due to blowing snow transport in and out of
the basin and transport between biomes within a basin is an important
component of the water budget that has been assessed in this study (Figs. 7, 8). Under ΔCV, the annual average blowing snow transport remains
unchanged in Wolf Creek, whereas it declines 14 mm (from 131 to 117 mm) in
Marmot Creek and 11 mm (from 24 to 13 mm) in Reynolds Mountain (Fig. 7).
Snow transport at high elevations in Marmot Creek declines 11 mm under
ΔC and increases 23 mm due to shorter fetches as the treeline moves
upslope with concomitant vegetation change (ΔCV). Therefore, the
impact of climate change in reducing snow redistribution from the alpine
biome in Marmot Creek is almost completely offset by vegetation change. At
lower elevations where the treeline current exists, snow transport decreases
56 mm under ΔC, likely due to higher threshold wind speeds for
transport and a shorter snow season. Snow transport in the valley bottom and the blowing snow sink regime in Reynolds Mountain, presently covered with a
willow forest, also decreases substantially from 79 to 37 mm (a 42 mm
decrease, p value ≤0.05) under climate change and deforestation (ΔCV).
Sublimation
The annual sublimation from all sources, including snow intercepted on the
canopy, snow surface, and blowing snow was examined under climate and
vegetation changes and is shown in Figs. 7 and 8. Sublimation from snow
intercepted on the canopy in Wolf Creek dominates the annual sublimation,
which is expected to increase in this basin as the treeline moves upward to
higher elevations. In Marmot Creek, annual sublimation increases 15 mm (Fig. 7, 119 to 134 mm) under ΔV but decreases 7 mm under ΔVC
(Fig. 7, 119 to 112 mm). The impact of vegetation on sublimation rates in
Reynolds Mountain is negligible, whereas climate change decreases sublimation
from 31 to 10 mm. Vegetation change enhances sublimation to varying
degrees in the different biomes of the three basins. Sublimation is
suppressed by increasing shrub tundra in higher elevations. However, ΔV causes sublimation to increase moderately in the Marmot Creek and Wolf Creek
basins due to enhanced sublimation of intercepted snow. Vegetation change
does not affect sublimation in Reynolds Mountain.
Evapotranspiration (ET)
ΔV also alters the annual evapotranspiration (ET). The simulations
show that, under ΔV, annual ET increases 28 mm (from 392 to 420 mm,
Fig. 7) as a result of afforestation of the clearings and upward movement
of the treeline in Marmot Creek. In contrast, ET decreases 14 mm in Wolf
Creek (from 130 to 116 mm, Fig. 7) and 18 mm in Reynolds Mountain (from
427 to 409 mm, Fig. 7). Increases in ET due to ΔC can be partially
offset by concomitant vegetation change in Wolf Creek and Reynolds Mountain.
ET increases the most in Marmot Creek, from 392 to 475 mm (83 mm,
p value <0.05), and the least in Wolf Creek, from 130 to 142 mm
(12 mm), under both vegetation change and climate change. Under ΔVC, ET
changes significantly in different elevation bands (Fig. 8). The increase
in ET due to ΔCV varies with elevation within each basin and reaches
23 mm at high elevations and 9 mm at low elevations in Wolf Creek, 61 mm at
low elevations and 249 mm at the treeline elevations in Marmot Creek, and 32 mm in the forest and 98 mm at the sheltered site in Reynolds Mountain (Fig. 8). This also shows the high variability of the annual ET amongst these
three basins.
Runoff characteristics
ΔV decreases the annual runoff volume in Wolf Creek, which counteracts the increasing effect of climate change on the annual runoff volume (Table 5, Fig. 3d). Changes in soil and vegetation decrease the annual runoff volume in
Marmot Creek (Table 5, Fig. 4e). With ΔVC, the annual runoff volume
decreases in Marmot Creek, while under combined climate–soil changes it
increases (Table 5, Fig. 4e). This shows that a combination of all factors,
vegetation, and soil changes have the largest, intermediate, and lowest effects, respectively,
and climate change has no effect on the annual runoff volume in Marmot Creek. In
Reynolds Mountain, change in annual runoff is evidenced only under current
climate and future vegetation (Table 5, Fig. 5e).
Simulated runoff characteristics including annual volume
under current and monthly perturbed climates and future vegetation in the
three basins. Bold and italic values denote significant changes with
p values of less than 0.05 and 0.1, respectively, based on a Mann–Whitney
U test. Simulated distributions with n=18 years for Wolf Creek, 9 years
for Marmot Creek, and 25 years for Reynolds Mountain over the present (base
case) period for each hydrological variable are compared with the simulated
future distributions obtained from 11 regional climate models
(11×n values). The percentage change, relative to the current
climate/vegetation, is given in parentheses.
Change caseWolf CreekMarmot CreekReynolds MountainNo changeBase246402371Future vegetationΔV228–262 (-7 to +7)336–373 (–16 to –7)340–379 (-8 to +2)Future soilΔS210 (-15)335 (–17)331 (-11)Future soil and vegetationΔVS173 (–30)411 (2)365 (-2)Future climateΔC286 (16)426 (6)375 (1)Future climate and vegetationΔVC265 (8)359 (–11)351 (-5)Future climate and soilΔSC250 (2)414 (3)342 (-8)Future climate, soil, and vegetationΔCVS282 (15)492 (22)368 (-1)Number of simulation years18925
Annual average hydrographs under present climate, present
vegetation, and present soil (base); present climate, future vegetation, and
present soil (ΔV); present climate, present vegetation, and future soil
(ΔS); present climate, future vegetation, and future soil (ΔVS);
future climate, present vegetation, and present soil (ΔC); future
climate, future vegetation, and present soil (ΔCV); future climate,
present vegetation, and future soil (ΔCS); and future climate, future
vegetation, and future soil (ΔCVS) in the three basins.
The average annual hydrographs for the present and future climate
simulations under vegetation and soil changes are shown in Fig. 9. With
ΔV, high flows are lower in all three basins, particularly in Wolf
Creek (Fig. 9a). ΔC causes the occurrence of high flows to be earlier in Wolf Creek
(Fig. 9b), leads to no change in Marmot Creek (Fig. 9d), and causes a shift to much
earlier high flows in Reynolds Mountain (Fig. 9f). Climate change (ΔC) and soil
change (ΔS) do not cause significant changes in the annual runoff
volumes in Marmot Creek and Reynolds Mountain, whereas in Wolf Creek climate
change (ΔC) increases and soil change (ΔS) decreases the
annual runoff volume (246 to 210 mm, Table 4, Fig. 3d). The combined effect
of climate–vegetation change (ΔCV) in these simulations advanced
the snow-free date by 14 d in Wolf Creek, 11 d in Marmot Creek, and 46 d in Reynolds Mountain and decreased the length of the snow cover season
by 9, 37, and 40 d in Wolf Creek, Marmot Creek, and Reynolds Mountain,
respectively (Table 4). ΔCV delayed the snow accumulation initiation
date by 15 d in Marmot Creek and 14 d in Reynolds Mountain. The
beginning of the melt season under ΔCV, measured from the timing of
peak SWE, advanced 22 d (4 April to 13 March) in Wolf Creek, and 34 d
(10 March to 4 February) in Reynolds Mountain (Table 4). The shift in the
timing of the melt season was reflected in the runoff timing (Fig. 9b,
f; Table 4).
Discussion
The interaction of vegetation, soil, and climate changes can either result
in large changes in snow and runoff regimes or they can offset the effect of one another.
For instance, an insignificant increase in peak SWE in the alpine biome in
Wolf Creek under ΔV can become important with concomitant climate
change in that it can offset the climate change effect under ΔCV
(Fig. 3a). ΔV decreases the annual runoff in Wolf Creek, whereas ΔC
counteracts the effect of vegetation change and increases the annual runoff
with ΔCV (Fig. 3d). The individual effects of soil change (ΔS) and
climate change (ΔC) on annual runoff in Marmot Creek are
statistically insignificant, but when they are combined (ΔCS), the
effect of the combination is enhanced, leading to a statistically
significant increase in the annual runoff volume (Fig. 4e). Therefore, the
increase in the annual runoff volume by climate change (ΔC) is offset by the
vegetation change effect (ΔCV) in Wolf Creek, and it is enhanced by
the soil change effect (ΔS) in Marmot Creek, whereas the effect of climate
change (ΔC) on annual runoff in Reynolds Mountain is not
significant, and vegetation change (ΔV) is the main driver of
the runoff changes in this basin. A decreasing effect of vegetation change
on annual runoff in Marmot Creek is offset by a combined soil and climate
change (ΔCVS and base are in the same group in Fig. 4e). This
suggests that not only climate change but also vegetation and soil changes
affect hydrological processes in cold regions, and small changes can trigger
significant hydrological changes if changes concur. Therefore, consideration
of all vegetation, soil, and climate changes in impact studies is necessary
(Pielke, 2005), especially in basins with near-freezing winter air
temperatures such as Reynolds Mountain, where vegetation–atmosphere
interactions are complex and nonlinear and can dampen or amplify climate
change (Bonan, 2008).
Similar to findings of Musselman et al. (2017) in the mountains of the
western USA and southwestern Canada, future snowmelt rates with combined
climate and vegetation change were found to be slower than the
present-climate rates in Reynolds Mountain and lower elevations in Marmot
Creek (Fig. 6f–k). In contrast, snowmelt rates under the combined effect of
climate change and anticipated shrub expansion into alpine tundra in Wolf
Creek (Fig. 6a) and upslope forest expansion in Marmot Creek (Fig. 6d)
remained similar to the present-climate rates. Shrub expansion into higher
elevations prolongs the snow season and increases peak SWEs, counteracting the
climate change impact on snowmelt. Therefore, relative to the base case, no
change in the future snowmelt was found under vegetation and climate changes
in cold and high-elevation environments. Although these snowmelt rates did not
decelerate under climate change as Musselman et al. (2017) found in warmer
environments, neither did they accelerate as found by Krogh and Pomeroy (2019) in a colder Arctic basin located 1000 km north of Wolf Creek.
Under combined climate and vegetation changes in Wolf Creek, the precipitation
and the rainfall ratio increase (Fig. 8), peak SWE declines (Table 4), ET and
sublimation increase (Fig. 8), and the snow season period shortens (Table 4),
which result in no change in annual total runoff (Fig. 3d). This implies
that the climate change effect that increases annual runoff in Wolf Creek is
offset by the vegetation change effect that decreases annual runoff, and the
increased precipitation effect is offset by the increased sublimation and ET effects in
this same region (Rasouli et al., 2019a). Unlike Wolf Creek, the annual runoff volume
declines under combined climate and vegetation changes (ΔCV case) in
Marmot Creek (Fig. 4e), which is due to significant decreases in sublimation
and snow transport and an increase in ET (Figs. 8, 9). The response of
simulated annual total runoff to climate and vegetation changes varies.
Annual runoff increases from Reynolds Mountain in the south to Wolf Creek in
the north under only climate as well as climate–soil changes, consistent
with the findings of Nijssen et al. (2001). Annual runoff increases with climate
change in Wolf Creek (Fig. 3d) and Marmot Creek (Fig. 4e), and decreases
with only vegetation or vegetation–soil changes in all three basins,
consistent with Bosch and Hewlett (1982), and with only soil changes in Wolf
Creek (Fig. 3e). Despite the snow regime in Reynolds Mountain, which is
sensitive to both climate and vegetation changes, only vegetation change
affects annual total runoff (Fig. 5e). Vegetation change moderates the
impact of climate change on ET to some extent by decreasing ET in Wolf Creek
and Reynolds Mountain (Figs. 7, 8). Under a combined climate and
vegetation change, ET increases in the three basins across the North
American Cordillera (Fig. 7). The response of the peak SWE to climate and
vegetation changes leads to a complex response of the annual runoff when the
soil and precipitation phase changes are also considered. Changes in runoff
characteristics become statistically significant when combined climate–vegetation–soil changes (ΔCVS) occur in Reynolds Mountain (Fig. 5e), climate–soil changes (ΔCS) occur in Marmot Creek (Fig. 4e),
and soil–vegetation changes (ΔVS) occur in Wolf Creek (Fig. 3e).
A deep snowpack is deposited at middle elevations in Marmot Creek due to
the strong winds, which scour blowing snow from the higher elevations to the
treeline (MacDonald et al., 2010). Under the simulations presented in this
paper and ongoing vegetation growth, alpine vegetation and shrubs in the
treeline will eventually convert to forest, which can change the snow regime
from a present-day blowing snow sink to a future forest with intercepted
snow on the canopy. A simulated snow regime change at middle elevations in
Marmot Creek leads to a substantial decrease in the maximum accumulated
snowpack (Fig. 4c). This is because of the shift in the forest role from
slowing snowmelt by shading the snow and sheltering the snow from wind to
accelerating midwinter snowmelt by removal of the forest canopy (Lundquist
et al., 2013). The peak SWE at low elevations also declines under future
deforestation and climate change in Marmot Creek (Figs. 4b, 7f). This
is because sublimation from blowing snow within the deforested portion of
the lower elevations becomes more important than sublimation from
intercepted snow on the canopy before deforestation. A higher sublimation
rate on the slopes with no vegetation cover has also been reported by Liston et
al. (2002). Furthermore, forest regrowth delays snow ablation because of the lower
net radiation under the canopy relative to clearings with no canopy (Gelfan
et al., 2004; Ellis et al., 2010). The impact of afforestation on the snowpack
in the forest clearings is stronger than that of climate change. Therefore,
an enhanced snowpack decline is expected in forest clearings under climate
and vegetation changes (Figs. 4c, 7g).
Sublimation losses do not only vary from one basin to another but vary among
the different elevation bands within each basin. For instance, at high
elevations in Wolf Creek, shrub tundra expansion enhances the sublimation by
increasing the snowpack. In contrast, both snowpack and sublimation decrease
under climate change. This shows that, in the alpine biome of Wolf Creek,
the impact of vegetation change on sublimation can be as important as the
impact of climate change and a combined climate and vegetation change leads to an
unchanged sublimation rate. At middle elevations in Wolf Creek, which are
currently covered by shrub tundra, a treeline shift into the shrub tundra biome
increases sublimation, whereas the opposite is true under climate change when
snowpack and sublimation both decrease. No changes are expected in the
sublimation at low elevations in Wolf Creek. Similar to Wolf Creek, the
impact of a combined climate and vegetation change on sublimation in Marmot
Creek varies with elevation. It causes an 8 mm decrease at high elevations
as a result of the upward movement of the treeline, a 12 mm increase in the
treeline blowing snow sink regime as shrubs turn to forest, and a 21 mm
decrease at low elevations as forest becomes uncovered and the snowpack becomes
shallower with warming. Different mechanisms are responsible for these
changes; annual sublimation decreases in the alpine biome with the upward
movement of the treeline as sublimation from blowing snow drops with upslope
forest expansion. At middle elevations, bushes are replaced by trees and
sublimation from intercepted snow on their canopy slightly increases. The
combination of topographic gradients and types of vegetation plays an
important role in snow redistribution and blowing snow sublimation. The
highest wind-driven redistribution of snow and the highest sublimation
occurs on leeward slopes, where there is little or no vegetation cover
(Liston et al., 2002). At low elevations in Marmot Creek, sublimation from
intercepted snow on the canopy decreases as deforestation occurs. This also
occurs in the deforested zone in Reynolds Mountain where sublimation
significantly decreases from 104 to 8 mm as a result of decreased
available snow combined with deforestation under climate change.
Shrub tundra expansion to higher elevations (Myers-Smith and Hik, 2018),
a community height increase (Bjorkman et al., 2018), and an increase in tree
growth rates (Innes, 1991) have shifted the windblown snow drifts into
higher elevations (Figs. 4a, 6a), which has offset the climate warming
effect on decreasing peak SWE in the alpine biome at Wolf Creek (Fig. 3a). A
20 %–60 % increase in tundra height is expected by the end of the century
(Bjorkman et al., 2018), which may change snow redistribution and soil
moisture availability in the higher latitudes. Despite a long snow cover
period at higher elevations with shrub tundra expansion, which may slow the
growth rate, snow insulates and warms the soil and increases the
productivity chance, leading to more expansion of warmth-demanding
vegetation types such as shrub tundra (Lamprecht et al., 2018). The balance
of these feedbacks in the future may depend on the changes in air
temperature, snow redistribution, and soil moisture, as well as their interactions
(Lawrence and Swenson, 2011).
In different biomes in each basin, the timing of the basin-scale snow cover
season was found to be insensitive to vegetation and soil changes under
present climate (Table 3). This result differs from other studies that have
found snow cover to be sensitive to vegetation on the prairies (Pomeroy and
Gray, 1994), in the Alps (Keller et al., 2005) and in shrub tundra (Pomeroy
et al., 2006). Biomes that are insensitive in our study are located at cold,
high elevations, where the snowpack is more resilient (Rasouli et al.,
2019a).
The simulation results presented here consider one future-climate scenario
(SRES A2) and generalized vegetation and soil changes that can be expected.
The simulations compare “snapshots” in time contrasting eight steady-state
conditions based upon a monthly climate perturbation that, in turn, is based upon RCM
projections which have preserved the past history of observed weather in these
three basins. Future weather may not necessarily resemble what has been
observed in the past. While steady-state conditions are useful for examining
the complex interactions between the effects of changes in climate,
vegetation, and soil, as presented here, transient models that could capture
the sequence of asynchronous changes in climate, vegetation, and soil, and
potential feedback are needed to fully understand the ongoing changes in
mountain watersheds.
Shifts in the timing of snow accumulation and snowmelt seasons have
important consequences and can change the timing, rate, and amount of
runoff in snow-dominated mountain basins (Callaghan et al., 2011). The
simulation results presented here demonstrate that the interactions of
changes in climate, vegetation, and soils are complex. Studies that consider
the future impacts of climate change should not exclude consideration of the
role of future vegetation.
Conclusions
Snow and runoff in three headwater mountain basins along the North American
Cordillera are vulnerable to changes in climate, vegetation, and soil. A
physically based semi-distributed hydrological model driven with monthly
perturbed climate based on observations and modeled changes in monthly
climatology was used to explore the effects of these changes. Changes in monthly climatology were obtained from 11
regional climate models. Climate changes, vegetation changes, and soil changes each
affect cold regions' hydrological mechanisms. The effects of vegetation
changes can be as large as those of climate change alone and decrease peak
SWE at middle elevations, as well as sublimation amounts. Shrub tundra expansion to
higher elevations in Wolf Creek shifted the windblown snow drifts into
higher elevations, which offset the climate warming effect on decreasing
peak SWE in the alpine biome. At high elevations, the impact of climate
change on peak SWE, snow transport in Reynolds Mountain, ET, and annual
total runoff is partially offset by the impact of vegetation change.
Simulations suggest that under both climate change and soil changes, annual
total runoff is expected to gradually increase from Reynolds Mountain in the
south to Wolf Creek in the north of the cordillera. With both vegetation and
soil changes, annual runoff will decrease. Simulations suggest that with all
three changes (climate, vegetation, and soil) annual runoff will decrease in
Reynolds Mountain, and remain unchanged in the Marmot and Wolf creeks.
The annual runoff volume decrease under soil change is larger than the
annual runoff volume increase under climate change in Wolf Creek.
Furthermore, the soil change has a more important role than the vegetation
change in decreasing runoff volume in Wolf Creek. To some extent, the
interaction of soil–climate changes moderates the counteracting
decreasing effect of soil change and the increasing effect of climate change on annual runoff volume. Interaction of soil–climate changes also has a more
important role in increasing the annual runoff volume than the effect of
climate change alone, soil change alone, or an interaction of all three soil–vegetation–climate changes in Marmot Creek. Further investigation in other mountainous
regions, especially in regions with near-freezing winter temperatures is
needed to better assess the impact of combined climate–vegetation–soil
changes. Mountain water resource systems that are vulnerable to warming and
land cover changes can be identified using the modeling strategy presented
here. Future vegetation and soil changes need to be considered, in addition
to a changing climate, to reduce the uncertainties regarding changing
mountain hydrology.
Data availability
Long-term datasets and descriptions of the
variables for each basin were published by Reba et al. (2011), Fang et al. (2019), and Rasouli et al. (2018, 2019b).
Author contributions
All three coauthors contributed to the
research design and writing the paper. KR developed the models
for Wolf Creek and Marmot Creek. JWP managed and supervised the research.
PHW helped with statistical analysis.
Competing interests
The authors declare that they have no conflict of interest.
Special issue statement
This article is part of the special issue “Understanding and predicting Earth system and hydrological change in cold regions”. It is not associated with a conference.
Acknowledgements
We thank Danny Marks of the United States Department of Agriculture and the late Rick Janowicz of Yukon Environment, who had a long-term commitment to operating and
providing the data for Reynolds Mountain and the Wolf Creek Research Basin,
respectively. The research funding sources include the Canada Research
Chairs program, the Natural Sciences and Engineering Research Council of
Canada through Discovery Grants, the Alexander Graham Bell Canada Graduate
Scholarship-Doctoral Program and Postdoctoral Fellowships, and the Changing
Cold Regions Network. We thank Xing Fang for help with the modeling of
Marmot Creek. The discussions and comments of Andrew Ireson and Lawrence Martz on an earlier draft of this paper are also appreciated, as are the helpful
comments and suggestions of the two anonymous reviewers.
Financial support
This research has been supported by the Natural Sciences and Engineering Research Council of Canada (grant nos. PDF 487795-2016 and CGSD3 – 459225-2014).
Review statement
This paper was edited by Sean Carey and reviewed by two anonymous referees.
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