Introduction
How combinations of temperature increases and precipitation changes
affect the magnitude and timing of peak snowpack and annual runoff in
mountain basins is investigated in this sensitivity study. High
elevation mountain headwater basins are hydrologically important, as
they store water in the form of snowpack during winter and release it in
spring and summer (Barry, 1992; Bales et al., 2006), and, ecologically
important as they are key zones for biodiversity due to steep gradients
of air temperature, precipitation, and topography (Beniston, 2003).
Mountain snowpacks are sensitive to warming (Minder, 2010). Air
temperature changes exert important controls on the hydrology of basins
where snowmelt is the dominant hydrological process (Marks et al., 1998;
Pederson et al., 2011; Sospedra-Alfonso et al., 2015). The contribution
of mountain headwaters to the downstream discharge of rivers ranges from
35% in cold and humid river basins to 90% in hot and arid basins
(Viviroli and Weingartner, 2004). Mountains cover 25% of the Earth’s
land surface (Diaz et al., 2003) and 26% of the world population live
in high-elevation areas (Meybeck et al., 2001). The origin of discharges
from 50% of the world’s rivers are mountain headwaters (Beniston,
2003). Snowmelt volume and timing play a key role in freshwater
availability, flood control, and ecological sustainability of cold
region mountain environments (Stewart et al., 2004; Semmens and Ramage,
2013).
The higher sensitivity of snow and frozen soils to warming makes cold
region mountain basins, those with mean annual air temperatures near
0oC, suitable study areas for investigating climate
change impacts on the hydrological cycle (Barry, 1992; Bunbury and
Gajewski, 2012). Climate warming effects have been studied in some
mountain headwater basins (e.g., Cayan, 1996; Stewart et al., 2004;
Bales et al., 2006), and warming is expected to continue to threaten the
ecological and hydrological integrity of these regions (Malmqvist and
Rundle, 2002). Fyfe and Flato (1999) showed that elevation becomes
important to the pattern of climate change over western North America
only when a significant continental-scale warming dominates, and it is
not detectable in the early stages of climate change. Late winter and
spring temperatures have a key role in the responsiveness of mountain
basins to a warming climate and snowmelt runoff timing in regions with
near-freezing air temperatures (Stewart et al., 2004; McCabe and Clark,
2005; Rasouli et al., 2019a, 2020). Mote et al. (2005) reported that
climatic trends and not changes in land use and forest canopy affect
snowpack in western North America. A significant increasing temperature
trend, especially in minimum temperature, led to a reduction in number
of soil freeze days, earlier occurrence of plant-water stress, and a
strong seasonal shift in streamflow throughout 1962-2006 in the high
elevation Reynolds Creek Experimental Watershed, USA (Nayak, 2008).
A common approach for investigating the hydrological response to climate
change is to apply climate model projections under different greenhouse
gas emission scenarios and to downscale regional atmospheric
circulations obtained from the climate models to variables at local
scales using statistical or dynamical methods (e.g., Jasper et al.,
2004; Fowler et al., 2007; McDonald et al., 2010). Mountain
hydrometeorology, however, poses challenges to statistical and dynamical
downscaling methods. The assumption in statistical downscaling that the
predictor–predictand relationship is stationary and future
relationships will be the same as past ones (Wilby and Wigley, 1997)
does not guarantee that statistical downscaling approaches would perform
better than the delta change method (Hay et al., 2000; Fowler et al.,
2007; Kay et al., 2009; Sunyer et al., 2012). Dynamical models driven by
an ensemble of multiple boundary conditions have high computational cost
at the high resolutions needed in mountains and so usually neglect
uncertainty and also require bias correction to provide reasonable
forcings (Fang and Pomeroy, 2020). A realistic downscaling of
atmospheric variables shows a high sensitivity to the choice of
downscaling methods (Wilby et al., 2000). These limitations make
consideration of an alternative solution necessary for mountainous
regions.
As biases due to scale and parametrization issues have not yet resolved
by statistical and dynamical downscaling methods, the alternative
perturbation method also known as delta change factor method (e.g.,
Stockton and Boggess, 1979; Semadeni-Davies et al., 2008; Kawase et al.,
2009), can produce plausible hydroclimatological changes for the future.
The perturbation method represents the changes in climatology between
current and future climates for variables such as precipitation and air
temperature (Stockton and Boggess, 1979; Pomeroy et al., 2015; Rasouli
et al., 2019a, 2019b). The method retains the main hydrometeorological
processes present in historical measurements, whilst minimizing
computational resources. The perturbation method has been widely used;
however, its application has been limited to air temperature changes
factors (e.g., ∆T = ±2°C in Nayak, 2008; Pomeroy et al., 2015) and
precipitation change factors (e.g., ∆P = ±25% in López-Moreno et al.,
2016).
The sensitivity of snow processes to warming were studied in the
Canadian Rockies (Pomeroy et al., 2015) and Reynolds Creek, Idaho
(Rasouli et al., 2015). The snow and runoff sensitivities to
precipitation change and warming were studied in Wolf Creek, Yukon
Territory (Rasouli et al., 2014). This sensitivity study applies similar
sensitivity analyses to both snow and runoff regimes and in a comparable
way for physically based cold regions hydrological models representing
the three headwater basins that span much of the northern North American
Cordillera. More specifically, this research investigates how the
magnitude and timing of peak snowpack and annual runoff respond to
combinations of temperature increases (0 to 5°C) and precipitation
changes (-20, -10, 0, +10, and +20%). By considering 30 combinations,
applied to the three mountain headwater basins, the sensitivity of
hydrological responses to changes in forcings can be compared. This
increases the understanding of the relationships between changes in
forcing and model response in these basins. The main question addressed
is whether the impact of warming on mountain snow and runoff hydrology
can be offset by precipitation increases. This has not been resolved in
the literature (e.g., Arnell, 1999; Prowse et al., 2006, Luo et al.,
2008). The specific objective for this sensitivity analysis is to
quantify the response of simulated mountain hydrological processes to
changes in air temperature and precipitation associated with future
climate change.