A large portion of the freshwater in western Canada originates as snowpack from the northern Rocky Mountains. Temperature and precipitation in the region control the amount of snow accumulated and stored throughout the winter, and the intensity and timing of melt during the spring freshet. Therefore, trends in temperature, precipitation, snow accumulation, and snowmelt over western Canada are examined using the Mann-Kendall non-parametric test and an original geographic information system (GIS)-based approach to trend analysis on a newly produced high-resolution gridded climate dataset for the period 1950–2010. Temporal and spatial analyses of these hydroclimatic variables reveal that daily minimum temperature has increased more than daily maximum temperature, particularly during the cold season, and at higher elevations, contributing to earlier spring melt. Precipitation has decreased throughout the cold season and increased in the warm season, particularly in the northern half of the study area. Snow accumulation has decreased through all months of the year while snowmelt results indicate slight increases in mid-winter melt events and an earlier onset of the spring freshet. This study provides a summary of detected trends in key hydroclimatic variables across western Canada regarding the effects these changes can have on the spring freshet and streamflow throughout the region.

INTRODUCTION

The world's freshwater reserves fluctuate widely by season and region due to variations in climate, which is a major controlling factor of the hydrological cycle. The availability of water resources at a regional scale is one of the most important aspects of climate change related to the modification of the hydrological cycle. Water is extremely important for both society and nature, and understanding how changes in climate can affect regional water supplies is crucial for water resources planning. Numerous changes have already been linked to rising air temperatures, including increasing atmospheric water vapour content and the resulting changes in precipitation patterns, snow cover reductions, melting of ice, and fluctuations in runoff and soil moisture (Bates et al. 2008). Therefore, examining the linkages between hydrologic and climatic variables, such as temperature, precipitation, snow accumulation, and snowmelt, can supply additional insight into the causes of observed trends in river flow. Study of spatial and temporal variations in trends of hydrologic and climatic variables will provide a better understanding of what changes have already occurred.

Much of the river flow in western Canada originates as mountain snowpack, particularly from the northern Rocky Mountains, which form the headwaters of some of North America's largest river systems: the Mackenzie River, the Saskatchewan River and the Columbia River. The Mackenzie River is the main North American river that transports freshwater to the Arctic Ocean (Woo & Thorne 2003). The freshwater inflow to the Arctic is an important factor in determining ocean convection in the sub-Arctic seas. Any alteration to the Arctic or sub-Arctic hydrological cycle can lead to changes in the amount of freshwater reaching the Arctic Ocean and thus the freshwater budget of the Arctic Ocean, which may have implications for global thermohaline circulation (Holland et al. 2007; Min et al. 2008). Flow from rivers such as the Saskatchewan and Columbia is critical to water-resource use, particularly in the dry, prairie interior of the mid-west. Given that these are primarily nival river regimes, and 50–80% of the annual flow volume is supplied by springtime melt of the winter snow accumulation, any climate-induced changes that affect the magnitude of their alpine snow accumulations, or the timing and volume of their subsequent melt, can have widespread downstream implications (Stewart et al. 2005). For example, if snowmelt occurs earlier, it will likely decrease summer-autumn flows, extend summer drought in downstream dry regions and, because of lower flows and higher water temperatures, stress aquatic ecosystems (e.g., Stewart 2009). The boundaries between these major watersheds are in close proximity, so the spatial distribution of snowfall and snowmelt can determine whether snowmelt contributes to the Mackenzie, Saskatchewan or Columbia rivers. Any north-south or east-west shifts in temperature and precipitation can have major effects on where the snowfall and snowmelt occur, and thus what water resources are available in each region.

Hydroclimatic changes have been previously documented for western Canada, though research has primarily focused on annual or seasonal changes for small regions (individual watersheds) or at coarser scales (Canada or Mackenzie River basin) (e.g., Moore & McKendry 1996; Zhang et al. 2000; Zhang et al. 2001a; Woo & Thorne 2003; Vincent et al. 2007; Burn 2008). These previous studies provide valuable information on individual river systems and watersheds or very large continental-scale regions, but this approach does not provide insight into hydroclimatic changes that modify the spatial distribution of rainfall and snowfall between the drainage basins of western Canada, and thus regional water availability in these major river systems. A geographic information system (GIS)-based approach to mapping the locations of trends that occur throughout multiple months in a particular season has not been previously done, and can help identify areas that have experienced consistent increases or decreases in a more specific manner than using a more regionalized approach. Given the heterogeneous changes to surface climate regimes in western Canada, this type of approach is necessary to evaluate hydroclimatic trends and variability within sub-basins of large watersheds to determine ‘water rich’ and ‘water poor’ regions as well as directional shifts in precipitation and snowfall patterns.

This study is part of the Climatic Redistribution of Western Canadian Water Resources (CROCWR) project, which was designed to quantify past, current, and potential future changes to water distribution in Canada. The analysis includes several individual studies that focus on evaluation of a series of hydroclimatic variables including atmospheric circulation patterns, hydroclimatic variables affecting streamflow, and streamflow (Prowse et al. 2013; Newton et al. 2014a, 2014b; Bawden et al. 2015). Water resources are essential for hydroelectricity generation, agricultural production, municipal and industrial use, and ecological integrity. Ever increasing demands for freshwater throughout the twenty-first century require better understanding of the effects of climate variability and change and the changes they can cause for streamflow in western Canada. Therefore, results from the CROCWR study will be invaluable to water resource managers and policy makers.

This research investigates the temporal and spatial variations in hydroclimatic conditions across western Canada. This involves meeting two primary objectives: (1) assess annual and monthly historical trends in hydroclimatic variables affecting river flows in western Canada using newly produced high resolution interpolated, gridded climate data (temperature, precipitation, snow accumulation, and snowmelt) for the time period 1950–2010; and (2) assess spatial variation and consistency in historical trends of the above hydroclimatic variables across western Canada. The variables chosen for study were selected for their strong influence on streamflow, particularly the spring freshet.

Study area

The study area for this project covers western Canada, from the west coast of British Columbia to western Manitoba and from the Canada–United States border to the Mackenzie River Delta in the northernmost reaches of continental Canada. This includes the Saskatchewan, Mackenzie, Fraser, and Columbia River Basins, and several small basins that drain coastal and southern British Columbia to the Pacific. A companion study (Bawden et al. 2015) has identified a series of hydrometric stations that correspond to distinct hydro-climatic regions contained within the study area. The study area is based on drainage areas of 37 hydrometric stations, but these are amalgamated into 8 study regions for analysis (Figure 1(a)).
Figure 1

(a) Map of study area, grey outlines indicate study watersheds, while coloured polygons show study regions used in analysis. (b) Hypsometric curves of each study region.

Figure 1

(a) Map of study area, grey outlines indicate study watersheds, while coloured polygons show study regions used in analysis. (b) Hypsometric curves of each study region.

The climate in western Canada is largely controlled by the Pacific-Decadal Oscillation (PDO) and El Niño-Southern Oscillation (ENSO). These teleconnections affect temperature and moisture availability and variability throughout the study area on a multi-decadal scale (Stewart 2009). This study area incorporates a variety of climatic regions, including prairie, mountain and northern permafrost areas. Much of this area exists within the alpine region, with the remainder at lower elevations in the boreal plains or prairies (Figure 1(b)).

The Mackenzie River basin covers several climatic regions, including cold temperate, mountain, sub-arctic, and arctic zones (Woo & Thorne 2003). The Liard River basin, Peace River basin, Athabasca River basin, and Great Slave-Upper Mackenzie region are all contained within the Mackenzie basin (Leconte et al. 2006; Burn 2008). The Peel River converges with the Mackenzie near the delta to create the Peel River-Lower Mackenzie region. The Saskatchewan River Basin includes the North and South Saskatchewan Rivers, which are fed by headwaters originating as glacier and snow melt in the Rocky Mountains (Cohen 1991). The Fraser River receives flow from snowmelt in spring, glacier melt in summer, and some rainfall throughout the year (Thorne & Woo 2011). The Columbia River Basin covers parts of seven western states and part of British Columbia, and a large portion of the flow is obtained from the Northern Rocky Mountains (Payne et al. 2004; Pederson et al. 2011). The smaller basins draining to the Pacific consist of several rivers with small watershed areas that drain the coastal mountainous areas of British Columbia. The landscape in this region consists of steep-sided fjords and valleys with mountain peaks, alpine ice fields, and glaciers occurring at high elevations (McCuaig & Roberts 2002).

DATA AND METHODS

Daily temperature and precipitation were obtained from a newly produced ANUSPLIN-generated dataset that covers Canada for the period 1950–2010 with a spatial resolution of 10 km × 10 km, known as the NRCan 2012 dataset (Hutchinson et al. 2009; McKenney et al. 2011). These data incorporate the effects of elevation in their calculation of point values. This dataset was chosen for its high spatial resolution and temporal coverage, its daily resolution, and temperature and precipitation variables. This was the only available dataset that provided gridded data produced from observed values over the entire study area at a daily timestep over a long historical period. It is the best available dataset for this study, and has been tested and shown to be a quality data product by Hutchinson et al. (2009) and McKenney et al. (2011), though it may not be as accurate over very high elevations and data sparse regions (Bussieres & Milewska 2010).

Data analysis was conducted on a monthly basis to identify month to month variation in the selected hydroclimatic variables and to determine trend consistency through multiple months. However, results were discussed and spatially analyzed on a cold/warm season basis. The cold season was defined as November through April with the warm season covering May to October. The cold season covers most of the snow accumulation through to the spring break-up across most of the study area, with the warm season including the end of break-up in the north through the dry summer months to the beginning of freeze-up. The seasons vary slightly across the study area due to variations in elevation as well as the large range of latitudes; however, the definitions were chosen to represent the cold and warm halves of the year throughout the majority of the study area and to allow comparison with companion studies by Newton et al. (2014a, 2014b) and Bawden et al. (2015).

Watershed delineation

Watershed delineations for the eight study regions named in Figure 1 were created based on a series of latitude-longitude points that correspond to the selected hydrometric stations from Environment Canada's HYDAT database. ArcHydro was used to delineate the contributing areas for each hydrometric station. ArcHydro is an object-oriented model that is capable of establishing a topological network that includes flow direction, connectivity and upstream/downstream relationships of stream segments using a digital elevation model, a stream network, and points to distinguish watershed outlets (Fürst & Hörhan 2009).

Modelling snowpack data

For this study, a temperature-index model was utilized to calculate snow accumulation and snowmelt. The primary advantage to using a temperature-index model is the wide availability of both daily temperature and daily precipitation data in addition to generally accurate model performance comparable to results obtained from energy-balance models (Gray & Prowse 1993; Hock 2003; Jost et al. 2012). The model assumed precipitation occurring at temperatures below 0 °C to be snow and added the amount to the snowpack in the form of snow water equivalent (SWE), while temperatures above 0 °C were considered to cause snowmelt (Bavera et al. 2012). Both snow accumulation and snowmelt were reported in millimeters of SWE as an accumulated total amount per month.

Due to varying topography and climatic regions in the study area, multiple snowmelt equations were employed in the snowmelt model. The melt equations are specific to differing regions and time periods, and were employed only in the regions for which they are calibrated (mountains of western Canada using Equation (1), midseason boreal snowmelt using Equation (2), period of major melt for boreal forest using Equation (3), and prairie snowmelt using Equation (4)) (Gray & Prowse 1993). The melt equations were used to calculate potential melt in millimeters, then compared to the daily average temperature value to determine whether or not the snowmelt was deducted from the snow pack.

Atmospheric conditions, topography, geographical location, properties of the snow cover, and occasionally time of year all modify the snowmelt properties and so many variations on the snowmelt equation exist. Gray & Prowse (1993) identified multiple snowmelt equations specific to differing regions in North America. The following equations were used in this study.

For the mountainous region of western Canada: 
formula
1
 
formula
 
formula

For boreal forest regions:

midseason snowmelt equation for boreal forest: 
formula
2
period of major melt equation for boreal forest: 
formula
3
For prairie regions: 
formula
4
where M is the meltwater depth in millimeters, Tm is the daily mean air temperature in °C, Tmax is the daily maximum air temperature in °C, and Tmin is the daily minimum air temperature in °C (Gray & Prowse 1993). These snowmelt equations are each calibrated for a specific region for a time period within the range of dates used in this study, and were therefore the best available at the time of analysis. However, due to changing conditions throughout the study area they may require recalibration for use in the future.

Trend detection

The Mann-Kendall non-parametric test (MK) is one of the most widely used non-parametric tests to detect significant trends in hydrological and meteorological time series (Mann 1945; Kendall 1975). The MK test is often paired with the Sen's slope estimator (Sen 1968), to calculate an estimate of the slope of the linear trend line. This test was selected for trend analysis of the NRCan 2012 temperature and precipitation data as well as the corresponding modeled snow accumulation and snowmelt data, and the results were then used to determine rate of change per decade using Sen's slope method to obtain the direction and magnitude of the trend in degrees centigrade per decade or millimeters per decade.

Spatial analysis and interpolation

Each individual 10 × 10 km pixel of the gridded temperature, precipitation and associated snow accumulation and snowmelt time series were analyzed for trends using MK and Sen's slope estimator, and then results were mapped over the study area (Farmer et al. 2009). The calculated trend values were then averaged by study region to obtain zonal means of rate of change for each variable annually as well as monthly.

Following the temporal analysis on each data point, the point files were converted to raster format for visual interpretation using Inverse Distance Weighting (IDW), with parameters chosen to minimize interaction between points. Interpolation methods, particularly simple methods like IDW, tend to work best and have the least error when used with datasets with even, dense sample distributions (Babish 2006), such as the NRCan 2012 dataset.

Trend consistency was also tested through the reclassification of each monthly interpolated trend map into increasing/decreasing values. This was accomplished by changing all statistically significant (10% or better) increasing trend values to the value of 1 and all other values to 0 or changing all decreasing trend values to the value of 1 and all other values to 0 then adding multiple month layers together to view increasing/decreasing trend consistency. This was done on a cold season/warm season basis for the study area.

RESULTS AND DISCUSSION

Daily maximum and minimum temperature

Mean annual air temperatures across western Canada generally range from −15 °C to 15 °C. Mean daily maximum temperature (Tmax) and daily minimum temperatures (Tmin) for the time period 1950–2010 are shown in Figure 2(a) and 2(b) and summarized by study region in Table 1.
Table 1

Regional annual averages and rates of change for the four hydroclimate variables, from 1950 to 2010. Regional averages include all calculated trend values for the time period 1950–2010

Study region Peel River-Lower Mackenzie Great Slave-Upper Mackenzie Liard River Peace River Atha-basca River Saskat-chewan River Fraser-Columbia Basins Pacific Basins 
Annual averages 
 Daily maximum temperature (oC) −2.7 −1.1 2.0 5.5 4.5 8.1 8.1 4.5 
 Daily minimum temperature (oC) −12.4 −10.7 −9.0 −5.6 −6.6 −4.1 −3.5 −5.2 
 Annual precipitation total (mm) 309.7 309.1 486.7 497.9 455.8 448.3 721.5 819.3 
 Annual snow accumulation total (mm SWE) 155.9 134.4 200.7 182.5 141.8 119.4 320.9 387.0 
 Annual snowmelt total (mm) 156.8 133.9 198.9 181.2 141.0 118.3 316.9 387.7 
Calculated trends 
 Daily maximum temperature (oC/decade) 0.5 0.4 0.4 0.4 0.4 0.3 0.2 0.2 
 Daily minimum temperature (oC/decade) 0.6 0.4 0.4 0.4 0.4 0.4 0.4 0.5 
 Precipitation trend (mm/decade) −0.2 −0.6 13.1 −9.7 0.6 0.4 12.6 16.3 
 Snow accumulation trend (mm SWE/decade) −2.3 −3.7 −8.8 −9.0 −6.7 −6.4 −5.8 −10.0 
 Snowmelt trend (mm/decade) −2.3 −3.6 −8.5 −8.8 −6.6 −6.3 −5.5 −9.9 
Study region Peel River-Lower Mackenzie Great Slave-Upper Mackenzie Liard River Peace River Atha-basca River Saskat-chewan River Fraser-Columbia Basins Pacific Basins 
Annual averages 
 Daily maximum temperature (oC) −2.7 −1.1 2.0 5.5 4.5 8.1 8.1 4.5 
 Daily minimum temperature (oC) −12.4 −10.7 −9.0 −5.6 −6.6 −4.1 −3.5 −5.2 
 Annual precipitation total (mm) 309.7 309.1 486.7 497.9 455.8 448.3 721.5 819.3 
 Annual snow accumulation total (mm SWE) 155.9 134.4 200.7 182.5 141.8 119.4 320.9 387.0 
 Annual snowmelt total (mm) 156.8 133.9 198.9 181.2 141.0 118.3 316.9 387.7 
Calculated trends 
 Daily maximum temperature (oC/decade) 0.5 0.4 0.4 0.4 0.4 0.3 0.2 0.2 
 Daily minimum temperature (oC/decade) 0.6 0.4 0.4 0.4 0.4 0.4 0.4 0.5 
 Precipitation trend (mm/decade) −0.2 −0.6 13.1 −9.7 0.6 0.4 12.6 16.3 
 Snow accumulation trend (mm SWE/decade) −2.3 −3.7 −8.8 −9.0 −6.7 −6.4 −5.8 −10.0 
 Snowmelt trend (mm/decade) −2.3 −3.6 −8.5 −8.8 −6.6 −6.3 −5.5 −9.9 
Figure 2

Annual means and trends in daily maximum (Tmax) and minimum (Tmin) temperatures during 1950–2010: (a) mean annual Tmax in °C; (b) mean annual Tmin in °C; (c) mean annual Tmax trend in °C/decade; and (d) mean annual Tmin trend in °C/decade. Only trend results statistically significant at 10% or better are shown, white areas indicate no significant trends.

Figure 2

Annual means and trends in daily maximum (Tmax) and minimum (Tmin) temperatures during 1950–2010: (a) mean annual Tmax in °C; (b) mean annual Tmin in °C; (c) mean annual Tmax trend in °C/decade; and (d) mean annual Tmin trend in °C/decade. Only trend results statistically significant at 10% or better are shown, white areas indicate no significant trends.

Tmax and Tmin have changed at the rate of 0.2 °C to 0.6 °C per decade over the time period 1950–2010 when averaged over each study region. The greatest Tmax trends are located in the northern portions of the study area, particularly the Peel, Liard, and Peace Rivers, with lower rates of change in the remaining regions (Figure 2(c)). Tmin trends are greatest in the mountainous regions in the western half of the study area, with increases of 0.7–1. 2 °C/decade (Figure 2(d)). Nearly all statistically significant trend results are positive, and cover 95% and 99% of the study area for Tmax and Tmin, respectively. This indicates that widespread statistically significant warming has occurred throughout nearly the entire the study area. These results are consistent with other recent studies (e.g. Zhang et al. 2000; Vose et al. 2005; Bates et al. 2008; Vincent et al. 2015), though they show a greater spatial continuity of statistically significant trends due to the use of gridded data. The regional trend averages for both Tmax and Tmin are summarized in Table 1. The regional trend values appear to be similar across the study area, but there are variations within each study region not captured by viewing only regional averages.

Monthly trend results using daily average Tmax and Tmin were averaged across each of the eight study regions and are given in Figure 3(a). The greatest Tmax and Tmin trends occurred during the cold season, particularly January and February, with the highest trend values located in the Liard, Peace and portions of the Peel region (Figure 3(b)). Throughout the cold season, trends are generally greater in the northern regions of the study area, particularly the Peel, Liard, and Peace regions. Many of the trend values for Tmin are greater than those for Tmax, and the greatest warming occurs during the cold season, with lower trend magnitudes during the warmer months.
Figure 3

(a) Monthly average Tmax and Tmin for each month spatially averaged for each study region. Tmax shown with solid symbols and lines, Tmin shown with unfilled symbols and dashed lines. (b) Spatially averaged regional rate of change in monthly mean Tmax and Tmin. Results include all calculated trend values. Tmax shown with solid symbols, Tmin shown with unfilled symbols.

Figure 3

(a) Monthly average Tmax and Tmin for each month spatially averaged for each study region. Tmax shown with solid symbols and lines, Tmin shown with unfilled symbols and dashed lines. (b) Spatially averaged regional rate of change in monthly mean Tmax and Tmin. Results include all calculated trend values. Tmax shown with solid symbols, Tmin shown with unfilled symbols.

Trend consistency also varied spatially and temporally throughout the year. Increasing trends in Tmax during the cold season are concentrated in the Upper Peace and Liard, as well as the Peel region (Figure 4(a)). These areas exhibit increasing Tmax trends for 4–6 months across 70% of the study area while the remainder shows increasing trends for 1–3 months during the cold season. Tmin trends show slightly more consistency when compared to cold season Tmax trends, with 73% of the study area having experienced 4–6 months of increasing trends. Increases in Tmin throughout the cold season are most concentrated at elevations above 1,000 m, in the western half of the study area, from southern British Columbia in the Fraser-Columbia to the Peel region (Figure 4(c)). These high elevation areas experienced increasing trends through 5–6 months of the cold season. The remainder of the study area shows consistency of increasing trends for about 3–4 months with some small areas showing trend consistency of only 1–2 months. There were very few statistically significant decreasing cold season trends that occurred throughout multiple months (not shown).
Figure 4

Trend consistency maps where colour corresponds to number of months with increasing trend through the cold season (November–April) or the warm season (May–October). (a) Tmax increasing trend consistency through the cold season. (b) Tmax increasing trend consistency through the warm season. (c) Tmin increasing trend consistency through the cold season. (d) Tmin increasing trend consistency through the warm season. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/nh.2016.057.

Figure 4

Trend consistency maps where colour corresponds to number of months with increasing trend through the cold season (November–April) or the warm season (May–October). (a) Tmax increasing trend consistency through the cold season. (b) Tmax increasing trend consistency through the warm season. (c) Tmin increasing trend consistency through the cold season. (d) Tmin increasing trend consistency through the warm season. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/nh.2016.057.

The warm season shows far fewer Tmax trends that occur through multiple months when compared to the cold season. Increasing trends are located in small patches throughout the study area with some small areas showing increasing trends through 3–5 months (Figure 4(b)). The majority of consistently increasing trends in Tmin occur in the western half of the study area (Figure 4(d)). Most of British Columbia experienced increasing Tmin trends throughout 4–6 months of the warm season, with scattered patches of trends through the rest of the study area, for 39% coverage of the total area. There were very few statistically significant decreasing warm season trends that occurred in multiple months, so they are not shown.

Precipitation

Mean annual precipitation varies across western Canada ranging from 1,200 to 1,800 mm/year in the west to 100 to 300 mm/year in the north, and 300 to 700 mm/year in the interior portions of the study area (Figure 5(a) and Table 1).
Figure 5

Precipitation average annual total and annual trends for 1950–2010. (a) Average annual precipitation in millimeters; (b) annual precipitation trend in mm/decade. Only trend results statistically significant at 10% or better are shown, white areas indicate no significant trends.

Figure 5

Precipitation average annual total and annual trends for 1950–2010. (a) Average annual precipitation in millimeters; (b) annual precipitation trend in mm/decade. Only trend results statistically significant at 10% or better are shown, white areas indicate no significant trends.

Statistically significant annual precipitation trends cover 30% of the study area and range from −10 to +16 mm/decade over the time period 1950–2010, or −0.2 to 2.7% of the annual total precipitation, when averaged over each study region. However, unlike temperature, each region contains widely varying trends (both increasing and decreasing significant trends), thus resulting in average trends near zero in some regions. Increasing precipitation rates occur mostly in higher elevation areas, with values up to 50 mm/decade in areas above 1,000 m, specifically in the southern Rocky Mountains and decreases of 10–30 mm/decade east of the Rocky Mountains in the headwater regions of the Peace, Athabasca, and Saskatchewan regions (Figure 5(b) and Table 1).

Given the large intra-annual variation in precipitation, analysis at a monthly scale provides additional insight into the composition of the annual trends. Monthly precipitation ranges from 10 to 97 mm across each of the eight study regions (Figure 6(a)). The highest amounts occur during the warm season, with values of 13–75 mm in all study regions, with the exception of the more coastally influenced Pacific region, where the greatest precipitation amounts fall during the cooler months of the year, with values up to 97 mm per month.
Figure 6

(a) Spatially averaged regional precipitation totals for each month. (b) Spatially averaged rate of change of monthly total precipitation in mm/decade, from 1950 to 2010. Results include all calculated trend values.

Figure 6

(a) Spatially averaged regional precipitation totals for each month. (b) Spatially averaged rate of change of monthly total precipitation in mm/decade, from 1950 to 2010. Results include all calculated trend values.

Monthly precipitation patterns have experienced a combination of increasing and decreasing trends between 1950 and 2010, which vary greatly depending on time of year and location. Results show decreases during the cold season in most regions, with the majority of trends between 0 and −5 mm/decade (Figure 6(b)). Trends in the Liard, Athabasca and Saskatchewan regions show decreases of 4–13% each month between November and February when trends are compared to monthly total precipitation. During the warm season precipitation increases up to 4 mm/decade were located throughout the study area, with the highest trends located in the northern regions of the study area in the Liard, Peace, and Pacific regions. Trends in the Liard region show increases of 4–7% each month between May and September when trends are compared to monthly totals. Similar patterns of precipitation change were detected by Vincent et al. (2015).

Throughout the cold season, decreasing trends occur in most months over a large portion of the study area (Figure 7(a)). Areas with detected decreases through 4–6 months include the Athabasca, Peace, Liard, and Saskatchewan regions, with 17% coverage of the total area. 58% of the remainder of the study area experienced 2–3 months of decreasing trends. There are very few increasing trends during the cold season, with only the small areas of high elevation in the Pacific and Fraser-Columbia regions experiencing increasing trends for 2–3 months of the cold season.
Figure 7

Trend consistency maps where colour corresponds to number of months with increasing or decreasing trend through the cold season (November–April) or the warm season (May–October), (a) decreasing precipitation trend consistency through the cold season, (b) increasing precipitation trend consistency through the warm season. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/nh.2016.057.

Figure 7

Trend consistency maps where colour corresponds to number of months with increasing or decreasing trend through the cold season (November–April) or the warm season (May–October), (a) decreasing precipitation trend consistency through the cold season, (b) increasing precipitation trend consistency through the warm season. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/nh.2016.057.

The warm season experienced very few decreasing trends while increasing trends during this season occur with much more consistency. Six percent of the study area experienced increasing trends through 4–6 months, these trends are primarily located within the Liard River (Figure 7(b)). Increasing trends through 2–3 months, covering 14% of the study area, are also located in the eastern Athabasca, Pacific, and southern Fraser-Columbia regions during the warm season. Warm season trends do not occur consistently throughout the southern half of the study area, but are primarily located throughout the north.

Snow accumulation

Annual snow accumulation computed over western Canada ranges from 0 up to 700 mm SWE with the highest values of 500–700 mm SWE in the coastal and Rocky mountain ranges, and values of 150–300 mm SWE at the middle elevations, and the lowest values of 70–140 mm SWE at lower elevations and in the Prairies (Figure 8(a) and Table 1).
Figure 8

Mean annual snow accumulation and trends for 1950–2010. (a) Mean annual snow accumulation in mm SWE; (b) annual trend of snow accumulation in mm SWE/decade. Only trend results statistically significant at 10% or better are shown, white areas indicate no significant trends.

Figure 8

Mean annual snow accumulation and trends for 1950–2010. (a) Mean annual snow accumulation in mm SWE; (b) annual trend of snow accumulation in mm SWE/decade. Only trend results statistically significant at 10% or better are shown, white areas indicate no significant trends.

The results averaged for each study region indicate rates of change in the annual snow accumulation that range from −2 to −10 mm SWE/decade over the time period 1950–2010 (Table 1). The annual trend map also shows that statistically significant trends cover 70% of the study area, with some areas with values as high as 50 mm/decade in the Fraser-Columbia and Pacific regions at elevations above 1,000 m or as low as −50 mm/decade in coastal areas (Figure 8(b)).

Seasonally, snow accumulation is greatest through the cold season in all study regions, with most taking place between November and March (Figure 9(a)). Snow accumulation has decreased across most of the study area for most months of the year (Figure 9(b)). November through April, regional averages show that snow accumulation has decreased by 1–3 mm SWE/decade, with larger decreases in coastal areas and headwater regions of the Saskatchewan, Athabasca, and Peace regions in the eastern Rocky Mountains. However, snow accumulation did increase by 2–10 mm/decade at high elevations in the Pacific and southern Fraser-Columbia, and at northern latitudes in the Peel region, specifically during November, January, and March. Increases in temperature during these months allow a greater capacity for water vapour storage, thus increasing the potential moisture content in the air, thereby leading to an increase in the accumulation of snow at these higher elevations (Hamlet et al. 2005). Additionally, Zhang et al. (2001a) and Vincent & Mekis (2006) detected increases in snowfall in northern Canada, particularly during the cold season.
Figure 9

(a) Spatially averaged snow accumulation totals for each month. (b) Monthly snow accumulation trends in mm SWE/decade spatially averaged for each study region, from 1950 to 2010. Results include all calculated trend values.

Figure 9

(a) Spatially averaged snow accumulation totals for each month. (b) Monthly snow accumulation trends in mm SWE/decade spatially averaged for each study region, from 1950 to 2010. Results include all calculated trend values.

Decreasing trends were quite consistent throughout the cold season across the study area. All study regions contain some areas with decreasing trends in snow accumulation through multiple months, though only 19% of the study area experienced decreases during 4–6 months (Figure 10(a)). The most consistent trends occur in the Athabasca region, with decreasing trends through all 6 months of the cold season. The Liard and Saskatchewan regions also contain decreasing trends through 4–5 months of the cold season. The southern Fraser-Columbia region has experienced increasing trends during 3 months of the cold season, indicating an overall increase in snow accumulation in this high elevation area, while the remainder of the study area shows very few trends consistently occurring through multiple months (Figure 10(b)).
Figure 10

Snow accumulation trend consistency through the cold season (November–April). Colour corresponds to number of months with increasing or decreasing trend: (a) decreasing trend consistency; (b) increasing trend consistency. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/nh.2016.057.

Figure 10

Snow accumulation trend consistency through the cold season (November–April). Colour corresponds to number of months with increasing or decreasing trend: (a) decreasing trend consistency; (b) increasing trend consistency. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/nh.2016.057.

Snowmelt

Annual snowmelt shows a wide range of values across western Canada, with average values of 250–700 mm/year in the west (i.e. at high elevations) and 80–120 mm/year in the north and the interior portions of the study area (Figure 11(a) and Table 1).
Figure 11

Mean annual snowmelt and trends for 1950–2010. (a) Mean annual snowmelt in mm, (b) annual snowmelt trends in mm/decade. Only trend results statistically significant at 10% or better are shown, white areas indicate no significant trends.

Figure 11

Mean annual snowmelt and trends for 1950–2010. (a) Mean annual snowmelt in mm, (b) annual snowmelt trends in mm/decade. Only trend results statistically significant at 10% or better are shown, white areas indicate no significant trends.

Statistically significant rates of change for annual total snowmelt cover 68% of the study area and range from −2 to −10 mm/decade over the time period 1950–2010 when averaged over each study region (Table 1). Most study regions contain both increasing and decreasing trends. Decreasing trends occur across the majority of the study area, which is expected due to the decreased snow accumulation detected in most regions. Decreases are located particularly at lower or mid-elevation areas in interior regions; these areas have experienced trends of −2 to −15 mm/decade while the increases are mostly in areas higher than 1,000 m, with values of 20–40 mm/decade in the southern Rocky Mountains and northern Pacific region (Figure 11(b)).

Snowmelt peaks in most regions during April or May, with monthly totals of 50–170 mm; this melt is a major contributing factor of spring and subsequent summer streamflow throughout the study region (Figure 12(a)). Values through the remainder of the year are low. Trends throughout the study area indicate increased snowmelt during January through April, and decreased snowmelt through May and June (Figure 12(b)). The increases in January and February are small, with increases in April up to 8 mm/decade with the highest trend values located in the Liard and Pacific regions. May and June have experienced snowmelt decreases in all study regions. Throughout most months from January to June, decreasing trends are generally located in areas where that snowmelt increased during previous months. These shifts in snowmelt indicate an earlier onset of the spring freshet.
Figure 12

(a) Spatially averaged snowmelt totals for each month. (b) Spatially averaged rate of change of monthly total snowmelt in mm/decade, from 1950 to 2010. Results include all calculated trend values.

Figure 12

(a) Spatially averaged snowmelt totals for each month. (b) Spatially averaged rate of change of monthly total snowmelt in mm/decade, from 1950 to 2010. Results include all calculated trend values.

Hydrologic relevance

Temperature is a primary controlling factor of whether or not precipitation occurs as rain or snow, and influences the rate and timing of snowmelt. Therefore, the spatially continuous increasing trends in temperature presented in this study that occurred consistently through multiple months of the cold and warm seasons, in addition to those detected by previous studies (e.g., Bates et al. 2008; Vincent et al. 2012; Vincent et al. 2015) may modify the proportion of rainfall to snowfall in the study area and also result in a shorter cold season and earlier start to the spring melt season. As temperatures fluctuate across the freezing point of water, snowpack in mountainous regions are directly affected by changes to the percentage of precipitation falling as rain or snow; coastal mountainous regions, especially the Pacific drainage region is particularly sensitive to this, since many mountainous areas have average winter and spring temperatures only slightly below 0 °C (Adam et al. 2009; Kapnick & Hall 2011). Shifts in precipitation type from snow to rain have already been documented in previous research (e.g., Vincent & Mekis 2006; Screen & Simmonds 2012), and thus have contributed to decreased snow storage during the cold season across the study area. Cold season snow accumulation acts as a natural reservoir, and is an important factor for the spring freshet and summer streamflow (Stewart 2009).

The widespread, spatially continuous temperature increases during the warm season also contribute to less water being available for streamflow. Though the trend magnitudes are lower in the warmer months of the year than the colder months, the increasing minimum temperature trends that occur consistently throughout the headwaters of the Athabasca and Saskatchewan regions during all 6 months of the warm season may be a contributing factor to the decreased summer streamflow in this area detected by Rood et al. (2008).

The increases in higher-latitude precipitation during the warm season indicate a shift toward precipitation occurring more at northern latitudes (Zhang et al. 2007; Vincent et al. 2015) as well as a shift toward the warmer months of the year. The detected precipitation trends have contributed to decreased streamflow and drier conditions across the Prairies during the warm season. The Liard basin has shown a marked shift in precipitation towards the warm season, with decreases throughout the cold season and increases in all 6 months of the warm season. This has likely contributed to the summer streamflow increases in the Liard River basin detected by Bawden et al. (2015). If the detected precipitation trends continue, the decreased precipitation and snow accumulation during the cold season across much of the study area along with the temperature increases throughout the year may make water management more difficult for dry areas of Canada, particularly the Prairies. These temperature and precipitation results are consistent with increased frequencies of mid-tropospheric synoptic climate types associated with higher air temperatures and lower precipitation throughout the cold season detected by Newton et al. (2014a).

A large portion of the streamflow in western Canada originates in the Rocky Mountains. These mountain watersheds are a key source of water for downstream users, and the spring freshet in particular provides a significant contribution to annual streamflow of the Mackenzie, Saskatchewan, and Fraser rivers, and is comprised of snowmelt from accumulation of snow during the cold season (Prowse et al. 2010). The spring freshet volume is largely dependent upon this winter snow accumulation, thus the widespread decreases to snow accumulation have likely contributed to decreases in snowmelt, and thus spring freshet volume, in addition to decreased warm season streamflow throughout much of western Canada (Hamlet et al. 2005; Schindler & Donahue 2006; Vincent & Mekis 2006).

The results also show some increases in snowmelt at lower elevations in the southwest of the study area during the cold season, indicating a greater frequency of mid-winter melt events, particularly in the Fraser-Columbia and Pacific regions. These events have likely contributed to some previously documented increases in cold season streamflow, particularly in the Fraser-Columbia, Pacific, and Peace regions (Burn & Elnur 2002; Rood et al. 2008; Bawden et al. 2015). Mid-winter melt events deplete the winter snowpack, thus further decreasing the amount of snow available for streamflow during the spring freshet and warm season.

Trends also indicate peak snowmelt has been shifting earlier in the year, from April and May toward March. Areas that experienced significant increases in snowmelt during March and April also experienced significant decreases during May and June. This trend corresponds to increased temperatures causing earlier snowmelt during these months, resulting in an earlier onset of the spring freshet (Whitfield 2001; Zhang et al. 2001b; Burn & Elnur 2002; Bonsal & Prowse 2003; Stewart et al. 2005; Schindler & Donahue 2006; Burn 2008; de Rham et al. 2008).

The interactions between trends in hydroclimatic variables within the study area combine to point out several major trends. The cold season has decreased in length due to spatially and temporally consistent increasing trends in both maximum and minimum temperature through nearly all months of the year. This has led to snowmelt and the spring freshet occurring earlier in the year. The decreased cold season length along with decreases in precipitation have led to less snow accumulation and thus less snowmelt, and likely a decreased spring freshet volume. Precipitation has also shifted toward warm season months and more northern latitudes, specifically the Liard region, with less precipitation falling in the driest parts of the study area throughout the cold season. Therefore summer streamflow is expected to be greater in the northern watersheds of the study area while the southern watersheds show less streamflow throughout the year. Streamflow in the major watersheds of western Canada are important to monitor since they are of significance for municipal and industrial use, agriculture, and energy generation. Changes to availability of these vital water resources require alterations in water resource management and policy.

CONCLUSION

Climate variables related to streamflow were assessed for trend over the period 1950–2010 using a newly produced interpolated, gridded climate dataset, the Mann-Kendall non-parametric test, and various spatial analysis techniques not previously used to study climate trends. Maximum and minimum temperatures have increased, both on an annual basis as well as through most months of the year. Minimum temperatures have generally increased more than maximum temperature. The greatest increases to both maximum and minimum temperature have occurred during the cold season. Additionally, the temperature increased more at northern latitudes, as well as at elevations above 1,000 m in the mountain ranges located within the study area. The results also indicate a redistribution of precipitation toward the warm season and northern latitudes. Snow accumulation during the cold season has decreased as a result of the decreased precipitation, and snowmelt has shifted earlier in the year, indicating greater mid-winter melt and an earlier spring freshet. These patterns of hydroclimatic change indicate northward shifts in overall moisture, shifting water resources away from the driest parts of the study area. When coupled with the increased temperatures throughout the study area, northern Canada appears to be getting more ‘water rich’ while southern Canada is shifting towards a ‘water poor’ regime, indicating the need for updated water management plans in Canada. Further research should include analysis of future projections through the use of climate scenarios to determine if these trends are likely to continue.

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