Hydrologic effects of climatic change in west-central Canada (original) (raw)

Abstract

The paper examines the impact of climatic change on the timing of the spring runoff event. Impact detection is accomplished using a non-parametric statistical test for trend that is applied to the assembled data sets. The application of the approach is to a set of 84 natural rivers from the west-central region of Canada. The results indicate that there are a greater number of rivers that exhibit earlier spring runoff than can be attributed to chance occurrence. The observed impacts on the timing of spring runoff are more prevalent in the recent portion of the data record, which is consistent with what one would expect if the impacts are a result of greenhouse gas induced climatic change.

Figures (11)

N.E., Northeastern Forest; N.W., Northwestern Forest; Pr., Prairie; C.S., Canadian Shield; Pl., Plains.

N.E., Northeastern Forest; N.W., Northwestern Forest; Pr., Prairie; C.S., Canadian Shield; Pl., Plains.

Trend test results for different segments of the data set Figure 1 shows the location of the stations which exhibit no trend at the 10% level, a decreasing trend at the 10% level, and a decreasing trend at the 5% level. There are relatively few noteworthy spatial patterns in the results displayed in Fig. 1. Most noticeable is the band of stations with a significant trend across the Saskatchewan—Manitoba border. Interestingly, this collection of stations is on the edge of the Plains physiographic region but straddles the Prairie and Northwest Forest climatic zones. It is thus difficult to attribute this clustering of stations with a significant trend to a particular set of physiographic and/or climatic conditions. Also of note is the large portion of the stations in northern Alberta that exhibit a significant trend, many of them significant at the 5% level. Other researchers (see, e.g. Houghton et al., 1990) have also noted larger climate change impacts, or potential for impacts, in northern areas. A similar pattern may exist in other northern regions of the study area; however, the majority of the stations in these areas either have short data records or are on regulated rivers.

Trend test results for different segments of the data set Figure 1 shows the location of the stations which exhibit no trend at the 10% level, a decreasing trend at the 10% level, and a decreasing trend at the 5% level. There are relatively few noteworthy spatial patterns in the results displayed in Fig. 1. Most noticeable is the band of stations with a significant trend across the Saskatchewan—Manitoba border. Interestingly, this collection of stations is on the edge of the Plains physiographic region but straddles the Prairie and Northwest Forest climatic zones. It is thus difficult to attribute this clustering of stations with a significant trend to a particular set of physiographic and/or climatic conditions. Also of note is the large portion of the stations in northern Alberta that exhibit a significant trend, many of them significant at the 5% level. Other researchers (see, e.g. Houghton et al., 1990) have also noted larger climate change impacts, or potential for impacts, in northern areas. A similar pattern may exist in other northern regions of the study area; however, the majority of the stations in these areas either have short data records or are on regulated rivers.

Characteristics for the selected stations

Characteristics for the selected stations

Fig. 2. Time series plot of the Julian day of the peak spring snowmelt runoff event for two stations from the Northeastern Forest climate zone. The Pinewood River data have a decreasing trend that is significant at the 10% level whereas the Neebing River data do not exhibit a trend at the 10% level.

Fig. 2. Time series plot of the Julian day of the peak spring snowmelt runoff event for two stations from the Northeastern Forest climate zone. The Pinewood River data have a decreasing trend that is significant at the 10% level whereas the Neebing River data do not exhibit a trend at the 10% level.

Fig. 3. Time series plot of the Julian day of the peak spring snowmelt runoff event for two stations from the Northwestern Forest climate zone. The Carrot River data have a decreasing trend that is significant at the 5% level whereas Kelsey Creek data do not exhibit a trend at the 10% level. ee OO OE IE EE EEE OOO There were no significant differences of note in the trend results or other station characteristics when the stations were subdivided from east to west, or when the stations were separated in accordance with the climatic zone or the physiographic zone. Also, no significant differences were observed when the stations were sub- divided by drainage basin area. However, an interesting result did emerge from a subdivision of the stations by the length of the data record. The data set was divided into two roughly equal segments with 41 short data record stations (record length less

Fig. 3. Time series plot of the Julian day of the peak spring snowmelt runoff event for two stations from the Northwestern Forest climate zone. The Carrot River data have a decreasing trend that is significant at the 5% level whereas Kelsey Creek data do not exhibit a trend at the 10% level. ee OO OE IE EE EEE OOO There were no significant differences of note in the trend results or other station characteristics when the stations were subdivided from east to west, or when the stations were separated in accordance with the climatic zone or the physiographic zone. Also, no significant differences were observed when the stations were sub- divided by drainage basin area. However, an interesting result did emerge from a subdivision of the stations by the length of the data record. The data set was divided into two roughly equal segments with 41 short data record stations (record length less

Fig. 4. Time series plot of the Julian day of the peak spring snowmelt runoff event for two stations from the Prairie climate zone. Mink Creek data have a decreasing trend that is significant at the 5% level whereas Birdtail Creek data do not exhibit a trend at the 10% level.

Fig. 4. Time series plot of the Julian day of the peak spring snowmelt runoff event for two stations from the Prairie climate zone. Mink Creek data have a decreasing trend that is significant at the 5% level whereas Birdtail Creek data do not exhibit a trend at the 10% level.

Summary statistics for the stations in the database

Summary statistics for the stations in the database

significant trend (at the 10% level). However, when the first and second half of the record are considered separately, there is a decreasing trend (P < 0.10) in the first half of the record and also a decreasing trend (P < 0.05) in the second half. This result serves to emphasize the nonuniformity in the trends and patterns in the data records. Also shown in Fig. 6 is a plot of the spring temperature in western Canada (following Skinner, 1992). This plot gives the average spring (March—May) temperature departures from the 1951-1980 average, for a compilation of stations in western Canada. The Bow River basin is within the area for which the average temperatures have been obtained. It can be seen that the smoothed curves in the upper and lower graphs in Fig.6 are nearly mirror images of each other. This implies that the occurrence of earlier spring runoff events can be directly attributed to increases in average temperatures during the spring period. It is also interesting to note that there is no significant trend in the entire spring temperature record (at the 10% level), whereas there is a highly significant increasing trend in the record for the data since 1950 (P < 0.01).

significant trend (at the 10% level). However, when the first and second half of the record are considered separately, there is a decreasing trend (P < 0.10) in the first half of the record and also a decreasing trend (P < 0.05) in the second half. This result serves to emphasize the nonuniformity in the trends and patterns in the data records. Also shown in Fig. 6 is a plot of the spring temperature in western Canada (following Skinner, 1992). This plot gives the average spring (March—May) temperature departures from the 1951-1980 average, for a compilation of stations in western Canada. The Bow River basin is within the area for which the average temperatures have been obtained. It can be seen that the smoothed curves in the upper and lower graphs in Fig.6 are nearly mirror images of each other. This implies that the occurrence of earlier spring runoff events can be directly attributed to increases in average temperatures during the spring period. It is also interesting to note that there is no significant trend in the entire spring temperature record (at the 10% level), whereas there is a highly significant increasing trend in the record for the data since 1950 (P < 0.01).

Fig. 6. Time series plot of the Julian day of the peak spring snowmelt runoff event for the Bow River, Alberta (upper plot). The lower plot shows the average spring (March—May) temperature departures from the 1951-1980 average for a collection of stations in western Canada.

Fig. 6. Time series plot of the Julian day of the peak spring snowmelt runoff event for the Bow River, Alberta (upper plot). The lower plot shows the average spring (March—May) temperature departures from the 1951-1980 average for a collection of stations in western Canada.

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