Assessment of impacts of climate change on water resources – a case study of the Great Lakes of North America

Abstract

Abstract. Historical trends in precipitation, temperature, and streamflows in the Great Lakes are examined using regression analysis and Mann-Kendall statistics, with the result that many of these variables demonstrate statistically significant increases ongoing for a six decade period. Future precipitation rates as predicted using fitted regression lines are compared with scenarios from Global Climate Change Models (GCMs) and demonstrate similar forecast predictions for Lake Superior. Trend projections from historical data are, however, higher than GCM predictions for Michigan/Huron. Significant variability in predictions, as developed from alternative GCMs, is noted. Given the general agreement as derived from very different procedures, predictions extrapolated from historical trends and from GCMs, there is evidence that hydrologic changes in the Great Lakes Basin are likely the result of climate change.

On the Impact of Recent Climate Change on Seasonal Floods—A Case Study from a River Basin in Southern Quebec

“…The Mann-Kendall test has been described in detail by many authors (Burn and Hag Elnur, 2002;Burn et al, 2004a;Cunderlik and Burn, 2004;McBean and Motiee, 2006). A brief description of the test results will be provided here.…”

“…McBean and Rovers (1998) outline a number of parametric and non-parametric methods used for the detection of trends in climatic and hydrologic data, while Kundzewizc and Robson (2004) review trend analysis methodologies in general. McBean and Motiee (2006) use a combination of the parametric "Simple Linear Regression Model" and the non-parametric Mann-Kendall test. The linear regression analysis is used in order to provide a primary indication about the existence of trends in precipitation, temperature and streamflow data series; the Mann-Kendall test detects trends that are monotonic but perhaps not linear (McBean and Motiee, 2006).…”

“…McBean and Motiee (2006) use a combination of the parametric "Simple Linear Regression Model" and the non-parametric Mann-Kendall test. The linear regression analysis is used in order to provide a primary indication about the existence of trends in precipitation, temperature and streamflow data series; the Mann-Kendall test detects trends that are monotonic but perhaps not linear (McBean and Motiee, 2006). A number of other authors have used the Mann-Kendall test to conduct trend analysis in streamflows and climatic variables in large regions (Burn et al, 2004a;Cheng et al, 2004;Cunderlik and Burn, 2004;Yue et al, 2003).…”

“…Burn et al (2004b) found that stations with significant hydrological trends had related changes in temperature, particularly winter and spring temperatures. McBean and Motiee (2006) used simple linear regression analysis and the MannKendall test to demonstrate significant increases in precipitation and streamflows in the Great Lakes region; temperature trends were not found to be significant. They suggest increases in precipitation could have dramatic impacts on water quantity, noting that a major impact would be changes in the frequency and magnitude of extreme hydrologic events (McBean and Motiee, 2006).…”

“…McBean and Motiee (2006) used simple linear regression analysis and the MannKendall test to demonstrate significant increases in precipitation and streamflows in the Great Lakes region; temperature trends were not found to be significant. They suggest increases in precipitation could have dramatic impacts on water quantity, noting that a major impact would be changes in the frequency and magnitude of extreme hydrologic events (McBean and Motiee, 2006). Very few studies have been made on the relationships between climatic variables and streamflow in relatively small watersheds in Canada.…”