effects of climate change on the great lakes
DESCRIPTION
Effects of Climate Change on the Great Lakes. ELIORA BUJARI May 5, 2009. Objective. Look at streamflow, precipitation, and temperature measurements over the past fifty eight years to study any statistical trends that indicate the effects of climate change on the Great Lakes. - PowerPoint PPT PresentationTRANSCRIPT
Objective
Look at streamflow, precipitation, and temperature measurements over the past fifty eight years to study any statistical trends that indicate the effects of climate change on the Great Lakes.
Use these trends to evaluate future predictions.
Location of the Lakes Contain about 6 quadrillion gallons of water, and
combined the lakes provide approximately 18% of the world’s freshwater supply.
Statistical Analysis
Mann-Kendall Analysis
Non-parametric method used in hydrologic data analysis to detect trends, using the S and Zs statistic.
Null hypothesis : there is no monotonic trend in the data.
Simple Linear Regression Analysis
Y = m x + b and R2 statistics Used to test the slopes of the trend lines and estimate future values.
Lake Levels At a 95% confidence interval the tests showed an increasing trend for the lake levels, except for Lake Superior
Mann-Kendall: S-score = 1819 Zs = 6.34 Result = Increasing Trend
Simple Linear Regression:
Water Level = 158.32 + 0.0081*Year
(77.92) (7.78)
R2 = 0.408 Se = 0.256 F = 60.58
1900 1920 1940 1960 1980 2000 2020173.2
173.4
173.6
173.8
174.0
174.2
174.4
174.6
174.8
175.0
175.2
Lake Erie Levels
95% CIRegression Line
Leve
l (m
)
Lake Levels
1900 1920 1940 1960 1980 2000 2020-1.00
-0.80
-0.60
-0.40
-0.20
0.00
0.20
0.40
0.60
0.80
1.00
Lake Erie
Lake Michigan
Lake Superior
Lake Huron
Lake Ontario
Diff
eren
ce in
leve
ls fr
om th
e m
ean
(m)
Temperature Trends No statistically significant trends on overlake temperatures for Lake Erie, Huron, and Ontario, but there is an increasing trend for Lake Michigan and Lake Superior.
Mann-Kendall: S-score = 135 Zs = 0.92 Result = No Trend
Simple Linear Regression:
Temperature = -6.806 + 0.009*Year
(-0.569) (1.54)
R2 = 0.039 Se = 0.743 F = 2.17
1940 1950 1960 1970 1980 1990 2000 20100
2
4
6
8
10
12
14
16Lake Erie Temperature: 1948-2005
95% CI
Tem
pera
ture
(0C)
Flow Trends
There are no Statistically Significant Trends for streamflow
1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 20100
750
1500
2250
3000
3750
4500
5250
6000
6750
7500
8250
9000Average Annual Streamflow from 1948-2005
Detroit RiverLinear (Detroit River)St Mary's River
Flow
(m3/
sec)
Precipitation Trends
Statistically Significant Increasing Trends for Lake Huron and Lake Ontario.
Mann-Kendall: S-score = 423 Zs = 2.83 Result = Increasing
Trend
Simple Linear Regression:
Precipitation = -224.4 + 0.150*Year
(2.269) (3.00)
R2 = 0.138 Se = 6.380 F = 8.975
1940 1950 1960 1970 1980 1990 2000 20100
10
20
30
40
50
60
70
80
90Precipitation over Lake Huron: 1948-2005
95% CI
Prec
ipit
ation
(mm
/yr)
Conclusions No statistically significant conclusions can be drawn about assessing potential future predictions.
The increasing trend for thelake levels can be explained by looking at short term fluctuations caused by strong winds, storm surge and ice development in the connecting channels; and long term crustal reboundingand increase consumption use.
Future Work
Look at the mass balance of the whole system and each lake individually to observe the contributing inflows and outflows and see how they have changed through time.
Analyze which factors are statistically important.
Compare the simple regression results with Global Climate Models.