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Data Set #043

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About the Data

About hydropower by state

    Hydroelectricity generated by dams has some environmental advantages over other sources of electricity such as nuclear reactors and coal-fired power plants. Hydropower generates essentially no greenhouse gases and produces essentially no solid or toxic wastes, once the facility is constructed. Hydropower is renewable; no finite resources such as uranium ore, coal or petroleum are consumed, once the facility is built. Hydropower also can re-use the same water over and over to generate electricity, if a single river or stream has a series of facilities along its course. Hydropower is not without its problems, however. Dams alter habitat in many ways; fertile agricultural valleys are often lost, salmon and other migratory fish are severely impacted, etc.

    The United States Geological Survey has compiled data on the hydroelectric power production of each state and territory in 1990, as well as the amount of water used to generate this electricity. Though not stated, hydropower presumably includes both dams and in-stream turbines, though dams must account for practically all of the production. The units are quite interesting. Water use is given in millions of gallons per day; Washington State uses the better part of a million million gallons every day. Why did the USGS choose the very tiny unit, gallon per day? Electricity production is given in millions of kilowatt-hours; a million kilos is a billion, thus the data are actually given in Gigawatt-hours. Washington generates just under 105 Gwh of hydroelectricity each year; how many hours in a year, and therefore how much hydroelectric capacity is there in Washington State?

    The data range over 4 or 5 orders of magnitude, making it difficult to see the data on a conventional linear diagram. The scatterplot shows the logarithm of water use versus the logarithm of hydroelectric production. As might be expected, there is a strong positive correlation between these two variables, though with some scatter. The student should recognize that this scatter is actually quite large, as each increment on the graph represents one order of magnitude in size. Students can fit a linear regression to the "logged" data, and then use algebra to determine the best fit power law regression, if necessary. Is the data actually linear?

    The graph might give some indication of the efficiency of hydropower generation. Points below the line indicate larger quantities of water used to generate smaller amounts of electricity than the "average" represented by the regression; Iowa, Kansas, and Rhode Island, for example. Why are these states inefficient? Points above the line might indicate higher efficiency; California, Colorado and Nevada, for example. Why are these states efficient?

Reference:   U.S. Department of the Interior, Estimated Use of Water in the United States in 1990, USGS National Circular 1081. http://water.usgs.gov/watuse/wucircular2.html.

     
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1990 hydropower data from the USGS

water used to generate hydropower in Millions of gallons per day

electricity generation in Millions of kilowatthours

state

water (Mg/d)

elec (M kwh)

log water

log elec

Alabama

218,199

10,340

5.34

4.01

Alaska

1,790

98

3.25

1.99

Arizona

31,801

8,180

4.50

3.91

Arkansas

60,367

4,885

4.78

3.69

California

75,013

23,906

4.88

4.38

Colorado

4,161

1,318

3.62

3.12

Connecticut

6,875

452

3.84

2.66

Delaware

0

0

   

D.C.

0

0

   

Florida

7,257

173

3.86

2.24

Georgia

51,678

4,706

4.71

3.67

Hawaii

264

8

2.42

0.90

Idaho

67,778

7,447

4.83

3.87

Illinois

27,108

771

4.43

2.89

Indiana

11,598

441

4.06

2.64

Iowa

1,148

13

3.06

1.11

Kansas

1,302

12

3.11

1.08

Kentucky

83,008

2,880

4.92

3.46

Louisiana

21,667

697

4.34

2.84

Maine

82,676

3,962

4.92

3.60

Maryland

25,912

2,307

4.41

3.36

Massachusetts

24,534

1,090

4.39

3.04

Michigan

109,602

3,043

5.04

3.48

Minnesota

18,808

843

4.27

2.93

Mississippi

0

0

   

Missouri

13,904

2,192

4.14

3.34

Montana

66,797

10,688

4.82

4.03

Nebraska

12,947

833

4.11

2.92

Nevada

3,492

1,617

3.54

3.21

New Hampshire

45,980

1,976

4.66

3.30

New Jersey

167

17

2.22

1.23

New Mexico

964

215

2.98

2.33

New York

459,199

29,355

5.66

4.47

North Carolina

66,876

7,074

4.83

3.85

North Dakota

10,941

1,720

4.04

3.24

Ohio

7,800

173

3.89

2.24

Oklahoma

47,943

2,865

4.68

3.46

Oregon

480,545

40,784

5.68

4.61

Pennsylvania

68,039

3,192

4.83

3.50

Puerto Rico

362

108

2.56

2.03

Rhode Island

339

6

2.53

0.78

South Carolina

63,407

3,885

4.80

3.59

South Dakota

41,116

4,267

4.61

3.63

Tennessee

159,743

11,758

5.20

4.07

Texas

15,825

1,566

4.20

3.19

Utah

1,880

481

3.27

2.68

Vermont

17,669

1,097

4.25

3.04

Virginia

22,854

4,052

4.36

3.61

Virgin Islands

0

0

   

Washington

670,103

87,295

5.83

4.94

West Virginia

32,707

1,329

4.51

3.12

Wisconsin

43,972

1,148

4.64

3.06

Wyoming

4,355

611

3.64

2.79

 
 

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