In cooperation with the U.S. Army Corps of Engineers 

Application of Wind Fetch and Wave Models for 

Habitat Rehabilitation and Enhancement Projects 

U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2008–1200

659

658

657

656

LOW Weighted Wind Fetch HIGH
Cover. Depiction of management scenario 4, weighted wind fetch results for the Capoli Slough Habitat Rehabilitation and Enhancement 

Project in Navigation Pool 9, Upper Mississippi River System. The background image is a grayscale version of a 2006 National Agriculture 

Imagery Program aerial photograph. 
Application of Wind Fetch and Wave 

Models for Habitat Rehabilitation and 

Enhancement Projects 

By Jason Rohweder, James T. Rogala, Barry L. Johnson, Dennis Anderson, 

Steve Clark, Ferris Chamberlin, and Kip Runyon 

In cooperation with the U.S. Army Corps of Engineers 

Open-File Report 2008–1200

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DIRK KEMPTHORNE, Secretary

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2008

For product and ordering information:

World Wide Web: http://www.usgs.gov/pubprod

Telephone: 1-888-ASK-USGS

For more information on the USGS—the Federal source for science about the Earth, its natural and living resources, 

natural hazards, and the environment:

World Wide Web: http://www.usgs.gov

Telephone: 1-888-ASK-USGS

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Suggested citation: 

Rohweder, Jason, Rogala, James T., Johnson, Barry L., Anderson, Dennis, Clark, Steve, Chamberlin, Ferris, and 

Runyon, Kip, 2008, Application of wind fetch and wave models for habitat rehabilitation and enhancement projects: 

U.S. Geological Survey Open-File Report 2008–1200, 43 p. 
iii

Contents

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Toolbox Installation........................................................................................................................................1

Wind Fetch Model..........................................................................................................................................3

Introduction............................................................................................................................................3

Methodology..........................................................................................................................................3

Wind Fetch Model Validation..............................................................................................................5

Two-Sample Permutation Test for Locations ..........................................................................8

Wave Model....................................................................................................................................................8

Introduction............................................................................................................................................8

Assumptions and Model Limitations ...............................................................................................11

Methodology........................................................................................................................................11

Adjusting Wind Speed Data.....................................................................................................11

Deep Water Test ........................................................................................................................12

Significant Wave Height...........................................................................................................14

Wave Length...............................................................................................................................15

Spectral Peak Wave Period .....................................................................................................15

Maximum Orbital Wave Velocity.............................................................................................15

Shear Stress ...............................................................................................................................15

St. Paul District Analyses ...........................................................................................................................17

Study Areas..........................................................................................................................................17

Capoli Slough Habitat Rehabilitation and Enhancement Project ......................................17

Harpers Slough Habitat Rehabilitation and Enhancement Project...................................19

Weighted Wind Fetch Analysis ........................................................................................................21

Land Raster Input Data .............................................................................................................21

Wind Direction Input Data........................................................................................................21

Weighted Wind Fetch................................................................................................................23

Analysis Results.........................................................................................................................24

Discussion...................................................................................................................................24

Sediment Suspension Probability Analysis....................................................................................24

Analysis Results.........................................................................................................................29

Discussion...................................................................................................................................34

St. Louis District Analysis...........................................................................................................................34

Study Area............................................................................................................................................34

Swan Lake Habitat Rehabilitation and Enhancement Project ...........................................34

Weighted Wind Fetch Analysis ........................................................................................................35

Land Raster Input Data .............................................................................................................35

U.S. Fish and Wildlife Service Sample Island Design..........................................................36

U.S. Army Corps of Engineers Sample Island Design..........................................................36

Wind Direction Input Data........................................................................................................37

Weighted Wind Fetch................................................................................................................37

Analysis Results.........................................................................................................................40

Discussion...................................................................................................................................40
iv

Spatial Datasets Used in Analyses...........................................................................................................40

Long Term Resource Monitoring Program 2000 Land Cover/Land Use Data 

for the Upper Mississippi River System ............................................................................40

Originator.....................................................................................................................................40

Abstract.......................................................................................................................................40

Online Linkage............................................................................................................................40

Long Term Resource Monitoring Program Bathymetric Data for the 

Upper Mississippi and Illinois Rivers.................................................................................40

Originator.....................................................................................................................................40

Abstract.......................................................................................................................................40

Online Linkage............................................................................................................................40

Acknowledgments.......................................................................................................................................43

References Cited..........................................................................................................................................43

Figures

1–5. Screen shots showing:

1. Windows Explorer view of extracted files.......................................................................2

2. ArcToolbox view of wave tools .........................................................................................2

3. Windows dialog box for selecting Waves toolbox.........................................................3

4. Sample text file with fetch direction input data .............................................................3

5. Fetch model dialog window prompting user input.........................................................4

6. Diagram showing example depictions of wind fetch calculated using the 

different methods..........................................................................................................................5

7. Map showing sample wind fetch model results for Swan Lake Habitat 

Rehabilitation and Enhancement Project (HREP)....................................................................6

8. Map showing wind fetch cell locations and prevailing wind directions used for 

model validation............................................................................................................................7

9. Graph showing results for two-sample permutation test for locations ..............................9

10. Screen shot showing wave model dialog window prompting user input.........................10

11. Screen shot showing sample text file depicting valid input values for wind data 

in wave model .............................................................................................................................10

12. Map showing visual depiction of Navigation and Ecosystem Sustainability 

Program subareas used to calculate average water depth................................................13

13. Map showing sample wave model outputs for scenario 4, Capoli Slough 

HREP .............................................................................................................................................16

14. Diagram depicting relationships of input and output parameters used within 

the wave model...........................................................................................................................17

15–17. Maps showing:

15. Location of Pool 9 Capoli Slough and Harpers Slough HREPs...................................18

16. Capoli Slough HREP with feature labels........................................................................19

17. Harpers Slough HREP with feature labels.....................................................................20

18. Aerial photograph showing location of revised island addition to Harpers Slough 

HREP area ....................................................................................................................................21

19. Sample copy of a National Climatic Data Center, Local Climatological Data 

summary sheet............................................................................................................................22

20. Graph showing breakdown of wind directions collected for La Crosse 

Municipal Airport site ................................................................................................................23
v

21. Screen shot showing weighted sum dialog window example ...........................................23

22–24. Maps showing:

22. Weighted wind fetch results for the Capoli Slough HREP..........................................25

23. Weighted wind fetch results for the Harpers Slough HREP.......................................26

24. Difference in weighted wind fetch from the existing conditions 

management scenario to scenarios 1, 2, 3, and 4 for the 

Capoli Slough HREP...........................................................................................................27

25. Graph showing numerical difference in weighted wind fetch from the existing 

conditions management scenario to scenarios 1, 2, 3, and 4 for the 

Capoli Slough HREP....................................................................................................................27

26. Map showing difference in weighted wind fetch from the existing conditions 

management scenario to scenarios 1, 2, 3, and 4 for the Harpers Slough HREP ............28

27. Graph showing numerical difference in weighted wind fetch from the existing 

conditions management scenario to scenarios 1, 2, 3, and 4 for the 

Harpers Slough HREP ................................................................................................................28

28. Diagram explaining process for calculating percent of days capable of 

suspending sediments ...............................................................................................................29

29–31. Maps showing:

29. Sediment suspension probability results for the Capoli Slough HREP.....................30

30. Sediment suspension probability results for the Harpers Slough HREP..................31

31. Difference in sediment suspension probability from the existing 

conditions management scenario to scenarios 1, 2, 3, and 4 for the 

Capoli Slough HREP...........................................................................................................32

32. Graph showing numerical difference in sediment suspension probability 

from the existing conditions management scenario to scenarios 1, 2, 3, and 4 

for the Capoli Slough HREP.......................................................................................................32

33. Map showing difference in sediment suspension probability from the 

existing conditions management scenario to scenarios 1, 2, 3, and 4 for the 

Harpers Slough HREP ................................................................................................................33

34. Graph showing numerical difference in sediment suspension probability 

from the existing conditions management scenario to scenarios 1, 2, 3, and 4 

for the Harpers Slough HREP....................................................................................................33

35. Map showing location of Swan Lake HREP...........................................................................34

36–38. Aerial photographs showing:

36. Location of revised island addition to Swan Lake HREP area ...................................35

37. Swan Lake HREP with U.S. Fish and Wildlife Service proposed islands 

labeled .................................................................................................................................36

38. Swan Lake HREP with U.S. Army Corps of Engineers proposed islands 

labeled .................................................................................................................................37

39. Sample copy of a National Climatic Data Center, local climatological data 

summary sheet............................................................................................................................38

40. Graph showing breakdown of wind directions collected for Lambert–St. Louis 

International Airport site ...........................................................................................................39

41. Screen shot showing weighted sum dialog window example ...........................................39

42. Map showing results of weighted wind fetch analysis for Swan Lake HREP..................41

43. Graphs showing percent decrease in total weighted fetch between existing 

conditions and U.S. Fish and Wildlife Service proposed island design for 

Swan Lake HREP.........................................................................................................................42

44. Graphs showing percent decrease in total weighted fetch between existing 

conditions and U.S. Army Corps of Engineers proposed island design for 

Swan Lake HREP.........................................................................................................................42
vi

Conversion Factors and Abbreviations

Multiply By To obtain

Length

centimeter 0.3937 inch 

meter 3.281 foot 

meter 1.094 yard 

Area

acre 4,047 square meter 

acre 0.4047 hectare 

acre 0.4047 square hectometer 

acre 0.004047 square kilometer 

Flow rate

meter per second 3.281 foot per second 

mile per hour 1.609 kilometer per hour 

Abbreviations used in this report

ASOS Automated Surface Observing System

CEM Coastal Engineering Manual

ESRI Environmental Systems Research Institute

GIS Geographic Information System

HREP Habitat Rehabilitation and Enhancement Project

IDOC Illinois Department of Conservation

LTRMP Long Term Resource Monitoring Program

MOWV maximum orbital wave velocity

NCDC National Climatic Data Center

SPM Shore Protection Manual

SWL still-water level

UMESC Upper Midwest Environmental Sciences Center

UMRS Upper Mississippi River System

USACE U.S. Army Corps of Engineers

USDA U.S. Department of Agriculture

USFWS U.S. Fish and Wildlife Service

USGS U.S. Geological Survey

Tables

1. Tabular summarization of wind fetch measurements calculated using the 

two different methods..................................................................................................................9

2. Summarization of results used to test for deep versus shallow water.............................14
Abstract 

Models based upon coastal engineering equations have 

been developed to quantify wind fetch length and several 

physical wave characteristics including significant height, 

length, peak period, maximum orbital velocity, and shear 

stress. These models, developed using Environmental Systems 

Research Institute’s ArcGIS 9.2 Geographic Information System platform, were used to quantify differences in proposed 

island construction designs for three Habitat Rehabilitation 

and Enhancement Projects (HREPs) in the U.S. Army Corps 

of Engineers St. Paul District (Capoli Slough and Harpers 

Slough) and St. Louis District (Swan Lake). Weighted wind 

fetch was calculated using land cover data supplied by the 

Long Term Resource Monitoring Program (LTRMP) for each 

island design scenario for all three HREPs. Figures and graphs 

were created to depict the results of this analysis. The difference in weighted wind fetch from existing conditions to each 

potential future island design was calculated for Capoli and 

Harpers Slough HREPs. A simplistic method for calculating sediment suspension probability was also applied to the 

HREPs in the St. Paul District. This analysis involved determining the percentage of days that maximum orbital wave 

velocity calculated over the growing seasons of 2002–2007 

exceeded a threshold value taken from the literature where fine 

unconsolidated sediments may become suspended. This analysis also evaluated the difference in sediment suspension probability from existing conditions to the potential island designs. 

Bathymetric data used in the analysis were collected from the 

LTRMP and wind direction and magnitude data were collected 

from the National Oceanic and Atmospheric Administration, 

National Climatic Data Center.

Introduction

The St. Paul District and the St. Louis District of the 

U.S. Army Corps of Engineers (USACE) tasked the Upper 

Midwest Environmental Sciences Center (UMESC) of the 

U.S. Geological Survey (USGS) with the development of 

geospatial models based on wind and water depths to assist 

in the planning for Habitat Rehabilitation and Enhancement 

Projects (HREPs), under the Environmental Management Program. This work is part of a project to better utilize Long Term 

Resource Monitoring Program (LTRMP) data and scientific 

expertise at UMESC for HREP activities. 

Using the models developed, UMESC was then asked to 

perform specific analyses to model weighted wind fetch for 

both districts and also the probability that fine unconsolidated 

particles would be suspended due to wind-generated waves 

for the HREPs within the St. Paul District. Wave data were 

created with algorithms that used wind fetch, wind direction, 

wind speed, and water depth as input parameters. The results 

of these analyses depict how wind fetch and fine unconsolidated particle suspension are affected by alternative HREP 

management scenarios, allowing managers to quantify gains or 

losses between these proposed management scenarios.

Toolbox Installation

The models described in this report can be downloaded 

at http://www.umesc.usgs.gov/management/dss/wind_fetch_

wave_models.html. To use the wind fetch and wave models, 

there are some preliminary steps that need to be followed for 

them to function correctly on the computer. First are a few 

software requirements that need to be met:

1. ArcGIS 9.2 or more recent

2. A Spatial Analyst License

3. Python 2.4 or more recent (automatically installed 

with ArcGIS)

4. Pywin32 (Python for Windows extension)

Pywin32 allows Python to communicate with COM servers such as ArcGIS, Microsoft Excel, Microsoft Word, etc. 

Python scripting in ArcGIS cannot work without this extension. This extension can be downloaded at: http://sourceforge.

net/project/platformdownload.php?group_id=78018

Application of Wind Fetch and Wave Models for 

Habitat Rehabilitation and Enhancement Projects

By Jason Rohweder1, James T. Rogala1, Barry L. Johnson1, Dennis Anderson2, Steve Clark2, 

Ferris Chamberlin2, and Kip Runyon2

1

U.S. Geological Survey. 

2

U.S. Army Corps of Engineers. 
2 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Once these software requirements are met, the user needs to 

1. Extract the .zip file “Waves.zip” to a project directory on your hard drive (fig. 1)

2. Open ArcMap 9.2 and activate ArcToolbox if not already activated (Windows -> ArcToolbox) 

3. Right-click inside the ArcToolbox panel and select Add Toolbox... (fig. 2) 

4. Open the extracted folder Waves and click on the Waves toolbox icon.

Figure 1. Windows 

Explorer view of 

extracted files.

Figure 2. ArcToolbox view of wave tools.
Wind Fetch Model 3

Wind Fetch Model

Introduction

Wind fetch is defined as the unobstructed distance that 

wind can travel over water in a constant direction. Fetch is an 

important characteristic of open water because longer fetch 

can result in larger wind-generated waves. The larger waves, 

in turn, can increase shoreline erosion and sediment resuspension. Wind fetches in this model were calculated using scripts 

designed by David Finlayson, USGS, Pacific Science Center, 

while he was a Ph.D. student at the University of Washington 

(Finlayson, 2005). This method calculates effective fetch using 

the recommended procedure of the Shore Protection Manual 

(U.S. Army Corps of Engineers, 1984). In Inland waters 

(bays, rivers, lakes, and reservoirs), fetches are limited by land 

forms surrounding the body of water. Fetches that are long in 

comparison to width are frequently found, and the fetch width 

may become quite important, resulting in wave generation 

significantly lower than that expected from the same generating conditions over more open waters (U.S. Army Corps of 

Engineers, 1977).

Methodology

The wind fetch scripts that the model operates from were 

developed by Finlayson using the Python scripting language 

and were originally designed to run on the ArcGIS 9.0 (Environmental Systems Research Institute ([ESRI] Redlands, California) Geographic Information System (GIS) platform. However, these scripts needed to be updated in order to operate 

using the most current ArcGIS revision, 9.2. The model was 

also modified to more efficiently meet the needs of USACE 

planning personnel. This modification gives the model the 

ability to calculate wind fetch for multiple wind directions 

based upon a text file listing individual compass directions. 

Figure 4 displays an example text file of wind directions used 

for the model.

You should now be ready to run the wind fetch and wave models within the Waves toolbox (fig. 3). 

Figure 3. Windows dialog 

box for selecting Waves 

toolbox. 

Figure 4. Sample text file with fetch direction input 

data. 
4 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Figure 5 shows an example of the wind fetch model’s 

input dialog within ArcGIS 9.2. The “Land Raster” input 

parameter is the full path to an ArcGIS raster dataset where 

each cell in the raster is evaluated as being “land” if the 

value > 0.0 and “water” if the value of that cell is <=0.0 or 

NODATA. When using the fetch model, it is important for the 

land raster to have all areas designated as “water” be enclosed 

by cells designated as “land.” “Unbounded fetches are an 

artifact of calculating fetch lengths on a raster that does not 

completely enclose the body of water. The length calculation 

extends only to the edge of the raster. Such cells represent a 

minimum fetch length only, and the fetch could be much larger 

depending on how much of the water body is missing. To easily identify these cells, Fetch returns a negative fetch length 

for unbounded fetches (Finlayson, 2005).” 

Scale plays an important role with respect to the land raster. If the cell size of the land raster becomes too large you risk 

the possibility that thin (approximating the width of the cell) 

islands will be lost. However, if the cell size of the land raster 

is too fine, the user may experience slow processing times and 

dramatically enlarged file sizes. There may be trial-and-error 

involved by the user to identify a land raster spatial resolution 

that balances the desire for detail with the dilemma of minimizing computer operating time and hard disk space. 

When the model is initiated, the “Calculation Method” 

defaults to “SPM.” The SPM acronym designates that this 

process uses the preferred methodology for calculating effective fetch as described in the Shore Protection Manual. This 

method spreads nine radials around the desired wind direction 

at 3-degree increments. The resultant wind fetch is the arithmetic mean of these nine radial measurements. 

Figure 5. Fetch model 

dialog window prompting 

user input. 

There have been two other calculation method options added, 

“Single” calculates wind fetch on a single radial and “SPMrestricted” calculates wind fetch using the average of five radials, spread three degrees apart. This more restricted method 

for calculating effective fetch may be more appropriate when 

the habitat project of interest has long and narrow fetches 

(Smith, 1991). Figure 6 shows an example of how fetch is 

calculated for one reference raster cell based upon a reference 

bearing of zero degrees using the three methods within the 

wind fetch model.

For the wind fetch analyses used within this report the 

SPM Method is used. The larger arc (24 degrees) probably 

represents a more real-world condition for the areas evaluated. Available wind data are frequently reported to the nearest 

ten degree. Wind direction is not consistent and varies even 

over the maximum 2-minute average wind speed. We are not 

taking into account wave refraction. However, in the examples 

provided, the large arc takes this into account somewhat and 

maybe more accurately predicts what the shadow zone might 

be around an island.
Wind Fetch Model 5

Each of the individual directional wind fetch outputs are 

saved to a specified “Output Workspace” and named according to their respective wind direction (prefixed with the letters 

“fet_” and ending with the three-digit wind direction [e.g., 

“180”]). 

Before the model can be executed, a scratch workspace 

must be designated using the “Environments...” button. It is 

suggested that the user select a workspace (folder) for this 

parameter and not use a geodatabase as is sometimes suggested in the ArcGIS literature. There have been issues with 

the model not operating when a geodatabase or an invalid 

workspace was selected.

Figure 7 gives an example depiction of wind fetch calculated using the Single, SPM-Restricted, and SPM calculation method for the Swan Lake HREP area using winds from 

0 degrees and 140 degrees using the U.S. Fish and Wildlife 

Service (USFWS) sample management scenario.

Wind Fetch Model Validation

A validation was performed to compare the results created using the wind fetch model described previously with 

another method of calculating wind fetch, which will be 

termed the measured-line method. The measured-line method 

of calculating fetch involved using trigonometric calculations 

to create vector lines within ArcGIS from a specific point 

within the area of interest. These lines were created using 

nine radials spread around the prevailing wind direction at 

three degree increments (SPM method of fetch calculation). 

The point from which the fetch was calculated was selected 

randomly within the area of interest, in this example Swan 

Lake HREP using the USFWS proposed island design. Next, 

the prevailing wind direction was then randomly selected for 

each fetch reference point. Lines were then generated using 

trigonometry and their length was calculated using ArcGIS. 

Figure 8 displays the location of each fetch reference point 

and the resulting lines that were generated showing the relative length and compass direction of the lines that are used to 

quantify the fetch using the measured-line fetch method. 

Figure 6. Example depictions of wind fetch calculated using the different methods. 
6 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Figure 7. Sample wind fetch model results for Swan Lake Habitat Rehabilitation and Enhancement Project. 

Single

0 Degrees

SPM-Restricted

0 Degrees

SPM-Restricted

140 Degrees

SPM

0 Degrees

SPM

140 Degrees

Single

140 Degrees

800.1 - 840

840.1 - 880

880.1 - 920

920.1 - 960

960.1 - 1,000

> 1,000

Land

1,000

Meters

480.1 - 520

200.1 - 240

240.1 - 280

280.1 - 320

320.1 - 360

360.1 - 400

400.1 - 440

440.1 - 480

520.1 - 560

560.1 - 600

600.1 - 640

640.1 - 680

680.1 - 720

720.1 - 760

760.1 - 800

Wind Fetch

Meters

0.1 - 40

40.1 - 80

80.1 - 120

120.1 - 160

160.1 - 200
Wind Fetch Model 7

Figure 8. Wind fetch cell locations and prevailing wind directions used for model validation. 

13 10

7

4

1

358

16

19

22

72

69

66

63

60

57

54

51

48

172 169

166 163 160

154

151

157

148

248

254 251

257 260 263 266

272 269

318

321

324 327 330 333 336339 342

100

Meters

100

Meters

50

Meters

200

Meters

500

Meters

1,000

Meters

400.1 - 450

450.1 - 500

500.1 - 550

550.1 - 600

600.1 - 650

650.1 - 700

700.1 - 750

750.1 - 800

800.1 - 850

850.1 - 900

900.1 - 950

950.1 - 1,000

1,000.1 - 1,050

1,050.1 - 1,100

1,100.1 - 1,150

1,150.1 - 1,200

1,250.1 - 1,300

1,300.1 - 1,350

1,350.1 - 1,400

1,400.1 - 1,450

1,450.1 - 1,500

1,500.1 - 1,550

1,550.1 - 1,600

1,200.1 - 1,250

Wind Fetch (Meters)

10 - 50

50.1 - 100

100.1 - 150

150.1 - 200

200.1 - 250

250.1 - 300

300.1 - 350

350.1 - 400

1,600.1 - 1,650

1,650.1 - 1,700

1,700.1 - 1,750

1,750.1 - 1,800

1,800.1 - 1,850

1,850.1 - 1,900

1,900.1 - 1,950

> 1,950

Swan Lake HREP Area of Interest

60 Degree SPM Wind Fetch

10 Degree SPM Wind Fetch

260 Degree SPM Wind Fetch

160 Degree SPM Wind Fetch

330 Degree SPM Wind Fetch

10 Degrees

60 Degrees

330 Degrees 260 Degrees 160 Degrees
8 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

The wind fetch was then calculated for the same area 

of interest using the same prevailing wind directions using 

the wind fetch model. The calculated wind fetch was then 

ascertained by identifying the cell within the area of interest 

that coincided with the reference point as determined earlier. 

Table 1 shows a breakdown of the measurements calculated 

using the measured-line method of fetch calculation versus the 

values obtained using the wind fetch model. We see a difference of less than 10 meters in the average fetch distance using 

the measured-line method and the results obtained using the 

wind fetch model. This is relevant since we are basing the 

wind fetch model calculations off of a 10-meter cell size input 

dataset.

Two-Sample Permutation Test for Locations

A permutation test was performed to determine whether 

the observed pattern (the wind fetch model results) happened 

by chance. Because sample sizes for the wind fetch model 

validation results were small (n = 5), A non-parametric twosample permutation test for locations was conducted (Manly, 

1997). This randomization test works simply by enumerating 

all possible outcomes under the null hypothesis, i.e., that no 

differences exist between the wind fetch model results and the 

measured lines of wind fetch, and then compares the observed 

wind fetch model results against this permuted distribution 

(based upon 5,000 permutations of the data). Results indicated 

no difference between the wind fetch model results and the 

measured-line fetch (L = 7.053, p = 0.9744).

In figure 9, the thick black line denotes the mean difference between the wind fetch model results and the measured 

lines of wind fetch relative to the distribution of all possible 

differences.

Wave Model

Introduction

A model was constructed within ArcGIS to create several 

useful wave outputs. Significant wave height, wave length, 

spectral peak wave period, shear stress, and maximum orbital 

wave velocity are all calculated using this model. Figure 10 

shows what the wave model dialog looks like for the user. 

Required inputs to the model include a directory of pre-created 

wind fetch outputs for the area of interest, a text file (.txt) of 

wind data (fig. 11), the height above ground in meters of the 

anemometer used to collect wind data, a checkbox to denote 

whether wind measurements were calculated overland, the 

density of water, a raster with bathymetric values for the area 

of interest, the threshold for maximum orbital wave velocity 

to use when calculating sediment suspension probability, and 

a workspace to store derived outputs. The text file of collected 

wind data is contained as comma-delimited numeric values 

consisting of the wind direction, followed by the wind speed, 

and finally the date of data collection expressed as a two-digit 

year, followed by a two-digit month, and finally the two-digit 

day (e.g. 020421 = April 21, 2002). 

It is important the date values be organized like this for 

the model to work correctly. 

The assembled wind speed data were adjusted to approximate a 1-hour wind duration, a 10-meter anemometer height 

above the ground surface, an overwater measurement, and also 

adjusted for coefficient of drag. These adjustments directly 

affect the input parameters of wave height, period, and length. 

Bathymetric (water depth) data used within the model were 

collected from the Long Term Resource Monitoring Program 

(see “spatial datasets used in analyses” section for detailed 

background information). 

The checkbox entitled “Overland Wind Measurement” 

should be checked if the wind data used within the model were 

collected on land and not over water which is the preferred 

alternative.

The decimal number required for the input parameter 

“MOWV Threshold for Calc. Sediment Suspension Probability (m/s)” is used in the calculation of sediment suspension probability (see section describing Sediment Suspension 

Probability Analysis for more information). Any maximum 

orbital wave velocity value derived that has a speed greater 

than or equal to the value specified will be attributed as having 

sufficient maximum orbital wave velocity to suspend unconsolidated fine sediment.

The user is given the opportunity to save the derived outputs permanently to their hard drive. This was done to give the 

user the opportunity to save space, as creating several of these 

floating-point raster datasets can quickly fill large amounts of 

disk space on the user’s computer. 

Before the model can be executed, a scratch workspace 

must be designated using the “Environments...” button. It is 

suggested that the user select a workspace (folder) for this 

parameter and not use a geodatabase as is sometimes suggested in the ArcGIS literature. There have been issues with 

the model not operating when a geodatabase or an invalid 

workspace was selected. 

Wave model outputs are named according to a three digit 

code as a prefix and then the date the wind data used were collected as a suffix. Sample output grid names are given below 

for all potential parameters: 

•	 Wave Height = hgt_020421

•	 Wave Period = per_020421

•	 Wave Length = len_020421

•	 Maximum Orbital Wave Velocity = vel_020421

•	 Shear Stress = str_020421

•	 Sediment Suspension Probability = vec_020421
Wave Model 9

Table 1. Tabular summarization of wind fetch measurements calculated using the two different methods. 

[°, degrees; %, percent]

Fetch reference angle

10° 60° 160° 260° 330°

Measured-Line Fetch (reference angle - 12°) 1289.42 545.48 66.05 134.82 356.59

Measured-Line Fetch (reference angle - 9°) 1335.20 548.21 72.19 68.75 340.99

Measured-Line Fetch (reference angle - 6°) 1388.38 550.05 72.32 67.62 278.12

Measured-Line Fetch (reference angle - 3°) 1455.85 554.45 70.61 56.45 244.43

Measured-Line Fetch (reference angle) 1518.06 560.03 73.10 55.85 225.17

Measured-Line Fetch (reference angle + 3°) 1595.90 566.77 85.51 55.41 207.63

Measured-Line Fetch (reference angle + 6°) 660.59 574.68 97.91 45.11 191.56

Measured-Line Fetch (reference angle + 9°) 682.17 583.77 96.78 45.01 176.74

Measured-Line Fetch (reference angle + 12°) 695.65 598.67 106.03 45.03 173.49

Measured-Line Fetch (average for 9 radials) 1180.14 564.68 82.28 63.78 243.86

Wind Fetch Model results (average for 9 radials) 1188.00 572.00 88.00 69.00 253.00

Difference (meters) 7.86 7.32 5.72 5.22 9.14

Percent difference 0.67% 1.30% 6.96% 8.18% 3.75%

Figure 9. Results for two-sample permutation test for locations. 
10 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Figure 10. Wave model dialog 

window prompting user input. 

Figure 11. Sample text file 

depicting valid input values 

for wind data in wave model. 
Wave Model 11

Assumptions and Model Limitations

The wave model described in this report provides a 

simplistic method for calculating multiple wave parameters. 

However, it should be noted that in many cases these simple 

methods have been replaced with more realistic, and much 

more complex, numerical wave models. This model provides 

a first-order approximation of the wave field and it should be 

noted that the methodology employed neglects the effect of 

bathymetry on wave growth. Also, since the method does not 

account for refraction or diffraction due to topography, reflection due to barriers (including the shoreline itself), wave-wave 

interactions, or wave-current interactions, the results are unrealistic and should be considered accurate only on a regional 

level and not on a cell-by-cell basis (D. Finlayson, USGS, 

Pacific Science Center, Santa Cruz, Calif., personal commun., 

2008.)

Wave height, period, and length inputs were derived 

based upon a deep-water model. There is no single theoretical development for determining the actual growth of waves 

generated by winds blowing over relatively shallow water 

(U.S. Army Corps of Engineers, 1984). Shallow water curves 

presented in the Shore Protection Manual (U.S. Army Corps 

of Engineers, 1984) are based on a successive approximation 

in which wave energy is added due to wind stress and subtracted due to bottom friction and percolation (Chamberlin, 

1994). While it is realized that the deep-water assumption will 

slightly over predict wave-height, a shallow water assumption 

would not only make computations more difficult, but it would 

also under predict wave height.

These models do not include the effect of terrestrial 

elevation on wave propagation. There is no accounting for 

island height or the height of trees on these terrestrial land 

forms. As wind is deflected up and over an island and its trees, 

a sheltered zone is created on the downwind side of the island 

(U.S. Army Corps of Engineers, 2006). This zone is roughly 

10 times the height of the island and its trees (Ford and Stefan, 

1980). The value for this sheltered zone hasn’t been stated in 

a quantitative fashion; however providing thermal refuge for 

migrating waterfowl is a desirable outcome of island projects 

(U.S. Army Corps of Engineers, 2006).

Vegetation effects were not incorporated into the model. 

Emergent vegetation can have an effect on wave growth by 

dissipating waves and thus reducing wave energy. 

Wave height was not tested for depth-limited breaking. 

If shallow bars or shoals exist along the fetch, they may also 

dissipate energy and limit the wave height. 

Also, neglecting diffraction of larger waves into the protected areas within the islands will underestimate wave energy 

in the protected area.

There have been issues during development with the 

wave model terminating unexpectedly before completion when 

attempting to calculate wave model outputs for a large number 

(~300) of iterations (days). This may depend upon how much 

memory is available on the user’s computer. Therefore, it may 

be necessary to split the input text file of wind data into more 

manageable pieces.

Methodology

Calculating the multiple wave characteristic raster 

outputs is accomplished using algorithms published in the 

Coastal Engineering Manual (U.S. Army Corps of Engineers, 

2002) and the Shore Protection Manual (U.S. Army Corps of 

Engineers, 1984). The following is a listing of variables used 

within these algorithms and a short description of what they 

represent: 

U = observed wind speed (miles per hour)

UA = adjusted wind speed (meters per second)

z = observed elevation of wind speed measurements 

(meters)

t = number of seconds to travel one mile

Ut

 = ratio of wind speed of any duration

Cd = coefficient of drag

U* = friction velocity

1 = 0.0413

2 = 0.751

m1 = 1⁄2 

m2 = 1/3

Hˆm0 = non-dimensional significant wave height

Hm0 = significant wave height (meters)

xˆ = non-dimensional wind fetch

x = wind fetch (meters)

g = acceleration of gravity (9.82 meters per second2)

Tˆp = non-dimensional spectral peak wave period

Tp = spectral peak wave period (seconds)

L = wave length (meters)

um = maximum orbital wave velocity at the bottom 

(meters per second)

df = water depth in the floodplain (meters)

τ = shear stress at the bottom (Newtons per square meter)

ρ = density of water (Kg/m3

) 

f = friction factor (assumed to be 0.032) 

Adjusting Wind Speed Data

The first step within the wave model is to make 

adjustments to the wind speed data to better approximate 

real-world conditions above water. Wind data used for the 

example analyses were collected from the National Oceanic 

and Atmospheric Administration, National Climatic Data 

Center (http://www7.ncdc.noaa.gov/IPS/LCDPubs?action=

getstate&LCD=hardcode). Wind data used in this analysis 

were collected only during the growing seasons (April–July) 

from 2002 to 2007. Only April data were available for 2007 

at the time of analysis. Specific wind parameter used was 
12 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

the maximum 2-minute average wind speed and direction (in 

miles per hour and degrees, respectively). The wind speed 

collected is adjusted to approximate a 10-meter anemometer 

height above the ground surface using the input within the 

model dialog entitled “Wind Measurement Height Above 

Ground (Meters).” Since the wind speed data were collected 

by the NCDC at the 10-meter elevation for these particular 

example locations, no adjustment is made to the wind speed 

data collected. The 10-meter elevation measurement guideline 

is established within the Automated Surface Observing 

System (ASOS) specifications. If however, the data collected 

were from an anemometer at an elevation other than 10 meters 

the following algorithm would have been applied:

UA = U (10/z)1/7

This approximation can be used if z is less than 20 meters 

(U.S. Army Corps of Engineers, 1984). 

Next, the wind speed is then corrected to better approximate a 1-hour wind duration. Most fastest mile wind speeds 

are collected using short time intervals, for the St. Paul and 

St. Louis District examples the maximum 2-minute average wind speed is used. It is most probable that on a national 

basis many of the fastest mile wind speeds have resulted from 

short duration storms such as those associated with squall 

lines or thunderstorms. Therefore, the fastest mile measurement, because of its short duration, should not be used alone 

to determine the wind speed for wave generation. On the 

other hand, lacking other wind data, the measurement can be 

modified to a time-dependent average wind speed (U.S. Army 

Corps of Engineers, 1984). Therefore, the 1-hour average 

wind speed is recommended when using a steady-state model 

for determining wave characteristics (Chamberlin, 1994). It 

is important to document, however, with shorter fetches the 

1-hour averaged wind speed may be longer than needed and 

may result in an underestimate of wave heights and periods. 

The following algorithms make this modification within the 

wave model:

t = 3600 / UA

Ut

 = 1.277 + 0.296 * tanh (0.9 * log10 (45/t)) 

UA = UA / Ut

Next, if the checkbox labeled “Overland Wind Measurement” is checked, the wind speed is adjusted to better approximate what the wind speed would be if it were collected over 

water (Chamberlin, 1994).

UA = 1.2 (UA)

Finally, the adjusted wind speed is converted from miles 

per hour to meters per second:

UA (meters per second) = UA (miles per hour)* 0.44704

This wind speed value (UA) is used in all subsequent 

wave model equations. It is important to note that the wind 

data used in these analyses were not corrected for stability or 

location. 

Deep Water Test 

A test was performed to ascertain whether deep-water 

or shallow-water wave models would be more appropriate for 

the analyses. In this test, if the ratio of water depth (h) to wave 

length (L) is greater than 0.5 we are in an area more typically 

classified as deep water and the calculated wave characteristics are virtually independent of depth, whereas if the ratio 

h/L is less than 0.05 we are in an area more typically thought 

of as shallow water (U.S. Army Corps of Engineers, 1977). 

For this test the typical water depth was calculated to be 

1.6092 meters. To determine this, the UMRS Pool 9 LTRMP 

bathymetric data were clipped using the Navigation and 

Ecosystem Sustainability Program’s spatial dataset depicting 

program subareas. Only the subareas that encompassed Capoli 

and Harpers Slough HREPs were used to calculate the mean 

water depth (fig. 12).

Next, the typical wave length was calculated. To accomplish this, the wave model was executed using 28 days of wind 

data from 2006. These 28 days encompassed the first week of 

each month during the growing season (April 1–7, May 1–7, 

June 1–7, and July 1–7, 2006). Upon completion of the model, 

the average wave length for all 28 iterations of the model was 

3.4988 meters (table 2).

The average water depth (1.6092) was then divided by 

the average wave length (3.4988) to get a ratio of 0.4898 that 

tends more towards what we classify as deep water (0.5). 

Thus, in the model and the following analyses, the wave calculations were based upon deep water wave theory.

It is recommended that deep water wave growth formulae be used for all depths, with the constraint that no wave 

period can grow past a limiting value (U.S. Army Corps of 

Engineers, 2002). A limiting wave period was then calculated 

and compared with typical wave periods for the study areas. It 

was found that the observed wave periods were less than the 

limiting wave period calculated using CEM Equation II-2-39 

(U.S. Army Corps of Engineers, 2002). The limiting wave 

period was calculated to be 3.9 seconds based upon the average water depth of 1.6092 meters calculated. It is unlikely that 

in our applications the wave period would exceed this value 

and become limited. 
Wave Model 13

Figure 12. Visual depiction of Navigation and Ecosystem Sustainability Program subareas used to calculate 

average water depth. 

Capoli Slough

Big Slough

Lower Pool 9

Harpers Slough

Lansing Big Lake

EXPLANATION

NESP Subareas

Capoli Slough HREP Area Of Interest

Harpers Slough HREP Area Of Interest

LTRMP Bathymetry

Meters

0.01 - 1

1.01 - 2

2.01 - 3

3.01 - 4

4.01 - 5

5.01 - 6

6.01 - 7

7.01 - 8

8.01 - 9

9.01 - 10

10.01 - 11

11.01 - 12

12.01 - 13

13.01 - 14

14.01 - 15

15.01 - 16

16.01 - 17

17.01 - 18

18.01 - 19

0 1,000 2,000 4,000

Meters
14 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Table 2. Summarization of results used to test for deep versus shallow water. 

[h/L, ratio of water depth to wave length]

Day Date Wind 

direction

Unadjusted 

wind speed 

(U) in

miles per hour

Wave height 

(H) 

in meters

Wave length 

(L) 

in meters

h/L

1 4/1/2006 320 21 0.2692 4.4784 0.3593

2 4/2/2006 340 22 0.2784 4.5167 0.3563

3 4/3/2006 330 30 0.3920 5.7217 0.2812

4 4/4/2006 300 18 0.2148 3.7027 0.4346

5 4/5/2006 150 13 0.1588 3.1032 0.5186

6 4/6/2006 140 16 0.1943 3.5205 0.4571

7 4/7/2006 10 21 0.2474 4.0030 0.4020

8 5/1/2006 150 20 0.2494 4.1930 0.3838

9 5/2/2006 260 13 0.1256 2.2573 0.7129

10 5/3/2006 300 22 0.2656 4.2657 0.3772

11 5/4/2006 300 17 0.2023 3.5573 0.4524

12 5/5/2006 320 17 0.2154 3.8597 0.4169

13 5/6/2006 210 18 0.1943 3.2237 0.4992

14 5/7/2006 190 18 0.2114 3.6171 0.4449

15 6/1/2006 320 14 0.1758 3.3710 0.4774

16 6/2/2006 330 12 0.1489 3.0008 0.5363

17 6/3/2006 40 12 0.1177 2.1935 0.7336

18 6/4/2006 150 14 0.1715 3.2668 0.4926

19 6/5/2006 200 18 0.2043 3.4546 0.4658

20 6/6/2006 280 22 0.2361 3.6343 0.4428

21 6/7/2006 330 21 0.2676 4.4357 0.3628

22 7/1/2006 300 20 0.2401 3.9877 0.4035

23 7/2/2006 270 12 0.1193 2.2298 0.7217

24 7/3/2006 30 12 0.1247 2.3767 0.6771

25 7/4/2006 340 15 0.1859 3.4514 0.4662

26 7/5/2006 300 13 0.1528 2.9512 0.5453

27 7/6/2006 220 9 0.0903 1.8721 0.8595

28 7/7/2006 200 20 0.2284 3.7205 0.4325

Averages 237 17 0.2029 3.4988 0.4898

Significant Wave Height

The highest point of the wave is the crest and the lowest 

point is the trough. For linear or small-amplitude waves, the 

height of the crest above the still-water level (SWL) and the 

distance of the trough below the SWL are each equal to the 

wave amplitude a. Therefore a = H/2, where H = the wave 

height (U.S. Army Corps of Engineers, 2002). Significant 

wave height is defined as the average height of the one-third 

highest waves, and is approximated to be about equal to the 

average height of the waves as estimated by an experienced 

observer (Munk, 1944). Significant wave height is calculated 

within the wave model according to the following formulae 

taken from the Coastal Engineering Manual (U.S. Army Corps 

of Engineers, 2002):

Cd ≈ 0.001 * (1.1 + (0.035 * UA))

U* = (Cd

) 1/2 *UA

xˆ = (g * x) / (U*)

2

Hˆm0 = 1 * (xˆ)m1

Hm0 = Hˆm0 * ((U*)2 / g)
Wave Model 15

The units for this output are meters. The top-left frame 

of figure 13 displays an example output for wave height using 

wind fetch calculated from 300 degrees and a wind speed of 

21 miles per hour for Capoli Slough HREP, management scenario 4. Areas within the HREP area of interest that are black 

denote land. The presence of “streaks” in this and the following figures are an unfortunate artifact of the stair-step nature 

of raster datasets. When polygons become thin (approximating the raster’s cell size, in this example 10 meters), gaps are 

created in the island areas during the conversion to a raster 

dataset. When fetch is then calculated at certain angles, the 

fetch calculation is unimpeded by land. A possible resolution 

to this problem would be to further decrease cell-size to 5 or 

even 2 meters but then analysis time increases significantly.

Wave Length

The wave length is the horizontal distance between two 

identical points on two successive wave crests or two successive wave troughs (U.S. Army Corps of Engineers, 2002). 

Wave length measurements within the wave model are based 

upon linear wave theory. Linear wave theory is easy to apply 

and gives a reasonable approximation of wave characteristics 

for a wide range of wave parameters (U.S. Army Corps of 

Engineers, 2002). The assumptions made in developing the 

linear wave theory are 

•	 The fluid is homogeneous and incompressible; therefore, the density ρ is a constant.

•	 Surface tension can be neglected.

•	 Coriolis Effect due to the Earth's rotation can be 

neglected.

•	 Pressure at the free surface is uniform and constant.

•	 The fluid is ideal or inviscid (lacks viscosity).

•	 The particular wave being considered does not interact 

with any other water motions. The flow is irrotational 

so that water particles do not rotate (only normal forces 

are important and shearing forces are negligible).

•	 The bed is a horizontal, fixed, impermeable boundary, 

which implies that the vertical velocity at the bed is 

zero.

•	 The wave amplitude is small and the waveform is 

invariant in time and space.

•	 Waves are plane or long-crested (two-dimensional).

Wave length is calculated within the wave model according to the following formula:

L = g Tp

2

 / 2π

The units for this output are meters. The top-right frame of 

figure 13 displays an example output for wave length using 

wind fetch calculated from 300 degrees and a wind speed 

of 21 miles per hour for Capoli Slough HREP, management 

scenario 4.

Spectral Peak Wave Period

The time interval between the passage of two successive wave crests or troughs at a given point is the wave period 

(U.S. Army Corps of Engineers, 2002). Spectral peak wave 

period is calculated within the wave model according to 

the following formulae taken from the Coastal Engineering 

Manual (U.S. Army Corps of Engineers, 2002): 

Tˆp = 2 * (xˆ)m2

Tp = (Tˆp * U*) / g

The units for this output are seconds. 

The middle-left frame of figure 13 displays an example 

output for wave period using wind fetch calculated from 

300 degrees and a wind speed of 21 miles per hour for Capoli 

Slough HREP, management scenario 4.

Maximum Orbital Wave Velocity

As waves begin to build, an orbital motion is created 

in the water column resulting in a bottom velocity and shear 

stress (U.S. Army Corps of Engineers, 2006). This orbital 

wave velocity can be sufficient enough to suspend unconsolidated sediments into the water column. In sufficiently 

deep water, the wave particle orbital velocity at the bottom is 

effectively zero and sediment particles on the bed do not experience a force due to surface wave motion (Kraus, 1991). The 

maximum orbital wave velocity is calculated within the wave 

model according to the following formula (Kraus, 1991):

um = π Hm0 / (Tp sinh (2π df / L))

Maximum orbital wave velocity is based upon linear 

wave theory (see section describing wave length). The units 

for this output are meters per second. The middle-right frame 

of figure 13 displays an example output for maximum orbital 

wave velocity using wind fetch calculated from 300 degrees 

and a wind speed of 21 miles per hour for Capoli Slough 

HREP, management scenario 4.

Shear Stress 

Shear stress is the drag force created on the bed by the 

fluid motion (Kraus, 1991). Shear stress at the bottom of the 

water column is understood to be an average over a wave 

period and is calculated within the wave model according to 

the following formula (Kraus, 1991):

τ = ρ f um

2

 / 2

The units for this output are Newtons per square meter. The 

bottom-left of figure 13 displays an example output for shear 

stress using wind fetch calculated from 300 degrees and a 

wind speed of 21 miles per hour for Capoli Slough HREP, 

management scenario 4. 

Figure 14 is a flowchart diagram depicting the relationships of the input and output parameters used to develop the 

wave models within the tool.
16 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Wave 

Height

Wave 

Length

Wave 

Period

Maximum 

Orbital Wave Velocity

Shear Stress

High: 0.5

 (Meters)

Low : 0.01

High : 9.4

 (Meters)

Low : 0.1

High : 2.4

 (Seconds)

Low : 0.2

High : 90

 (Meters/Sec)

Low : 0

High : 130,284

 (Newtons/Sq. Meter)

Low : 0

Capoli Slough HREP Area of Interest

Land (Scenario 4)

1,000

Meters

Figure 13. Sample wave model outputs for scenario 4, Capoli Slough Habitat Rehabilitation and Enhancement Project. 
St. Paul District Analyses 17

Figure 14. Diagram depicting relationships of input and output parameters used within the wave model. 

St. Paul District Analyses

Study Areas

The study areas for these analyses are Capoli Slough and 

Harpers Slough HREPs in Navigation Pool 9 of the Upper 

Mississippi River System (UMRS; fig. 15). Both of these 

proposed HREPs are being designed to not only achieve goals 

and objectives related to the improvement of habitat but to also 

have a physical impact on riverine processes. Both projects 

intend to slow the loss of existing islands and to also restore 

islands that were lost. 

“Islands reverse many of the effects of lock and dam 

construction. A new island essentially becomes the 

new natural levee, separating channel from floodplain, reducing channel-floodplain connectivity, 

and increasing channel flow while decreasing the 

amount of floodplain flow. This increases the velocity in adjacent channels increasing the erosion and 

transport of sediment. Wind fetch and wave action is 

reduced in the vicinity of islands, reducing the resuspension of bottom sediments, floodplain erosion, 

and shoreline erosion. In some cases, islands act 

primarily as wave barriers and don’t alter the riverwide distribution of flow. Islands reduce the supply 

of sediment to the floodplain potentially decreasing 

floodplain sediment deposition” (U.S. Army Corps 

of Engineers, 2006). 

Capoli Slough Habitat Rehabilitation and 

Enhancement Project

Capoli Slough HREP is described in the USACE fact 

sheet as a side channel/island complex located on the Wisconsin side of the Mississippi River navigation channel in Pool 9, 

about five miles downstream of Lansing, Iowa. The site lies 

within the Upper Mississippi River National Wildlife and Fish 

Refuge (U.S. Army Corps of Engineers, n.d.a). 
18 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Many of the natural islands bordering the navigation 

channel have eroded, and many are disappearing. Erosion 

from wave action and main channel flows are reducing the 

size of the wetland complex, resulting in the loss of aquatic 

vegetation and the shallow protected habitats important for 

the survival of many species of fish and wildlife (U.S. Army 

Corps of Engineers, n.d.a).

The proposed project would restore islands to reduce 

fetch lengths. Breached areas would be stabilized using rock 

sills, and partial-closing structures would be constructed to 

reduce the effect of main channel flows. Material to restore the 

island complex would be dredged from the immediate vicinity to provide additional deepwater fish habitat benefits. It is 

estimated that the project would provide both fish and wildlife 

benefits by creating a “shadow” effect behind and downstream 

of the islands. About 600 acres of backwater habitat would be 

directly affected (U.S. Army Corps of Engineers, n.d.a).

Six specific habitat objectives were outlined in the Capoli 

Slough HREP Problem Appraisal Report (U.S. Army Corps of 

Engineers, 2001).

1. Increase the acreage of emergent vegetation and 

floating-leafed vegetation by 10 percent over 2000 

(LTRMP land cover) coverage.

2. Within the Capoli Slough complex, maintain Capoli 

Slough and other well-defined running slough habitats and restore similar habitat where possible.

3. Maintain isolated wetlands and aquatic areas within 

the Capoli Slough complex.

4. Maintain existing islands and increase the acreage of 

island habitat.

5. Provide waterfowl and turtle nesting habitat within 

or near the Capoli Slough complex.

6. Enhance and (or) develop protected off-channel 

lacustrine fisheries habitat within the Capoli Slough 

complex, consistent with other habitat goals and 

objectives.

Figure 15. Location 

of Pool 9 Capoli Slough 

and Harpers Slough 

Habitat Rehabilitation 

and Enhancement 

Projects. 

COUNTY HWY N

WATERVILLE RD

COUNTY

HWY C

COUNTY

TRUNK

HWY A52

STATE HWY 249

STATE

COLUMBUS RD

HWY 171

COUNTY HWY H

STATE

HWY 82

STATE HWY 26

COUNTY

HWY A26

STATE HWY 82

STATE HWY 9

COUNTY

HWY A52

STATE HWY 35

COUNTY

HWY CB

STATE HWY 35

STATE

HWY 364

COUNTY HWY K

STATE HWY 56

COUNTY HWY X52

STATE

HWY 9

Wisconsin

Iowa

Minnesota

Crawford

Vernon

Houston

Allamakee

0 2 4 8

Miles

IA

MN

WI

HREP 

Locations

Major Roadways

USFWS Refuge

UMRS Navigation Pool 9

Land

Water

States

Counties

Capoli Slough HREP

Harpers Slough HREP

EXPLANATION
St. Paul District Analyses 19

Figure 16 gives a visual representation of the Capoli 

Slough HREP area using the 2000 LTRMP Land Cover/

Land Use spatial data layer as a backdrop. The yellow Capoli 

Slough HREP area of interest polygon was created by buffering land areas affected by the HREP 500 meters. When 

interpreting the legend, features labeled “Added for Scenario 

3”, for example, also include previous island designs from 

Scenarios 1 and 2 as well as existing land to create the complete Scenario 3 island design assemblage used in the models. 

Features are labeled according to USACE HREP planning 

maps.

Harpers Slough Habitat Rehabilitation and 

Enhancement Project

The Harpers Slough HREP is described in the USACE 

fact sheet as a 2,200-acre backwater area located primarily 

on the Iowa side of the Mississippi River in Pool 9, about 

3 miles upstream of Lock and Dam 9. The site lies within the 

Upper Mississippi River National Wildlife and Fish Refuge 

(U.S. Army Corps of Engineers, n.d.b). 

The area is used heavily by tundra swans, Canada geese, 

puddle and diving ducks, black terns, nesting eagles, bitterns, and cormorants and is also significant as a fish nursery 

area. Many of the islands in the area have been eroded or lost 

because of wave action and ice movement. This allows more 

turbulence in the backwater area, resulting in less productive 

habitat for fish and wildlife. Harpers Slough is one of the few 

remaining areas in lower Pool 9 where high quality habitat 

could be maintained (U.S. Army Corps of Engineers, n.d.b). 

The proposed project would restore about 25,000 feet of 

islands at the upper portion of the area using material from 

the backwater and near the main channel. About 8,000 feet of 

islands in the lower portion of the area would be stabilized. 

The project would slow the loss of existing islands, reduce the 

flow of sediment-laden water into the backwaters, and increase 

the diversity of land and shoreline habitats (U.S. Army Corps 

of Engineers, n.d.b).

Island F

Island E

Island B

Island I

Island H

Island A

Island D

Island C

Island K3

Island K2

Island G

Island K

Island 2

Island 1

Island 3

Island 4

Island 8

Island 6

Island 7

Island 9

Island 11

Island 10

Emergent

Wetland K

Emergent

Wetland G

Emergent

Wetland I

Emergent

Wetland C

Rock Mound

Wetland E

Rock Mound

Wetland C

Cobble

Liner A

Cobble

Liner B

Closure A

Closure B

Closure E

Closure D

Closure C

658

657

0 500 1, 250 000

Meters

Background image is a USGS

National Elevation Dataset

Revised 2000 LTRMP 

Land Cover/Land Use

Existing Land

Water

Added for Scenario 4

Added for Scenario 3

Added for Scenario 2

Added for Scenario 1

COE Sail Line

River Miles

Capoli Slough HREP 

Area of Interest 

EXPLANATION

Figure 16. Capoli Slough Habitat Rehabilitation and Enhancement Project with feature labels. 
20 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

There are four goals outlined within the Harpers Slough 

rough draft Definite Project Report (U.S. Army Corps of 

Engineers, 2005).

1. Maintain and (or) enhance habitat in the Harpers 

Slough backwater area for migratory birds.

2. Create habitat for migratory and resident vertebrates 

with emphasis on marsh and shorebirds, bald eagles, 

and turtles.

3. Improve and maintain habitat conditions for backwater fish species.

4. Enhance secondary and main channel border habitat 

for riverine fish species and mussels.

Figure 17 gives a visual representation of the Harpers 

Slough HREP area using the 2000 LTRMP Land Cover/Land 

Use spatial data layer as a backdrop. The yellow Harpers 

Slough HREP area of interest polygon was created by buffering land areas affected by the HREP 500 meters. When interpreting the legend, features labeled “Added for Scenario 3,” 

for example, also include previous island designs from Scenarios 1 and 2 as well as existing land to create the complete 

Scenario 3 island design assemblage used in the models. Features are labeled according to USACE HREP planning maps.

Island I1

Seed

Island

Island X1

Island X3

Island A2

Seed

Island

Island D

Island UV

Island I2

Island X1

Island P

Island X2

Island A3

Island I3

Island RS

Emergent

Wetland

Emergent

Wetland

Emergent

Wetland

Isolated

Wetland

Off-shore

Rock

Mound A1

Off-shore

Rock

Mound K

Rock

Sill X1

Rock

Sill A3

Rock

Sill I3

Rock

Sill P

Rock

Sill I

655

654

653

652

651

0 500 1, 250 000

Meters

Background image is a USGS

National Elevation Dataset

Revised 2000 LTRMP 

Land Cover/Land Use

Harpers Slough HREP

Area of Interest 

Existing Land

Water

Added for Scenario 4

Added for Scenario 3

Added for Scenario 2

Added for Scenario 1

COE Sail Line

River Miles

EXPLANATION

Figure 17. Harpers Slough Habitat Rehabilitation and Enhancement Project with feature labels. 
St. Paul District Analyses 21

Weighted Wind Fetch Analysis

Land Raster Input Data

The 2000 land cover data created by the LTRMP were 

used to depict the land/water interface used within the wind 

fetch model for this particular analysis (see “spatial datasets 

used in analyses” section for detailed background information). Some details in existing land/water morphology were 

updated using existing island polygons supplied by the 

USACE for Capoli Slough HREP. Also, an existing barrier island was digitized and included into all management 

scenarios for Harpers Slough HREP (fig. 18). This island was 

created just to the west of river mile 654. 

Island design scenarios were provided by the St. Paul 

District, U.S. Army Corps of Engineers and incorporated into 

the 2000 LTRMP land cover. These land/water datasets provided the base layers used to calculate fetch. To be used within 

the model, these land/water datasets were given a new field. 

This field was attributed so all land polygons were “1” and all 

water polygons were attributed as “0.” The polygons were then 

converted from their native polygonal (shapefile) format into 

an ESRI raster format (Grid) to be used in the model. The field 

that was added was used to assign values to the output raster. 

This was accomplished in ArcGIS 9.2 using the “Feature to 

Raster” tool. The output rasters have a cell size of 10 meters. 

The specific island configuration scenario to be used 

within the wind fetch model is designated using the “Land 

Raster” control on the wind fetch model dialog window. 

Wind Direction Input Data

Wind direction data used within the wind fetch model 

were collected from the National Oceanic and Atmospheric 

Administration, National Climatic Data Center (NCDC) 

(http://www7.ncdc.noaa.gov/IPS/LCDPubs?action=getstat

e&LCD=hardcode). The specific wind parameter used was 

the maximum 2-minute average wind direction. Wind data 

used in this analysis were collected only during the growing 

seasons (April–July) from 1998 to 2007. All daily wind data 

were used regardless of collected wind speed. Wind data for 

significant events could be selected manually to represent 

wind speeds and directions of primary concern. Only April 

data were available for 2007 at the time of analysis. Figure 19 

gives an example of NCDC local climatological data for May 

2006 from the La Crosse Municipal Airport. This was the 

closest data collection location to the study areas of Capoli 

and Harpers Slough HREPs.

Figure 18. Location of revised island addition to Harpers Slough Habitat Rehabilitation and Enhancement Project area. 
22 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Figure 19. National Climatic Data Center, Local Climatological Data summary sheet. 
St. Paul District Analyses 23

Weighted Wind Fetch

Wind fetch was calculated at 10 degree increments 

around entire compass for each management scenario using 

the wind fetch model. Individual fetch raster outputs were 

then multiplied by the percentage of wind observed from its 

respective direction. Figure 20 depicts graphical breakdown of 

wind direction frequencies. Of note are peaks in wind frequency from the south and the northwest. Then these weighted 

individual wind fetch outputs were summed to create a final 

weighted wind fetch model for each particular management 

scenario. All of this process takes place with the help of the 

ArcGIS Weighted Sum Tool that is within the Spatial Analyst 

toolbox (fig. 21).

Another possible method for weighting the collected 

wind data instead of by the percentage of observations from 

each respective direction would be to weight according to the 

average intensity of the wind from each direction or some 

combination of the two methods. Alternatively, you could 

weight only for intensities greater than a certain threshold. 

Figure 20. Breakdown of wind directions 

collected for La Crosse Municipal Airport 

site. 

Figure 21. Weighted sum dialog 

window example. 
24 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Analysis Results

Weighted wind fetch was calculated for UMRS Pool 9 

for each potential management scenario; No-Action, Existing 

Conditions, Scenario 1, Scenario 2, Scenario 3, and Scenario 4. 

Figures 22 and 23 display the results of the weighted 

wind fetch analysis for each management scenario, for the 

Capoli Slough HREP and Harpers Slough HREP, respectively. 

Figure 24 depicts the difference in weighted wind fetch 

in meters from the existing conditions management scenario to 

scenarios 1, 2, 3, and 4 for Capoli Slough HREP.

Figure 25 shows the numerical difference in weighted 

wind fetch from the existing conditions management scenario 

to scenarios 1, 2, 3, and 4 for Capoli Slough HREP.

Figure 26 depicts the difference in weighted wind fetch 

in meters from the existing conditions management scenario to 

scenarios 1, 2, 3, and 4 for Harpers Slough HREP.

Figure 27 shows the numerical difference in weighted 

wind fetch from the existing conditions management scenario 

to scenarios 1, 2, 3, and 4 for Harpers Slough HREP.

Discussion

Using this weighted fetch analysis approach it is possible to quantify the amount of wind fetch for each of the 

separate island design management scenarios and compare 

how the addition of potential island structures may affect wind 

fetch. This approach took into account historical wind data. 

Site-specific wind data would have been preferred but this 

was unavailable. The ability to decrease wind fetch within 

the HREP locations would benefit these sites by lessening 

the forces applied due to wave energy and thereby decreasing turbidity. With the addition of features for each management scenario progressing from 1 to 4 we see decreases in the 

amount of weighted wind fetch within both study areas. The 

next step would be to perform a cost-benefit analysis to ascertain whether the monetary costs of the additional features with 

each successive island design are worth the modeled ecological benefits.

Sediment Suspension Probability Analysis

Many factors affect aquatic plant growth. These may 

include site-characteristic changes in climate, water temperature, water transparency, pH, and oxygen effects on CO2

assimilation rate at light saturation, wintering strategies, grazing and mechanical control (removal of shoot biomass), and 

of latitude (Best and Boyd, 1999). According to Kreiling and 

others, 2007, “light, rather than nutrients, was the main abiotic 

factor associated with the peak Vallisneria shoot biomass in 

Pool 8.” Wave action has a direct effect on water transparency. 

When sediments are suspended by wave action, it causes an 

increase in water turbidity. High turbidity can reduce aquatic 

plant growth by decreasing water transparency, thus limiting 

light penetration. 

The sediment suspension probability analysis developed 

for Capoli and Harpers Slough HREPs involved executing 

the wave models to calculate maximum orbital wave velocity 

(MOWV) outputs for each potential management scenario and 

applying these MOWV values to predict sediment suspension 

probabilities. According to Coops and others, 1991, “maximal wave heights and orbital velocities were concluded to be 

key factors in the decreased growth rates of plants at exposed 

sites.”

The MOWV was calculated once daily over the growing 

season (April through July) encompassing the 6-year period 

between 2002 and 2007 (n = 640 days). Only April data were 

available for the year 2007 at the time analysis was executed. 

The MOWV of 0.10 meters per second was then selected to 

represent velocities required to suspend fine unconsolidated 

sediments (Håkanson and Jansson, 1983). 

Bathymetric data used in the wave model equations were 

obtained from the Long Term Resource Monitoring Program 

(see “spatial datasets used in analyses” section for detailed 

background information). The bathymetric data had to be 

modified when calculating the MOWV for the “No Action” 

management scenario. All island areas that were predicted to 

be lost in that scenario were given the lowest water depth for 

those areas, in this example 0.01 meters (1 centimeter).
St. Paul District Analyses 25

No-Action

1 oiranecS 2 oiranecS

3 oiranecS 4 oiranecS

Existing

Conditions

1,000

Meters

Weighted Wind Fetch (Meters)

0

1 - 100

101 - 200

201 - 300

301 - 400

401 - 500

501 - 600

1,801 - 1,900

1,901 - 2,000

2,001 - 2,100

2,101 - 2,200

2,201 - 2,300

2,301 - 2,400

2,401 - 2,500

2,501 - 2,600

2,601 - 2,700

2,701 - 2,800

2,801 - 2,900

2,901 - 3,000

> 3,000

1,201 - 1,300

1,301 - 1,400

1,401 - 1,500

1,501 - 1,600

1,601 - 1,700

1,701 - 1,800

HREP Area of Interest

601 - 700

701 - 800

801 - 900

901 - 1,000

1,001 - 1,100

1,101 - 1,200

Land

Figure 22. Weighted wind fetch results for the Capoli Slough Habitat Rehabilitation and Enhancement Project. 
26 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

No-Action

1 oiranecS 2 oiranecS

3 oiranecS 4 oiranecS

Existing

Conditions

2,000

Meters

Weighted Wind Fetch (Meters)

0

1 - 100

101 - 200

201 - 300

301 - 400

401 - 500

501 - 600

1,801 - 1,900

1,901 - 2,000

2,001 - 2,100

2,101 - 2,200

2,201 - 2,300

2,301 - 2,400

2,401 - 2,500

2,501 - 2,600

2,601 - 2,700

2,701 - 2,800

2,801 - 2,900

2,901 - 3,000

> 3,000

1,201 - 1,300

1,301 - 1,400

1,401 - 1,500

1,501 - 1,600

1,601 - 1,700

1,701 - 1,800

HREP Area of Interest

601 - 700

701 - 800

801 - 900

901 - 1,000

1,001 - 1,100

1,101 - 1,200

Land

Figure 23. Weighted wind fetch results for the Harpers Slough Habitat Rehabilitation and Enhancement Project. 
St. Paul District Analyses 27

Scenario 1

3 oiranecS 4 oiranecS

Scenario 2

1,000

Meters

Weighted Wind Fetch (Meters)

0

1 - 100

101 - 200

201 - 300

301 - 400

401 - 500

501 - 600

1,801 - 1,900

1,901 - 2,000

2,001 - 2,100

2,101 - 2,200

2,201 - 2,300

2,301 - 2,400

2,401 - 2,500

2,501 - 2,600

2,601 - 2,700

2,701 - 2,800

2,801 - 2,900

2,901 - 3,000

> 3,000

1,201 - 1,300

1,301 - 1,400

1,401 - 1,500

1,501 - 1,600

1,601 - 1,700

1,701 - 1,800

HREP Area of Interest

601 - 700

701 - 800

801 - 900

901 - 1,000

1,001 - 1,100

1,101 - 1,200

Land

Figure 24. Difference in 

weighted wind fetch from 

the existing conditions 

management scenario 

to scenarios 1, 2, 3, and 

4 for the Capoli Slough 

Habitat Rehabilitation and 

Enhancement Project. 

Figure 25. Numerical difference in weighted wind 

fetch from the existing conditions management scenario 

to scenarios 1, 2, 3, and 4 for the Capoli Slough Habitat 

Rehabilitation and Enhancement Project. 
28 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Scenario 1

3 oiranecS 4 oiranecS

Scenario 2

2,000

Meters

Weighted Wind Fetch (Meters)

0

1 - 100

101 - 200

201 - 300

301 - 400

401 - 500

501 - 600

1,801 - 1,900

1,901 - 2,000

2,001 - 2,100

2,101 - 2,200

2,201 - 2,300

2,301 - 2,400

2,401 - 2,500

2,501 - 2,600

2,601 - 2,700

2,701 - 2,800

2,801 - 2,900

2,901 - 3,000

> 3,000

1,201 - 1,300

1,301 - 1,400

1,401 - 1,500

1,501 - 1,600

1,601 - 1,700

1,701 - 1,800

HREP Area of Interest

601 - 700

701 - 800

801 - 900

901 - 1,000

1,001 - 1,100

1,101 - 1,200

Land

Figure 27. Numerical difference in weighted wind fetch 

from the existing conditions management scenario to 

scenarios 1, 2, 3, and 4 for the Harpers Slough Habitat 

Rehabilitation and Enhancement Project. 

Figure 26. Difference in 

weighted wind fetch from 

the existing conditions 

management scenario 

to scenarios 1, 2, 3, and 

4 for the Harpers Slough 

Habitat Rehabilitation and 

Enhancement Project. 
St. Paul District Analyses 29

The next step in the analysis involved reclassifying areas 

within the output MOWV raster that had MOWV values 

>= 0.10 meters per second with a “1” value and reclassifying areas within the output MOWV raster that had MOWV 

< 0.10 meters per second with a “0” value. This was done for 

all 640 raster outputs. Next, these individual reclassified raster 

datasets were merged together into one raster dataset and 

the values divided by the total number of days (640) to get a 

percentage of days that MOWV was at least 0.10 meters per 

second for each individual raster cell. This value then represents the probability to suspend fine unconsolidated particles. 

Figure 28 gives a graphical illustration of the process used to 

create the final outputs using four hypothetical raster datasets 

as an example.

Analysis Results

Sediment suspension probability was calculated for 

UMRS Pool 9 for each potential management scenario: 

No-Action, Existing Conditions, Scenario 1, Scenario 2, 

Scenario 3, and Scenario 4. 

Figures 29 and 30 display the results of the sediment 

suspension probability analysis for each management scenario, 

for the Capoli Slough and Harpers Slough HREP, respectively. 

Figure 31 depicts the difference in sediment suspension 

probability from the existing conditions management scenario 

to scenarios 1, 2, 3, and 4 for Capoli Slough HREP.

Figure 32 shows the numerical difference in sediment 

suspension probability from the existing conditions management scenario to scenarios 1, 2, 3, and 4 for Capoli Slough 

HREP.

Figure 33 depicts the difference in sediment suspension 

probability from the existing conditions management scenario 

to scenarios 1, 2, 3, and 4 for Harpers Slough HREP.

Figure 34 shows the numerical difference in sediment 

suspension probability from the existing conditions management scenario to scenarios 1, 2, 3, and 4 for Harpers Slough 

HREP.

Figure 28. Diagram explaining process for calculating percent of days capable of suspending sediments. 
30 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

No-Action

1 oiranecS 2 oiranecS

3 oiranecS 4 oiranecS

Existing

Conditions

1,000

Meters

Sediment Suspension Probability (Percentage of Days)

Land HREP Area of Interest

0

0.1 - 5

5.1 - 10

10.1 - 15

15.1 - 20 40.1 - 45

20.1 - 25

25.1 - 30

30.1 - 35

35.1 - 40

45.1 - 50

50.1 - 55

55.1 - 60

60.1 - 65

65.1 - 70

70.1 - 75

75.1 - 80

80.1 - 85

85.1 - 90

90.1 - 95

95.1 - 100

Figure 29. Sediment suspension probability results for the Capoli Slough Habitat Rehabilitation and Enhancement 

Project. 
St. Paul District Analyses 31

No-Action

1 oiranecS 2 oiranecS

3 oiranecS 4 oiranecS

Existing

Conditions

2,000

Meters

Sediment Suspension Probability (Percentage of Days)

Land HREP Area of Interest

0

0.1 - 5

5.1 - 10

10.1 - 15

15.1 - 20 40.1 - 45

20.1 - 25

25.1 - 30

30.1 - 35

35.1 - 40

45.1 - 50

50.1 - 55

55.1 - 60

60.1 - 65

65.1 - 70

70.1 - 75

75.1 - 80

80.1 - 85

85.1 - 90

90.1 - 95

95.1 - 100

Figure 30. Sediment suspension probability results for the Harpers Slough Habitat Rehabilitation and Enhancement 

Project. 
32 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Scenario 1

3 oiranecS 4 oiranecS

Scenario 2

1,000

Meters

Sediment Suspension Probability (Percentage of Days)

Land HREP Area of Interest

0

0.1 - 5

5.1 - 10

10.1 - 15

15.1 - 20 40.1 - 45

20.1 - 25

25.1 - 30

30.1 - 35

35.1 - 40

45.1 - 50

50.1 - 55

55.1 - 60

60.1 - 65

65.1 - 70

70.1 - 75

75.1 - 80

80.1 - 85

85.1 - 90

90.1 - 95

95.1 - 100

Figure 31. Difference 

in sediment suspension 

probability from the existing 

conditions management 

scenario to scenarios 1, 2, 3, 

and 4 for the Capoli Slough 

Habitat Rehabilitation and 

Enhancement Project. 

Figure 32. Numerical difference in sediment suspension 

probability from the existing conditions management 

scenario to scenarios 1, 2, 3, and 4 for the Capoli Slough 

Habitat Rehabilitation and Enhancement Project. 
St. Paul District Analyses 33

Scenario 1

3 oiranecS 4 oiranecS

Scenario 2

2,000

Meters

Sediment Suspension Probability (Percentage of Days)

Land HREP Area of Interest

0

0.1 - 5

5.1 - 10

10.1 - 15

15.1 - 20 40.1 - 45

20.1 - 25

25.1 - 30

30.1 - 35

35.1 - 40

45.1 - 50

50.1 - 55

55.1 - 60

60.1 - 65

65.1 - 70

70.1 - 75

75.1 - 80

80.1 - 85

85.1 - 90

90.1 - 95

95.1 - 100

Figure 33. Difference 

in sediment suspension 

probability from the 

existing conditions 

management scenario 

to scenarios 1, 2, 3, and 

4 for the Harpers Slough 

Habitat Rehabilitation and 

Enhancement Project. 

Figure 34. Numerical difference in sediment suspension 

probability from the existing conditions management 

scenario to scenarios 1, 2, 3, and 4 for the Harpers Slough 

Habitat Rehabilitation and Enhancement Project. 
34 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Discussion

This analysis provides a simplistic approach to forecasting wave effects on the suspension of fine unconsolidated 

sediment particles. Based upon this approach, it is possible to 

depict changes in sediment suspension probability for several 

potential island construction scenarios at the identified HREP 

areas both with maps and summary charts. By decreasing 

the potential for sediments to be suspended, there would be a 

decrease in turbidity. Decreasing turbidity would increase light 

penetration and, therefore, create conditions more conducive 

to aquatic plant growth. This approach took into account historical wind data. Site-specific wind data would have been preferred but this was unavailable. With the addition of features 

for each management scenario progressing from 1 to 4, we 

see decreases in the percentage of days with MOWV capable 

of suspending fine unconsolidated particles within both study 

areas. Likewise, with the weighted wind fetch analysis, the 

next step would be to perform a cost-benefit analysis to ascertain whether the monetary costs of the additional features with 

each successive island design are worth the modeled ecological benefits.

St. Louis District Analysis

Study Area

Swan Lake Habitat Rehabilitation and 

Enhancement Project

The study area for this analysis was Swan Lake HREP 

which is located near the confluence of the Illinois and Mississippi Rivers within the UMRS near Brussels, Illinois (fig. 35). 

Figure 35. Location of Swan Lake Habitat Rehabilitation and Enhancement Project. 

Illinois

Missouri

Jersey

Calhoun

Greene

St.

Charles

Background image 

is the USGS 

National Elevation 

Dataset.

0 2 4 8

Miles

Two Rivers National 

Wildlife Refuge

Big Muddy National Fish

and Wildlife Refuge 

IL

IA

MO

HREP 

Location

Swan Lake HREP Area

LTRMP Land Cover

Land

Water

USFWS Refuge

States

Counties

EXPLANATION
St. Louis District Analysis 35

Swan Lake HREP is described in the 1993 USACE definite project report as being located adjacent to the west bank 

of the Illinois River between river miles 5 and 13. The immediate project area includes 2,900-acre Swan Lake, 200-acre 

Fuller Lake, and approximately 950 acres of bottomland forest 

and 550 acres of cropland surrounding these lakes (totaling 

4,600 acres). Also included in the project area is the local 

watershed adjacent to Swan Lake’s west shore (U.S. Army 

Corps of Engineers, 1993). 

Management of the project area is divided. Fuller Lake 

and the uppermost 300 acres of Swan Lake are managed 

for the USFWS by the Illinois Department of Conservation (IDOC). The remaining 2,600 acres of Swan Lake are 

managed directly by the USFWS as part of the Mark Twain 

National Wildlife Refuge. East of the project area is the Stump 

Lake HREP and to the southwest, the project abuts the Calhoun Point HREP area. Collectively, these three areas comprise about one-fourth of all wetland and deepwater habitats to 

be found in the lower 80 miles of the Illinois River valley, and 

they form an integral component of a nationally significant 

ecosystem (U.S. Army Corps of Engineers, 1993).

Swan Lake is vitally important as habitat for both waterfowl and fish. The lake lies within a portion of the Mississippi Flyway designated as an area of major concern under 

the North American Waterfowl Management Plan. Ongoing 

habitat loss has reduced the value of this area for waterfowl as 

a migration feeding and resting area. From a fisheries standpoint, the lake furnishes a major portion of the region’s available spawning, rearing, and wintering habitat. The lake is open 

to both sport and commercial fishing. Biologists are concerned 

that a continuing loss of river backwater habitat could result in 

a future reduction in fish abundance and diversity (U.S. Army 

Corps of Engineers, 1993).

Weighted Wind Fetch Analysis

Land Raster Input Data

The 2000 land cover data created by the LTRMP were 

used to depict the land/water interface used within the wind 

fetch model for this particular analysis (see “spatial dataset 

used in analysis” section for detailed background information). 

A line of human-made island structures that exist between the 

northwest and southeast sections of the lower pool of the Swan 

Lake HREP were added to the base 2000 land/water dataset 

(fig. 36). These islands will have an effect on wind fetch so it 

was deemed essential to include in the following island design 

scenarios. 

Figure 36. Location of revised island addition to Swan Lake Habitat Rehabilitation and Enhancement Project area. 
36 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

U.S. Fish and Wildlife Service Sample Island 

Design

Figure 37 gives a visual representation of the Swan Lake 

HREP area and USFWS sample islands using 2006 USDA 

National Agriculture Imagery Program aerial photography 

as a backdrop. The yellow Swan Lake HREP area of interest 

polygon was created by selecting the polygons identified as 

“water” in the 2000 LTRMP land cover/land use spatial data 

layer within the lower pool of the Swan Lake HREP area. 

A sample island design was created by personnel at Two 

Rivers National Wildlife Refuge to help decrease wind fetch 

within Swan Lake. The USFWS staff at the refuge were given 

a map of current weighted wind fetch to help place the islands. 

These islands are displayed in purple in figure 37 and have a 

total acreage of 12.395 acres. Features are labeled according to 

randomly generated numbers preceded by an “A” (northwest 

section of Swan Lake HREP area) or a “B” (southeast section 

of Swan Lake HREP area) to differentiate the separate portions of the Swan Lake area of interest. 

0 500 1, 250 000

Meters

Background image is a 2006

USDA National Agriculture

Imagery Program Aerial Photo

Swan Lake HREP 

Area of Interest 

USFWS Proposed 

Ill

Island Design inois River

A1

A2

B1 B2

Figure 37. Swan Lake Habitat Rehabilitation and Enhancement Project with U.S. Fish and Wildlife Service proposed 

islands labeled. 

U.S. Army Corps of Engineers Sample Island 

Design

Figure 38 gives a visual representation of the Swan Lake 

HREP area using 2006 USDA National Agriculture Imagery 

Program aerial photography as a backdrop and also includes a 

sample island design created by staff at the USACE St. Louis 

District office to impede wind fetch. The USACE staff at the 

district were given a map of current weighted wind fetch to 

help place the islands. These islands are displayed in purple 

in figure 38 and have a total area of 40.085 acres. Features are 

labeled according to randomly generated numbers preceded 

by an “A” or a “B” to differentiate the separate portions of the 

Swan Lake area of interest.

These land/water datasets provided the base layers used 

to calculate fetch. To be used within the model, these land/

water datasets were given a new field. This field was attributed 

so all land polygons were “1” and all water polygons were 

attributed as “0.” The polygons were then converted from their 

native polygonal (shapefile) format into an ESRI raster format 
St. Louis District Analysis 37

(Grid) to be used in the model. The field added was used to 

assign values to the output raster. This was accomplished in 

ArcGIS 9.2 using the “Feature to Raster” tool. The output 

rasters have a cell size of 10 meters.

The specific island configuration scenario to be used 

within the wind fetch model is designated using the “Land 

Raster” control on the wind fetch model dialog window. 

Wind Direction Input Data

Wind direction data used within the wind fetch model 

were collected from the National Oceanic and Atmospheric 

Administration, National Climatic Data Center (NCDC) 

(http://www7.ncdc.noaa.gov/IPS/LCDPubs?action=getstate

&LCD=hardcode). The specific wind parameter used was the 

maximum 2-minute average wind direction. Wind data used 

in this analysis was collected only during the growing seasons 

(April–July) from 1998 to 2007. All daily wind data were used 

regardless of collected wind speed. Wind data for significant 

events could be selected manually to represent wind speeds 

and directions of primary concern. Only April data were available for 2007 at the time of analysis. Figure 39 gives an example of NCDC local climatological data for April 2007 from the 

Lambert–St. Louis International Airport. This was the closest 

NCDC data collection location to Swan Lake HREP.

Weighted Wind Fetch

Wind fetch was calculated at 10-degree increments 

around entire compass for each management scenario using 

the wind fetch model. Wind fetch was calculated using the 

SPM calculation method. Individual fetch raster outputs were 

then multiplied by the percentage of wind observed from its 

respective direction. Figure 40 depicts graphical breakdown 

of wind direction frequencies. Of note are peaks in wind 

frequency from the south and the northwest. These weighted 

individual wind fetch outputs were summed to create a final 

weighted wind fetch model for each particular management 

scenario. All of this process takes place with the help of the 

ArcGIS Weighted Sum Tool that is within the Spatial Analyst 

toolbox (fig. 41).

B7

B8

B9

B6

B5

B4 B3

B2

B1

A6

A5

A4

A2 A3

A1

0 500 1, 250 000

Meters

Background image is a 2006

USDA National Agriculture

Imagery Program Aerial Photo

Swan Lake HREP 

Area of Interest 

USACE Proposed

Ill

Island Design inois River

Figure 38. Swan Lake Habitat Rehabilitation and Enhancement Project with U.S. Army Corps of Engineers proposed 

islands labeled. 
38 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Figure 39. National Climatic Data Center, local climatological data summary sheet. 
St. Louis District Analysis 39

Figure 40. Breakdown of 

wind directions collected for 

Lambert–St. Louis International 

Airport site. 

Figure 41. Weighted 

sum dialog window 

example. 
40 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Another possible method for weighting the collected 

wind data instead of by the percentage of observations from 

each respective direction would be to weight according to the 

average intensity of the wind from each direction or some 

combination of the two methods. Alternatively, you could 

weight only for intensities greater than a certain threshold. 

Analysis Results

Weighted wind fetch was calculated for Swan Lake 

HREP for each potential management scenario: Existing Conditions, USFWS Island Design, and USACE Island Design. 

The top-left frame of figure 42 displays the results of the 

weighted wind fetch analysis for the existing conditions management scenario, for the Swan Lake HREP. The middle-left 

frame of figure 42 displays the weighted wind fetch results for 

the USFWS Island Design, and the bottom-left frame of figure 42 displays the difference in weighted fetch from the existing conditions scenario to the island design scenario proposed 

by the USFWS. The middle-right frame of figure 42 displays 

the weighted wind fetch results for the USACE Island Design, 

and the bottom-right frame of figure 42 displays the difference 

in weighted fetch from the existing conditions scenario to the 

island design scenario proposed by the USACE. 

Figure 43 displays the percent decrease in total weighted 

fetch between existing conditions and the USFWS proposed 

island design for Swan Lake HREP. 

Figure 44 displays the percent decrease in total weighted 

fetch between existing conditions and the USACE proposed 

island design for Swan Lake HREP.

Discussion

Using this weighted fetch analysis approach, it is possible to quantify the amount of wind fetch for each of the 

separate island design management scenarios and compare 

how the addition of potential island structures may affect wind 

fetch. This approach took into account historical wind data. 

Site-specific wind data would have been preferred but this 

was unavailable. The ability to decrease wind fetch within 

the HREP locations would benefit these sites by lessening 

the forces applied due to wave energy and thereby decreasing turbidity. With the addition of features for the USFWS 

and USACE management scenarios, we see decreases in the 

amount of weighted wind fetch within the Swan Lake HREP 

area. The next step would be to perform a cost-benefit analysis 

to ascertain whether the monetary costs of the proposed features with each island design are worth the modeled ecological 

benefits.

Spatial Datasets Used in Analyses

Long Term Resource Monitoring Program 

2000 Land Cover/Land Use Data for the 

Upper Mississippi River System

Originator

U.S. Geological Survey Upper Midwest Environmental 

Sciences Center Long Term Resource Monitoring Program

Abstract

The UMESC created high-resolution land cover/use 

data sets for the UMRS from 1:24,000-scale color infrared 

aerial photographs collected in 2000. The photographs were 

interpreted using a minimum mapping unit of 1-hectare and 

10-percent minimum vegetation cover. The photographs were 

interpreted to delineate land cover/land use, percent vegetation cover, tree height, and hydrology regime. The geographic 

extent of the UMRS is the Mississippi River from Cairo, 

Illinois, to Minneapolis, Minnesota, and the Illinois River from 

its confluence with the Mississippi near Grafton, Illinois, to 

Lake Michigan.

Online Linkage

http://www.umesc.usgs.gov/data_library/land_cover_

use/2000_lcu_umesc.html

Long Term Resource Monitoring Program 

Bathymetric Data for the Upper Mississippi 

and Illinois Rivers

Originator

U.S. Geological Survey Upper Midwest Environmental 

Sciences Center Long Term Resource Monitoring Program

Abstract

Water depth is an important feature of aquatic systems. 

On the UMRS, water depth data are important for describing 

the physical template of the system and monitoring changes 

in the template caused by sedimentation. Although limited 

point or transect sampling of water depth can provide valuable 

information on habitat character in the UMRS as a whole, the 

generation of bathymetric surfaces are critical for conducting 

spatial inventories of the aquatic habitat. The maps are also 

useful for detecting bed elevation changes in a spatial manner 

as opposed to the more common method of measuring changes 

along transects. The UMESC has been collecting bathymetric 

data within the UMRS since 1989 in conjunction with the 

LTRMP.

Online Linkage

http://www.umesc.er.usgs.gov/aquatic/bathymetry/

download.html
St. Louis District Analysis 41

Weighted Wind Fetch

Existing Conditions

Weighted Wind Fetch

USFWS Island Design

Weighted Wind Fetch

USACE Island Design

Difference in Weighted

Wind Fetch Between 

Existing Conditions and

USFWS Island Design

Difference in Weighted

Wind Fetch Between 

Existing Conditions and

USACE Island Design

1,000

Meters

1,000

Meters

1,000

Meters

1,000

Meters

Weighted Wind Fetch

Meters

0

0.1 - 40

40.1 - 80

80.1 - 120

120.1 - 160

160.1 - 200

200.1 - 240

240.1 - 280

280.1 - 320

320.1 - 360

360.1 - 400

400.1 - 440

440.1 - 480

480.1 - 520

520.1 - 560

560.1 - 600

600.1 - 640

640.1 - 680

680.1 - 720

720.1 - 760

760.1 - 800

800.1 - 840

840.1 - 880

880.1 - 920

920.1 - 960

960.1 - 1,000

> 1,000

1,000 Land Meters

Figure 42. Results of weighted wind fetch analysis for Swan Lake Habitat Rehabilitation and Enhancement Project. 
42 Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Figure 43. Percent decrease in total weighted fetch between existing conditions and U.S. Fish and Wildlife Service 

proposed island design for Swan Lake Habitat Rehabilitation and Enhancement Project. 

Figure 44. Percent decrease in total weighted fetch between existing conditions and U.S. Army Corps of Engineers 

proposed island design for Swan Lake Habitat Rehabilitation and Enhancement Project. 
References Cited 43

Acknowledgments

We thank Michael Walker and Jon Hendrickson, 

U.S. Army Corps of Engineers, St. Paul District and 

John Mabery, U.S. Fish and Wildlife Service, Two Rivers 

National Wildlife Refuge for their assistance with this project. 

We thank Dr. Wayne Thogmartin for his assistance in the 

statistical validation of the wind fetch model. This report also 

was made measurably better by the comments of reviewers.

References Cited

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Rohweder and others—Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects—Open-File Report 2008–1200