The document summarizes research on wind and wave measurements in irrigation reservoirs. Synchronous measurements were taken of wind, waves, and levee erosion at a field site in Arkansas. Wave characteristics including height, period, and energy spectrum were measured. Empirical wave prediction methods were compared to field data. Floating wave barriers were studied as a protection technique through laboratory experiments and modeling. Fetch length and reservoir orientation relative to wind direction were found to be key factors controlling wave size and embankment erosion. Ongoing research aims to better understand the relationship between waves and erosion rates.

1. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
Wind and Wave Measurements in
Irrigation Reservoirs
Yavuz Ozeren
National Center for Computational Hydroscience and Engineering
The University of Mississippi, Oxford, MS
Daniel Wren
USDA‐ARS, National Sedimentation Laboratory, Oxford MS
Michele Reba
USDA‐ARS, Delta Water Management Research Unit, Jonesboro, AR

2. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
Introduction
• The earthen embankments of these reservoirs
often experience significant erosion primarily
due to wind‐generated waves; therefore,
require annual repairs if they are not
protected.
• The design of effective embankment
protection requires knowledge of the wind‐
generated wave characteristics and their
relationship to embankment erosion.
• Irrigation reservoirs are commonly
used for irrigation water storage in
lower Mississippi river floodplain.
• A field measurement station was installed in an
irrigation reservoir near Harrisburg, AR, to
acquire synchronous measurements of wind and
wave properties along with levee erosion data.

3. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
Field Site

4. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
Field Site
• Wave staffs
• Wind gauge
• Erosion pins
• Ground‐based LIDAR

5. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
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Field Measurements
An example time series water surface displacement data (June, 2012,
Jonesboro, AR). The vertical axis is vertical water surface displacement.
Five‐hour‐average energy spectrum of the
measured waves in July 19, 2012
Wave period, wave height and wind speed histograms for the
time period between June 2012 and October 2012.

6. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
Field Measurements
Wave characteristics
R26
(March 2005)
R26
(June 2008)
R27
(June 2012)
Wind speed, U10 (m/s) 14 (NE) 13 (SW) 9.5 (S)
Fetch length 586 450 470
Wave height, Hm0 (m) 0.25 0.23 0.14
Peak period, Tp (s) 1.7 1.6 1.4
Significant period, Ts (s) 1.7 1.6 1.2
Mean period, Tm (s) 1.4 1.4 1.1
Significant wave height, Hs (m) 0.23 0.20 0.13
Maximum wave height, Hmax (m) 0.38 0.39 0.24
RMS wave height, Hrms (m) 0.17 0.12 0.09
The ranges of measured wave parameters compared to field
measurements in 2005, 2008 and 2012.

7. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
44.0
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U
gH
28.0
2
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p
U
gF
U
gT
Wave Prediction
Method Hm0 (m) Tp (s) tmin
(min)
JONSWAP 0.11 1.1 15.2
Wilson (1965) 0.17 1.3 12.5
SMB, Bretschneider (1970) 0.19 1.7 9.4
Krylow (1976) 0.21 1.6 ‐
Donelan (1980) 0.16 1.4 10.3
Ozeren and Wren (2010) 0.14 1.3 11.8
Comparison of empirical wind wave prediction methods
72.0
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8. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
Erosion

9. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
Protection techniques

10. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
Floating Wave Barriers

11. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
Floating Wave Barriers

12. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
Floating Wave Barriers
T = 0.6 s, H = 28 mm, h = 0.466m
2.00 2.24 2.48 2.72 2.96 3.20
x (m)
0.0
0.6
z (m)
t=24.399208 s
2.00 2.24 2.48 2.72 2.96 3.20
x (m)
t=24.598543 s
Laboratory and numerical experiments
Shafer lake (2005‐2009)

13. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
Shape and Orientation

14. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
Shape and Orientation
Internal Levees (U = 10 m/s) Floating wave barriers (U = 10 m/s, Breakwater size = 0.5 m)

15. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
LMRB

16. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
Irrigation
reservoir
(R)
Area – A
(m2
)
Levee
Length (m)
Max. Fetch
– Fmax (m)
Max. fetch
azimuth
(deg.)
Shape
factor
17 116,500 1,336 483 ‐35 1.02
21 123,525 1,421 516 33 0.95
14 125,753 1,404 500 ‐47 1.01
20 126,755 1,377 510 49 1.02
19 128,328 1,411 510 43 1.01
7 132,719 1,422 508 ‐49 1.04
3 138,417 1,585 636 22 0.78
27 142,109 1,529 562 26 0.94
9 151,950 1,931 772 12 0.58
11 163,354 1,927 796 72 0.6
4 164,865 1,626 605 ‐59 0.95
2 167,344 1,687 666 ‐37 0.84
8 180,782 1,842 715 22 0.78
22 198,299 1,802 662 ‐31 0.94
13 206,061 1,737 610 ‐51 1.1
23 209,621 2,150 660 ‐80 0.84
10 234,147 1,871 677 ‐43 1.05
18 251,165 2,199 866 19 0.75
26 286,009 2,239 851 65 0.85
12 300,383 2,244 836 ‐33 0.91
5 303,328 2,267 840 ‐31 0.9
15 341,414 2,368 865 ‐58 0.94
1 351,303 2,413 920 ‐30 0.9
6 462,435 2,742 1030 ‐44 0.93
24 464,613 3,119 1119 19 0.75
16 774,962 3,814 1472 47 0.78
28 818,208 4,106 1311 ‐81 0.86
25 1,264,481 4,561 1690 ‐24 0.93

17. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
• For a given wind speed, fetch length is the key parameter that
controls the size of the waves generated in irrigation
reservoirs.
• The orientation of the reservoir relative to the predominant
wind direction has a strong influence on embankment erosion
in irrigation reservoirs, such that, reducing the fetch length in
the prevailing wind direction can significantly reduce
embankment erosion.
• Ongoing experimental research and reservoir assessment field
studies will provide better information about the relations
between the wave size and the erosion retreat rate.
Conclusions

18. 69th SWCS International Annual Conference, 27 - 30 July, 2014, Lombard, ILNational Center for Computational
Hydroscience and Engineering
The University of
Mississippi
Acknowledgments
Carlos Alonso
USDA‐ARS National Sedimentation Lab. Oxford, MS (retired)
Denis Carman
White River Irrigation District, AR
Keith Admire
USDA‐NRCS National Water Management Center Little Rock, AR
Mustafa Altinakar
NCCHE, The University of Mississippi, Oxford, MS
Paul Work
USGS, Sacramento, CA
Technical support:
Glen Grey
Jacob Ferguson
Alan Barger