Waves, Wakes, and Water Clarity:
New Geospatial Tools to Help
Manage Sediments
Mark Fonseca, Ph.D.
CSA Ocean Sciences Inc.
Amit Malhotra, M.Sc.
Geohorizons
Jud Kenworthy, Ph.D.
Unaffiliated
Three Tools, Two Problems
• WEMo – Wave exposure model
• BoMo – Boat wake model
• OWMo – Optical water quality model
• Average conditions – Are two conditions different?
• Extreme events – What drives responses?
Wave Exposure Model
Search on: Wemosoftware
WEMo Output
1.
Geographic coordinate (UTM)
2. Wave energy (j m -1 wave crest)
3. Max wave height
4. Significant wave height
5.
Direction of waves
6. Average wave power
7.
Seafloor
▫ Horizontal velocity
▫ Shear stress
▫ Critical shear stress (particle size specific)
8. Sediment motion (Y/N)
0.45
Time Series Plot 6 Hr MVA
0.4
Sensor
WEMo
Exposed side
0.35
0.3
R2 = 0.75
0.25
0.2
0.15
Wave ht. in m
0.1
0.05
0
1
101
201
301
401
501
0.4
0.35
R2 = 0.74
Sheltered side
0.3
0.25
0.2
0.15
0.1
0.05
0
1
101
201
301
401
Previous Landscape extent
application; National Weather Service
• 4 km from shore – spacing 1 km
• Otherwise – spacing 10 km
0
5
10
20
30
40
Kilometers
sig. wvht (ft)
Sig.
Sig.wv
wvht
ht(m)
(m)
0
0
5
5
10
10
20
20
30
30
30
40
40
40
Kilometers
Kilometers
Kilometers
0 - 1.6
0 0- -0.48
0.48
1.6 - 3.0
0.49
0.49- 0.92
- 0.92
3.0 - 4.3
0.93
0.93- 1.32
- 1.32
4.3 - 5.6
1.33
1.33- 1.71
- 1.71
5.6 - 6.9
1.72
1.72- 2.11
- 2.11
6.9 - 8.3
2.12
2.12- 2.53
- 2.53
8.3 - 9.9
2.54
2.54- 3.02
- 3.02
9.9 - 10.5
3.03
3.03- 3.2
- 3.2
•Northeast 80 knots
Southwest
knots
•
•
•
•
Waves
Saltmarsh width
Restored marsh limits
Stone sills….
Marsh width (m)
19 y-old restored saltmarsh
Stone sills in NC
Natural marsh
Wave energy (J / m)
Fonseca et al…. long ago
Recomputed from Fonseca and Bell 1998
Mitigation Strategy
• Reduce wave energy on patchy
seagrass beds
• Facilitate bed coalescence
• Increase cover per unit area seafloor
• Create non-discounted, acre-years of
Barden’s Inlet dredge material
island seagrass service flows
Boat Wake Model (BoMo)
Boat Wakes (BoMo) vs. Wind Waves (WEMo)
52-ft Displacement Hull
Wave heights
Erosion zones
3 knots
10 knots
20 knots
wind
Provided quantitative basis for slow speed zone
• Forecast to reduce erosion
• Adds ~10 min. to transit time
Tipping Point Between Wind Wave and Boat Wake Dominance
Optical Water Quality Model (OWMo)
+ Graphical user interface (GUI)
 Predicts geography of biological light requirements (SS, chl a, CDOM)
 Possible link with WEMo / BoMo - geospatial forecasts of wind and
boat wake effects on water quality
 Informs ‘what-if’ and cost-benefit questions (scenario gaming)
Works forwards & backwards
• Slide CHL and/or
TSS to see new
potential habitat
• Set a depth or
acreage target and
see required CHL
and TSS levels
St. Lucie estuary
Applying models…..
• Average conditions – are two conditions different?
• Extreme events – what drives responses?
•
•
•
•
•
•
Extent
Resolution
Duration
Intensity
Return interval
Sequence
Dissecting an extreme event
March 1993 “Storm of the Century”
Cape Lookout, North Carolina
Cumulative frequency distribution
of hourly wind speed (kph1) observations
CLKN7 (Cape Lookout, NC) 1984-2011
1 convert to mph: kph * 0.6214
Peak sustained wind
March 1993 storm
(66.6)
(50.0)
(39.2)
(19.4)
100
•
36 events from 1984 – 2011 (27y) equal or greater max speed
Wind speed (kilometers h-1 )
90
80
~12-14.5h at 99.9th percentile
70
99.9th
60
~21h at 99th percentile
50
99th
40
95th
30
0
10
20
30
Hours
40
50
60
Avg time between events = 2.65 y
Extreme events
• Traditional means and variance can be misleading
• ‘Clock-setting’ events can re-align our perception of drivers
• Long-term data, high temporal resolution
• New metrics that include elements of extremes
(esp. duration, intensity and sequence)
Opportunities – new tools, new context
• Seagrass mitigation planning
• Restoration site selection
• Shoreline management
• Sediment resuspension forecasts
• Water quality targets and expectations
• Vessel traffic management / erosion control
• Improved linkage of cause and effect